Relapse prevention in patients with anxiety or depressive disorders

RELAPSE PREVENTION IN PATIENTS WITH ANXIETY OR DEPRESSIVE DISORDERS

ESTHER KRIJNEN-DE BRUIN

Department of Psychiatry, location VUmc

VRIJE UNIVERSITEIT

Relapse prevention in patients with anxiety or depressive disorders ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. V. Subramaniam, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de Faculteit der Geneeskunde op donderdag 17 juni 2021 om 11.45 uur in de aula van de universiteit, De Boelelaan 1105

door Esther Krijnen-de Bruin geboren te Utrecht

ISBN: 978-94-6423-298-1 Cover design & lay-out: Wendy Schoneveld || www.wenziD.nl Printed by: ProefschriftMaken || Proefschriftmaken.nl This thesis was prepared at the Department of Research and Innovation at GGZ inGeest, and the Department of Psychiatry, Amsterdam UMC, VU University Amsterdam, within the Amsterdam Public Health research institute.

Financial support for the publication and distribution of this thesis was kindly provided by the Department of Psychiatry, Amsterdam UMC, VU University Amsterdam. © Esther Krijnen-de Bruin, 2021 All rights reserved. No part of this thesis may be reproduced, stored or transmitted in any form or by any means without prior permission of the author, or the copyright owning journals for previously published chapters.

VRIJE UNIVERSITEIT

Relapse prevention in patients with anxiety or depressive disorders ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. V. Subramaniam, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de Faculteit der Geneeskunde op donderdag 17 juni 2021 om 11.45 uur in de aula van de universiteit, De Boelelaan 1105

door Esther Krijnen-de Bruin geboren te Utrecht

Promotoren:

prof.dr. B.K.G. van Meijel

prof.dr. A. van Straten

Copromotoren:

dr. A.D.T. Muntingh

dr. N.M. Batelaan

CONTENTS CHAPTER 1

General introduction

CHAPTER 2

Psychological interventions to prevent relapse in anxiety

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and depression: A systematic review and meta-analysis CHAPTER 3

The GET READY relapse prevention program for anxiety and

63

depression: A mixed-methods study protocol CHAPTER 4

Usage intensity of a relapse prevention program and its

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relation to symptom severity in remitted patients with anxiety and depression: Pre-post study CHAPTER 5

Evaluation of a blended relapse prevention program for

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anxiety and depression in general practice: Qualitative study CHAPTER 6

The Assessment of Self-management in Anxiety and

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Depression questionnaire (ASAD): A psychometric evaluation CHAPTER 7

Summary & General discussion

169

APPENDICES Dutch summary | Nederlandse samenvatting

193

Acknowledgements | Dankwoord

199

Curriculum vitae

202

Dissertation series

203

1

GENERAL INTRODUCTION

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“My name is John and I am 55 years old. I am divorced and I have two adult children. I have experienced a depression twice. The first time was after my brother passed away. We got along well, and I was heartbroken. I was unable to talk about my feelings of grief with others, and instead focused on working as hard as I could. This led me to place too much pressure on myself, which resulted in me experiencing a burn-out in conjunction with severe symptoms of depression. The second time occurred when my wife and I had relationship issues. Over the years, we grew apart and were no longer able to live together. Ultimately, we decided to split up, which culminated in a very difficult period for me. During this time, my mother also became very ill, and I spent considerable time taking care of her. I’ve come to realize over the last several years that I have not spent enough time thinking about what I really want and what I care about. Rather, I focused too much on both the opinions and needs of others. In combination with these other life events, I was no longer able to sufficiently cope with the stress I was experiencing. Through therapy, I learned to listen to my own feelings and to do what is right for me. I have also become cognizant of the fact that I am vulnerable to developing symptoms of depression, and, as such, that I need to keep a close eye on myself. In doing so, I hope to prevent new symptoms. I drew up a relapse prevention plan, which lists activities that I can do whenever I feel that I am on the verge of relapsing. This helps me to focus on doing activities that I know are good for me, but that I simply do not always fancy doing, such as, for example, meeting friends, working out or cleaning my home.

While both my family and my job are still incredibly important to me, I no longer let them take control of my life.”

This is the case of John1, a patient who is currently in remission from depression.

Like many other patients who have experienced depressive episodes, there is a risk that he may relapse. John is aware of his vulnerability to relapse and thus tries to prevent this through employing relapse prevention strategies. This means that if John experiences an increase in his symptoms, he knows what to do in order to try and prevent a full-blown relapse.

It is evident from clinical practice and scientific literature that many patients who have experienced depression lack the relapse prevention strategies that are required to prevent relapse. This is partly due to the fact that relapse prevention is currently granted insufficient attention within the context of mental health care. Besides the prevention of depressive disorders – as mentioned in the case of John – the prevention of anxiety disorders also warrants closer attention, because these disorders are just as prevalent and have high recurrence rates. Given the aforesaid lack of attention to relapse prevention and the concurrence of anxiety and depressive disorders, the

1 The case of John is a hybrid case with a fictive name, based on multiple patients.

General introduction | 9

present thesis examines relapse prevention strategies for patients in remission from both anxiety and depressive disorders.

The introductory chapter of the thesis provides background information on anxiety and depressive disorders before proceeding to explicate the epidemiology, burden of disease and course of symptoms for anxiety and depressive disorders. Next, the chapter provides an overview of the common treatment methods for anxiety and depressive disorders, along with the opportunities for relapse prevention, the current organization of care related to relapse prevention, the role of mental health professionals (MHPs), and the expedience of applying self-management strategies to prevent relapses. Finally, the chapter outlines some of the limitations of current relapse prevention programs, before then providing a brief description of the GET READY relapse prevention program. The chapter closes by delineating the aims and outline of the thesis.

Anxiety and depressive disorders Anxiety disorders are classified as a group of mental disorders that are characterized by anxiety and fear. These disorders, according to the classification of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) [1], include panic disorder (with or without agoraphobia), agoraphobia, specific phobia, social phobia, generalized anxiety disorder, obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD) (Table 1). Although OCD and PTSD have subsequently been reclassified within other categories in the DSM-5, the descriptions below correspond to their previous categorization in the anxiety disorders group in the DSM-IV. Depressive disorders, including major depressive disorder and dysthymia, are characterized by a sad mood and loss of interest or pleasure (Table 1). For the purposes of this thesis, the decision was made to use the classifications from the DSM-IV, because at the start of the study, DSM-5 was not yet implemented in Dutch mental health care.

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Table 1. Anxiety and depressive disorders according to DSM-IV.

Anxiety disorders according to DSM-IV Panic disorder (with or without agoraphobia) The most important characteristics of a panic disorder are recurrent, unexpected panic attacks, ongoing concern about experiencing a further panic attack as well as its possible implications and consequences, and a change of behavior related to the attacks. These panic attacks consist of short periods of intense fear or discomfort, accompanied by physical and psychological symptoms, which typically subside after 10 minutes. Panic disorders can be diagnosed both with or without agoraphobia. When patients experience a panic disorder with agoraphobia, they subsequently avoid certain situations or places to prevent a further attack.

Agoraphobia Patients with agoraphobia experience anxiety over being in places or situations that are either difficult or embarrassing to escape from, or in which help is not available if they need it. More specifically, patients often experience extreme fear if they have to travel in a bus, train or car, are in a crowd or standing in a line, are on a bridge, or are outside on their own. These situations are typically either avoided, or endured with great distress.

Specific phobia Patients with a specific phobia experience an excessive fear of specific objects, animals or situations. Exposure to these kind of stimuli induces an anxiety response. Frequent specific phobias are, for example, the fear of spiders, mice, elevators and flying. Most of the time these stimuli are avoided, and patients are cognizant of the fact that their fear is excessive or unreasonable.

Social phobia Social phobia (or social anxiety disorder as it is also known) is characterized by a persistent fear towards social or performance-based situations. This is because patients with social phobia are afraid to humiliate or embarrass themselves, by, among other things, blushing or sweating. They ordinarily avoid social or performance-based situations, or attend and endure extreme distress.

Patients recognize that their fear is excessive or unreasonable, but are simply unable to overcome it.

Generalized anxiety disorder In most cases, patients who suffer from a generalized anxiety disorder experience excessive anxiety and worry towards a wide range of different situations or activities, for a period of at least six months. Patients find it incredibly difficult to control this worry, which is why they often experience additional symptoms, such as restlessness, irritability, sleep disturbance, distress, and impaired functioning.

Obsessive-compulsive disorder Patients with an obsessive-compulsive disorder experience compulsive thoughts (obsessions) and/or other compulsions. Obsessions are recurrent and persistent thoughts, impulses or images that are experienced as intrusive and inappropriate, and cause anxiety and distress. An example of such thoughts would be a repeated thought that you may infect others or be infected by others, or a thought about hurting others. Ordinarily, patients try to control this disorder by engaging in compulsions, which are repetitive behaviors that seek to reduce distress or prevent a certain situation from occurring. Examples of such compulsions are cleaning, checking whether the door is locked or making sure things are positioned symmetrically.

Post-traumatic stress disorder Patients with a post-traumatic stress disorder have been exposed to a traumatic event and subsequently experience negative consequences in their daily lives. Patients re-experience this traumatic event in manifold ways, such as, for example, via recurrent distressing dreams or intrusive, distressing recollections of the event. Patients often avoid situations, people or objects that remind them of the traumatic event. Moreover, patients routinely experience symptoms of increased arousal, which were not present prior to the trauma.

General introduction | 11

Depressive disorders according to DSM-IV Major depressive disorder A major depressive disorder (MDD) is characterized by (1) having a depressed mood, and/or (2) a loss of interest or pleasure in daily activities. In addition to this, patients display several of the following symptoms: (3) sleep problems, (4) fatigue, (5) feelings of worthlessness or excessive or inappropriate guilt, (6) problems in concentration or decision-making, (7) change in appetite or weight change, (8) psychomotor agitation or retardation, and (9) thoughts of death and suicide.

In order to diagnose MDD, a patient must be experiencing at least five of the above nine symptoms. These symptoms should be present across the largest part of the day and occur on an almost daily basis, for at least a two-week period. Furthermore, MDD can result in impaired social, occupational and/or educational functioning.

Dysthymia Dysthymia is classified as a more persistent and chronic form of depression, but with milder levels of symptoms. Symptoms are typically present for at least a two-year period.

Epidemiology and burden of disease Around 615 million people globally are affected by anxiety and depressive disorders, which means that these disorders are among the most prevalent mental health disorders [2]. In the Netherlands, around 20% of the population experience an anxiety and/or depressive disorder over the course of their life [3].

Anxiety and depressive disorders place a heavy burden on people, insofar as these disorders are associated with a high level of disability and reduced quality of life, functioning and well-being [4–6]. Moreover, these disorders also cause a tremendous economic burden worldwide [7].

Anxiety and depressive disorders often coincide with one another [8]. Of all those patients that are currently diagnosed with an anxiety/depressive disorder, the vast majority (75-81%) have experienced a comorbid depressive/anxiety episode at least once in their life [9]. The comorbidity of these disorders has been found to be associated with long-term disability from work, increased absenteeism, longer duration of symptoms, and increased symptom severity [9,10].

Course of symptoms Many patients with an anxiety and/or depressive disorder experience chronic symptoms. Chronicity levels range from 24.5% for patients with depression, up to 41.9% for patients with anxiety, and as high as 56.8% for patients with comorbid depression and anxiety [11]. Risk factors for anxiety and depression chronicity are early onset, high psychopathology, loss or adversity during childhood, longer duration of index episode, higher number of previous episodes, older age, and comorbid depression and anxiety [11–13]. Patients in remission from an anxiety or depressive

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disorder are prone to relapse, with up to 57% of remitted patients experiencing a relapse of either their index disorder or another anxiety or depressive disorder within the first four years of remission [14]. The relapse rates among patients with anxiety disorders have been reported as ranging from 22% to 58% [11,15–17], while among patients with depressive disorders the relapse rates vary from 27% to 77% [18–21].

These reported differences in relapse rates may, in part, derive from variation in baseline symptoms, different definitions of relapse, different follow-up durations, and different treatments provided in the acute phase. Several risk factors for relapse have been identified in extant literature. Patients that achieve partial rather than full remission are at a higher risk of relapse [22,23]. With respect to patients with anxiety disorders, decreased functioning, anxiety sensitivity, and previous episodes of anxiety have been identified as risk factors for relapse [16,24]. Risk factors for relapse among patients with depressive disorders are, among other things, a high number of previous episodes, negative experiences in youth, and a prior severe depressive episode [25,26].

Remission and recovery There is a long-standing debate in academic literature concerning how to define remission, partial remission and recovery. Full remission indicates that the patient no longer meets the DSM criteria for a particular disorder and experiences no more than minimal symptoms [27]. Partial remission also indicates that the patient no longer meets the DSM criteria for a disorder, but that they nevertheless continue to display minimal symptoms. While these aforesaid definitions by Frank et al. [27] are commonly used, they leave room for interpretation, insofar as it is often difficult in practice to determine whether someone is experiencing ‘minimal symptoms’ or ‘more than minimal symptoms’.

An extensive array of questionnaires have been used to assess symptom severity, while a variety of cut-off points are used to define (partial) remission and relapse. For example, several studies classify patients as being in remission if they score <10 [28–30] on the Hamilton Depression Rating Scale-17 (HDRS-17), while others use a cut-off of <11 [31–33], or even <14 in some studies [34,35]. These examples underscore the heterogeneity of definitions used in research.

A further issue is that the term recovery is also frequently used in the literature to indicate that a longer period of remission has been achieved and that patients have subsequently entered into the maintenance phase [27] (Figure 1). If someone is recovered, then treatment will either be discontinued, or the focus of the treatment will shift to the prevention of a new episode of the disorder. As well as symptomatic recovery, people also recover their ability to function and participate in society, to return to work or study, and live their lives in accordance with their own preferences and standards. In this respect, recovery also refers to “a movement towards health

General introduction | 13

and meaning rather than avoidance of symptoms” [36]. In the present thesis, we use the term remission to indicate both full and partial remission and recovery. Remission implies that a patient no longer meets the criteria for a DSM disorder. Although these terms are primarily used in extant literature on depressive disorders, they are also applicable to anxiety disorders.

Relapse and recurrence In parallel with the aforementioned debate about remission and recovery, there is a similar debate in the field pertaining to the use of the terms relapse and recurrence.

Relapse is defined as “a return of symptoms satisfying the full syndrome criteria for an episode that occurs during the period of remission, but before recovery” [27] (Figure 1). The term ‘recurrence’ is often used alongside ‘relapse’ in extant literature. The difference between the two terms derives from their distinct timeframes: a relapse occurs after a period of remission in the continuation phase, while a recurrence occurs after a period of recovery within the maintenance phase (Figure 1). In this thesis, the term relapse is used to indicate both relapse and recurrence, as these terms are often used interchangeably in the literature [37].

Figure 1. Overview of definitions. Modified based on criteria from Frank et al. [27].

Treatment In recent decades, research has shown that many treatments for anxiety and depressive disorders in the acute phase are effective [38,39]. In accordance with national and international guidelines, the treatment for these disorders often consists of psychological and/or pharmacological treatments [40–43]. Out of the available psychological treatments, cognitive behavioral therapy (CBT) has received the most

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attention from researchers. CBT aims to challenge and change negative thought patterns (cognitions), as these profoundly impact upon how people react to (stressful) situations, as well as how they behave and feel. Behavioral activation is also a critically important aspect of CBT, which focuses on increasing people’s engagement in activities and decreasing their avoidant and isolating behaviors. CBT has been found to be effective in reducing symptoms for both anxiety and depressive disorders [44,45].

Other forms of evidence-based psychological treatments are psychodynamic therapy, interpersonal therapy, and mindfulness [38]. In clinical practice, a variety of treatments are used for patients with depressive disorders, while exposure therapy is the most common treatment for patients with anxiety disorders. Psychological and pharmacological treatments appear to be equally effective for patients with anxiety and depressive disorders [46]. In fact, a combination of both psychological and pharmacological treatments has been argued to be the most effective [47]. However, many patients favor psychological treatments over pharmacological treatments [48,49].

Motivation for this preference may stem from the fact that patients assume that psychological treatments solve the cause of the disorder, or it may be grounded in health concerns related to the side effects of medication [49,50].

Traditionally, treatments are provided by a professional via face-to-face (FTF) contact. However, in light of the outbreak of COVID-19 and ongoing lockdown measures, there has been a marked shift towards conducting treatments online.

Ordinarily, online treatment consists of online E-health modules, personal feedback from a professional, and the possibility to exchange text messages via an online platform and engage in video calls. These E-health modules are based on regular treatment protocols and are divided into separate lessons. Their principal difference from traditional treatments is the delivery mode of the treatment. Specific advantages of online treatments are that they are easily accessible, potentially more cost-effective, facilitate multimedia interactivity, and enhance the possibilities for symptom monitoring [51,52].

Given that patients who have undergone treatment for anxiety and depressive disorders often experience relapse, and the risk of relapse increases with every new episode, one of the major challenges in terms of managing these disorders is the prevention of relapse [53]. Although national and international guidelines [40–43] stipulate that attention should be paid to relapse prevention over the course of treatment, it appears that this is often not the case in clinical practice. During informal conversations with therapists, some noted that during treatment they solely wanted to focus on positive aspects, rather than discussing ‘negative’ subjects such as a patient’s vulnerability to relapse. This was found to be the same for patients themselves: therapists were under the impression that patients did not want to be confronted with their vulnerability to relapse. However, due to the high prevalence of relapse, paying special attention to relapse prevention is warranted.

General introduction | 15

Relapse prevention After completing treatment in mental health care, patients who are vulnerable to relapse should be provided with relapse prevention strategies. Given the high relapse rates among patients with anxiety and depressive disorders, paying sufficient attention to relapse prevention is especially pertinent for this group of patients. Generally speaking, the guidelines recommend two relapse prevention strategies for patients who are in remission from anxiety and depressive disorders: 1) continuation of antidepressant medication (ADM), and 2) psychological relapse prevention interventions [41,54–56].

Although continuation of ADM after treatment in the acute phase has been shown to reduce relapse rates [57–59], not to mention that relapse rates are lower for those who continue to use ADM than for those who discontinue use [57,58], psychological relapse prevention interventions are potentially preferable to maintenance ADM (M-ADM) for the following reasons. First, M-ADM can often be accompanied by serious adverse effects [60], which, in turn, might lead to non-adherence [61]. Moreover, most patients have reservations about the long-term effects of using medication [62], while discontinuation of ADM has also been found to be challenging [57,58]. Second, given that patients prefer psychological treatments over pharmacological treatments [48,49], they may also prefer psychological interventions over M-ADM to prevent relapse. Finally, there is evidence to suggest that psychological relapse prevention interventions are more effective in preventing relapse than ADM [63].

The combination of ADM and psychological relapse prevention interventions appears to be a promising approach in this respect, albeit this approach needs to be tailored to individual patients [31]. For example, some patients might experience positive effects from M-ADM and, hence, no longer feel the need for additional psychological interventions. Others might prefer psychological interventions, because they feel these interventions target the underlying causes of their disorder, while others may experience the most benefit from a combination of M-ADM and psychological interventions. This serves to illustrate why relapse prevention strategies need to be customized to each patient, insofar as doing so is likely to enhance both adherence to, and the effectiveness of, the treatment.

Preventive cognitive therapy (PCT), CBT and mindfulness-based cognitive therapy (MBCT) are the predominant evidence-based psychological relapse prevention interventions for depressive disorders. All relapse prevention programs ordinarily consist of the following key ‘ingredients’: a relapse prevention or crisis management plan, symptom monitoring, psychoeducation, reinforcement of self-management strategies, feedback and homework exercises [64–67]. In most studies, psychological relapse prevention interventions are carried out in an outpatient mental health care setting. Most of these programs involve FTF contact, but programs using online formats are increasingly available [68]. Another format that acquires greater consideration is

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a blended format, which offers both FTF contact and online components. While one major advantage of online sessions is that they are potentially (cost) effective, if little to no guidance is offered, then patients often find it difficult to adhere to the program [69–71]. Consequently, the combination of FTF contact and online sessions might constitute an effective approach to relapse prevention.

In contrast to the strong evidence base for relapse prevention in depressive disorders, only a handful of psychological relapse prevention randomized controlled trials (RCTs) have been conducted among patients with remitted anxiety disorders. For example, White et al. [81] found that patients who received maintenance CBT had lower relapse rates compared to those patients who only received assessment. Scholten et al. [82] concluded that there was no significant difference between the relapse rates for patients who received both CBT and discontinuation of ADM and those who only received discontinuation of ADM. From a patient perspective, there appears to be a need for further support from professionals regarding relapse prevention [72,73]. Indeed, Muntingh et al. [72] found that patients prefer a relapse prevention program that includes regular FTF contact with a professional, flexible time investment based on their individual needs, and a personalized prevention plan.

Organization of care In the Netherlands, there has been an emergent focus on the prevention of diseases – especially over the past decade – both in terms of preventing new disorders and recurring disorders. Consequently, self-management and recovery have taken on increased importance and been pinpointed as requiring attention, such as, for example, through E-mental health programs [74]. The impetus here is to provide effective care with the lowest possible intensity, which means that patients without a DSM disorder or who exhibit very mild symptoms receive care in primary care practices, patients with mild and moderate disorders receive care from the ‘generalist basic’ mental health services [GB-GGZ], while patients with severe and complex disorders receive care from specialized mental health care services [S-GGZ]. The rationale for this is that it would signal a partial shift away from treating patients in intensive, specialized mental health care services towards treatment in less intensive mental health services, including primary care. In order to support general practitioners (GPs) in primary care practices, a mental health professional (MHP) [POH-GGZ] is now available in most general practices. As described below, these MHPs can encourage patients to utilize self-management strategies in order to effectively cope with their disorder and its attendant consequences, and in terms of supporting remitted patients to prevent relapse.

General introduction | 17

Role of mental health professionals Mental health care in primary care is primarily provided by MHPs, who consist of (community) mental health nurses, social workers or psychologists, and report to the GP. Given that GPs are ordinarily located nearby patients’ homes, not to mention that these services are freely available, MHPs are easily approachable. Consequently, they play a pivotal role in terms of symptom monitoring, encouraging self-management, and, ultimately, relapse prevention [75].

In an ideal situation, therapists send a referral letter to the GP/MHP after patients have undergone treatment within specialized mental health care. The MHP would then contact the patient to organize a meeting. Patients can also contact the MHP after completing treatment to arrange a meeting. In this meeting, the MHP would discuss what the patient needs to do in the event of impending relapse, and provide them with self-management strategies that they can use. They will then collectively decide upon the frequency of their FTF contact. During these moments of FTF contact, shared decision-making between MHPs and patients is of vital importance for maintaining and empowering patients’ mental health.

Today, MHPs are expected to provide relapse prevention programs to patients who are in remission from an anxiety or depressive disorder. However, research has shown that MHPs feel that they require additional tools to provide more effective relapse prevention programs [72].

Self-management John: “Last Monday I had an appointment with my mental health professional. Every 3 months I have a ‘check-in appointment’, in which we discuss how I am doing and how I have handled difficulties. On this occasion, we discussed strategies to stay mentally fit. For me, it always helps to visit friends, and I know I should keep doing this, even if I don’t feel like doing it. My mental health professional challenged me to think of other things I can do to gain more control over my life. She suggested using self-management strategies, such as gaining more knowledge about my depression, keeping a diary to monitor my symptoms, engaging in activities such as sports, and building a routine of activities. Together we picked a few of these strategies that I could try out over the next 3 months. Although it is not always easy for me, it feels good to actively work on my recovery and to notice that I am feeling better. It especially helps me to routinely plan activities. What also helps is the knowledge that I have a check-in appointment with my mental health professional every 3 months, as she is very supportive, and we can evaluate my activities together.”

Given that the course of anxiety and depressive disorders often resemble the course of chronic diseases, a chronic disease care model is required [76]. Within a chronic care model, self-management plays an integral part in managing chronic diseases [77–79]. Self-management has been defined in manifold ways. Lorig [80] defines self-

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management as “learning and practicing skills necessary to carry on an active and emotionally satisfying life in the face of a chronic condition” (p. 11), while Barlow et al.

[81] define it as “the individual’s ability to manage the symptoms, treatment, physical and psychosocial consequences and life style changes inherent in living with a chronic condition”(p. 178). A central theme within both of these definitions is enhancing individuals’ abilities and skills to deal with a chronic disease, which includes, among other things, action planning, decision-making, and the formation of a patient-provider partnership [79].

In recent years, there has been an emergent recognition of the importance of recovery within mental health care [82,83]. With respect to recovering from mental health disorders, self-management has been identified as being of paramount importance [84–86], and, in fact, as being essential to the prevention of relapse. While this increased focus on recovery has hitherto principally been targeted at patients with severe mental disorders, it could also be applicable to patients with anxiety and depressive disorders, for whom the disorder has a chronic course. Generally speaking, patients with mental health disorders display a positive attitude towards employing self-management strategies as part of their recovery, and, indeed, most of them have the capability to use them [87,88]. However, it might not be as straightforward for all patients with anxiety and depressive disorders to employ the self-management strategies that are most appropriate for their personal situation. For example, it was found that patients with higher scores of anxiety and depressive symptoms after heart surgery, engaged in less self-management strategies [89]. Therefore, it is critically important to encourage and support patients to use self-management strategies that are particularly relevant for their specific situation. Doing so is vital, because research has shown that if self-management techniques are sufficiently utilized by patients, then this can reduce their symptoms and improve their overall functioning [90], which, in turn, helps to prevent a subsequent relapse.

Limitations of current relapse prevention programs It is important to note that there are specific limitations with current psychological relapse prevention programs. First, there are no relapse prevention programs currently available that target both anxiety and depressive disorders, which is problematic given that these disorders are often comorbid and people often relapse into another disorder (i.e., from an anxiety disorder into a depressive disorder, and vice versa). Second, the programs are currently not specifically tailored to patients’ individual preferences, which has been shown to increase acceptance and adherence towards the program, as well as it subsequent effectiveness [91]. Third, many programs continue to be provided solely in outpatient mental health care, despite the fact that primary care facilities are increasingly supposed to provide relapse prevention programs, with MHPs

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taking a leading role. Fourth, to the best of our knowledge, no blended interventions for patients in remission from anxiety and depression are currently available, which once again is problematic insofar as this provides a promising approach.

GET READY program In order to address these aforesaid limitations of current programs, we developed the GET READY relapse prevention program. GET READY stands for Guided E-healTh for RElapse prevention in Anxiety and Depression. The program focuses on patients who are in remission from anxiety disorders and/or depressive disorders. Patients’ preferences were explicitly taken into account through the inclusion of regular FTF contact with professionals, flexible time investment from patients, and a personalized relapse prevention plan [72]. Furthermore, the relapse prevention program was specifically developed to be provided in primary care by MHPs. Alongside FTF contact between patients and MHPs, in which relapse prevention was discussed and a personalized relapse prevention plan was developed, the program also consisted of online E-health modules that were designed to encourage the use of self-management strategies. Finally, the program offered a mood and anxiety diary to patients, which enabled them to monitor their symptoms.

Aims and outline of the thesis This thesis focuses on relapse prevention amongst patients with remitted anxiety and depressive disorders. Hence, it aims to contribute towards improving the quality of life for these patients. First, we conduct a systematic review and meta-analysis of extant psychological relapse prevention interventions, in order to assess their effectiveness for patients with remitted anxiety or depressive disorders. Next, we evaluate the newly developed GET READY relapse prevention program within several empirical studies.

Finally, given our focus on the use of self-management strategies, we psychometrically test a newly developed self-management questionnaire. The thesis is structured as follows.

Chapter 2 presents the findings of our systematic review and meta-analysis of whether psychological relapse prevention interventions are effective in preventing relapse. Pubmed, PsycINFO and Embase were systematically searched for RCTs (n = 40) including patients with remitted anxiety or depressive disorders, who either received a psychological intervention to prevent relapse, or received treatment as usual. In addition, studies were included that compared psychological interventions in addition to M-ADM to M-ADM only. Chapter 3 delineates the study protocol of the GET READY study. It describes the development, implementation and evaluation of the GET READY program. For the overall research project, a mixed-method study design was chosen to provide insight into patients’ usage of the program (quantitative), the

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association between usage intensity and the course of symptoms (quantitative), as well as the perspectives of users (both patients and MHPs) of the program (qualitative).

Chapter 4 presents the results of the quantitative evaluation of the GET READY program. A total of 113 patients participated in the GET READY study, by completing four questionnaires over the course of 9 months. The GET READY program was implemented by 54 MHPs across the Netherlands. Patients had access to the online modules and had FTF meetings with MHPs. Insight was gained into the usage intensity, course of symptoms, and the association between usage intensity and course of symptoms. Chapter 5 reports the results of the qualitative evaluation of the GET READY program. This study aimed to shed light on both the perspectives of users (both patients and MHPs) of the GET READY program, and those factors that influenced the use and implementation of the GET READY program in general practice. Through conducting individual semi-structured interviews with pairs of patients and MHPs (N=26) and two additional focus groups, we gained insight into patients and MHPs’ experiences and perspectives. In Chapter 6, the results of the exploratory and confirmatory factor analysis of the ‘Assessment of Self-management in Anxiety and Depression’ questionnaire (ASAD) are described. This questionnaire examined the self-management strategies utilized by 171 patients with (chronic or partially remitted) anxiety and depressive disorders, in order to examine the underlying factor structure and psychometric properties. Finally, Chapter 7 provides a summary of the main findings of the research, before proceeding to discuss the results in context of extant literature and describe the implications for future research and clinical practice.

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PSYCHOLOGICAL INTERVENTIONS TO PREVENT RELAPSE IN ANXIETY AND DEPRESSION: A SYSTEMATIC REVIEW AND META-ANALYSIS SUBMITTED FOR PUBLICATION

Esther Krijnen-de Bruin, Willemijn D. Scholten, Anna D.T. Muntingh, Otto R. Maarsingh, Berno van Meijel, Annemieke van Straten, Neeltje M. Batelaan

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Abstract Purpose The aim of this review is to establish the effectiveness of psychological relapse prevention interventions, as stand-alone interventions and in combination with maintenance antidepressant treatment (M-ADM) or antidepressant medication (ADM) discontinuation for patients with remitted anxiety disorders or major depressive disorders (MDD).

Methods A systematic review and a meta-analysis were conducted. A literature search was conducted in PubMed, PsycINFO and Embase for randomized controlled trials comparing psychological relapse prevention interventions to treatment as usual (TAU), with the proportion of relapse/recurrence and/or time to relapse/recurrence as outcome measure.

Results Forty RCTs were included. During a 24-month period, psychological interventions significantly reduced risk of relapse/recurrence for patients with remitted MDD (RR 0.76, 95% CI: 0.68-0.86, p<0.001). This effect persisted with longer follow-up periods, although these results were less robust. Also, psychological interventions combined with M-ADM significantly reduced relapse during a 24-month period (RR 0.76, 95% CI: 0.62-0.94, p=0.010), but this effect was not significant for longer follow-up periods.

Conclusions In patients with remitted MDD, psychological relapse prevention interventions substantially reduce risk of relapse/recurrence. It is recommended to offer these interventions to remitted MDD patients. Studies on anxiety disorders are needed.

Systematic review registration number PROSPERO 2018: CRD42018103142 Keywords: Anxiety disorder, Major depressive disorder, Psychological interventions, Relapse, Recurrence, Review

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Introduction Anxiety and depressive disorders are a major public health issue, affecting approximately 615 million people worldwide [1]. In recent decades, many treatments for anxiety and depression in the acute phase have proven effective [2,3]. However, relapse1 is common in these patients [4,5], even for those who have adequately responded to treatment in the acute phase. In anxiety disorders, 29% of patients experienced relapse within 12 months following treatment [6]. Likewise, with regard to major depressive disorder (MDD), 30% of patients relapsed within 24 months after treatment [7]. Most explanations for the high relapse risk in anxiety disorders and MDD are based on two hypotheses: 1) some individuals have a greater premorbid vulnerability than others, and this risk remains constant across the course of successive episodes, or b) ‘the scarring-hypothesis’, which suggests that each depressive episodes leaves residual effects that increase vulnerability for the next episode [8], caused by biological factors, cognitive factors and stress-related factors. Effective treatment in the acute phase therefore does not guarantee a good prognosis over time. This suggests that relapse prevention is required in order to keep remitted patients stable over time.

Guidelines for anxiety disorders and MDD generally recommend two strategies for preventing relapse after remission has been achieved: 1) continuation of antidepressant medication (ADM), and/or 2) psychological relapse prevention interventions [9–12].

Continuation of ADM after treatment in the acute phase reduces relapse rates [13–15].

Meta-analyses indicate that, when ADM is continued after the initial response to ADM, 16-18% of patients with remission from an anxiety or depressive disorder experienced relapse, while 36-41% of these patients relapsed if ADM was discontinued [13,14].

However, psychological relapse prevention interventions might be a better treatment option for some patients than maintenance ADM (M-ADM) for several reasons. First, patients who experience serious adverse effects of M-ADM (e.g. sexual dysfunction, dry mouth) [16] might be reluctant to adhere to ADM during asymptomatic periods [17]. Indeed, non-adherence to ADM is apparently common among remitted patients [18]. Second, because patients prefer psychological treatment over pharmacological treatment [19], they might also prefer psychological interventions to M-ADM for relapse prevention. The long-term use of ADM may therefore be neither feasible nor desirable for every remitted patient. A third reason, as reported in one meta-analysis, is that psychological interventions were more successful than ADM in preventing relapse, as patients receiving psychological interventions had 17% less risk

1 In this paper, the term ‘relapse’ is used to refer to both relapse and recurrence, as these terms are often used interchangeably [67], indicating a return to full symptoms and meeting the criteria for anxiety disorder or MDD following remission or recovery [68].

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of relapse than patients receiving M-ADM [20]. Therefore, psychological interventions are important in the prevention of relapse.

Meta-analyses focusing on psychological relapse prevention interventions for depressive disorders indicate that these interventions are effective in preventing relapse, with reductions of 22-50% in relapse [20–25]. Most of the studies included focused on cognitive behavioral therapy (CBT), cognitive therapy (CT) and mindfulness-based cognitive therapy (MBCT). Meta-analyses conducted by Biesheuvel-Leliefeld et al. [20] and by Clarke et al. [21] also included studies on interpersonal therapy (IPT). To date, no systematic reviews and/or meta-analyses are available with regard to psychological interventions for preventing relapse in patients with remitted anxiety disorders. This is remarkable, given the high prevalence of anxiety disorders, particularly in light of the fact that relapse is at least as prevalent in anxiety disorders as it is in MDD [4].

Previous meta-analyses contain very little information about the effectiveness of adding psychological interventions to M-ADM or the discontinuation of ADM, even though this approach could be promising for preventing relapse [26]. Although metaanalyses have reported results of studies allowing the use of M-ADM, they include no separate analyses concerning the additive effect of psychological interventions during M-ADM or discontinuation of ADM. Furthermore, existing meta-analyses report on only a limited follow-up duration of 24 months, while studies with longer follow-up durations are becoming increasingly available. Moreover, no meta-analyses have been performed with regard to the effectiveness of psychological relapse prevention interventions for patients with remitted anxiety disorders. For clinical practice, it is also important to know whether the timing and type of interventions are associated with relapse risks. For example, it has not been consistently examined and reported whether relapse prevention interventions are more effective for patients who have received other interventions prior to the relapse prevention intervention [20,21,25]. Additional insight into influencing factors could provide recommendations for clinical practice.

The current systematic review and meta-analysis is intended to update current research, leading to more robust estimates of the effects of psychological interventions for preventing relapse. Besides, this study is intended to extend previous research by 1) including studies regarding the prevention of anxiety disorders, 2) including studies with longer follow-up durations, 3) studying the effects of adding psychological interventions to maintenance ADM or discontinuation of ADM, as most remitted patients are using ADM or discontinue their medication, and 4) performing subgroup analyses on timing and type of interventions. Furthermore, current gaps in research will be identified and these could serve as research agenda for future research. In short, the aim of this systematic review and meta-analysis is to examine the effectiveness of psychological relapse prevention interventions, as compared to treatment as usual, for patients with remitted anxiety disorders or MDD.

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Methods Design To examine the effectiveness of psychological interventions, we conducted a systematic review and meta-analysis. We also performed subgroup-analyses and meta-regression analyses to investigate whether the timing and type of interventions were associated with risk of relapse. The study was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [27].

The protocol for this systematic review and meta-analysis was registered in PROSPERO with the number CRD42018103142 (https://www.crd.york.ac.uk/prospero/display_ record.php?ID=CRD42018103142).

Literature search We searched PubMed, PsycINFO and Embase (from inception to February 2020) for randomized controlled trials including patients with a remitted anxiety disorder or MDD who had received a psychological intervention to prevent relapse, comparing this intervention to TAU, and reporting on relapse rate and/or time to relapse. A certified librarian (CP) and EKB performed the search using the following search terms: depressive disorder, anxiety disorder, psychotherapy, relapse/recurrence, and randomized controlled trials. Terms were adapted for each database, and no limits or filters were applied (see Appendix 2.1). Only published articles written in English or Dutch were included.

The following inclusion criteria were applied: a) a randomized controlled trial, b) examining adult patients (18 years and older) with a prior anxiety disorder and/or MDD, c) who were in remission at randomization, d) receiving a psychological intervention with the aim of preventing relapse, e) compared with TAU, and f) with relapse rates and/or time to relapse as outcome.

For ‘remission’, ‘relapse’ and ‘recurrence’, we used the definitions applied in the original articles. No time limits were applied with regard to when patients had experienced their prior anxiety disorders and/or MDD. All follow-up durations were allowed. We considered psychological relapse prevention interventions as stand-alone treatments, as well as psychological relapse prevention interventions combined with M-ADM or with discontinuation of ADM. Psychological relapse prevention interventions as stand-alone treatments were compared to TAU. TAU was considered as treatment that patients would normally receive, and could consist of no treatment at all; evaluation only; monitoring; non-specific support; or any

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other treatment that was not specifically aimed at relapse prevention. Therefore, studies in which two psychological interventions aimed at preventing relapse were compared to each other were excluded. Because maintenance treatment with antidepressants in itself reduces the risk of relapse, and because discontinuation of antidepressants in itself increases such risks, studies in which a psychological relapse prevention intervention was given in combination with one of these treatment strategies were considered separately. When examining the effect of psychological relapse prevention interventions in combination with M-ADM, the control group also consisted of M-ADM. Likewise, when psychological prevention interventions were given in combination with discontinuation of ADM, the control group also consisted of discontinuation of ADM. An overview of interventions and controls is provided in Table 1. Stepped care studies were excluded, because not all patients in one condition received the same treatment.

Table 1. Overview of comparisons of interventions and control groups, for anxiety and depression studies with different follow-up durations.

Intervention

Control

Psychological interventions

Treatment as usual

Psychological interventions + M-ADM

M-ADM

Psychological interventions + discontinuation of ADM

Treatment as usual + discontinuation of ADM

Note: psychological interventions = cognitive behavioral therapy (CBT), cognitive therapy (CT), preventive cognitive therapy (PCT), internet-based CBT, continuation cognitive therapy (C-CT), maintenance cognitive behavioral therapy (M-CBT), mobile cognitive therapy, mindfulness-based cognitive therapy (MBCT), interpersonal psychotherapy (IPT), (cognitive) psychoeducation ((C)PE) with therapeutic components, cognitivebehavioral analysis system of psychotherapy (CBASP); M-ADM = maintenance antidepressant medication; treatment as usual = no treatment, evaluation only, monitoring, non-specific support.

The screening of titles and abstracts was performed by three researchers: EKB screened all of the records, with WS and JG each screening half of the records. The computer program ‘Rayyan’ was used to facilitate this process [28]. After the initial screening, the full-text screening was also performed by three researchers: EKB screened all of the records, with WS and JG each assessing half of the records. Disagreements were resolved by consensus-based discussion until consensus was reached.

Data extraction Data were extracted using a template based on the Cochrane Data Extraction and Assessment Template [29]. The following data were extracted: 1) participant

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characteristics (including age, gender, number of previous episodes required for inclusion in the study, number of participants), 2) study characteristics (including study setting, definition of remission, definition of relapse, relapse rates, duration of followup) and 3) intervention and comparison characteristics (including type and duration of intervention). Each of the three researchers independently extracted the data from the articles using this template. These sheets were subsequently compared to check the extracted data. In the event of uncertainties about the data, the authors of the original articles were contacted to provide clarification. Remaining disagreements were resolved by discussion with NB until consensus was reached. When relapse rates were not provided in the article, they were computed based on the number of relapses and the total number of patients in each group.

Quality assessment We used the Cochrane Collaboration’s tool for assessing risk of bias in order to assess the quality of the studies [30]. For each study, the risk of bias was assessed for the domains ‘random sequence generation’, ‘allocation concealment’, ‘blinding of outcome assessment’, ‘incomplete outcome data’, ‘selective reporting’ and ‘other bias’, with a low, high or unclear risk. This task was performed by two researchers (EKB and WS).

Disagreements were resolved by discussion until consensus was reached.

Meta-analysis We aimed to establish the effectiveness of psychological relapse prevention interventions in anxiety disorders and MDD, distinguishing three intervention groups— psychological interventions a) as stand-alone treatments, b) in combination with M-ADM and c) in combination with ADM discontinuation—along with their control counterparts (i.e. TAU, M-ADM, discontinuation of ADM). The primary outcome measures were proportion of relapse and time to relapse. Meta-analysis was used to synthesize the findings, with effect sizes measured as risk ratios for relapse. Risk ratios with 95% confidence intervals were chosen, as they are more conservative than odds ratios are [31], and they can be easily compared with other systematic reviews [20–23].

Effect sizes were based on intention-to-treat (ITT) data. The studies included differed according to various aspects, including type of disorder, interventions and demographic variables. Heterogeneity was therefore assumed. For this reason, a random effects model was used for the meta-analysis of the studies. Heterogeneity was explored using the Q-value and the I² statistic. A significant Q-value indicates evidence of heterogeneity [32]. The I² statistic is the ‘percentage of total variation across studies that is due to heterogeneity rather than chance’. It can range from 0 to 100, with values of 25%, 50% and 75% indicating low, moderate and high heterogeneity, respectively [33]. In cases where there was a paucity of data, no meta-analysis was performed. Qualitative description of the data was provided instead.

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Separate analyses were planned to synthesize studies including patients with anxiety disorders and MDD. Studies that allowed medication use were included in the main analysis, and the impact of including these studies was assessed using a sensitivity analysis. Studies in which medication use was not allowed were subjected to separate meta-analysis, and these results were compared to those of the main analysis.

Studies with two intervention groups and two control groups were analyzed separately.

For studies with two eligible interventions and one control group, the control group was split in half for the purpose of analysis, as proposed by Higgins et al. [34].

When possible, subgroup analyses were a priori defined and performed with regard to whether patients had received any intervention (psychological or pharmacological) prior to the relapse prevention intervention (yes/no), type of intervention (e.g. MBCT and CBT), setting (community, primary care, specialized care) and mode of delivery (online/face-to-face, guided/unguided). Meta-regression analyses were also a priori defined and performed to estimate the influence of the number of earlier episodes required for inclusion in the study and the duration of the interventions (in weeks) on the outcomes of the study. All subgroup analyses and meta-regression analyses were performed on the studies included in the main analysis.

The software package Comprehensive Meta-Analysis version 3.0 was used for analyses [35].

Results The titles and abstracts of 4,607 records were screened, after removing 2,717 duplicates. Of these records, 96 were assessed as full-text, 40 were included in the qualitative synthesis and 35 were included in the quantitative synthesis (see Figure 1).

Only two studies were found regarding the effectiveness of psychological interventions for the prevention of relapse of anxiety disorders [36,37]. It was therefore not possible to subject these studies to meta-analysis, and they were described qualitatively instead. Only three studies were identified in which ADM was discontinued, with different follow-up durations. These studies were also described qualitatively.

Although we had originally aimed to synthesize the results on time to relapse as well, this was often not reported. Even when it was reported, there was too much variation in the presentation of the results to allow for summarization. The effect of interventions on time to relapse was therefore not analyzed.

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Given that different studies had different durations of follow-up, we conducted separate analyses of studies with a follow-up duration up to and including 24 months and those with a follow-up duration of more than 24 months. This made it possible to include multiple papers about the same study with different follow-up durations (e.g. one up to and including 24 months and one of more than 24 months). For the main analysis, a follow-up duration up to and including 24 months was chosen with TAU as the control group.

Figure 1. Flowchart of the studies included.

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Characteristics of the studies The characteristics of the studies are presented in Appendix 2.2. The studies were published between 1990 and 2020. Sample sizes for the 35 studies that were included in the meta-analyses ranged from 14 to 460. In all, the studies concerned 3,729 unique patients, with 1,949 in the intervention groups and 1,780 in the control groups. Sixteen of the studies were conducted in specialized care. Seventeen studies evaluated some variant of cognitive behavioral therapy, according to the description of the original articles: cognitive behavioral therapy (CBT) (number of studies [k] = 4), cognitive therapy (CT) (k =4), preventive cognitive therapy (PCT) (k = 3), internet-based CBT (k = 2), continuation cognitive therapy (C-CT) (k = 2), maintenance cognitive behavioral therapy (M-CBT) (k = 1) and mobile cognitive therapy (k = 1). Eleven trials evaluated mindfulnessbased cognitive therapy (MBCT), five trials evaluated interpersonal psychotherapy (IPT), two trials evaluated (cognitive) psychoeducation ((C)PE) with therapeutic components and one trial evaluated cognitive-behavioral analysis system of psychotherapy (CBASP).

The duration of the interventions ranged from 6 to 156 weeks, and the duration of follow-up ranged from 6 to 66 months. Most studies offered face-to-face contacts in group format. Almost all interventions were standardized, followed a strict protocol, and most studies offered around 10 sessions. In addition, most of the studies included in our meta-analysis had a follow-up duration up to and including 24 months (k = 27).

Three studies [38–40] had two intervention groups and two control groups. One study had two intervention groups and one control group [41]. The total number of comparisons is therefore 26 for stand-alone psychological interventions and 9 for M-ADM combined with a psychological relapse prevention intervention, as compared to M-ADM only. Several studies had multiple follow-up points, varying from 26 to 66 months [42–49].

Risk of bias appraisal The risk-of-bias assessment for each study is summarized in Appendix 2.3. Risk of bias was generally low on the domains ‘random sequence generation’ (68% low risk of bias), ‘allocation concealment’ (58% low risk of bias), ‘blinding of outcome assessment’ (70% low risk of bias) and ‘incomplete outcome data’ (60% low risk of bias). As it was not possible to conceal psychological interventions from participants and personnel, all studies had a high risk of performance bias, and this is therefore not reported in Appendix 2.3. Most studies had an unclear risk of selective reporting bias, as many studies were not registered, study protocols were missing or pre-specified primary outcome measures were not reported. The risk of other bias was heterogeneous: 17 studies had a low risk of other bias, 9 had a high risk (e.g. due to specific problems mentioned by the authors, flaws in design, the absence of structured interviews or small sample) and 10 studies had an unclear risk of other bias.

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Studies on anxiety disorders Our literature search revealed two papers on the prevention of relapse in patients with remitted anxiety disorders. White et al. [37] compared M-CBT to assessment only, and included only patients for whom anxiolytic medication had already been discontinued.

Patients in the M-CBT group had significantly lower relapse rates (5.2%) compared to those in the assessment-only group (18.4%) at 21-month follow-up.

Scholten et al. [36] compared a CBT intervention plus discontinuation of ADM with discontinuation of ADM alone. They found no significant difference in relapse rates between patients in the intervention group and those in the control group (67% vs.

65%).

Studies on depressive disorders Psychological interventions versus treatment as usual Main analysis: ≤24 months Data were available for 21 comparisons with a follow-up duration up to and including 24 months. These studies had an average follow-up duration of 16.2 months, with a range of 8 to 24 months. In all, 2,715 patients were included in this analysis. The summary risk ratio of relapse was 0.76 (95% CI: 0.68-0.86, p<0.001, I2=25.312) for patients in the psychological intervention group versus TAU, indicating that risk of relapse was reduced by 24% for patients who received psychological relapse prevention interventions, as compared to those who received TAU. For patients in the intervention group, the summary relapse prevalence was 34.7% (95% CI: 28.0% - 41.9%), while for patients in the TAU group the summary relapse prevalence was 47.2% (95% CI: 40.0% - 54.6%). The Duval and Tweedie trim-and-fill procedure indicated a slight change in the RR after adjustment (summary adjusted risk ratio 0.80, 95% CI: 0.70-0.92), with four imputed studies.

Several of the studies included in this meta-analysis allowed the use of ADM during the intervention, while other studies did not [50–54]. A sensitivity analysis with only studies in which medication was not allowed (number of comparisons = 5) revealed a risk ratio of 0.67 (95% CI: 0.50-0.90, p=0.007). These results did not significantly differ from studies in which medication use was allowed.

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Figure 2. Meta-analysis of psychological interventions vs. TAU, up to and including 24 months.

Note. CI = confidence interval; CPE = cognitive psychoeducation.

Subgroup analyses Differences in whether patients had received an intervention (psychological or pharmacological) prior to the relapse prevention intervention (yes/no) and type of intervention (CBT/MBCT) did not significantly affect the risk of relapse. IPT was not included in the subgroup analysis for type of intervention, as only one study was available with results up to and including 24 months [39]. Of note, this study showed no significant difference between the intervention and the control group). Planned subgroup analyses on setting and mode of delivery could not be performed, as there was either not enough or too much variation in the data. The subgroup analyses can be found in Appendix 2.4.

Meta-regression analyses There was no statistically significant relationship between the number of previous episodes required for inclusion in the study and the outcome (B=0.02, 95% CI: -0.14 to 0.19, p=0.77). The influence of the duration of interventions was also not related to the outcome (B=0.003, 95% CI: -0.003 to 0.007, p=0.34).

>24 months Five studies were included in the meta-analysis for studies with a follow-up duration of more than 24 months, with a total of 588 patients. Three studies in this meta-

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analysis were follow-ups to studies that were included in the main analysis [43,45,49].

The average follow-up period in this group was more than 3 years (38.6 months, range 26 to 66 months). The risk ratio of relapse in these studies was 0.78 (95% CI: 0.62-0.98, p=0.036) for patients in the psychological intervention group versus TAU, indicating that risk of relapse was reduced by 22% for patients who received psychological relapse prevention interventions, as compared to those who received TAU. For patients in the intervention group, the summary relapse prevalence was 49.6% (95% CI: 29.6% - 69.8%), while for patients in the TAU group the summary relapse prevalence was 70.0% (95% CI: 51.8% - 83.6%). This effect is similar to the effect up to and including 24 months, but with greater heterogeneity (Q-value=10.325, df=4, p=0.035, I2=61.261). These findings therefore suggest that the preventive effect persists over time.

Psychological interventions plus M-ADM versus M-ADM ≤24 months In the meta-analysis of studies with a follow-up duration up to and including 24 months, which compared psychological relapse prevention interventions plus M-ADM to M-ADM only, six studies were included, with a total of 651 patients. The average follow-up in this group was 17.3 months, with a range of 6 to 24 months. When comparing psychological interventions plus M-ADM with M-ADM only, the risk ratio of relapse for these studies is 0.76 (95% CI: 0.62-0.94, p=0.010, I2<0.001). For patients in the intervention plus M-ADM group, the summary relapse prevalence was 26.9% (95% CI: 16.4% - 40.8%), while for patients in the M-ADM only group the summary relapse prevalence was 31.9% (95% CI: 18.5% - 49.2%). The addition of psychological interventions to M-ADM appears to be effective in preventing relapse.

>24 months Three studies with a follow-up period of more than 24 months compared psychological interventions plus M-ADM to M-ADM only, with a total of 264 patients. Of these three studies, one was a follow-up to another study that was included in the meta-analysis up to and including 24 months [46]. The average follow-up in this group was more than 4 years (52.2 months, range of 36 to 63 months). The risk ratio of relapse for these studies is 0.87 (95% CI: 0.62-1.21, p=0.396). For patients in the intervention plus M-ADM group, the summary relapse prevalence was 34.2% (95% CI: 12.6% - 65.1%), while for patients in the M-ADM only group the summary relapse prevalence was 43.4% (95% CI: 20.2% - 69.9%). The addition of psychological interventions to M-ADM does not appear to be significantly effective in preventing relapse over a follow-up period of more than 24 months. No evidence of heterogeneity was found (Q-value=2.357, df=2, p=0.308, I2=15.158).

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Psychological interventions plus discontinuation of ADM vs. TAU plus discontinuation of ADM Three studies were found in which ADM was discontinued in the intervention group, as well as in the TAU group [55–57]. As there was only one study with a follow-up period up to and including 24 months, and only two studies with a follow-up period of more than 24 months, we did not conduct a meta-analysis of these studies. In one study, the relapse rate was significantly lower in the discontinuation plus CBT group (25%), as compared to the discontinuation group (80%) [56].The relapse prevention effect was not significant in the other two studies [55,57]. For patients in the intervention plus discontinuation group, the summary relapse prevalence was 27.2% (95% CI: 15.6% 43.1%), while for patients in the TAU plus discontinuation group the summary relapse prevalence was 58.9% (95% CI: 33.9% - 80.0%).

Discussion Findings and comparison with existing literature This study focuses on psychological relapse prevention interventions for patients with remitted anxiety disorders or MDD. For patients with remitted MDD, psychological interventions reduced the risk of relapse by 24%, as compared to TAU within the first 24 months after the start of a relapse prevention intervention. This effect persisted up to 3 years. When psychological interventions were offered in combination with M-ADM, the risk of relapse was also reduced by 24% within the first 24 months, although this did not remain significant over a longer period. Due to a paucity of studies, no metaanalysis was performed with regard to the effectiveness of psychological relapse prevention interventions combined with discontinuation of ADM. Likewise, due to a lack of studies, no meta-analysis was performed with regard to the effectiveness of psychological relapse prevention interventions for patients with remitted anxiety disorders.

Our results are consistent with those reported by Clarke et al. [21] as they showed a 22% reduction in relapse rate, and lower than the 36% reduction that was found by Biesheuvel-Leliefeld et al. [20], when preventive psychological interventions were compared with TAU. The latter difference might be explained by the fact that inclusion criteria in our study were more strict regarding remission at randomization. Therefore, we excluded a number of studies, which were included by them [58–63]. As they included studies with patients who had more severe symptoms, these patients might have experienced more benefit from the relapse prevention interventions. This could explain the larger relapse rate reduction found by Biesheuvel-Leliefeld et al. [20]. In contrast to these studies, we included more comparisons in our meta-analysis, as the

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process of splitting follow-up durations into two categories (up to and including 24 months and more than 24 months) allowed us to include multiple follow-up periods for the same study. This is in contrast to the analytical strategy applied by Clarke et al.

[21] and by Biesheuvel-Leliefeld et al. [20], who considered only the results of one follow-up period for each study. In addition, we expanded their meta-analyses to include more recent studies, as these two meta-analyses included studies until 2013 and 2014, respectively. Both the inclusion of multiple follow-up periods for the same study and the addition of recent studies may result in a more reliable effect size compared to these earlier meta-analyses.

Although we might assume that the effect of psychological interventions decreases as follow-up time increases, the studies with a mean follow-up duration of over 3 years indicated that psychological interventions still appear to protect against relapse when compared to TAU. However, these findings were less robust than the findings up to and including 2 years. This study is the first to report meta-analytical results over a follow-up period of more than 2 years.

This study also compared psychological relapse prevention interventions plus M-ADM to M-ADM only. Psychological interventions were effective in preventing relapse up to and including 2 years, but no positive effect could be established after a longer follow-up period of more than 2 years. This could have been due to limited power in the meta-analysis, as only three studies were included. The additional effect of psychological interventions was not studied in other meta-analyses, as they compared psychological interventions to ADM [20,23,25]. As many remitted patients use M-ADM, and M-ADM in itself affects relapse rates [14], this comparison is highly relevant for clinical practice.

In this study, the effect sizes of the various types of interventions were comparable.

This finding was also reported by Biesheuvel-Leliefeld et al. [20]. We found that CBT was effective in preventing relapse, as also reported by Zhang et al. [25] and by Clarke et al. [21]. In addition, we found that MBCT was effective in preventing relapse, as previously reported by Piet and Hougaard [23] and by Clarke et al. [21]. In contrast, Zhang et al. [25] found MBCT only to be effective in patients with at least three earlier episodes. Theoretically, preventive CT targets the content of cognition as key mechanisms for relapse. Dysfunctional beliefs are assumed to be latent in the remitted phase, but can be triggered by life events, stress or sad mood, and thereby cause recurrence of depression. MBCT on the other hand, is presumed to target both the process, as well as the content of cognition. It is supposed to help develop a detached and decentered relationship to thoughts and feelings, breaking the connection between mood reactivity and recurrence of depression. However, few studies have directly tested mediation of preventive psychological interventions in relapse and recurrence prevention. Further research is required to understand the working mechanism of psychological relapse prevention interventions [64].

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The results of this study also appear to extend previous observations. As suggested

by Zhang et al., [25] we analyzed whether the effectiveness of psychological interventions differed for patients who had received an intervention (psychological or pharmacological) prior to the relapse prevention intervention, and we found no differences between the two subgroups. This is in contrast to the study by BiesheuvelLeliefeld et al. [20], which found that psychological relapse prevention interventions were more effective if they were offered shortly after the conclusion of active treatment.

Another important finding of our analysis was that studies on psychological relapse prevention in anxiety disorders are scarce. Only two studies on this topic could be included in our systematic review and, for this reason, no meta-analysis was conducted.

Given the differences in research design and contradictory findings in these two studies, no clear conclusion could be drawn with regard to the effectiveness of relapse prevention interventions for patients with anxiety disorders. These studies differed with regard to the timing of discontinuation: Scholten et al. [36] discontinued ADM during the study, whereas White et al. [37] included only patients for whom psychopharmacological treatment had already been discontinued before randomization. It is therefore likely that these patients differed in terms of the severity of symptoms.

The scarcity of studies on anxiety disorders was surprising, given that relapse is at least as prevalent in anxiety disorders as it is in depressive disorders [4]. One explanation might be the prevailing idea among professionals that treatment for anxiety disorders is more effective in the long-term than treatment for depressive disorders, along with a possible lack of awareness regarding the unfavorable long-term course of anxiety. Professionals might therefore think that relapse prevention is less necessary for this group of patients. Another explanation could be that studies focusing on MDD are more common than studies on anxiety disorders.

Strengths and limitations This study has several strengths. Firstly, it is the first study to analyze data over a followup period of 3 years. Secondly, in contrast to other meta-analyses [20,21,25], we included more recent trials in our analyses, addressing not only patients suffering from MDD but also from anxiety disorders. A third strength of this study is the inclusion of different treatment strategies (and related control groups), which enabled us to analyze both the stand-alone effect of psychological interventions and their add-on effect to M-ADM. A fourth and final strength is that the quality of the study was safeguarded by reporting in line with the PRISMA guidelines [27], by pre-registering in PROSPERO and by performing the data screening, data extraction and risk of bias appraisal with multiple researchers, thereby increasing the completeness of the data [32].

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This study is also subject to several limitations. Firstly, it was not possible to execute some of the planned analyses, due to incomplete data (e.g. on the effectiveness of psychological interventions for anxiety disorders and in combination with discontinuation of ADM). Secondly, differences in methodological designs were found in the studies included (e.g. the definition of relapse or remission and the different measures used to assess relapse and remission). This might have resulted in heterogeneity in the data. Thirdly, evidence of publication bias was found, although this did not significantly change the estimated effect size.

Implications for future practice and research Given that psychological relapse prevention interventions for remitted depressed patients reduce the risk of relapse by 24%, relapse prevention should be offered to all patients who are in remission from MDD. This corresponds to current guideline recommendations about providing psychological relapse prevention interventions after remission had been achieved [9–12]. Moreover, as our results suggest an additive effect of psychological relapse prevention on M-ADM up to and including 2 years, all patients on M-ADM should be offered psychological relapse prevention in the 2 years after remission.

This study highlighted several gaps in current knowledge, and provides input for the research agenda in this field. First, it reveals a need for research into relapse prevention for patients with anxiety disorders, as this could provide insight into the effectiveness of psychological interventions for these disorders. Second, more studies should be performed with longer follow-up durations, in order to provide more robust effect estimates and to establish long term effectiveness of psychological interventions.

This is especially relevant as the risk of relapse persists over time [65]. Third, more research is needed on effective relapse prevention interventions combined with discontinuation of ADM, as most patients have reservations about the long-term use of medication [66], even though the risk of relapse during discontinuation is high [15].

Conclusion Psychological relapse prevention interventions are effective in reducing the risk of relapse for patients with remitted MDD, including over a long follow-up period of more than 3 years. All patients in remission from MDD should receive psychological relapse prevention interventions. Due to a paucity of data, no conclusions could be drawn with regard to the effectiveness of relapse prevention interventions for anxiety disorders and the effectiveness of relapse prevention interventions combined with discontinuation of ADM. Future studies should focus on these topics.

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46 | Chapter 2

ACKNOWLEDGEMENTS We thank Caroline Planting (CP) of the VU University Medical Centre for her help with conducting the literature search, and Jasmijn Geerlings (JG) for her help with screening and data-extraction.

ROLE OF FUNDING SOURCES Funding for this study was provided by SIA-RAAK: The Taskforce for Applied Research, part of the Netherlands Organization for Scientific Research (NWO, grant number 2015-02-36P). SIA-RAAK had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Systematic review and meta-analysis | 47

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Systematic review and meta-analysis | 53

Appendix 2.1. Search strategy The literature search was conducted in February 2020. Searches were performed in the following databases and article indexes (number of articles retrieved): PubMed (2,290) Embase (3,198) PsycINFO (1,836)

To illustrate, the following Embase search is indicative of searches performed in other databases.

No.

Query

#8

#6 AND #7

#7

‘clinical trial’/de OR ‘controlled clinical trial’/de OR ‘randomized controlled trial’/de OR ‘randomized controlled trial*’:ab,ti,kw OR ‘controlled clinical trial*’:ab,ti,kw OR randomized:ab,ti,kw OR randomized:ab,ti,kw OR placebo*:ab,ti,kw OR randomly:ab,ti,kw OR rct:ab,ti,kw OR ‘controlled trial*’:ab,ti,kw OR ‘clinical trial*’:ab,ti,kw

#6

#3 AND #4 AND #5

#5

‘relapse prevention’/exp OR ‘remission’/exp OR ‘recurrent disease’/exp OR ‘relapse’/exp OR ‘secondary prevention’/exp OR relaps*:ab,ti,kw OR remission*:ab,ti,kw OR recurren*:ab,ti,kw OR prevent*:ab,ti,kw OR exacerbat*:ab,ti,kw OR maintenan*:ab,ti,kw OR continuat*:ab,ti,kw OR discontinuat*:ab,ti,kw OR remitted*:ab,ti,kw

#4

‘psychotherapy’/exp OR ‘problem solving therapy’/exp OR psychotherap*:ab,ti,kw OR ‘cognitive therap*’:ab,ti,kw OR ‘cognitive behavior therap*’:ab,ti,kw OR ‘cognitive behavior therap*’:ab,ti,kw OR ‘cognitive behavioral therap*’:ab,ti,kw OR ‘cognitive behavioral therap*’:ab,ti,kw OR mindfulnes*:ab,ti,kw OR mindfullnes*:ab,ti,kw OR ‘problem solving*’:ab,ti,kw OR ‘psychodynamic therap*’:ab,ti,kw OR ‘psycho-dynamic therap*’:ab,ti,kw OR ‘psychoanalytic therap*’:ab,ti,kw OR ‘behavior therap*’:ab,ti,kw OR ‘behavior therap*’:ab,ti,kw OR ‘behavioral therap*’:ab,ti,kw OR ‘behavioral therap*’:ab,ti,kw OR ‘psychological intervention*’:ab,ti,kw OR ‘psychological treatment*’:ab,ti,kw OR ‘psychological therap*’:ab,ti,kw OR ‘interpersonal therap*’:ab,ti,kw OR (ipt:ab,ti,kw AND interperson*:ab,ti,kw) OR (pst:ab,ti,kw AND problem*:ab,ti,kw) OR ‘implosive therap*’:ab,ti,kw OR ‘exposure therap*’:ab,ti,kw OR ‘maintenance cbt’:ab,ti,kw OR ‘maintenance ct’:ab,ti,kw OR ‘booster sessi*’:ab,ti,kw OR ‘solution focused therap*’:ab,ti,kw

#3

#1 OR #2

#2

‘anxiety disorder’/de OR ‘generalized anxiety disorder’/exp OR ‘panic’/exp OR ‘phobia’/exp OR ‘anxiety disorder*’:ab,ti,kw OR agoraphobi*:ab,ti,kw OR ‘panic disorder*’:ab,ti,kw OR ‘panic attack*’:ab,ti,kw OR ‘generalized anxiety disorder*’:ab,ti,kw OR (gad:ab,ti,kw AND anxiet*:ab,ti,kw) OR ‘generalised anxiety disorder*’:ab,ti,kw OR claustrophobi*:ab,ti,kw OR phobi*:ab,ti,kw OR ‘recurrent anxiet*’:ab,ti,kw OR ‘remitted anxiet*’:ab,ti,kw OR ophidiophobi*:ab,ti,kw OR acrophobi*:ab,ti,kw

#1

‘major depression’/exp OR ‘major depression’ OR ‘chronic depression’/exp OR ‘chronic depression’ OR ‘mixed anxiety and depression’/exp OR ‘mixed anxiety and depression’ OR ‘recurrent brief depression’/exp OR ‘recurrent brief depression’ OR ‘treatment resistant depression’/exp OR ‘treatment resistant depression’ OR ‘major depression*’:ab,ti,kw OR ‘depressive disorder*’:ab,ti,kw OR ‘mood disorder*’:ab,ti,kw OR ‘severe depression*’:ab,ti,kw OR mdd:ab,ti,kw OR ‘recurrent depression*’:ab,ti,kw OR ‘remitted depression*’:ab,ti,kw OR ‘depressive episod*’:ab,ti,kw OR ‘chronic depression*’:ab,ti,kw

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Comparison

Intervention

Duration follow-up

Duration intervention (wks)

% female

Age

Type of disorder

First author (year)

N

Appendix 2.2. Study characteristics

BiesheuvelLeliefeld et al.

(2017)

248

MDD

48.7 (11.7)

69.8

8

12 months

Self-help PCT

TAU

Bockting et al. (2005)

172

MDD

44.7 (9.5)

73.5

8

24 months

PCT + TAU

TAU

Bockting et al. (2009) Follow-up

172

MDD

44.7 (9.5)

73.5

8

66 months

PCT + TAU

TAU

Bockting et al. (2018)

204

MDD

47.1 (9.9)

66.5

8

24 months

PCT + M-ADM

M-ADM

Bondolfi et al. (2010)

60

MDD

47.5

71.6

8

14 months

MBCT + TAU

TAU

de Jonge et al. (2019)

214

MDD

43.4 (11.3)

68.2

8

15 months

PCT + TAU

TAU

Fava et al. (1994)

40

MDD

46.1 (3.7)

67.5

20

29 months

CBT + Discontinuation discontinuation ADM ADM

Fava et al.

(1998)

40

MDD

46.9 (11.2)

60

20

29 months

CBT + Discontinuation discontinuation ADM ADM

Frank (1990)

53

MDD

40.2 (10.9)

76.6

17

36 months

M-IPT + M-ADM M-ADM

Godfrin and Van Heeringen (2010)

106

MDD

45.7 (10.6)

81.1

8

14 months

MBCT + TAU

TAU

Holländare et al. (2011)

84

MDD

45.3 (12.8)

84.5

10

8 months

Internet-based CBT

TAU

Holländare et al. (2013) Follow-up

67

MDD

45.3 (12.8)

84.5

10

26 months

Internet-based CBT

TAU

Huijbers et al. (2015)

68

MDD

51.8 (14.2)

72

8

15 months

MBCT + M-ADM M-ADM

Jarrett et al. (2000)

14

MDD

41.2 (10.1)

84

35

24 months

C-CT

TAU

Jarrett et al. (2001)

84

MDD

42.7 (1.14)

72.6

35

24 months

C-CT

TAU

Klein et al. (2004)

82

MDD

45.1 (11.4)

67.1

52

12 months

CBASP

TAU

Relapse rate control (%)

Relapse rate intervention (%)

Definition of relapse

Definition of remission

Setting

Systematic review and meta-analysis | 55

Community and Primary care Full or partial remission of recurrent MDD

MDD according to SCID-I

36

50

Community and Specialized care

Remission according to DSM–IV criteria, HRSD < 10

MDD according to SCID-I

56

64

Community and Specialized care

Remission according to DSM–IV criteria, HRSD < 10

MDD according to SCID-I

78

87

Community, Primary and Specialized care

HRSD ≤ 10, last MDE ended at Unclear least 2 months and no longer than 2 years before study entry

43

60

Community, Primary and Specialized care

MADRS ≤13

MDE according to SCID

29

34

Specialized care

Remission according to SCID-I, HDRS <14

MDE according to SCID-I

23

33

Specialized care

Full remission & rated as ‘better’ or ‘much better’ on GRSI

RDC-defined MDE

15

35

Specialized care

Full remission & rated as ‘better’ or ‘much better’ on GRSI

RDC-defined MDE

25

80

Unknown

HRSD ≤ 7& RSD ≤ 5 for a total RDC-defined MDD AND HRSD 24 of 20 weeks ≥ 15 AND RSD ≥ 7

21

Specialized care

HRSD <14, no current MDE MDD according to SCID-I according to DSM-IV & end of the last episode being at least 8 weeks before study entry

30

68

Community

BDI ≤ 10

MDD according to DSM-IV

11

38

Community

BDI ≤ 10

MDD according to DSM-IV

14

61

Specialized care

Full (≤11 on IDS-C) or partial MDE according to SCID-I (>11 on IDS-C) remission, not meeting DSM-IV criteria for MDD

36

37

Specialized care

HRSD ≤ 9, no MDD

RDC-defined MDD OR patient 40 had treatment

83

Specialized care

HRSD-17 ≤ 9, no MDD

MDE according to DSM-IV criteria, using LIFE

39

50

Specialized care

Reduction from the acute phase baseline of at least 50% and HRSD-24 ≤ 15

HRSD-24 ≥ 16 on two consecutive visits AND MDD according to DSM-IV

3

21

2

56 | Chapter 2

Comparison

Intervention

Duration follow-up

Duration intervention (wks)

% female

Age

Type of disorder

First author (year)

N

Appendix 2.2. Continued

Klein et al. (2018)

264

MDD

46 (10.8)

75

13

24 months

mobile CT

TAU

Ma and Teasdale (2004)

75

MDD

44.5 (9.0)

76

34

14 months

MBCT

TAU

Meadows et al. (2014)

203

MDD

48.4 (12.4)

81.3

8

26 months

MBCT + TAU

TAU

Morokuma et al. (2013)

34

MDD

42.8

56.2

6

10 months

PE + TAU

TAU

Paykel et al. (1999)

158

MDD

43.4 (10.5)

49.5

20

16 months

CT + M-ADM

M-ADM

Paykel et al. (2005) Follow-up

158

MDD

43.4 (10.5)

49.5

20

63 months

CT + M-ADM

M-ADM

Perlis et al. (2002)

132

MDD

39.9 (10.3)

54.5

26

6 months

CBT + M-ADM

M-ADM

Petersen et al. (2010)

26

MDD

43.6

54

80

20 months

CBT + M-ADM

M-ADM

Petersen et al. (2010) Placebo

29

MDD

43.6

54

80

20 months

CBT + placebo

Placebo

Reynolds et al. (1999)

53

MDD

67.6 (5.8)

74.9

156

36 months

IPT + M-ADM

M-ADM

Reynolds et al. (1999) Placebo

54

MDD

67.6 (5.8)

74.9

156

36 months

IPT + placebo

Placebo

Reynolds et al. (2006)

63

MDD

77.3 (6.4)

63.6

104

24 months

IPT + M-ADM

M-ADM

Reynolds et al. (2006) Placebo

53

MDD

76.5 (4.9)

65.9

104

24 months

IPT + placebo

Placebo

Community, Primary and Specialized care

HRSD ≤ 10, in remission for at MDD according to SCID least 8 weeks but no longer than 24 months according to SCID-I

Relapse rate control (%)

Relapse rate intervention (%)

Definition of relapse

Definition of remission

Setting

Systematic review and meta-analysis | 57

44

49

Community and Primary care HAMD <10

MDE according to SCID

39

62

Primary and Specialized care No current MDE

Unclear

45

55

Specialized care

Remission: HRSD ≤ 6, partial remission: according to DSM- IV

MDE according to DSM-IV

6

36

Specialized care

HDRS <8, BDI <9 at 2 successive ratings 4 weeks apart

MDD according to DSM-III-R 23 for a minimum of 1 month AND at 2 successive face-to-face assessments required to meet severity criteria for MDD AND HDRS ≥ 17

34

Specialized care

HDRS <8, BDI <9 at 2 successive ratings 4 weeks apart

MDD according to DSM-III-R 60 for a minimum of 1 month AND at 2 successive face-to-face assessments required to meet severity criteria for MDD AND HDRS ≥ 17

65

Specialized care

HAMD-17 ≤ 7 for at least 3 weeks

MDE according to DSM OR HAMD-17 ≥ 15 at two consecutive visits

6

8

Specialized care

HAMD-17 ≤7 for 3 consecutive weeks

MDD according to SCID OR HAMD-17 ≥ 15 at two consecutive visits

36

29

Specialized care

HAMD-17 ≤7 for 3 consecutive weeks

MDD according to SCID OR HAM-D-17 ≥ 15 at two consecutive visits

45

50

Specialized care

HRSD-17 ≤ 10 for 3 consecutive weeks

RDC-defined MDE

20

43

Specialized care

HRSD-17 ≤ 10 for 3 consecutive weeks

RDC-defined MDE

64

90

Specialized care

HRSD ≤10

MDE according to DSM-IV AND HRSD ≥ 15

29

34

Specialized care

HRSD ≤10

MDE according to DSM-IV AND HRSD ≥ 15

60

56

2

58 | Chapter 2

Comparison

Intervention

Duration follow-up

Duration intervention (wks)

% female

Age

Type of disorder

First author (year)

N

Appendix 2.2. Continued

Scholten et al. (2018)

87

Anxiety 41.7 (12.7) disorder

60

17

16 months

CBT + Discontinuation discontinuation ADM ADM

Segal et al. (2010)

56

MDD

44 (11)

63

8

18 months

MBCT + Discontinuation discontinuation ADM ADM

Segal et al. (2020)

460

MDD

48.3 (14.9)

75.6

12

15 months

MBCT

TAU

Shallcross et al. (2015)

92

MDD

34.9 (11.4)

76

8

14 months

MBCT

TAU

Shallcross et al. (2018) Follow-up

92

MDD

34.9 (11.4)

76

8

26 months

MBCT

TAU

Stangier et al. (2013)

180

MDD

48.6 (11.6)

72.2

35

20 months

M-CBT

TAU

Teasdale et al. (2000)

145

MDD

41.3 (10.6)

76

8

14 months

MBCT

TAU

White et al. (2013)

157

Anxiety 37.8 (11.9) disorder

66.8

39

21 months

M-CBT

TAU

Wilkinson et al. (2009)

45

MDD

74.0 (7.3)

62.2

10

12 months

CBT

TAU

Williams et al. (2014)

136

MDD

43 (12)

72

8

12 months

MBCT

TAU

Williams et al. (2014) CPE

138

MDD

43 (12)

72

8

12 months

CPE

TAU

Interventions: PCT = Preventive Cognitive Therapy, CBT = Cognitive Behavioral Therapy, TAU = Treatment As Usual, MBCT = Mindfulness-Based Cognitive Therapy, M-IPT = Maintenance Interpersonal Psychotherapy, IPT = Interpersonal Psychotherapy, C-CT = Continuation-Cognitive Therapy, M-ADM = Maintenance Antidepressant Medication, CBASP = Cognitive Behavioral Analysis System of Psychotherapy, (C)PE = (Cognitive) Psychoeducation, CT = Cognitive Therapy, M-CBT = Maintenance-Cognitive Behavioral Therapy Measures: BDI = Beck Depression Inventory, SCID = Structured Clinical Interview for DSM-IV, HRSD/HDRS/HAMD = Hamilton Rating Scale for Depression, MADRS = Montgomery-Åsberg Depression Rating Scale, RDC = Research Diagnostic Criteria, GRSI = Global Rating Scale of Improvement, RSD = Raskin Severity of Depression, LIFE = Longitudinal Interval Follow-up Evaluation, CGI = Clinical Global Improvement Other:MDD = Major Depressive Disorder, MDE = Major Depressive Episode

Relapse rate control (%)

Relapse rate intervention (%)

Definition of relapse

Definition of remission

Setting

Systematic review and meta-analysis | 59

Community, Primary and Specialized care

No disorder, according to SCID-I

Anxiety disorder OR MDD according to SCID-I

61

58

Community, Primary and Specialized care

Stable remission: HRSD ≤ 7, MDD according to SCID-I, unstable remission HRSD ≤ 7 for at least 2 weeks with occasional elevation to 8-14

38

60

Primary care

PHQ-9 ≥5 and ≤9, residual depressive symptoms

14

23

Community and Primary care Remission of at least 1 month MDD according to SCID prior to interview

33

30

Community and Primary care Remission of at least 1 month MDD according to SCID prior to interview

48

50

Community and Specialized care

HAM-D ≤9 in 8 weeks before randomization

51

60

Community

Remission or recovery, HRSD MDE according to SCID < 10

44

58

Specialized care

40% reduction of PDSS-IE score relative to baseline & CGI score of ‘much’ or ‘very much’ improved relative to baseline study entry

PHQ-9 ≥15

MDE according to DSM-IV criteria, using LIFE

2 weeks with 1) ≥ 40% 5 increase in PDSS score relative to post-acute treatment score and 2) CGI score of ‘much worse’ or ‘very much worse’ relative to post-acute treatment status

18

Primary and Specialized care MADRS <10, remitted for at least 2 months

MADRS ≥10

28

44

Community, Primary and Specialized care

Remission for the previous 8 weeks (no core symptom of depression or suicidal feelings during at least 1 week)

MDD according to SCID criteria, for at least 2 weeks

46

53

Community, Primary and Specialized care

Remission for the previous 8 weeks (no core symptom of depression or suicidal feelings during at least 1 week

MDD according to SCID criteria, for at least 2 weeks

50

53

2

60 | Chapter 2

Appendix 2.3. Risk of bias appraisal First author

Year

Random Allocation Blinding of Incomplete Selective sequence concealment outcome outcome reporting generation assessment data

Other bias

Biesheuvel-Leliefeld

2017

Low risk

High risk

Low risk

Low risk

High risk

Low risk

Bockting

2005

Low risk

Low risk

Low risk

Low risk

Unclear

Low risk

Bockting_FU

2009

Low risk

Low risk

Low risk

Unclear

Unclear

Low risk

Bockting

2018

Low risk

Low risk

Low risk

Unclear

Low risk

Low risk

Bondolfi

2010

Low risk

Low risk

Low risk

Low risk

Unclear

Low risk

de Jonge

2019

Low risk

Low risk

Low risk

Low risk

High risk

Unclear

Fava

1994

Unclear

Unclear

Low risk

Low risk

Unclear

High risk

Fava

1998

Unclear

Unclear

Unclear

Low risk

Unclear

Unclear

Frank

1990

Unclear

Unclear

Low risk

Low risk

Unclear

Low risk

Godfrin

2010

Low risk

Low risk

Unclear

Low risk

Unclear

Unclear

Holländare

2011

Low risk

Unclear

Unclear

Low risk

Unclear

Low risk

Holländare_FU

2013

Low risk

Unclear

Unclear

Low risk

Unclear

Low risk

Huijbers

2015

Low risk

Low risk

High risk

High risk

Low risk

High risk

Jarrett

2000

Unclear

Unclear

High risk

Unclear

Unclear

High risk

Jarrett

2001

Low risk

Unclear

High risk

Low risk

Unclear

Low risk

Klein

2004

Unclear

Unclear

Low risk

Low risk

Unclear

High risk

Klein

2018

Low risk

Low risk

Low risk

Low risk

Low risk

Low risk

Ma

2004

Unclear

High risk

Low risk

Unclear

Unclear

Unclear

Meadows

2014

Low risk

Low risk

Low risk

Low risk

High risk

Low risk

Morokuma

2013

Low risk

Low risk

Low risk

Low risk

Unclear

High risk

Paykel

1999

Low risk

Low risk

Low risk

Low risk

Unclear

Unclear

Paykel_FU

2005

Low risk

Low risk

Low risk

Low risk

Unclear

Unclear

Perlis

2002

Unclear

Unclear

Low risk

High risk

Unclear

Unclear

Petersen

2010

Unclear

Unclear

Low risk

Low risk

Unclear

High risk

Reynolds

2006

Low risk

Low risk

Low risk

Unclear

High risk

Low risk

Reynolds

1999

Low risk

Low risk

Low risk

Low risk

Unclear

Low risk

Scholten

2018

Low risk

Low risk

High risk

Low risk

Low risk

High risk

Segal

2010

Low risk

Low risk

Low risk

Low risk

Unclear

Unclear

Segal

2020

Low risk

Low risk

Low risk

Unclear

Low risk

High risk

Shallcross

2015

Low risk

Low risk

Low risk

High risk

Unclear

Unclear

Shallcross_FU

2018

Low risk

Low risk

Low risk

High risk

Unclear

Unclear

Stangier

2013

Low risk

Low risk

Low risk

High risk

Low risk

Low risk

Teasdale

2000

Low risk

Low risk

Low risk

Low risk

Unclear

Low risk

White

2013

Unclear

Unclear

Low risk

Low risk

Unclear

High risk

Wilkinson

2009

Low risk

Low risk

Low risk

Low risk

Unclear

Low risk

Williams

2014

Low risk

Low risk

Low risk

Unclear

Low risk

Low risk

Systematic review and meta-analysis | 61

Appendix 2.4. Subgroup analyses

2

Figure 2.4.1. Subgroup analysis on whether patients had received an intervention (psychological or pharmacological) prior to the relapse prevention intervention

Figure 2.4.2. Subgroup analysis on type of intervention

3

THE GET READY RELAPSE PREVENTION PROGRAM FOR ANXIETY AND DEPRESSION: A MIXED-METHODS STUDY PROTOCOL PUBLISHED IN BMC PSYCHIATRY 2019, 19:1–11

Esther Krijnen-de Bruin, Anna D.T. Muntingh, Adriaan W. Hoogendoorn, Annemieke van Straten, Neeltje M. Batelaan, Otto R. Maarsingh, Anton J.L.M. van Balkom, Berno van Meijel

64 | Chapter 3

Abstract Background Since anxiety and depressive disorders often recur, self-management competencies are crucial for improving the long-term course of anxiety and depressive disorders.

However, few relapse prevention programs are available that focus on improving selfmanagement. E-health combined with personal contact with a mental health professional in general practice might be a promising approach for relapse prevention.

In this protocol, the GET READY (Guided E-healTh for RElapse prevention in Anxiety and Depression) study will be described in which a relapse prevention program is developed, implemented and evaluated. The aim of the study is to determine patients’ usage of the program and the associated course of their symptoms, to examine barriers and facilitators of implementation, and to assess patients’ satisfaction with the program.

Methods Participants are discharged from mental healthcare services, and are in complete or partial remission. They receive access to an E-health platform, combined with regular contact with a mental health professional in general practices. Online questionnaires will be completed at baseline and after 3, 6 and 9 months. Also, semi-structured qualitative individual interviews and focus group interviews will be conducted with patients and mental health professionals.

Discussion This mixed-methods observational cohort study will provide insights into the use of a relapse prevention program in relation to the occurrence of symptoms, as well as in its implementation and evaluation. Using the results of this study, the relapse prevention program can be adapted in accordance with the needs of patients and mental health professionals. If this program is shown to be acceptable, a randomized controlled trial may be conducted to test its efficacy.

Trial registration Retrospectively registered in the Netherlands Trial Register (NTR7574; 25 October 2018).

Keywords: Anxiety, Depression, Recurrence, Relapse prevention, Self-management, E-health, Mixed-methods research, Study protocol

Study protocol | 65

Background The course of anxiety and depressive disorders is often unfavorable, with chronic [1,2] or intermittent episodes of anxiety and/or depression [3] and a high risk of relapse.

Percentages of 22-58 for anxiety [1,3–5] and 27-77 for depression [6–9] have been reported as relapse rates with higher rates in longer follow-up studies [1,6].

Furthermore, patients often achieve partial remission instead of full remission, and have residual symptoms [10]. The risk of relapse is higher for patients with a partial remission when compared to patients with full remission [11]. Moreover, even if remission is achieved, patients with residual symptoms have a three times higher risk of relapse than patients without residual symptoms [12]. Since anxiety and depression are often recurrent and patients remain vulnerable, these disorders should be approached as chronic diseases. Chronic care models, previously developed for other chronic diseases such as diabetes [13], can be applied. One essential element of chronic care models is the support of self-management [14]. Lorig [15] defined self-management as “learning and practicing skills necessary to carry on an active and emotionally satisfying life in the face of a chronic condition” (p.11). Self-management for anxiety and depression focuses on recovery and stabilization of symptoms, prevention of relapse, and improving functioning and quality of life [16,17]. People with recurrent anxiety and depression should be supported in performing self-management strategies.

One of the major challenges in the management of anxiety and depression symptoms is the prevention of relapse [18]. In their meta-analysis, Biesheuvel-Leliefeld et al. [19] concluded that relapse prevention strategies such as cognitive therapy or mindfulness-based cognitive therapy are effective in reducing relapse of depression.

However, few relapse prevention programs are available for this patient group of depressed patients. In an empirical study from the same authors, the efficacy of a self-help preventive cognitive therapy combined with weekly telephone guidance in preventing depression was examined [20]. They demonstrated that this was significantly more effective than care as usual. To date, little is known about the efficacy of relapse prevention strategies for patients with anxiety disorders [21]. The fact that depression and anxiety are often comorbid, and relapse into another disorder frequently occurs (from anxiety to depression and vice versa), highlights the need to target both anxiety and depression in a single relapse prevention program.

Over the past two decades, it has been suggested that primary healthcare facilities should play a vital role in the long-term treatment of patients with anxiety and depression [22,23]. In the Netherlands, primary mental healthcare is usually provided by a mental health professional (MHP), working in a general practice and reporting to the general practitioner (GP). This MHP could be a (community) mental health nurse, a social worker or a (junior) psychologist. Since general practices are always located

3

66 | Chapter 3

close to where patients live, and the services are freely available, the MHPs are easily approachable. They can play a pivotal role in the monitoring of symptoms and the support of self-management, and therefore in the prevention of relapse. However, many MHPs are unfamiliar with relapse prevention interventions, including the use of supporting tools to monitor symptoms [24]. To encourage general practices to offer structured relapse prevention, while also supplying supporting tools for MHPs, the use of E-health could offer a solution. E-health tools can be easily tailored to the needs and preferences of patients, which is important for the tools’ acceptability and effectiveness.

Most (92%) of the MHPs in the Netherlands are already familiar with E-health [25]. If the use of E-health is embedded in personal contact with a MHP, it is likely to be more effective [26].

We therefore developed a relapse prevention program that can be offered in general practices by MHPs to patients with (partially) remitted anxiety or depression.

This program aims to support self-management skills and provides tools for monitoring symptoms. The E-health modules can be individually tailored to the needs of patients, and is combined with regular contact with the MHP. The aim of the present study is to implement and evaluate this guided self-help online relapse prevention program for patients who are completely or partially in remission from anxiety and/or depressive disorders, and who previously received treatment in mental healthcare services. This study will provide insight into: 1) the extent to which patients make use of the relapse prevention program; 2) the factors that influence the use of the program; 3) the association between usage intensity and course of symptoms; 4) barriers and facilitators in implementation of the program; and 5) how patients evaluate the program.

Methods/design The methods section is divided into three parts: 1) the development of the relapse prevention program; 2) the content of the relapse prevention program; and 3) the study design.

1. Development of the relapse prevention program The program was developed using input from different studies. Muntingh et al. [27] examined preferences of patients regarding relapse prevention and revealed that patients prefer a relapse prevention program that is effective but not too time-consuming, taking up a maximum of one hour a week. Using a personal relapse prevention plan, in combination with regular contact with a professional (about once every three months)

Study protocol | 67

was the most preferred relapse prevention strategy. The use of a relapse prevention plan as a practical aid for the early recognition and management of potential triggers and signs that indicate relapse is in accordance with the NICE guidelines [28]. According to several studies, relapse prevention should be flexible and tailored to the patient’s individual situation and preferences in order to increase acceptability [29,30]. Our online program therefore consists of a personal relapse prevention plan and flexible E-health modules aiming at the promotion of self-management skills. The MHP can individually tailor the program in conjunction with the patient.

The initial format and underpinning of the relapse prevention program was discussed with academic experts, a panel of eight patients, and four MHPs. The content of the E-health modules was written by two expert psychologists, based on the principles of cognitive behavioral therapy (CBT). This therapy is effective in the treatment of anxiety and depression [31], and in preventing relapse in depression [19]. Some optional modules were added at the request of patients, such as healthy food and physical exercise. These modules contain psychoeducation and the ability to plan healthy behavior, with the aim of increasing physical and mental health. Preliminary versions of the E-health modules were reviewed by the members of the research team and E-health developers. Also, the patient panel reviewed the modules and provided feedback. This feedback was thoroughly discussed and processed by the researchers.

For example: more lengthy text parts were placed in ‘read more’ menus, an overview page was created, and the possibility to print text was added. Finally, the adjusted content was released to the online platform.

2. Content of relapse prevention program Online program The online program consists of three basic components and 12 optional modules (see Figure 1). The three basic components are: ‘Relapse psychoeducation’, ‘Relapse prevention plan’, and ‘Mood & anxiety diary’. As soon as the patient completes the module ‘Relapse psychoeducation’, the optional follow-up psychoeducation modules ‘Depression’, ‘Anxiety’ and ‘Medication’ will appear. Following the module ‘Relapse prevention plan’, the patient can choose which other optional modules he or she wishes to complete, based on own preferences and goals, thus offering the opportunity for the patient to customize treatment. The dotted lines in Figure 1 indicate that certain modules refer automatically to other optional follow-up modules.

The modules include short videos on what to expect in the module, written information, exercises, and clinical examples of fictional patients. In all modules except

3

68 | Chapter 3

the psychoeducation modules, patients have the possibility to ask for feedback from the MHP. For a more detailed overview of the contents of the E-health program, see Table 1.

It takes about 30-60 minutes to complete each module. In each module, patients draft plans related to the specific content of that module, and are encouraged to continue practicing, by offering the possibility to print out the plans.

Patients receive reminders via email regarding the completion of modules in the E-health platform. They also receive a newsletter every six weeks to keep them involved in the program by providing information about numbers of included patients, experiences of other patients and interesting articles or facts about anxiety and depression. The MHP has access to the patient’s account, and can check whether the patient has been using the diary to monitor symptoms of anxiety and depression. Also, the MHP can monitor the patient’s individual use of the different modules. In turn, MHPs can provide feedback on the completed modules and start a conversation in the E-health platform with the patient.

Figure 1. Content of E-health program.

Study protocol | 69

Table 1. Overview of module content.

Module

Module content

Relapse

Information regarding relapse and relapse prevention Video: experiences of patients Overview of relapse prevention program

Relapse prevention plan

Formulating a relapse prevention plan Information about support from family/friends Choosing which optional modules to complete

Depression

Information regarding symptoms, differences in disorders, causes and prevalence of depression Links to websites for more information

Anxiety

Information regarding symptoms, differences in disorders, causes and prevalence of anxiety Links to websites for more information

Medication

Information regarding antidepressive medication Information regarding benzodiazepines

Alcohol and other substances

Information regarding use of alcohol and psychological symptoms Advice on how to reduce alcohol intake Information regarding other substances (marihuana and tobacco) and psychological symptoms Exercise: registering use of substances Exercise: motivation to change behavior Plan to change behavior

Exposure

Information on exposure Exercise: avoidance Plan for exposure

Physical exercise

Information regarding exercise Plan to increase physical exercise Links to websites for more information

Healthy food

Information on healthy food Advice on healthy food Plan to improve your diet

Negative thinking

Information on (un)helpful thoughts Exercise: make a thought schedule

Relaxation

Information regarding physical and psychological effects of relaxation Information regarding mindfulness Exercises in mindfulness Plan to increase mindfulness/relaxation

Worrying

Exercise and information on registering worrying Exercises on worrying

Behavioral activation

Information on importance of behavioral activation Information regarding physical and psychological effects of pleasurable activities Exercise: planning pleasurable activities

Sleep

Information regarding sleep and psychological symptoms Advice on how to improve sleep Exercise: completing a sleep diary Exercise: restoring your sleep rhythm Exercise: activities during the day

3

70 | Chapter 3

Role of MHP The MHP and the patient will have at least one face-to-face contact during the ninemonth period of the study, and are encouraged to meet each other every three months.

During the first contact, the patient and MHP will start drawing up the relapse prevention plan (if not yet available) and decide on the frequency and number of contacts. In the follow-up contacts, the outcomes of the ‘mood and anxiety diary’, the use of the available modules and possible questions will be discussed. The time required for the first contact is 45 minutes, and 20 minutes for the follow-up contacts.

The MHP can actively support the patient in using the online program and provide online feedback at the request of the patient.

3. Study design In this mixed-methods observational cohort study, the relapse prevention program we developed will be implemented and evaluated. This program is targeted at patients who have been discharged from mental healthcare services, and are in complete or partial remission from an anxiety or depressive disorder. This relapse prevention program is called ‘GET READY’ and offers access to an E-health platform, combined with regular contact with a MHP for a period of nine months. General practices will be included in this study. Eligible patients completed mental health treatment for anxiety or depression and are in (partial) remission. Patients will complete online questionnaires at baseline, after 3, 6 and 9 months. In addition, individual interviews and focus group interviews will be held with patients as well as MHPs to evaluate the program and its implementation.

Definition of terms Throughout the literature, several terms are used regarding relapse and remission.

Based on the definitions described by Frank et al. [32], we will make use of three terms: the term ‘relapse’ refers to a return of full symptomatology in concordance with the DSM-IV criteria for a depressive or anxiety disorder [33]. The term ‘full remission’ indicates that no more than minimal symptoms are present and DSM-IV criteria for a disorder have not been fulfilled. In addition, ‘partial remission’ also indicates that DSMIV criteria for a disorder have not been fulfilled, but that more than minimal symptoms are present.

Setting This study will be performed in two settings: 1. General practices throughout the Netherlands, with the participation of approximately 50 MHPs. Patients follow the program at home via an E-health platform, accompanied by face-to-face contact with the MHPs.

Study protocol | 71

2. Ambulatory mental healthcare services with the participation of eligible patients whose GP is not willing to participate in this study. A trained MHP will deliver the relapse prevention program using the same protocol as in the participating general practices.

Recruitment of MHPs We aim to recruit 50 MHPs throughout the Netherlands. Recruitment will be done via telephone, letters, advertisements on websites for MHPs, and via the professional networks of the researchers. For the MHPs working in a general practice, the GP agrees that the MHP participates in this study. Informed consent will be obtained from the MHPs before inclusion.

Recruitment of participants Patients will be recruited via general practices and mental healthcare services. Patients are eligible to participate when they have been treated for an anxiety disorder and/or a depressive disorder in mental healthcare services and are in full or partial remission, according to their clinician. To confirm the clinician’s judgement regarding remission status, the Inventory of Depressive Symptomatology (IDS-SR) and the Beck Anxiety Inventory (BAI) will be administered at baseline [34,35]. Patients with scores > 39 on the IDS-SR and > 30 on the BAI are excluded from the study, since these scores indicate severe symptoms [36,37]. Inclusion criteria are: patients have completed their treatment for anxiety and/or depression within the last two years, have a score on the Global Assessment of Functioning scale (GAF) of 50 or higher, are at least 18 years old, and have sufficient command of the Dutch language. Patients are excluded if they participate in another structured psychological intervention, when they do not have access to the internet, or when the severity of a comorbid psychiatric disorder requires specialized treatment.

Recruitment via general practices Each MHP is requested to include all patients that completed mental health treatment for anxiety and depression and meet the inclusion criteria. MHPs will be asked to identify eligible patients through their patient files. MHPs invite potentially eligible patients for a consultation to discuss participation in the study, to provide information about the study and to check whether patients meet the inclusion criteria. If interest is shown in the study, the researcher contacts the patient and sends the baseline questionnaire. When patients have completed the baseline questionnaire, they receive access to the E-health platform. Eight days after sending the invitation for login, the researchers check if the patient has logged in. If not, they contact the patient to offer technical or practical support.

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Recruitment via mental healthcare services Patients who completed their treatment and are recruited via mental healthcare services, will be contacted by the researchers directly. These patients will be supported during the GET READY program by a MHP working in the ambulatory mental healthcare.

Implementing the relapse prevention program Training of the MHP Each MHP participates in a four-hour training course, focusing on the background and relevance of relapse prevention in anxiety and depressive disorders and potential effective intervention strategies regarding relapse prevention. Next, the content and use of the E-health platform is explained. Finally, information is provided about the study protocol. This training course will be given by either a psychologist or psychiatrist (both part of the research team), together with the first author of this paper.

Support for the MHP After completing the training course, MHPs will receive an information package, including a protocol in which the following topics are described: recruitment of patients, the content of the face-to-face contact with patients, instructions on how to complete the case registration forms, and a guide on the E-health platform, containing screenshots. The package also includes invitation and information letters for patients.

The researchers offer monthly individual consultation via phone to the MHPs to support them in recruiting patients, discuss possible issues, and answer additional questions. Every month the MHPs receive a newsletter to update them on the study and motivate them to continue including patients.

Quantitative data Data collection – measurements Patients are asked to complete four online questionnaires: at baseline (T0), after three months (T3), after six months (T6), and after nine months (T9). It takes approximately 20-30 minutes to complete the questionnaires. Patients receive email invitations and if they do not complete the questionnaire, weekly reminders are sent.

Next, patients are requested to complete the ‘mood & anxiety diary’ every week to rate their level of anxiety and depression. They can complete the diary on their smartphone or on a computer.

After each face-to-face contact, the MHP completes a case registration form. This form contains information on the duration and content of the face-to-face contact, clinical status description, and whether additional appointments were made.

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Data collection – outcome measures Use of relapse prevention program Data will be collected regarding the use of the E-health platform data (number of logins, number of completed/uncompleted modules, and number of diary entries) and the frequency of contact with the MHPs, registered via the case registration forms.

Demographics and clinical variables Sociodemographic characteristics and clinical variables of patients will be assessed at baseline, see Table 2. In addition, patients are asked to estimate their risk of relapse, and to indicate the expected effect of the program.

Self-management strategies Self-management strategies will be measured using the ‘Self-management in depression and anxiety’ questionnaire. This questionnaire was developed during a study on selfmanagement interventions for chronic anxiety and depression [38]. It consists of 45 items describing strategies that patients use to cope with anxiety and depression. Each item is rated on a 5-point Likert scale ranging from 1 (not at all) to 5 (a lot). The total score can be calculated by summing the individual scores.

Anxiety and depression scores Anxiety severity will be measured by the Beck Anxiety Inventory (BAI), a 21-item tool, in which each item is rated on a 0 to 3 point scale, resulting in a total score between 0 to 63, with ≥ 30 indicating severe anxiety [34]. This tool is reported to have a good reliability [39] and validity [40].

The Anxiety Sensitivity Index (ASI) is a 16-item questionnaire for measuring anxiety sensitivity. Each item is rated on a 5-point Likert scale with scores from 0 (barely) to 4 (very much), with a total score ranging from 0 (no anxiety sensitivity) to 64 (severe anxiety sensitivity) [41]. The ASI is a reliable measure [42]. Anxiety sensitivity has been found to be a predictor for relapse in patients with remitted anxiety disorders [3].

The Inventory of Depressive Symptomatology – self-report (IDS-SR) is a 30-item questionnaire for measuring severity of depressive symptoms [35]. Each item is rated on a 0 to 3-point scale, and by summing 28 of the 30 items the total score ranges from 0 to 84, with ≥ 39 indicating severe depressive symptoms. The questionnaire has highly acceptable psychometric properties [43].

Anxiety and mood data are also collected in the weekly diary. Mood is measured by asking ‘how would you rate your mood today?, from 1 (very sad) to 10 (very happy)’.

Anxiety is measured by asking ‘how would you rate the intensity of anxiety today?, from 1 (very relaxed) to 10 (very anxious/tense)’.

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Functioning General functioning and disability will be measured using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). This 36-item tool measures six domains: cognition, mobility, self-care, getting along, life activities and participation.

Each item is rated on a 5-point Likert scale with scores from 0 (no difficulty) to 4 (extreme difficulty or cannot do). By using the ‘item-response theory’-based scoring, the scores will range from 0 (no disability) to 100 (full disability) [44]. The WHODAS 2.0 is reported to have strong psychometric properties [45].

Healthcare use Healthcare and medication use will be measured using an adjusted version of the Trimbos/iMTA Questionnaire for Costs Associated with Psychiatric Illness (TiC-P). Only psychotropic medication will be registered. Health care use is measured as the number of contacts with different healthcare providers. The TiC-P is a feasible and reliable instrument for measuring healthcare use and costs [46].

Satisfaction with the relapse prevention program Satisfaction with the relapse prevention program will be assessed using the ‘Satisfaction with treatment measure’. This 14-item measure provides insight into overall satisfaction, how helpful and useful patients valued the program, perceived support and effect [47].

Also patients will be asked to rate each online module. The original scale was translated into Dutch by the authors, with permission of the author.

Quantitative data analysis For each of the quantitative research questions, a separate analysis will be performed using log data from the E-health platform, data from the case registration forms that have been completed by the MHPs, and data from the four questionnaires: 1) To what extent do patients use a tailored relapse prevention program?

The use of the tailored relapse prevention program will be described, focusing on different aspects of its use, such as the number of login sessions, the amount of time spent online, the number of completed modules, the number of diary entries, the number of sessions and the number of online and face-to-face conversations with the MHP. Descriptive statistics will be used to provide insight into these aspects of the use of the relapse prevention program.

2) What factors influence the use of the program?

The use of the tailored relapse prevention program may differ across patients, and may depend on age, education level and clinical situation. We will explore possible

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Table 2. Information on data collection.

Research question

Type

Outcome measures

1) T o what extent do patients use a tailored relapse prevention program?

Quantitative

Use of the relapse prevention program (log data)

2) W hat factors influence the use of the program?

Quantitative

T0

T3

T6

x

x

x

T9 After study x

Case registration form

3) W hat is the association between usage intensity and course of symptoms?

Quantitative

x

Demographic variables: - Gender - Age - Nationality - Ethnicity - Socioeconomic status - Marital status - Education - Employment status

x

Clinical variables: - Earlier treatment of depression and/or anxiety - Number of previous episodes - Age of onset of symptoms - Family history of depression and/or anxiety - Estimated risk of relapse - Estimated effect of the program

x

Self-management strategies

x

Use of the relapse prevention program (log data)

x

x

x

x

BAI

x

x

x

x

ASI

x

x

x

x

IDS-SR

x

x

x

x

WHODAS 2.0

x

x

x

x

TiC-P

x

x

x

x

Weekly mood and anxiety diary

x

x

x

x

3

x

Case registration form

4) W hat are barriers and facilitators in the implementation of the program?

Qualitative

5) H ow do patients evaluate the program?

Qualitative

x

Individual interviews

x

Focus group interview Satisfaction with treatment measure

x x

Individual interviews

x

Focus group interview

x

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differences in usage between groups of patients systematically, considering sociodemographic factors, clinical symptoms and self-management strategies.

3) What is the association between usage intensity and course of symptoms?

Descriptive statistics will be used to provide insight into course of symptoms for ‘highuse’ participants and ‘low-use’ participants. In order to analyze the association between usage intensity and course of symptoms, multiple regression analyses will be performed. We will first analyze the change in anxiety severity from baseline to followup (9 months) with the following independent variables: intensity of E-health use, number of diary entries and number of contacts with the MHP. We will repeat these analyses for the depression outcomes. In addition, analyses will be performed using ‘deterioration: yes or no’ as outcome variable. Deterioration is defined as an increase of 1 standard deviation on the IDS-SR and/or on the BAI. The standard deviation will be calculated using data from the NESDA study [48], the study from Kok et al. [49], and the present study. This analysis will be performed using a time-lag model, in which the outcome will be assessed using determinants from an earlier measurement (deterioration at timet predicted by usage intensity at timet-1), since we assume that usage intensity might influence whether deterioration occurs at a later point in time.

Because of the observational nature of the data, it will be difficult to draw conclusions about the effects of the relapse prevention program. However, we will conduct additional explorative analyses to estimate the association between usage intensity and course of symptoms. All data analysis will be performed using SPSS statistical analysis software.

Sample size In order to determine the sample size, we assumed a moderate effect (r = 0.24 that corresponds to Cohen’s d = 0.5) of the intensity of program use (X) on the change in symptoms of anxiety and depression (Y). Since this is a non-randomized study, we will use a set of covariates W to correct for selectivity in the uptake of the program. In applying the G*Power 3 software [50] to determine the sample size, we assume that the effect of X corresponds to a 6% of explained variance of Y (equivalent to the moderate effect, since R2 = r2 = 0.242 = 0.06) above the covariates W and assume a 6% reduction of the total variance in Y of the residual variance due to the use of covariates of W, leading to a partial R2 = 0.06 or, equivalently, an effect size of f2 = 0.0638.

Furthermore, setting a = 0.05 and the power of 1 – = 0.80, the sample size calculation shows that 126 patients are needed. Patients will be considered as drop-out when they refuse to complete questionnaires. With an estimated attrition of 20% (i.e. 80% complete at least one follow-up questionnaire), we aim to include 158 patients.

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Qualitative data Data collection – measurements The individual interviews and focus group interviews are conducted to assess implementation and satisfaction with the program.

Individual interviews Paired interviews will be conducted separately with patients and their MHPs in order to gain insight into both perspectives on one case. These paired interviews provide valuable insights regarding similarities and differences in experiences of MHPs and patients [51,52]. Purposive sampling will be used to select patients and realize sufficient variation in our sample with respect to gender, age, severity of symptoms, and use of the program [53]. Patients will be invited by email and telephone to participate in a semi-structured interview to evaluate their experience with the relapse prevention program. If willing to participate, their MHP will be invited as well. The interviews will be conducted by two researchers, who will prepare the interviews by performing two test interviews. A senior researcher will provide supervision and participate in the analysis. We aim to conduct 12-15 interviews with patients and 12-15 interviews with MHPs. The final number of interviews depends on when data saturation is achieved.

A topic guide is developed to support the interview process (see Appendix 3.1). This guide was drafted by the first author and reviewed by two experts, and inspired by the Consolidated Framework For Implementation Research (CFIR) [54]. Main topics are: experiences with the relapse prevention program, use of the relapse prevention program, useful and less useful aspects of the program, and suggestions to improve the program. Input from the E-health platform will be used, such as completed and uncompleted modules, use of the diary, and number of online conversations with the MHP. The topic guide will be evaluated and updated after conducting four interviews.

The MHPs of patients who participate in the interviews will also be invited by email and telephone to participate in an interview. Besides evaluating the program (research question 5), implementation barriers and facilitators will be discussed in these interviews (research question 4), see Appendix 3.2 for the topic guide.

These interviews will be conducted in a setting selected by participants and will take approximately 45 minutes.

Focus group interviews After completing the individual interviews, two focus group interviews will be conducted, one with 8-10 patients and one with 8-10 MHPs. The goal of the focus group interviews is to present, test and discuss preliminary findings and conclusions from the individual interviews. A focus group interview is appropriate for this situation, since the group

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interaction provides insight into topics of agreement and favorable and unfavorable topics, and experiences with the program can be shared [55]. A moderator will lead the group discussion, and an assistant moderator will take notes, observe and keep track of the time [56]. The input from the individual interviews will be used in these focus group interviews, to discuss desirable changes to the E-health program, in order to further improve its quality and usability. In order to obtain new perspectives on the evaluative data from the individual interviews, one half of the focus group participants will not have participated in a previous individual interview. The other half of the focus group members will be purposively selected from the patients and MHPs who previously participated in the individual interviews, where the selection is based on the diverging perspectives on using the relapse prevention program. These focus group interviews will be conducted in a mental healthcare facility and will take approximately 90 minutes.

Qualitative data analysis For each of the qualitative research questions, a separate analysis will be performed: 4) What are barriers and facilitators in the implementation of the program?

The barriers and facilitators in the implementation of the program will be assessed through the semi-structured interviews and focus group interviews with the MHPs. These interviews will be audio recorded, and transcribed verbatim. Data will be sorted using the CFIR [54], which indicates five domains of implementation (intervention characteristics, outer setting, inner setting, characteristics of individuals and process).

Data collection will alternate with data analysis and new topics will be discussed in the following interviews. Two researchers will independently openly code the first three interviews, compare the codes and draft a coding tree. The coding tree will be complemented through the following interviews. This data will be analyzed using thematic analysis [57], which means that the interviews will be coded for themes, these codes will then be sorted and analyses will be performed using software program MaxQDA. When reporting the data, quotations will be used to illustrate the findings.

During this process, multiple researchers will be involved in order to increase the validity and reliability [56]. From the beginning of data collection until the end of data analysis, detailed field notes will be documented, containing specific situations, reflections, and ideas and thoughts of the researchers [56]. In addition, a summary will be made of each interview, containing the most important findings.

5) How do patients evaluate the program?

The evaluation of the program will be assessed by the semi-structured interviews and focus group interviews with the patients. In addition, in the last follow-up questionnaire (T9), patients will be asked about their satisfaction with the program and to rate every

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module they completed on a scale from 0-10. The data from the interviews and focus group interviews will be analyzed in the same way as described above (research question 4). Data from T9 will be analyzed using descriptive statistics.

Discussion Providing relapse prevention for anxiety and depression is important, since these disorders are often chronic and recurrent. In this study we will implement and evaluate a newly developed relapse prevention program, specifically targeted at patients that are (partially) remitted from an anxiety disorder or depression. The mixed-methods approach in this study will provide valuable insights into how patients use the program, what influences the use of the program, how usage intensity influences symptoms and how patients evaluate the program. In addition, information on implementation will be provided which may be relevant for broad implementation of the program. The findings of this study can be used to further refine and adapt the program as preferred by patients and MHPs. A strength of this study is that the relapse prevention program has been developed based on patient preferences and in close collaboration with patients. Additionally, this program is not only web-based, but also supplemented by contact with MHPs. Earlier research suggests that E-health can be especially effective when accompanied by therapist contact [58]. By using log data to establish the usage of the program, the actual use and usage behavior can be determined [59]. Furthermore, by using mixed methods, a complete view on the use of the program and its evaluation can be obtained [59].

This design is not appropriate to examine efficacy, since only within-group effect sizes can be determined, which might be considered a limitation of this study. However, the aim of this study was not to examine the efficacy of the program, but its acceptability. If the program is acceptable, a randomized controlled trial should be conducted to determine the efficacy of the program.

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ABBREVIATIONS MHP: mental health professional; CBT: cognitive behavioral therapy; DSM: diagnostic and statistical manual of mental disorders; GET READY: Guided E-healTh for RElapse prevention in Anxiety and Depression; BAI: Beck Anxiety Inventory; ASI: Anxiety Sensitivity Index; IDS-SR: Inventory of Depressive Symptomatology – self-report; WHODAS: World Health Organization Disability Assessment Schedule; TiC-P: Trimbos/ iMTA Questionnaire for Costs Associated with Psychiatric Illness; CFIR: Consolidated Framework For Implementation Research

FUNDING This study is funded by SIA-RAAK: The Taskforce for Applied Research, part of the Netherlands Organization for Scientific Research (NWO). The funder had no role in study design, data collection and analysis, interpretation of data, and preparation of the manuscript.

ACKNOWLEDGEMENTS Not applicable.

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43. Trivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, Crismon ML, Shores-Wilson K, Toprac MG, Dennehy EB, White B, Kashner TM. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psych. Psychol Med [Internet] 2004 Jan 14;34(1):73–82. [doi: 10.1017/S0033291703001107] 44. WHO. WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) [Internet]. 2018 [cited 2018 Aug 14]. Available from: http://www.who.int/classifications/icf/WHODAS2.0_36itemsSELF.pdf 45. Konecky B, Meyer EC, Marx BP, Kimbrel NA, Morissette SB. Using the WHODAS 2.0 to assess functional disability associated with DSM5 mental disorders. Am J Psychiatry [Internet] NIH Public Access; 2014 Aug [cited 2016 Dec 2];171(8):818–819. PMID:25082488 46. Bouwmans C, De Jong K, Timman R, Zijlstra-Vlasveld M, Van der Feltz-Cornelis C, Tan SS, Hakkaart-van Roijen L. Feasibility, reliability and validity of a questionnaire on healthcare consumption and productivity loss in patients with a psychiatric disorder (TiC-P). BMC Health Serv Res [Internet] 2013;13(1):217.

PMID:23768141 47. Richards D, Murphy T, Viganó N, Timulak L, Doherty G, Sharry J, Hayes C. Acceptability, satisfaction and perceived efficacy of “Space from Depression” an internet-delivered treatment for depression. Internet Interv The Authors; 2016;5:12–22. [doi: 10.1016/j.invent.2016.06.007] 48. Penninx BWJH, Beekman ATF, Smit JH, Zitman FG, Nolen WA, Spinhoven P, Cuijpers P, De Jong PJ, Van Marwijk HWJ, Assendelft WJJ, Van Der Meer K, Verhaak P, Wensing M, De Graaf R, Hoogendijk WJ, Ormel J, Van Dyck R. The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods.

Int J Methods Psychiatr Res [Internet] Wiley-Blackwell; 2008 Sep;17(3):121–140. [doi: 10.1002/mpr.256] 49. Kok G, Burger H, Riper H, Cuijpers P, Dekker J, van Marwijk H, Smit F, Beck A, Bockting CLH. The ThreeMonth Effect of Mobile Internet-Based Cognitive Therapy on the Course of Depressive Symptoms in Remitted Recurrently Depressed Patients: Results of a Randomized Controlled Trial. Psychother Psychosom [Internet] 2015 Feb 21;84(2):90–99. PMID:25721915

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50. Faul F, Erdfelder E, Lang A-G, Buchne, Buchner A, Buchne. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39(2):175–191.

PMID:17695343 51. Bosman RC, Huijbregts KM, Verhaak PF, Ruhé HG, van Marwijk HW, van Balkom AJ, Batelaan NM. Longterm antidepressant use: a qualitative study on perspectives of patients and GPs in primary care. Br J Gen Pract [Internet] 2016 [cited 2017 Sep 14];66(651):e708–e719. [doi: 10.3399/bjgp16x686641] 52. Dikkers MF, Westerman MJ, Rubinstein SM, Van Tulder MW, Anema JR. Why neck pain patients are not referred to manual therapy: A qualitative study among Dutch primary care stakeholders. PLoS One [Internet] 2016;11(6):1–18. PMID:27311067 53. Coyle, I. T, Coyne IT. Sampling in qualitative research. Purposeful and theoretical sampling; merging or clear boundaries? J Adv Nurs [Internet] 1997;26(3):623–630. PMID:9378886 54. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science.

Implement Sci [Internet] 2009 Dec 7;4(1):50. PMID:19664226 55. Duggleby W. What about focus group interaction data? Qual Health Res 2005;15(6):832–840.

PMID:15961879 56. Boeije H. Analyseren in kwalitatief onderzoek. 2nd ed. Amsterdam: Boom Lemma; 2014.

57. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol [Internet] 2006 Jan;3(2):77–101.

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Appendix 3.1. Topic guide interview patient Main questions

Additional questions

Introduction

Sign informed consent Introduce yourself Mention the duration of the interview (45 minutes) Ask permission to audio record the interview, and start the recording Mention that the name and personal data is saved separately from research data Mention the purpose of the interview

What is your experience with the relapse prevention program in general?

What were your expectations of the relapse prevention program?

Could you tell more about the role of the MHP? · What did you expect from the MHP at the beginning of the study? · How did you experience the contacts? · How did you experience the support from the MHP? · In which way did the MHP help you to stay healthy? · What could be improved in the guidance from the MHP? · Who initiated the contact and how did you experience this?

What is your experience with the E-health program? · Usability · Meeting your needs · Pleasure/satisfaction · Available choices · Use of language · Design · Time investment Did the program help you to stay healthy/without symptoms? · In which way did the program help you to stay healthy?

How do you feel about the combination of E-health and having contact with the MHP?

What were the most useful and the least useful parts of the E-health program?

· Which modules did you complete? What made you choose these modules? · What were your motives concerning using or not using the modules? · Which modules were set up for you, but not completed? · Did you complete the diary? · How much did you use the message function within the program? · According to the questionnaires, your symptoms have decreased/ increased. How did you experience this?

What do you like about the relapse prevention program and what could be improved?

What is the most useful aspect of the relapse prevention program?

What could be improved in the relapse prevention program?

What did you miss in the relapse prevention program?

Completion

Are there other topics you would like to discuss?

Do you have any questions?

Would you like to receive the outcomes of the study?

Would you be interested in participating in a focus group interview?

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Appendix 3.2. Topic guide interview MHP Main questions

Additional questions

Introduction

Sign informed consent Introduce yourself Explain which patient the interview is about Mention the duration of the interview (45 minutes) Ask permission to audio record the interview, and start the recording Mention that the name and personal data is saved separately from research data Mention the purpose of the interview

Practical questions

How many hours a week do you work as MHP? Do you work in multiple general practices?

How many minutes does a regular contact last?

How many MHPs/GPs are working in this general practice?

What is your experience with the relapse prevention program?

How did you offer the relapse prevention program to the patient? · How were follow-up contacts planned? · Who initiated the contact and how did you experience this? · How many contacts did you have? · What did you discuss during the contacts? · Did you stimulate the patient to use the relapse prevention program? In which way? · How did the program influence the health of the patient? · To what extent did the program meet the patients’ symptoms?

What did you expect from the patient at the beginning of the study?

How did you offer the relapse prevention program to other patients? *What was it like to offer the relapse prevention program to the patient?

What is your experience with the E-health program? · Usability/structure · Design · Use of language · Time investment · Aspects: what did you use/not use, experience with aspects, relapse prevention plan · Message function/providing feedback

What made it easier or harder to implement the relapse prevention program in the general practice?

The relapse prevention program itself: intervention characteristics · What did you think about the quality of the relapse prevention program? · Did you ever apply relapse prevention strategies before? How does this program compare to other strategies that you are familiar with? · *How complicated is the intervention?

Factors within the general practice: inner setting · How could you apply the relapse prevention program in your ‘normal work’? · Did you experience support from the general practice or GP? How? · In the general practice, what is the willingness to change? · How did having/not having time affect implementation?

Characteristics of individuals · Did you feel confident offering the relapse prevention program?

Why/why not?

Process of implementation · Did you experience support from the research team? How? Influence from outer setting · Did you have contact with specialized mental healthcare services?

What was the effect?

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Main questions

Additional questions

What do you like about the relapse prevention program and what could be improved?

What is the most useful aspect of the relapse prevention program?

What could be improved in the relapse prevention program? *What did you miss in the relapse prevention program?

Would you use the relapse prevention program if available after completion of the study? What is needed?

Completion

Are there other topics you would like to discuss?

Do you have any questions?

Would you like to receive the outcomes of the study?

Would you be interested in participating in a focus group interview?

* If not discussed yet, also ask this question

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USAGE INTENSITY OF A RELAPSE PREVENTION PROGRAM AND ITS RELATION TO SYMPTOM SEVERITY IN REMITTED PATIENTS WITH ANXIETY AND DEPRESSION: PRE-POST STUDY SUBMITTED FOR PUBLICATION

Esther Krijnen-de Bruin, Anna D.T. Muntingh, Evelien M. Bourguignon, Adriaan W. Hoogendoorn, Otto R. Maarsingh, Anton J.L.M. van Balkom, Neeltje M. Batelaan, Annemieke van Straten, Berno van Meijel

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Abstract Background Given that relapse is common in patients in remission from anxiety and depressive disorders, relapse prevention is needed in the maintenance phase. While existing psychological relapse prevention interventions have proven to be effective, they are not explicitly based on patients’ preferences. Hence, we developed a blended relapse prevention program based on patients’ preferences, which was delivered in primary care practices by mental health professionals (MHPs). This program comprises contact with MHPs, completion of core and optional online modules (including a relapse prevention plan), and keeping a mood & anxiety diary in which patients can monitor their symptoms.

Objectives The aims of this study were to provide insight into 1) usage intensity of the program (over time), 2) the course of symptoms during the 9 months of the study, and 3) the association between usage intensity and the course of symptoms.

Methods The Guided E-healTh for RElapse prevention in Anxiety and Depression (GET READY) program was guided by 54 MHPs working in primary care practices. Patients in remission from anxiety and depressive disorders were included. Demographic and clinical characteristics, including anxiety and depressive symptoms, were collected via online questionnaires at baseline and after 3, 6, and 9 months. Log data was collected to assess the usage intensity of the program.

Results A total of 113 patients participated in the study. Twenty-seven patients (23.9%) met the criteria for the ‘minimal usage intensity’ measure. The core modules were used by ≥70% of the patients, while the optional modules were used by <40% of the patients.

Usage decreased quickly over time. Anxiety and depressive symptoms remained stable across the total sample; a minority of 15% of patients experienced a relapse in their anxiety symptoms, while 10% experienced a relapse in their depressive symptoms.

Generalized estimating equations (GEE) analysis indicated a significant association between more frequent face-to-face (FTF) contact with the MHPs and an increase in both anxiety symptoms (B=0.84, 95% CI 0.39-1.29) and depressive symptoms (B=1.12, 95% CI 0.45-1.79). Diary entries and the number of completed modules were not significantly associated with the course of symptoms.

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Conclusions Although the core modules of the GET READY program were used by most of the patients and all patients saw a MHP at least once, usage decreased quickly over time.

Most patients remained stable while participating in the study. The significant association between the frequency of contact and the course of symptoms most likely indicates that those who received more support had more symptoms, and thus it is questionable whether the support offered by the program was sufficient to prevent these patients from relapsing.

Keywords: Relapse prevention, Anxiety disorder, Depressive disorder, E-health Primary care practice, Usage intensity, Self-management

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Introduction Despite effective treatments for anxiety and depressive disorders [1,2], maintenance phase relapse rates are high. Indeed, up to 57% of remitted patients experience a relapse of either their index disorder or another anxiety or depressive disorder within four years of remission [3]. Hence, relapse prevention is crucial in the maintenance phase. Having access to a relapse prevention program could help patients to recognize early warning signs of relapse and take appropriate actions to prevent full relapse.

There are several relapse prevention programs currently available for patients with remitted anxiety and/or depressive disorders. Previous research on patients with a depressive disorder showed that psychological relapse prevention programs reduce both residual symptoms [4,5] and relapse rates by 36% compared to treatment-as-usual [6]. Most relapse prevention programs solely involve face-to-face (FTF) contact, but programs using online formats are increasingly available [7].

Although online programs have the advantage of being easily accessible and flexible [8], the majority of them have low usage and high attrition rates [9–11]. This potentially undermines their effectiveness. A possible limitation of existing relapse prevention programs is that they are not explicitly based on patients’ preferences; taking these preferences into account can increase acceptance and adherence, which, in turn, enhances their effectiveness [12].

In the Netherlands, relapse prevention is provided by mental health professionals (MHPs) in primary care practices. However, many MHPs are unfamiliar with relapse prevention interventions, while the tools to support MHPs in providing relapse prevention are lacking [13].

Therefore, we developed the blended relapse prevention program ‘GET READY’ (Guided E-healTh for RElapse prevention in Anxiety and Depression), which is explicitly based on patients’ preferences. The program aimed to prevent relapsing by promoting self-management skills. Patients’ preferences were obtained via a ‘discrete choice experiment’, in which a set of tasks comprising alternative hypothetical treatment options could be chosen by participants [14]. Patients preferred a relapse prevention program that included regular contact with a professional, flexible time investment based on their needs, and a personalized prevention plan. The purpose of the GET READY intervention was to provide a flexible program that could be used over a longer period, depending on the symptom level of the patient.

Based on these preferences, the GET READY program includes (1) regular FTF contact with a MHP, (2) online modules based on evidence-based (cognitive behavioral) interventions, divided into two core modules (including a personalized relapse prevention plan) and 12 optional modules, and (3) a mood & anxiety diary

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to monitor symptoms. Depending on the symptom level and needs of the patient, the program can be used over a longer period.

This study examined 1) usage intensity of the program (over time), 2) the course of symptoms during the 9 months of the study, and 3) the association between usage intensity and the course of symptoms.

Methods Design The GET READY study was a pre-post study for remitted patients with an anxiety and/ or depressive disorder [15]. This paper presents the results pertaining to the usage intensity of the GET READY program, the course of symptoms (at baseline and after 3, 6, and 9 months), and the association between usage intensity and the course of symptoms.

Setting The study was conducted in 50 primary care practice settings across the Netherlands.

In the Netherlands, most primary care physicians (PCPs) employ a MHP (i.e. nurse, psychologist, or social worker) who provides support and treatment for patients with mild mental health problems. These MHPs were involved in the GET READY program.

Alternatively, for those patients whose MHP was not participating in the study, the program was offered via an ambulatory mental health care center. Patients began with a FTF meeting with a MHP, whereby they started composing a personalized relapse prevention plan. Next, patients could access online modules and a weekly diary via their computer, tablet, or smartphone. They were able to send online messages to their MHP, ask for online feedback on completed modules, and schedule FTF meetings with their MHP. All MHPs received a four-hour training course, in which background information on relapse prevention, strategies for relapse prevention, and practical advice on using the program was provided [15]. PCPs did not play an active role in the study, although some MHPs regularly discussed patients with the PCP in their primary care practice.

Participants Patients were eligible to participate if they had received treatment in specialized mental health care centers for anxiety and/or depressive disorder in the previous two years.

After receiving acute-phase treatment, they were referred to primary care services.

They had to be in full or partial remission according to their MHP or clinician (clinical judgment), have scored 50 or higher on the Global Assessment of Functioning scale

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[16], be at least 18 years old, and be sufficiently fluent in Dutch. Patients were excluded if they were participating in another structured psychological intervention, had no access to the internet, or still received specialized treatment for a comorbid psychiatric disorder. Maintenance antidepressant use was allowed.

Procedures We sought to recruit 50 MHPs and 126 patients for this study. Sample size calculations have been described elsewhere [15]. MHPs and patients were recruited from April 2017 to November 2018.

Fifty-four MHPs working in primary care practices throughout the Netherlands were recruited via telephone, letters, advertisements on MHP websites, and through the researchers’ professional networks. Informed consent was obtained from MHPs at the start of the training course. PCPs had to agree that MHPs participated in the GET READY study.

Patients were recruited either by their MHP or by their clinician at the end of their treatment (N=113), who provided brief information about the study. If patients were interested in participating, then the MHP or clinician asked consent from the patient to provide their contact details to the researchers. Next, consenting patients were contacted by the researchers and received additional information.

Informed consent was obtained prior to administering the baseline questionnaire.

This questionnaire assessed whether patients met the inclusion criteria pertaining to remission, by administering the Inventory of Depressive Symptomatology (IDS-SR) and the Beck Anxiety Inventory (BAI). Remission was defined as a score of <39 on the IDSSR and a score of <30 on the BAI. Scores above these cut-off points indicate severe symptoms that require additional treatment to relapse prevention [17,18]. Therefore, patients with a score of ≥39 on the IDS-SR or ≥30 on the BAI were excluded from the study.

Ethical approval The Medical Ethics Committee of the Amsterdam UMC, location VU University Medical Centre deemed that ethical approval was not required according to Dutch legislation (registration number 2016.280), and thus gave their permission to conduct the study.

GET READY program The central aim of the program was to prevent relapse via the promotion of selfmanagement skills. In the field of mental health, strengthening self-management skills is increasingly important, insofar as it allows patients to self-manage their own mental health [19]. More information regarding the content of the GET READY program has been published previously [15].

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The program comprised several components. The program offered both FTF and online contact with a MHP. Every patient had at least one FTF engagement at the start of the study, and patients and MHPs were encouraged by the researchers to have FTF contact every 3 months. In addition, patients were encouraged to contact MHPs if their symptoms increased. In the FTF contact between patients and MHPs, usage of the program was discussed, and patients were encouraged to use the relapse prevention plan and to complete the diary and online modules. Patients were able to request online feedback from their MHP when using the modules. Besides the feedback on specific modules, patients and MHPs could also send and receive messages via the online platform. MHPs had access to their patients’ data and could check whether they had logged in, or if they had completed modules and the weekly diary. In the event that a patient did not complete a module within a week, they were sent an automatic reminder.

The online modules were divided into the two core modules ‘relapse psychoeducation’ and ‘relapse prevention plan’ (see Appendix 4.1), and 12 optional modules, which included three psycho-education modules with information on depression, anxiety, and medication. The other nine optional modules contained information on specific topics, such as ‘exposure’, ‘negative thoughts’, and ‘sleep’ (see Figure 1). These modules also contained exercises, videos, and examples of fictive patients. Some modules had overlapping themes, and patients could easily open these linked modules from the other module (see the dotted lines in Figure 1).

Finally, the GET READY program included a ‘mood & anxiety diary’, which allowed patients to monitor their symptoms. Patients received weekly reminders to complete the diary.

When patients logged in for the first time, the core components ‘relapse psychoeducation’, ‘relapse prevention plan’ and the ‘mood & anxiety diary’ were available. If patients completed the ‘relapse psycho-education’ module, the ‘depression/anxiety/ medication psycho-education’ modules were automatically setup. Likewise, if patients completed the ‘relapse prevention plan’, they could choose which optional modules they wish to complete, based on their preferences and goals.

Data collection Patients were invited to complete online questionnaires at baseline (T0) and after 3 (T1), 6 (T2), and 9 months (T3). Completion of the questionnaires took 20-30 minutes.

If necessary, patients received an online reminder after one week. As part of the treatment protocol, patients were also prompted to complete the mood & anxiety diary once a week for a period of 9 months (39 times). MHPs were requested to complete a case registration form after each FTF contact, in which the clinical status of patients and the duration and content of the FTF contacts were described.

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In order to assess the usage intensity of the program, log data from the online platform was collected.

Figure 1. Overview of E-health modules.

Measures Demographic and clinical variables Demographic and clinical variables of patients were assessed at baseline using the online questionnaire. Moreover, in the baseline questionnaire patients were asked to score their own perceived risk of relapse, as well as their expectations about the effectiveness of the relapse prevention program (0-100%). Anxiety severity was measured using the BAI, and symptoms in the past week were assessed. This questionnaire contains 21 items, all of which are rated on a 0 to 3-point scale, with a total score ranging from 0 to 63, with ≥ 30 indicating severe anxiety symptoms [20].

Severity of depression was measured using the IDS-SR [21]. Depressive symptoms in the past week were assessed. This questionnaire contains 30 items, all of which are rated on a 0 to 3-point scale, and when adding up 28 of the 30 items the total score ranged from 0 to 84, with ≥ 39 indicating severe depressive symptoms [18]. To provide insight into the baseline clinical characteristics of patients, anxiety sensitivity and general functioning and disability were also measured. Anxiety sensitivity was measured using the Anxiety Sensitivity Index (ASI) [22]. This questionnaire has 16 items, all of

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which are rated on a 0 to 4-point scale, with a total score ranging from 0 (no anxiety sensitivity) to 64 (severe anxiety sensitivity). General functioning and disability was measured using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). This questionnaire has 36 items, all of which are rated on a 0 to 4-point scale, with a total score ranging from 0 (no disability) to 100 (full disability) [23].

Medication and healthcare use was measured using the Trimbos/iMTA Questionnaire for Costs Associated with Psychiatric Illness (TiC-P) [24].

Primary outcome Program usage variables Log data from the online platform was used to assess the online usage intensity of the program. This included the number of messages from patients to MHPs or vice versa, the number of completed modules, and the number of diary entries. The frequency of FTF contact between patients and MHPs was registered with the TiC-P [24].

Participants were divided into low and regular users based on the median of the separate usage variables, as the data was non-normally distributed. If participants had completed at least the median amount of FTF contact with the MHP (one), modules (four), and diary entries (four), then they were classified as regular users of these specific usage variables. If they completed less than the median of the separate usage variables, then they were considered to be low users. Furthermore, a ‘minimal usage intensity’ measure was composed. If patients had at least one FTF contact during the intervention period, completed the core components of the program (relapse psychoeducation module, relapse prevention plan, at least four mood & anxiety diary entries), and completed at least one extra module, then they were classified as regular users.

If they did not complete these components, they were considered to be low users.

Course of symptoms To explore the course of symptoms during the study, the severity of anxiety and depressive symptoms were measured at baseline and three-month intervals (T1, T2, T3) using the BAI and the IDS-SR. Deterioration/relapse was defined as an increase of at least one standard deviation (SD) on the IDS-SR and/or of an increase on the BAI between T0 and T3. Similarly, symptom improvement was defined as a decrease of at least one SD. The SD was calculated using data from the NESDA study [25], the study of Kok et al. [5], and the present study, resulting in a SD on the IDS-SR of 9.3 and a SD of 6.6 on the BAI. By approaching the definition of relapse this way, patients can be regarded as their own controls, and an increase of one SD most likely indicates a clinically significant increase in symptoms, and thus indicate relapse.

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Statistical analysis Descriptive statistics were used to describe the characteristics of the participants, to illustrate the extent to which patients used the program (over time), and to explore the course of symptoms.

Explorative analyses were conducted to study the association between usage intensity and the course of symptoms. The course of symptoms was determined for both regular and low users in accordance with the ‘minimal usage intensity’ measure, as well as for the separate usage intensity measures. Differences in anxiety and depressive symptoms between regular and low users were tested using the Mann-Whitney U-test (as these were non-normally distributed), while Bonferroni corrections were applied to correct for multiple testing [26]. Generalized estimating equations (GEE) analyses were carried out to examine the longitudinal association between the different usage intensity variables and the course of symptoms. The usage intensity variables indicated usage of the program between baseline and T1, T1 and T2, and T2 and T3. In this way, the association between usage intensity and the course of symptoms, at the point of each follow-up questionnaire, was assessed by taking into account the usage intensity in the period immediately prior to the follow-up questionnaire. A time-lag model was used, in which an adjustment was made for the outcome at time point t – 1, as it assumed that the outcome at time t was predicted by the outcome at time t – 1 (see Figure 2).

All data analyses were performed using SPSS 26. Further details regarding the methods employed in this study can be found in the study protocol [15].

Figure 2. Time-lag model. T0: baseline assessment, T1: assessment after 3 months, T2: assessment after 6 months, T3: assessment after 9 months.

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Results Participant characteristics The demographic and clinical characteristics of the participants (N=113) are reported in Table 1. The mean age at baseline was 43 years (SD 12.9). More than half of the participants were female (57.5%), while more than half of the participants attended higher professional education or university (56.6%). Overall, 36.3% of the participants reported being treated for a depressive disorder, 23.9% stated they had been treated for an anxiety disorder, and 39.8% stated they had been treated for both.

Table 1. Demographic and clinical characteristics of the total sample (N=113).

Variables

Value

Demographic variables Age (years), mean (SD)

42.9 (12.9)

Sex (female), n (%)

65 (57.5)

Nationality (Dutch), n (%)

105 (92.9)

Marital status, n (%) Single

45 (39.8)

In relationship

68 (60.2)

Highest educational level, n (%) High-school

23 (20.3)

Secondary vocational education

22 (19.5)

Higher professional education or university

64 (56.6)

Unknown

4 (3.6)

Occupational, n (%) Employed

79 (69.9)

Sick leave

18 (15.9)

Other

16 (14.2)

Clinical variables Clinical history, n (%) Treatment for depressive disorder

41 (36.3)

Treatment for anxiety

27 (23.9)

Treatment for both depressive disorder and anxiety

45 (39.8)

Number of times received treatment for anxiety and/or depressive disorder, mean (SD)

3.5 (3.3)

Time passed since referral back to the primary care physician from specialized care (months), mean (SD)

5.9 (6.3)

Age of first onset, mean (SD)

27.6 (13.8)

Positive family history of anxiety and/or depressive disorder, n (%)

60.0 (53.1)

Anxiety sensitivity (ASI), mean (SD)

10.7 (7.9)

General functioning and disability (WHODAS 2.0), mean (SD)

23.6 (15.0)

Anxiety severity (BAI), mean (SD)

10.2 (6.6)

Depression severity (IDS-SR), mean (SD)

20.6 (9.5)

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Usage intensity The use of the program is described in three subcategories: 1) contact with MHP, 2) completed modules, and 3) diary entries.

Contact with MHP The option to correspond online with MHPs via the online platform was rarely exercised by participants. In total, the 113 patients sent 157 online messages to their MHPs (Mdn 0.0, interquartile range [IQR] 0.0-2.0), and received 260 messages in return from their MHPs (Mdn 1.0, IQR 0.0-3.0). Sixty-five patients (57.5%) never sent a message to their MHP, and 45 patients (39.8%) never received a single message from their MHP. All participants had initial FTF contact with their MHP. During the 9 months of the study, there were a total of 260 FTF follow-up meetings (Mdn 1.0, IQR 0.0-4.0). Fortynine participants (43.4%) did not have any follow-up meetings with their MHP. Forty-one participants (36.3%) met their MHP at least every 3 months, as prescribed in the research protocol. The number of FTF appointments ranged from 0 to 13.

Completed modules A median of four modules were completed by the participants (IQR 2.0-8.0). Of the 113 participants, one (0.01%) completed all 14 available modules, while 17 participants (15%) failed to complete any modules. The two core modules were completed the most: 74.3% (84/113) of the participants completed the module ‘Relapse psycho-education’ and 69.9% (79/113) completed the module ‘Relapse prevention plan’. Forty-six to 54% of patients completed the other three psycho-education modules, while less than 40% of patients completed the optional modules.

Figure 3. Usage of the modules, diary and FTF contacts over time.

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Diary entries The number of diary entries varied substantially across the participants, ranging from 0 to 159, with a median of four (IQR 1.0-15.0). Seventeen participants (15%) never reported on their mood and anxiety. Only 12 participants (10.6%) completed the diary weekly for the entire duration of the study.

Usage of the program decreased considerably over time, as can be seen in Figure 3. In particular, there was a strong decrease in both the number of completed modules and number of diary entries. The median for when participants completed their last module was 31 days (IQR 10.0-92.5) after registering on the online platform.

Course of symptoms In the overall sample, anxiety and depressive symptoms decreased slightly over time.

For all 113 participants, the mean BAI score at baseline was 10.2 (SD 6.6). After 9 months, the mean BAI score of the remaining 79 participants was 9.3 (SD 8.2). The differences over time were not significant, as indicated by the overlapping error bars in Figure 4. A completer-analysis (which included only those patients who completed T3) produced similar results.

Figure 4. Course of anxiety symptoms over time, with error bars indicating 95% confidence intervals.

The mean IDS-SR score of all 113 participants decreased from 20.6 (SD 9.5) at baseline to 17.3 (SD 11.8) at 9 months (T3). The differences over time were not significant, as indicated by the overlapping error bars in Figure 5. A completer-analysis produced similar results.

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Figure 5. Course of depressive symptoms over time, with error bars indicating 95% confidence intervals.

Regarding changes in symptomatology (stable / deteriorated / improved), for anxiety symptoms, it was found that the majority of the 79 patients who completed T3 remained stable over time (52/79, 65.8%), 12 patients (15.2%) experienced a deterioration of at least one SD (defined as a relapse), and 15 patients (19%) saw their anxiety symptoms improve.

The numbers were comparable for depression symptoms: 53 patients (67.1%) remained stable, eight patients (10.1%) deteriorated/relapsed, and 18 patients’ (22.8%) depressive symptoms improved.

Seven patients (8.9%) experienced a deterioration in both their anxiety and depressive symptoms. For all three categories (stable / deteriorated / improved), antidepressant medication use remained largely stable. For depressive symptoms, most patients in the stable and deterioration group used antidepressant medication: 56.6% and 75% respectively. In the improved group, 50% used antidepressant medication. For anxiety symptoms, also the majority of patients in the stable and deterioration group used antidepressant medication: 63.5% and 58.3% respectively.

In the improved group, 33.3% used antidepressant medication.

Association between usage intensity and course of symptoms Minimal usage intensity measure Of the 113 patients, 27 (23.9%) met the criteria for the ‘minimal usage intensity’ measure, and, hence, these patients were defined as ‘regular users’. Figure 6 depicts the course of anxiety symptoms for both regular and low users, as measured by the combined ‘minimal usage intensity’ measure. No significant differences were found in the anxiety symptoms between regular and low users (T0: U=1122.0, P=.79; T1: U=840.0, P=.52; T2: U=738.5, P=.79; T3: U=623.5, P=.59).

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Figure 6. BAI scores for low and regular use according to the minimal usage intensity measure.

Note. Minimal usage intensity measure was defined as: at least one FTF contact during the intervention period, completed relapse psycho-education module and relapse prevention plan, at least four mood & anxiety diary entries, completed one extra module.

Figure 7 depicts the course of depressive symptoms for both regular and low users.

Although the mean scores for regular users were higher across all the time points, no statistically significant differences were found between low and regular users (T0: U=1025.0, P=.36; T1: U=700.0, P=.07; T2: U=708.0, P=.57; T3: U=506.5, P=.08).

Figure 7. IDS-SR scores for low and regular use according to the minimal usage intensity measure.

Note. Minimal usage intensity measure was defined as: at least one FTF contact during the intervention period, completed relapse psycho-education module and relapse prevention plan, at least four mood & anxiety diary entries, completed one extra module.

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The number of appointments in specialized mental health care facilities during the study did not significantly differ between regular and low users (T1: U=909.0, P=.92; T2: U=702.0, P=.39; T3: U=631.0, P=.55). There was a significant difference between regular and low users in terms of the number of appointments they had with a psychologist or psychiatrist in a private practice at T3 (U=575.0, P=.04), namely that low users had more appointments than regular users. However, after applying the Bonferroni correction this difference was no longer significant. No significant differences in medication use between regular and low users were found (T0: U=1148.0, P=.92; T1: U=900.5, P=.87; T2: U=727.5, P=.66; T3: U=645.0, P=.71).

Separate usage intensity measures The mean BAI scores and IDS-SR scores for regular users (median use of usage variable or higher) and low users (below median of usage variable) on the separate usage intensity measures across all four time points are shown in Appendix 4.2. Patients who had one or more FTF meetings with their MHP, after the initial FTF contact, experienced a higher score on the BAI and IDS-SR at T3. For diary entries and the number of completed modules, the BAI and IDS-SR scores did not differ between regular and low users.

GEE analyses In the GEE analyses, all of the separate usage variables were used to model the course of anxiety and depressive symptoms in a multivariate analysis. GEE analyses indicated no significant association between module completion and number of diary entries, and the course of anxiety or depressive symptoms (Table 2).

A significant association was found between the frequency of FTF contact with MHPs and the course of anxiety and depressive symptoms. The coefficient of 0.84 (95% CI 0.39-1.29) indicates that each additional FTF meeting with a MHP was associated with an increased BAI score of 0.84 in the next measurement (corrected for the BAI score one measurement prior). Similarly, the coefficient of 1.12 (95% CI 0.45-1.79) indicates that each additional FTF meeting with a MHP was associated with an increased IDS-SR score of 1.12 in the next measurement (corrected for the IDS-SR score one measurement prior). Therefore, more FTF contact with MHPs was significantly associated with higher anxiety and depressive scores.

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Table 2. GEE analysis, longitudinal associations of separate usage intensity variables with anxiety and depressive symptoms.

Anxiety symptoms B (SE)

95% CI

0.12 (0.13)

-0.15, 0.38

FTF contact MHP

0.84 (0.23)

0.39, 1.29

Diary completion

-0.05 (0.03)

Module completion

-0.10, 0.003

Depressive symptoms P value

B (SE)

95% CI

0.06 (0.12)

-0.18, 0.30

.65

< .001

1.12 (0.34)

0.45, 1.79

.001

.07

-0.04 (0.03)

-0.09, 0.02

.19

.39

P value

Discussion Principal results This study has shown the usage intensity of the GET READY relapse prevention program, explored the course of symptoms of participants across the duration of the study, and examined the association between usage intensity and the course of symptoms.

The core modules were used by ≥70% of the patients, while optional modules were regarded as elective and used as such (<40% of the patients). Of the 113 patients, 27 (23.9%) were defined as regular users, according to the minimal usage intensity measure. Usage of the self-management components of the program (the online modules and online mood & anxiety diary) decreased quickly over time. Although no causal effect of the GET READY intervention on the severity of psychopathology could be established due to its pre-post design, it appeared that most patients remained stable or experienced symptom improvement while they engaged with the GET READY program. Having more FTF contact with MHPs was significantly associated with an increase in anxiety and depressive symptoms. The other usage intensity variables were not significantly associated with the course of symptoms.

Overall, the participants were highly educated and employed. These results are consistent with other studies on web-based or E-health interventions [27,28], which have shown that this group is more likely to use online interventions. Similarly to Kontos et al. [28], we also found it difficult to access patients with lower educational levels, which is problematic given that this program might also be beneficial for this group.

Therefore, future relapse prevention studies should attempt to access participants with lower educational levels, by seeking input from this group during the developmental phase of interventions.

The core components of the program were used fairly well, as the two core modules ‘relapse psycho-education’ and ‘relapse prevention plan’ were completed by around 74% and 70% of patients, respectively. As expected, optional modules were used less frequently than the core modules, with less than 40% of patients completing them.

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This result is consistent with data from Hollandäre et al. [29], who showed that their basic modules were used more often than optional modules. Nonetheless, usage of the optional modules in this study was relatively low in comparison to other studies [30–33]. The average usage intensity in these other programs was higher, with around 50% of participants completing all available modules. However, these studies varied in terms of the number of modules (N=3-12), not to mention that the online programs were not focused on relapse prevention, but rather on treating anxiety and depressive disorders. In the present study, patients had already finished treatment for anxiety and/or depressive disorders, were in remission, and therefore may not have felt the need to actively engage in a relapse prevention program. One explanation for the relatively low usage could be simply that the patients experienced ‘treatment fatigue’ [34]. Another explanation might be that, since all the patients had received treatment prior to this study, the lessons learned from treatment were very much at the forefront of their mind and, as such, they felt no desire to repeat these lessons in the relapse prevention program. Indeed, it appeared that patients selected the modules that applied to their situation. To conclude, the optional modules in our relapse prevention program were regarded as elective and used as such.

Usage of the program decreased rapidly over time, as most patients used the program for a median of 1 month after registering on the online platform. Although this finding has been reported in previous studies on (online) guided self-help programs [10,11], it was contrary to the aim of the intervention, which was to provide a flexible program that can be used over a longer period of time, depending on patients’ symptom levels. Prior studies demonstrated that both the absence of symptoms and an increase of symptoms might hinder patients’ capacity to actively use a program.

Potentially, patients with fewer symptoms may not need to engage with the entire program to feel well again and cease using the program after obtaining the benefits [35,36]. At the same time, a qualitative study on the GET READY program indicated that increased symptom levels might also limit patients from further using the program [37]. An increase in depressive or anxiety symptoms may result in avoidance behavior, which may also lead to avoiding actively working on the online modules. This underlines the importance of the proactive role to be played by MHPs, namely in terms of stimulating patients who are vulnerable to relapsing to continue using the program.

Another important way of keeping patients engaged might be the further personalization of the intervention content, for example by increasing the depth of tailored feedback, providing real-time feedback and customizing the content based on current symptoms [9,37].

Although all of the patients were in remission, they nevertheless appeared vulnerable to relapse: patients had already received an average of 3.5 treatments in specialized care, 53.1% (60/113) had a family history of anxiety/depression, and around 40% (45/113) had received treatment for both an anxiety and a depressive disorder,

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while their baseline mean symptom levels showed mild residual anxiety and depressive symptoms. In the overall sample, anxiety and depressive symptoms decreased slightly over time. Most participants remained stable, while a minority of 19-23% of patients experienced symptom improvement. Only 10-15% of the patients experienced a relapse. In comparison to other studies, our results show lower relapse rates [38,39].

Hardeveld et al. [38] found that after 10 months, 20-30% of patients experienced a relapse of their depressive symptoms. Similarly, Taylor et al. [39] found that around 30% of patients experienced a relapse of their anxiety symptoms within a year.

Although no causal pathway could be established in this pre-post study, these results nevertheless indicate that the GET READY program could potentially protect patients from relapse. However, as the definition of relapse differs across studies, comparing the results can be difficult. Therefore, efforts should be made in the field to reach a consensus regarding the definition and assessment of relapse in depression and anxiety disorders. Moreover, the effectiveness of the GET READY program in preventing relapse should be tested in a randomized controlled trial (RCT).

Patients that experienced a deterioration in symptoms more often used antidepressant medication than patients whose symptoms improved. However, this result should be interpreted with caution, as no causal pathway can be established.

This study design is not feasible to investigate the influence of medication on the course of symptoms.

Patients who had more FTF contact with MHPs had significantly higher anxiety and depressive scores than patients who had less FTF contact with MHPs. It is questionable whether the support they received by their MHP was sufficient to engender a subsequent decrease in symptoms. At the same time, this result might indicate that the online program in itself does not provide enough support to patients who experience a deterioration of symptoms. As aforesaid, this is a pre-post study, so no causal pathway could be established [40]. An alternative explanation for this significant association might be that patients adequately responded to early symptoms of relapse, by reaching out to their MHP. This explanation is in line with an earlier study, which showed that patients with more severe symptoms were more likely to receive help [41].

Furthermore, no evidence was found for an association between the number of completed modules and diary entries on the one hand, and the course of symptoms on the other hand. Although no comparison with other relapse prevention programs is currently possible, other treatment studies have found that more completed online modules are associated with better anxiety and depression outcomes [31,42]. The same applies to the number of diary entries [43]. When comparing this study to these studies, it becomes apparent that the sample size of these studies was larger. Therefore, as well as the difference in population (remitted vs. present disorder) and aims of the program (relapse prevention vs. treatment), these studies may also have had more scope to detect an association.

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Limitations There are several potential limitations to this study. First, attrition from the study was relatively high, with only 79 (70%) participants completing the last follow-up questionnaire. Despite this, the statistical methods applied in this study, especially GEE analyses, are expedient for handling missing data. Second, self-selection bias and the fact that the patients were highly educated might restrict the generalizability of the results. However, Donkin et al.’s [44] study showed no indication that these factors actually limit the generalizability, as they found no evidence that these factors were related to study outcomes. Third, this study had a limited follow-up period of 9 months.

A longer follow-up period of 2 years would have provided greater insight into the course of anxiety and depressive symptoms over a longer period of time, which, in turn would have facilitated better comparison with other studies [38,45]. However, for pragmatic reasons, it was not feasible to extend the follow-up period. Fourth, due to methodological considerations no time-to-event analysis could be performed, as the assumptions for this analysis could not be met. Finally, the definitions of ‘regular use’ that were used in this study should be interpreted with caution. As the median of several usage intensity measures was relatively low (i.e. FTF contact median=1), ‘regular use’ could still indicate relatively low usage when compared to the intended amount of usage (i.e. FTF contact once every 3 months=3 FTF meetings). However, to enhance readability we opted to use the terms ‘regular use’ and ‘low use’.

Implications for practice and research This study highlights the importance of providing personalized and guided relapse prevention to remitted patients with anxiety and depressive disorders. Usage of the program decreased quickly over time, possibly indicating a rapid decrease in the motivation of patients. As aforesaid, this decrease in motivation can be explained by different causal factors. Therefore, MHPs have the important task of monitoring and motivating patients via personalized intervention strategies, thus ensuring that patients receive guidance when they need it the most.

Further research in a RCT with a longer follow-up duration is necessary to establish the effectiveness of blended relapse prevention programs. Within the design of a RCT, greater insight can also be obtained into the association between usage intensity and the course of symptoms.

Conclusions When relapse prevention was offered, most patients used the core modules, while optional modules were completed by a smaller sample. As indicated in an earlier study [14], the patients showed that they preferred a low level of time investment for relapse prevention programs. Despite the relatively low usage and low time investment, most patients remained stable while participating in the GET READY study. Patients who had

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more FTF contact with their MHP experienced more anxiety and depressive symptoms.

Due to the pre-post design of this study, no causal pathway could be established. A RCT is needed to provide insight into the effectiveness of the GET READY program and to further explore the causal relationship between usage intensity and the course of symptoms.

ACKNOWLEDGEMENTS AM, NB, AS and BM obtained funding for this study. EKB, AM, NB, AS, OM, AB and BM contributed to the design of the study. EKB, AM and BM coordinated the recruitment of mental health professionals and patients and the data collection. AH advised in data analysis. EB participated in data analysis. EKB analyzed the data and drafted the manuscript. All authors revised and commented on the manuscript. All authors read and approved the final manuscript.

The authors gratefully acknowledge the contribution of all patients, mental health professionals, primary care practices, research assistants, data managers, and all others who contributed to the study.

FUNDING This study is funded by SIA-RAAK: The Taskforce for Applied Research, part of the Netherlands Organization for Scientific Research (NWO). The funder had no role in study design, data collection and analysis, interpretation of data, and preparation of the manuscript.

ABBREVIATIONS ASI: Anxiety Sensitivity Index BAI: Beck Anxiety Inventory FTF: face-to-face GEE: Generalized estimating equations GET READY: Guided E-healTh for RElapse prevention in Anxiety and Depression IDS-SR: Inventory of Depressive Symptomatology IQR: interquartile range MHPs: mental health professionals PCPs: primary care physicians RCT: randomized controlled trial TiC-P: Trimbos/iMTA Questionnaire for Costs Associated with Psychiatric Illness WHODAS 2.0: World Health Organization Disability Assessment Schedule 2.0

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Appendix 4.1. Home page for patients with core modules ‘relapse psycho-education’ and ‘relapse prevention plan’, and the ‘mood & anxiety diary’

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Figure 4.2.2. IDS-SR scores for low and regular use of separate usage intensity measures.

Figure 4.2.1. BAI scores for low and regular use of separate usage intensity measures.

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Appendix 4.2. Low and regular use of separate usage intensity measures

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EVALUATION OF A BLENDED RELAPSE PREVENTION PROGRAM FOR ANXIETY AND DEPRESSION IN GENERAL PRACTICE: QUALITATIVE STUDY PUBLISHED IN JMIR FORMATIVE RESEARCH 2021, 5:1–10

Esther Krijnen-de Bruin (shared first author), Jasmijn A. Geerlings (shared first author), Anna D.T. Muntingh, Willemijn D. Scholten, Otto R. Maarsingh, Annemieke van Straten, Neeltje M. Batelaan, Berno van Meijel

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Abstract Background Existing studies have yet to investigate the perspectives of patients and professionals concerning relapse prevention programs for patients with remitted anxiety or depressive disorders in primary care. User opinions should be considered when optimizing the use and implementation of interventions.

Objective This study aimed to evaluate the GET READY relapse prevention programs for patients with remitted anxiety or depressive disorders in general practice.

Methods Semistructured interviews (N=26) and focus group interviews (N=2) with patients and mental health professionals (MHPs) in the Netherlands were performed. Patients with remitted anxiety or depressive disorders and their MHPs who participated in the GET READY study were interviewed individually. Findings from the interviews were tested in focus group interviews with patients and MHPs. Data were analyzed using thematic analysis.

Results Participants were positive about the program because it created awareness of relapse risks. Lack of motivation, lack of recognizability, lack of support from the MHP, and symptom severity (too low or too high) appeared to be limiting factors in the use of the program. MHPs play a crucial role in motivating and supporting patients in relapse prevention. The perspectives of patients and MHPs were largely in accordance, although they had different perspectives concerning responsibilities for taking initiative.

Conclusions The implementation of the GET READY program was challenging. Guidance from MHPs should be offered for relapse prevention programs based on eHealth. Both MHPs and patients should align their expectations concerning responsibilities in advance to ensure optimal usage. Usage of blended relapse prevention programs may be further enhanced by diagnosis-specific programs and easily accessible support from MHPs. Keywords: Relapse prevention, Anxiety disorder, Depressive disorder, E-health, General practice, Qualitative research

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Introduction The high prevalence of anxiety and depressive disorders is a major public health problem, affecting 615 million people globally [1]. Although effective treatment interventions (psychological as well as pharmacological) are available [2–5], 57% of patients in remission from anxiety disorders or depression experience a relapse within 4 years [6]. Effective relapse prevention provided in general practice could increase quality of life, decrease the high burden of disease for patients with anxiety and depressive disorders, and prevent the need for treatment in a (more costly) specialized mental health care setting [7].

Existing knowledge about effective components of relapse prevention programs and effective ways of implementation remains limited. Several effective relapse prevention programs for patients with remitted depressive disorders were examined in a meta-analysis by Biesheuvel-Leliefeld et al [8], although few studies on relapse prevention concern patients with anxiety disorders [9–12]. A limited number of relapse prevention programs use eHealth, even though it offers improved access to evidencebased treatments [13]. Results concerning effectiveness in these guided eHealth studies for patients with remitted depressive disorders are conflicting: One reports a lower relapse rate after 2 years, while another does not [14,15]. Two other studies, both guided [16] and unguided [17], report a decrease in residual depressive symptoms after participating in an online relapse prevention intervention [16,17]. Variations in type of treatment, guidance, and the duration of the intervention might explain the conflicting results of these studies.

Knowledge concerning how patients and professionals value these programs is lacking. Also, knowledge regarding the appreciation of specific program components is missing. Additional insight into the valuation, feasibility, and usability of relapse prevention programs could allow optimization of such programs, as well as their implementation and use.

To our knowledge, no previous studies have investigated the perspectives of users concerning relapse prevention programs in general practice, although some do focus on users’ perspectives regarding blended interventions (eHealth combined with faceto-face contact) for depression treatment. In a study on the perspectives of patients concerning a blended cognitive behavioral therapy program for depression, Urech et al [18] reported that patients appreciate the constant availability of the online program and the possibility of reflecting on their progress. At the same time, however, patients feel pressure to complete modules, experience a lack of flexibility, and have difficulty finding motivation to complete the online modules.

In addition to the patients’ perspectives on relapse prevention interventions, it is important to consider the perspectives of the professionals providing the program:

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If professionals do not support the intervention, patients are less likely to use it [19].

According to professionals, advantages of blended interventions include access to online content between face-to-face sessions for patients and the fact that the structure of the online format provides focus in the treatment. At the same time, however, professionals note that technical issues could be burdensome to patients, and they do not appreciate the limited possibility of customization for online programs [20].

This article describes findings from a qualitative study conducted as part of the GET READY (Guided E-healTh for RElapse prevention in Anxiety and Depression) study [21], in which a blended relapse prevention program tailored to the patients’ preferences [22] was developed and tested. The overall aims of the GET READY study were to implement and evaluate the GET READY relapse prevention program. This program is offered by mental health professionals (MHPs) in general practices in the Netherlands to patients who are in remission from anxiety or depressive disorders.

The aim of the current study was to provide insight into the perspectives of users (both patients and MHPs) on the GET READY relapse prevention program, specifically regarding expectations of the program, attractiveness of the program, collaboration and communication between patients and MHPs, usability (especially in case of an increase of symptoms), and subjective effectiveness. In addition, the aim was to provide insight into factors that influence the use and implementation of the GET READY program in general practice.

Methods Study design We conducted a qualitative study as part of the GET READY study. First, semistructured individual interviews were conducted with pairs of patients and MHPs. We then conducted 2 focus group interviews—one with patients and one with MHPs—to reflect on the findings from the individual qualitative interviews. The COnsolidated criteria for REporting Qualitative studies guideline [23] was followed in reporting on this study.

The completed checklist can be found in Appendix 5.1.

Sampling and recruitment for the qualitative study For the individual interviews, purposive sampling was performed (based on sex, age, clinical variables, and place of residence) among all 113 patients participating in the GET READY intervention program, with the aim of including 12-15 patients and 12-15 of their MHPs. All patients enrolled in the GET READY study were at least in partial remission from an anxiety or depressive disorder and had completed treatment in specialized mental health care within the past 2 years. The researchers invited patients

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to participate in the individual interviews by telephone or email. The MHPs of patients agreeing to participate were invited to participate as well. In the Netherlands, most general practices employ MHPs—with professional backgrounds in community mental health, social work, or psychology—to provide mental health services [24]. Besides screening, diagnostics, providing psychoeducation, and supporting self-management, one of their tasks is to support relapse prevention [25]. Patients whose MHPs declined to participate were not interviewed. By interviewing both the patient and their MHP, we aimed to gain insight into similarities and differences in perspectives within and between these groups.

For the 2 focus groups, patients and MHPs received invitations by email. Patients and MHPs participating in the individual interview could also participate in the focus group interviews.

All participants gave written informed consent and were offered a €25 (US $30.34) gift voucher for participating in the individual or the focus group interviews. The Medical Ethical Committee of the VU University Medical Center Amsterdam judged that ethical approval was not required according to Dutch legislation. The methods of the full GET READY study are described in detail in the study protocol [21]. The GET READY program consists of 3 core components: (1) relapse psychoeducation module, (2) relapse prevention plan, and (3) weekly diary in which patients can monitor their symptoms. Furthermore, 12 optional eHealth modules are offered. All modules are focused on promoting self-management skills, by providing information, exercises, videos, and examples of fictive patients. As described, this program is offered to patients by MHPs. Patients had at least one face-to-face contact with their MHP during the GET READY study and were encouraged to visit their MHP once every 3 months, for a period of 9 months. Further details about the GET READY intervention can be found in Appendix 5.2.

Data collection The interviews were conducted individually with patients and MHPs by JG, EKB, and two Master’s students in medicine. All researchers had prior experience with qualitative research. Separate topic lists were developed for patients and MHPs (see Appendix 5.3 and Appendix 5.4), based on the aims of the study, the content of the GET READY intervention, the Consolidated Framework for Implementation Research [26], and literature on qualitative research [27,28]. In short, the topic lists contained questions regarding expectations of the program, attractiveness of the program, collaboration and communication between patients and MHPs, usability (especially in case of an increase of symptoms), and subjective effectiveness of the relapse prevention program.

The interviewers did not know the patients in advance. Although they were familiar with the researchers, the MHPs were encouraged to express all comments and criticism they might have.

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The interviews were conducted in the patients’ homes or the general practice location between February 2018 and February 2019. Each interview lasted about 45 minutes. Data collection and analysis occurred in an iterative process, with intermediate analyses guiding subsequent data collection [29]. Data were collected until data saturation was reached (ie, when no new themes emerged from the interviews).

After completing the individual interviews, 2 focus group interviews were conducted in June 2019 and September 2019 at the research clinic, one with patients and one with MHPs. These interviews were moderated by BM, an experienced researcher in the field of qualitative methodology. In the focus group interviews, preliminary findings from the individual interviews were presented, and input from participants was collected about their perceptions on remarkable findings in the data. Each focus group interview lasted about 90 minutes.

Individual interviews and focus group interviews were audio recorded, transcribed verbatim, and summarized. The transcripts were checked for accuracy (by reading and listening) and corrected as needed by EKB. Participants were anonymized from transcription to the reporting of the data, with only the interviewers having access to the identification key.

Data analysis Data from the first sequence of individual interviews were analyzed according to the 6 steps of thematic analysis suggested by Braun and Clarke [29]. All interviews were read and re-read carefully, and initial ideas about the content of the data were recorded in the field notes (Step 1). All interviews were coded independently by 2 researchers using MAXQDA 12 [30] (EKB and JG or Master’s student). This was followed by comparing the codes and resolving disagreements through discussion. After 3 interviews, a first draft of the coding tree was prepared, and it was supplemented or adjusted regularly, based on the intermediate analyses of data (Step 2). We searched the coded data for themes, which we subsequently reviewed and defined. Preliminary themes and subthemes were discussed within the project group. Coded segments were divided among the themes and read carefully, and relevant segments were selected. A summary was prepared for each theme (Steps 3, 4, and 5). The final step consisted of producing a comprehensive and detailed report of relevant segments for each theme and selecting the most compelling ones.

Results Demographic and clinical characteristics Demographic and clinical variables of the patients and MHPs are presented in Table 1. Our sample contained 13 pairs of patients and their MHPs, resulting in 26

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individual interviews. One MHP was interviewed twice about 2 different patients. Seven patients participated in the focus group interview. None of the patients participated in both the individual and focus group interviews. Six MHPs participated in the other focus group interview, 2 of whom had also participated in an individual interview.

Reasons for nonparticipation are provided in Appendix 5.5.

Table 1. Demographic and clinical characteristics of patients and mental health professionals (MHPs).

Characteristics

Individual interviews

Focus group interviews

Patients (n=13)

MHPs (n=12)

Patients (n=7)

MHPs (n=6)

21-63

27-58

31-70

41-60

20-39

6

4

2

0

40-59

5

8

3

5

≥60

2

0

2

1

Age range (years) Age (years), n

Sex, n

Female

9

11

4

5

Male

4

1

3

1

Diagnosis (in remission), n

a

Anxiety disorder

4

N/Aa

2

N/A

Depressive disorder

4

N/A

0

N/A

Anxiety and depressive disorder

5

N/A

5

N/A

N/A: not applicable.

Overview of the themes Three central themes emerged from the data: “perceived value of the relapse prevention program,” “usability of the relapse prevention program,” and “need for guidance.” Each theme is considered in detail in the following paragraphs, and an overview of the themes can be found in Table 2.

Perceived value of the relapse prevention program The first theme emerging from the data was the “perceived value of the relapse prevention program.” This theme was defined using 3 subthemes: (1) prior expectations, (2) evaluation of the program, and (3) factors inhibiting use of the program.

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Table 2. Overview of the main themes and subthemes and a description of their content.

Main and subthemes

Content

Perceived value of the relapse prevention program Prior expectations

Positive expectations of patients and MHPsa before using the program increased motivation for use

Evaluation of the program

Attitudes towards the program and its (subjective) effects (eg, increased awareness of relapse risks)

Factors inhibiting use of the program

Specific factors that reduce motivation to use the program (eg, absence of current symptoms)

Usability of the relapse prevention program

Technical aspects, attractiveness, and reflection on choices in the design of the program (eg, positive or negative views about reminders)

Need for guidance

a

Personal contact is essential

Added value of personal contact with MHP, prerequisite for active use of the program

Initiating contact

Belief that the other party (ie, patient or MHP) is responsible for taking initiative

MHPs: mental health professionals.

Prior expectations Prior expectations of the relapse prevention program and, by extension, motivation for its use were related to several factors, starting with the current level of symptoms experienced by patients, along with the perceived risk of relapse and the expectation that the relapse prevention program could relieve symptoms. MHPs mentioned that they noticed these factors in their patients, and patients also mentioned these factors.

Patients who had current symptoms, a high perceived risk of relapse, and a belief that the program could help prevent relapse appeared to have a high motivation for active use of the program.

Evaluation of the program Many patients mentioned the importance of the relapse prevention program following recovery from anxiety or depressive disorders. They particularly appreciated the active role assigned to the patients themselves within the program, thereby encouraging them to be active participants in their process to remain well. According to the patients, the program raised awareness of relapse risks: I find it very useful to raise my own awareness, so that I become more aware of the impact I can have, and therefore be more active in my own recovery.

[34003, female, 42 years old]

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The focus group with patients showed that, given the diversity of modules, the relapse prevention program had relevant components for all patients. Several patients explicitly mentioned that the program provided a sense of security and stability at times when they showed signs of impending relapse.

Factors inhibiting use of the program Patients with few or very few symptoms believed that they would experience few, if any, benefits from participating in the program, thereby reducing their motivation to use or continue to use the program. Patients in this relatively stable situation found it more difficult to imagine the possibility of a future relapse, and they saw no immediate need to engage in active relapse prevention. On the other hand, having many symptoms could also hinder the use of the program, as a perceived lack of concentration and energy was a reason for decreased use.

According to MHPs, some patients feared that the use of the relapse prevention program could actually lead to dysregulation: But at times I got the impression that people thought “yes, I’m doing well now” and that they were frightened that if they were to do something about their condition, they would feel less well.

[MHP 39, female]

Usability of the relapse prevention program Many patients and MHPs considered the online modules inviting, due to their appealing layout and normalizing effect. They indicated that the program normalized vulnerability to relapse: Completing mental health care treatment does not mean that all the symptoms and problems have been overcome nor that aggravation of symptoms can be ruled out in the future. Several patients and MHPs found the program easy to use: Thought it was really good. I thought it was well structured. Clear, simple to use for both the MHP and the patient.

[MHP 39, female] The relapse prevention program provided MHPs with practical tools for cooperating with patients in relapse prevention. The patients were motivated by the targeted suggestions for choosing relevant modules, given their problems and needs at that time. Moreover, they felt that the content of the eHealth modules corresponded to previous treatment in specialized mental health care. Some patients appreciated receiving this information again, especially as they had forgotten some of the content.

In contrast, some patients were annoyed by the repetition of information from previous

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treatment. Some patients found the program’s focus on anxiety and depression restrictive. In their opinion, this did not enhance recognizability, particularly for those who had experienced only 1 of the 2 disorders.

One adverse aspect of the practical usability was that patients had to log on to a computer to work with the online modules. The patients suggested that it would have been easier to use an app. Patients participating in the focus group regarded the pressure caused by the program (by reminders and mandatory fields) as unpleasant and often irritating. On the other hand, the reminders in the program were sometimes also seen as a necessary “stick,” which actually helped patients to continue with the program.

Patients did not always agree with each other. While some appreciated the clarity of the eHealth program, others found navigating the online platform confusing, as they had no clear overview of the available modules. They would have preferred a more intuitive program: I sometimes found the navigation on the site rather complicated. It wasn’t very logical.

[25002, female, 40 years old] This was confirmed by patients and MHPs participating in the focus groups.

Need for guidance The third theme relates to the “Need for guidance.” Both patients and MHPs considered the quality of the contact between patients and MHPs essential for effectiveness in preventing relapse.

Personal contact is essential After patients started using the eHealth modules, patients and MHPs were encouraged to have personal contact with each other once every 3 months. Patients indicated that contact with their MHPs was particularly vital to helping them use or continue to use the eHealth modules in times of reduced stability.

Several patients reported having become aware of their current symptoms when preparing for their contact with their MHPs, because they knew that symptom levels would be discussed. The very prospect of the meeting seemed to increase awareness, which benefitted the focus of the conversation.

Both groups identified the combination of the eHealth program and the personal contact between patients and MHPs as a factor facilitating the use of the program.

They noted that these elements complement and reinforce each other and that they would be of less value separately:

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I don’t think it’s possible to do it just with eHealth. And only seeing an MHP wouldn’t work either as this is just a snapshot in time and it’s difficult to provide all the background information during that session. eHealth provides more background information, while the MHP gives practical tips.

[54001, female, 30 years old] MHPs reported being happy to get patients started with eHealth modules, as this meant that the patients would have an active role in their own recovery: It is good to be able to work with the relapse prevention program, in whatever form, in between the sessions and not just let it come down to those 30 or 40 minutes a month.

[MHP 25, male] The combination of reminders from the eHealth program and the MHP provided an incentive for active use of the program. In the focus group interview with patients, it became apparent that patients receiving more support from an MHP appreciated the relapse prevention program more than patients who had received less or minimal support. The latter group indicated that they would have preferred to receive more support from the MHP in using the eHealth program.

The focus groups with patients and MHPs clearly indicated the importance of tailoring the level of support to individual patients, taking into account their coping styles and current symptom levels. The data further suggest the need to establish who will take primary responsibility when symptoms increase: Is the patient able to do this, or is active support by the MHP needed?

Initiating contact During the focus group interviews, MHPs clearly differed from patients in their task interpretations. The MHPs strongly emphasized the patient’s self-management skills, while patients expected MHPs to play a more active role if and when symptoms were to get worse. The capacity of MHPs was an impeding factor, placing limits on the active approach and support of patients. As a result, patients requiring more support were not always reached successfully: Our consultation hour is busy enough, so if, for instance, someone doesn’t show up twice in a row for an appointment, and you have called them, then that’s it. After all, we have so many patients who can’t wait to get an appointment, so that also plays a role.

[MHP 34, female]

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Discussion Principal findings Both the patients and MHPs in our study were predominantly positive about the blended relapse prevention program. It created awareness of relapse risks, and users appreciated its usability and accessibility. Lack of motivation, lack of recognizability, lack of support from the MHP, and symptom severity (too low or too high) appeared to be limiting factors in the use of the program. The implementation of the program was thus challenging. Several patients and MHPs regarded the program as easy to use and clearly structured, although others referred to a lack of intuitive design and overview of modules. Patients and MHPs agreed that the combination of eHealth modules and face-to-face contact is essential. According to the respondents, the MHP plays a crucial role in motivating and supporting patients in the use of the relapse prevention program. Surprisingly, the level of agreement between MHPs and their patients was high. The paired interviews revealed no striking discrepancies within the pairs of patients and MHPs. However, the focus group interviews did reveal significant discrepancies, as MHPs assumed a certain level of self-management skills in patients, while patients articulated their limitations in this respect, expressing a desire for more direct and personalized support from their MHPs.

Limitations This study has several limitations. One limitation of this study is the possibility of response bias, as patients knew the objectives of the study and might have given socially desirable answers. At the start of the interviews, we emphasized our openness to all feedback, including critical comments on the program. There was also a risk of selection bias, with participants who agreed to participate in the interviews possibly having been more positive towards the program than those who did not participate.

Nonetheless, both positive and negative perspectives were explicitly discussed during the interviews. Furthermore, recall bias might have occurred, given the time elapsed between completing the program and the individual interview or focus group interview for some patients (range: 0-6 months for the individual interviews and 0-12 months for the focus group interviews). We noticed that some patients tended to forget which eHealth modules they had completed and whether they had received online feedback.

To reduce this bias, patients could request an overview of their completed modules and number of feedback messages to and from the MHP during the interview. In addition, patients could remain engaged after the intervention period, as they received monthly newsletters about the study and still had access to the program. The longer duration between completion of the program and the focus group interviews was caused by the fact that the focus group interviews could be prepared and conducted only after all individual interviews were conducted and analyzed.

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Comparison with prior work The positive attitudes of MHPs and patients towards the program and the perceived increase in awareness of relapse risks are consistent with findings from previous research on relapse prevention for depression [31–33].

Our study revealed several factors influencing implementation, including motivation, recognizability, support received from the MHP, and symptom severity. Program use and implementation are facilitated by motivation and the perceived effectiveness of the program, as well as by the presence of current symptoms and the perceived high risk of future relapse. These findings are consistent with previous findings [34,35] demonstrating that motivation and perceived effectiveness increase adherence. On the contrary, lack of motivation impeded the use of the program, specifically in patients with few symptoms. A similar finding was suggested by Biesheuvel-Leliefeld et al [36], who may have found an indication of motivation issues among remitted patients, as they had major difficulties recruiting participants for their relapse prevention study.

Another factor influencing use and implementation in our study was recognizability.

This seems to correspond to findings reported by Gerhards et al [34] that patient perceptions that a program is not applicable to them act as a barrier to program usage.

Our results further indicate that program implementation is determined by whether patients received support from their MHPs. This finding has also been reported in previous studies [31,33,34,37,38]. Accessible personal contact with and an active approach by the MHP appears to be the key to successful implementation of a program.

No unambiguous confirmation regarding the influence of symptom level on implementation and usage of relapse prevention programs was found in the literature.

Interestingly, we found that both excessively low and excessively high perceived symptom levels hindered program use and implementation. According to a literature review on dropout from internet-based treatment, adult patients with few symptoms of any psychological disorder and those with more severe depressive symptoms were more likely to dropout from these treatments [39]. These findings might be generalizable to relapse prevention programs for anxiety and depressive disorders, as the setup of such internet-based treatments is similar to that of existing relapse prevention programs.

We identified different perspectives regarding responsibilities, with MHPs perceiving patients to be remitted and therefore relying on their self-management skills, while patients expected support and monitoring from their MHPs, particularly when symptoms worsened. A parallel finding is described in previous literature [40], with patients feeling that general practitioners should initiate contact, while general practitioners expect patients to contact them if needed. We found that these different expectations also exist between MHPs and patients, which has not been described before in the scientific literature.

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Implications for practice and research The present study highlights the importance of guidance in eHealth-based relapse prevention for anxiety and depression. The level of guidance from and engagement of the MHP emerged as crucial factors in the success of the relapse prevention program.

The self-management skills of patients and desired level of support should thus be aligned in advance, particularly in case of worsening symptoms.

Because self-management skills might differ over time, among other things depending on symptoms, it is essential to discuss and align needs over the course of the contacts, possibly enhancing implementation of relapse prevention programs based on eHealth.

Given the lack of studies specifically addressing associations between symptom levels and adherence to relapse prevention programs, further quantitative studies on this association are needed. One appropriate design could involve using Ecological Momentary Assessment [41] to assess symptom levels and log data from an eHealth platform to assess adherence.

When developing new relapse prevention interventions, attention should be paid to accessible guidance by professionals, accessibility through an app, along with a clear and intuitive, flexible structure for the eHealth component. Also, specific interventions for specific diagnoses might increase recognizability.

Conclusions Our findings suggest that personalized guidance from MHPs should be offered for eHealth-based relapse prevention programs, taking into account the preferences of patients and their level of self-management competencies. Both MHPs and patients should align expectations and needs in advance, as well as during the intervention, in order to increase implementation and enable optimal usage.

ACKNOWLEDGMENTS Funding for this study was provided by SIA-RAAK: The Taskforce for Applied Research, part of the Netherlands Organization for Scientific Research (NWO) and Stichting Stoffels-Hornstra. We are grateful to Master’s students Annabel van der Hulst and Elise van der Laan for conducting and coding interviews and to all participants for taking the time and effort to participate in this study.

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AUTHORS’ CONTRIBUTIONS EKB, AM, OM, AVS, NB, and BM designed the study. EKB and JG recruited participants for the interviews and focus group interviews. EKB and JG conducted interviews and were primary analysts of the data. BM moderated the focus group interviews. AM and BM consulted on the data analysis. EKB and JG wrote the first draft of the manuscript.

All authors discussed interpretation of results and contributed to and approved the final manuscript.

ABBREVIATIONS GET READY: Guided E-healTh for RElapse prevention in Anxiety and Depression MHP: mental health professional

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15. Klein NS, Kok GD, Burger H, van Valen E, Riper H, Cuijpers P, Dekker J, Smit F, van der Heiden C, Bockting CLH. No Sustainable Effects of an Internet-Based Relapse Prevention Program over 24 Months in Recurrent Depression: Primary Outcomes of a Randomized Controlled Trial. Psychother Psychosom [Internet] 2018;87(1):55–57. PMID:29306953 16. Kok G, Burger H, Riper H, Cuijpers P, Dekker J, van Marwijk H, Smit F, Beck A, Bockting CLH. The ThreeMonth Effect of Mobile Internet-Based Cognitive Therapy on the Course of Depressive Symptoms in Remitted Recurrently Depressed Patients: Results of a Randomized Controlled Trial. Psychother Psychosom [Internet] 2015 Feb 21;84(2):90–99. PMID:25721915 17. Hoorelbeke K, Koster EHW. Internet-delivered cognitive control training as a preventive intervention for remitted depressed patients: Evidence from a double-blind randomized controlled trial study. J Consult Clin Psychol [Internet] 2017 Feb;85(2):135–146. PMID:27362792 18. Urech A, Krieger T, Möseneder L, Biaggi A, Vincent A, Poppe C, Meyer B, Riper H, Berger T. A patient post hoc perspective on advantages and disadvantages of blended cognitive behaviour therapy for depression: A qualitative content analysis. Psychother Res [Internet] 2019 Nov 8;29(8):986–998. [doi: 10.1080/10503307.2018.1430910] 19. Baumeister H, Reichler L, Munzinger M, Lin J. The impact of guidance on Internet-based mental health interventions - A systematic review. Internet Interv [Internet] Elsevier B.V.; 2014;1(4):205–215. [doi: 10.1016/j.invent.2014.08.003] 20. Titzler I, Saruhanjan K, Berking M, Riper H, Ebert DD. Barriers and facilitators for the implementation of blended psychotherapy for depression: A qualitative pilot study of therapists’ perspective. Internet Interv [Internet] 2018;12:150–164. [doi: 10.1016/j.invent.2018.01.002] 21. Krijnen-De Bruin E, Muntingh ADT, Hoogendoorn AW, Van Straten A, Batelaan NM, Maarsingh OR, Van Balkom AJLM, Van Meijel B. The GET READY relapse prevention programme for anxiety and depression: A mixed-methods study protocol. BMC Psychiatry 2019;19(1). [doi: 10.1186/s12888-019-2034-6] 22. Muntingh ADT, Hoogendoorn AW, Van Schaik DJF, Van Straten A, Stolk EA, Van Balkom AJLM, Batelaan NM. Patient preferences for a guided self-help programme to prevent relapse in anxiety or depression: A discrete choice experiment. Eisenbarth H, editor. PLoS One [Internet] 2019 Jul 18;14(7):e0219588. [doi: 10.1371/journal.pone.0219588] 23. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Heal Care [Internet] 2007 Sep 16;19(6):349–357.

PMID:17872937 24. Magnée T, de Beurs DP, Schellevis FG, Verhaak PF. Antidepressant prescriptions and mental health nurses: an observational study in Dutch general practice from 2011 to 2015. Scand J Prim Health Care [Internet] 2018;36(1):47–55. [doi: 10.1080/02813432.2018.1426145] 25. National Counsel Mental Health Professionals. Functie- & competentieprofiel “Praktijkondersteuner huisarts GGZ” 2020 [Job and competence profile “Mental Health Professional” 2020] [Internet]. 2020. Available from: https://www.poh-ggz.nl/wp-content/uploads/2020/03/Definitief-Functie-en-competentieprofielPOH-GGZ-2020-versie-1.0-04032020.pdf 26. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science.

Implement Sci [Internet] 2009 Dec 7;4(1):50. PMID:19664226 27. Boeije H. Analyseren in kwalitatief onderzoek. 2nd ed. Amsterdam: Boom Lemma; 2014.

28. Baarda B, Bakker E, Fisher T, Julsing M, Peters V, van der Velden T, de Goede M. Basisboek Kwalitatief Onderzoek. Derde druk. Groningen/Houten: Noordhoff Uitgevers bv; 2013.

29. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol [Internet] 2006 Jan;3(2):77–101.

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30. VERBI Software. MAXQDA 12. Berling, Germany: VERBI Software; 2015.

31. Boggs JM, Beck A, Felder JN, Dimidjian S, Metcalf CA, Segal Z V. Web-based intervention in mindfulness meditation for reducing residual depressive symptoms and relapse prophylaxis: A qualitative study. J Med Internet Res [Internet] JMIR Publications Inc.; 2014 [cited 2016 Jul 6];16(3):1–12. PMID:24662625 32. Allen M, Bromley A, Kuyken W, Sonnenberg SJ. Participants’ Experiences of Mindfulness-Based Cognitive Therapy: “It Changed Me in Just about Every Way Possible.” Behav Cogn Psychother [Internet] 2009 Jul 10;37(4):413–430. PMID:19508744 33. Lillevoll KR, Wilhelmsen M, Kolstrup N, Høifødt RS, Waterloo K, Eisemann M, Risør MB. Patients’ Experiences of Helpfulness in Guided Internet-Based Treatment for Depression: Qualitative Study of Integrated Therapeutic Dimensions. J Med Internet Res [Internet] 2013 Jun 20;15(6):e126. [doi: 10.2196/jmir.2531] 34. Gerhards SAH, Abma TA, Arntz A, de Graaf LE, Evers SMAA, Huibers MJH, Widdershoven GAM. Improving adherence and effectiveness of computerised cognitive behavioural therapy without support for depression: A qualitative study on patient experiences. J Affect Disord [Internet] 2011 Mar;129(1–3):117–125. [doi: 10.1016/j.jad.2010.09.012] 35. Cuijpers P, van Straten A, Warmerdam L, van Rooy MJ. Recruiting participants for interventions to prevent the onset of depressive disorders: Possible ways to increase participation rates. BMC Health Serv Res [Internet] BioMed Central; 2010 Dec 25 [cited 2016 Jul 6];10(1):181. PMID:20579332 36. Biesheuvel-Leliefeld KEM, Dijkstra-Kersten SMA, van Schaik DJF, van Marwijk HWJ, Smit F, van der Horst HE, Bockting CLH. Effectiveness of Supported Self-Help in Recurrent Depression: A Randomized Controlled Trial in Primary Care. Psychother Psychosom [Internet] 2017;86(4):220–230. [doi: 10.1159/000472260] 37. Kelders SM, Kok RN, Ossebaard HC, Van Gemert-Pijnen JE. Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions. J Med Internet Res [Internet] 2012 Nov 14 [cited 2017 May 12];14(6):e152. PMID:23151820 38. Apolinário-Hagen J, Kemper J, Stürmer C. Public Acceptability of E-Mental Health Treatment Services for Psychological Problems: A Scoping Review. JMIR Ment Heal [Internet] 2017;4(2):e10. PMID:28373153 39. Melville KM, Casey LM, Kavanagh DJ. Dropout from Internet-based treatment for psychological disorders.

Br J Clin Psychol [Internet] 2010 Nov;49(4):455–471. [doi: 10.1348/014466509X472138] 40. Bosman RC, Huijbregts KM, Verhaak PF, Ruhé HG, van Marwijk HW, van Balkom AJ, Batelaan NM. Longterm antidepressant use: a qualitative study on perspectives of patients and GPs in primary care. Br J Gen Pract [Internet] 2016 [cited 2017 Sep 14];66(651):e708–e719. [doi: 10.3399/bjgp16x686641] 41. Shiffman S, Stone AA, Hufford MR. Ecological Momentary Assessment. Annu Rev Clin Psychol [Internet] United States; 2008 Apr;4(1):1–32. PMID:18509902

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Appendix 5.1. COREQ checklist Location in manuscript (Section, page no.)

Domain 1: Research team and reflexivity Personal Characteristics 1. Interviewer/facilitator Which author/s conducted the interview or focus group?

JG, EKB, AH (acknowledgements), EL (acknowledgements), BM

Page 121-122

2. Credentials What were the researcher’s credentials?

E.g. PhD, MD

EKB: MSc JG: MSc ADTM: PhD WDS: PhD ORM: MD, PhD AS: PhD NMB: MD, PhD BM: PhD AH: Master student EL: Master student

3. Occupation What was their occupation at the time of the study?

EKB: PhD student; JG: psychologist and researcher; AM: psychologist and researcher; WS: psychotherapist and researcher; OM: general practitioner and researcher; AVS: Professor of Clinical Psychology; NB: psychiatrist and researcher; BVM: Professor of Mental Health Nursing.

4. Gender Was the researcher male or female?

Males and Females

5. Experience and training What experience or training did the researcher have?

All researchers had prior experience with qualitative research.

Page 121

6. Relationship established Was a relationship established prior to study commencement?

No (patients) and yes (professionals)

Page 121

7. Participant knowledge of the interviewer What did the participants know about the researcher? e.g. personal goals, reasons for doing the research

Participants were briefed about the purpose of the study

Appendix 5.3 & 5.4

8. Interviewer characteristics What characteristics were reported about the interviewer/facilitator? e.g.

Bias, assumptions, reasons and interests in the research topic

None

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Relationship with participants

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Appendix 5.1. Continued Location in manuscript (Section, page no.)

Domain 2: study design Theoretical framework 9. Methodological orientation and Theory What methodological orientation was stated to underpin the study? e.g. grounded theory, discourse analysis, ethnography, phenomenology, content analysis

Topic lists based on the Consolidated Framework for Implementation Research.

Analyses conducted with thematic analysis.

Page 121-122

10. S ampling How were participants selected? e.g. purposive, convenience, consecutive, snowball

Purposive

11. M ethod of approach How were participants approached? e.g. face-to-face, telephone, mail, email

Telephone or email

Page 120-121

12. S ample size How many participants were in the study?

36 participants

Page 122-123

13. N onparticipation How many people refused to participate or dropped out?

Reasons?

See Appendix 5.5

Appendix 5.5

Page 120

Setting 14. S etting of data collection Where was the data collected? e.g. home, clinic, workplace

Individual interviews: patients’ homes, general practice location; Focus-group interview: research clinic

Page 122

15. P resence of non-participants Was anyone else present besides the participants and researchers?

No

16. D escription of sample What are the important characteristics of the sample? e.g. demographic data, date

See Table 1

Page 123

17. I nterview guide Were questions, prompts, guides provided by the authors? Was it pilot tested?

Yes

Page 121, Appendix 5.3 & 5.4

18. R epeat interviews Were repeat interviews carried out? If yes, how many?

Yes, one MHP was interviewed twice, since two of his patients both agreed to participate

Page 123

19. A udio/visual recording Did the research use audio or visual recording to collect the data?

Individual interviews and focus-group interviews were audio recorded, transcribed verbatim and summarized.

Page 122

Data collection

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Appendix 5.1. Continued Location in manuscript (Section, page no.)

20. F ield notes Were field notes made during and/or after the interview or focus group?

Yes

Page 122

21. D uration What was the duration of the interviews or focus group?

Individual interviews: 45 minutes Focus-group interviews: 90 minutes

Page 122

22. D ata saturation Was data saturation discussed?

Yes

Page 122

23. T ranscripts returned Were transcripts returned to participants for comment and/or correction?

No

Domain 3: analysis and findings Data analysis 24. N umber of data coders How many data coders coded the data?

4

Page 122

25. Description

of the coding tree Did authors provide a description of the coding tree?

Yes

Page 122

26. D erivation of themes Were themes identified in advance or derived from the data?

Themes were derived from the data.

Page 122

27. S oftware What software, if applicable, was used to manage the data?

MAXQDA 12

Page 122

28. P articipant checking Did participants provide feedback on the findings?

Yes, by performing the focus-group interviews.

Page 122

Reporting 29. Q uotations presented Were participant quotations presented to illustrate the themes / findings? Was each quotation identified? e.g. participant number

Yes

Page 124-127

30. D ata and findings consistent Was there consistency between the data presented and the findings?

Yes

31. C larity of major themes Were major themes clearly presented in the findings?

Yes

Page 123-127

32. C larity of minor themes Is there a description of diverse cases or discussion of minor themes?

Yes

Page 124-127

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Appendix 5.2. GET READY intervention The GET READY relapse prevention program was developed for general practice and consists of several elements. First, patients are invited by their MHPs for a face-to-face session (F2F), in which an individual relapse prevention plan is discussed. Second, patients receive access to an E-health platform. Third, patients are monitored by their MHPs and can schedule regular F2F sessions. The E-health platform provides three basic components and 12 optional modules, which patients can select and prioritize according to their needs and preferences (Figure 5.2.1). Each module takes 20-30 minutes to complete. Based on module completion, pop-up suggestions appear about related modules that might be interesting to the patient. A diary is also available, in which patients monitor symptoms weekly. The diary is available via the computer and via an app. All other modules are accessible through the computer. All modules aim to promote self-management skills (e.g. seeking help in case of impending relapse or pro-active planning of healthy behavior to cultivate stability and psychological and physical wellbeing). Patients receive weekly reminders to complete the selected online modules, receiving feedback from their MHPs upon request.

Figure 5.2.1. Overview of E-health modules, adapted from previous publication [21]. Dotted lines indicate that modules have overlapping themes and that modules can be easily opened from the other modules.

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Appendix 5.3. Topic guide interview patient Main questions

Additional questions

Introduction

Sign informed consent Introduce yourself Mention the duration of the interview (45 minutes) Ask permission to audio record the interview, and start the recording Mention that the name and personal data is saved separately from research data Mention the purpose of the interview

What is your experience with the relapse prevention program in general?

What were your expectations of the relapse prevention program?

Could you tell more about the role of the MHP? · Did you already know the MHP at the beginning of the study? · What did you expect from the MHP at the beginning of the study? · How did you experience the contacts? · How did you experience the support from the MHP? · In which way did the MHP help you to stay healthy? · What could be improved in the guidance from the MHP? · Who initiated the contact and how did you experience this? · What did you expect from the MHP if symptoms worsened?

What is your experience with the E-health program? · Usability · Meeting your needs · Pleasure/satisfaction · Available choices · Use of language · Design · Time investment Did the program help you to stay healthy/without symptoms? · In which way did the program help you to stay healthy? · If the program did not help: did other things help? · If you experienced a period of worsening symptoms: what would you have needed to use the program?

How do you feel about the combination of E-health and having contact with the MHP? · If you had contacts with the MHP but did not use E-health: what motivated you to have contact with the MHP?

What were the most useful and the least useful parts of the E-health program?

· Which modules did you complete? What made you choose these modules? · What were your motives concerning using or not using the modules? · Which modules were set up for you, but not completed? · Did you complete the diary? · How much did you use the message function within the program? · According to the questionnaires, your symptoms have decreased/ increased. How did you experience this?

What do you like about the relapse prevention program and what could be improved?

What is the most useful aspect of the relapse prevention program?

What could be improved in the relapse prevention program?

What did you miss in the relapse prevention program?

Completion

Are there other topics you would like to discuss?

Do you have any questions?

Would you like to receive the outcomes of the study?

Would you be interested in participating in a focus group interview?

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Appendix 5.4. Topic guide interview MHP Main questions

Additional questions

Introduction

Sign informed consent Introduce yourself Explain which patient the interview is about Mention the duration of the interview (45 minutes) Ask permission to audio record the interview, and start the recording Mention that the name and personal data is saved separately from research data Mention the purpose of the interview

Practical questions

How many hours a week do you work as MHP? Do you work in multiple general practices?

How many minutes does a regular contact last?

How many MHPs/GPs are working in this general practice?

What is your experience with the relapse prevention program?

How did you offer the relapse prevention program to the patient? · How were follow-up contacts planned? · Who initiated the contact and how did you experience this? · How many contacts did you have? · What did you discuss during the contacts? · Did you already know the patient before the beginning of the study? · Did you stimulate the patient to use the relapse prevention program?

In which way? · How did the program influence the health of the patient? · To what extent did the program meet the patients’ symptoms?

How did you offer the relapse prevention program to other patients? *What was it like to offer the relapse prevention program to the patient?

What is your experience with the E-health program? · Usability/structure · Design · Use of language · Time investment · Aspects: what did you use/not use, experience with aspects, relapse prevention plan · Message function/providing feedback

What made it easier or harder to implement the relapse prevention program in the general practice?

The relapse prevention program itself: intervention characteristics · What did you think about the quality of the relapse prevention program? · Did you know the content of the modules? · Did you ever apply relapse prevention strategies before? How does this program compare to other strategies that you are familiar with? · How do you feel about the combination of contacts and E-health? · *How complicated is the intervention?

Factors within the general practice: inner setting · How could you apply the relapse prevention program in your ‘normal work’? · Did you experience support from the general practice or GP? How? · In the general practice, what is the willingness to change? · How did having/not having time affect implementation?

Characteristics of individuals · Did you feel confident offering the relapse prevention program? Why/ why not?

Process of implementation · Did you experience support from the research team? How? Influence from outer setting · Did you have contact with specialized mental healthcare services?

What was the effect?

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Main questions

Additional questions

What do you like about the relapse prevention program and what could be improved?

What is the most useful aspect of the relapse prevention program?

What could be improved in the relapse prevention program? *What did you miss in the relapse prevention program?

Would you use the relapse prevention program if available after completion of the study? What is needed?

Completion

Are there other topics you would like to discuss?

Do you have any questions?

Would you like to receive the outcomes of the study?

Would you be interested in participating in a focus group interview?

* If not discussed yet, also ask this question

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Appendix 5.5. Reasons for nonparticipation Initially, 35 patients were invited for the individual interviews. Of the 19 agreeing to participate, 13 (37%) were selected and interviewed. In all, 17 MHPs were invited for the individual interviews. Of the 14 agreeing to participate, 12 (71%) were selected and interviewed. Reasons for nonparticipation are presented in Table 5.5.1.

Table 5.5.1. Reasons for nonparticipation in individual interviews.

Invited Agreed to Interviewed Reasons for nonparticipation participate

Patients

35

19

13

Demographic variables overlapped with participating patients (N=6) First agreed to participate but later unreachable (N=6) Too difficult to talk about (N=2) Comorbid symptoms (N=2) MHPs did not wish to participate (leading to nonparticipation by patients) (N=2) No interest (N=2) No time (N=1) Did not use the program (N=1)

MHPs

17

14

12

No interest (N=2) Patient did not wish to participant (leading to nonparticipation by the MHP) (N=1) Already interviewed about another patient (N=1) Not reachable (N=1)

In all, 98 patients were asked to participate, and seven (7%) participated in the focusgroup interview. Of the 50 MHPs invited to participate, six (12%) participated in the focus-group interview. Reasons for nonparticipation are presented in Table 5.5.2.

Table 5.5.2. Reasons for nonparticipation in the focus-group interview.

Invited Interviewed Reasons for nonparticipation Patients

98

7

No contact (N=55) No interest (N=16) No time (N=16) Not able to travel (N=2) Did not use the program (N=1) Too difficult to talk about (N=1)

MHPs

50

6

No contact (N=39) No interest (N=4) No time (N=1)

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THE ASSESSMENT OF SELF-MANAGEMENT IN ANXIETY AND DEPRESSION QUESTIONNAIRE (ASAD): A PSYCHOMETRIC EVALUATION SUBMITTED FOR PUBLICATION

Esther Krijnen-de Bruin, Anna D.T. Muntingh, Aagje Evers, Stasja Draisma, Annemieke van Straten, Henny Sinnema, Jan Spijker, Neeltje M. Batelaan, Berno van Meijel

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Abstract Objective To examine the underlying factor structure and psychometric properties of the Assessment of Self-management in Anxiety and Depression (ASAD) questionnaire, which was specifically designed for patients with (chronic) anxiety and depressive disorders. Moreover, this study assesses whether the number of items in the ASAD can be reduced without significantly reducing its precision.

Methods The ASAD questionnaire was completed by 171 participants across two samples: one sample comprised patients with residual anxiety or depressive symptoms, while the other consisted of patients who have been formally diagnosed with a chronic anxiety or depressive disorder. All participants had previously undergone treatment. Both exploratory (EFA) and confirmatory factor analyses (CFA) were conducted. Internal consistency and test-retest reliability were also assessed.

Results Both EFA and CFA indicated three solid factors: Seeking support, Daily life strategies and Taking ownership (Comparative Fit Index = 0.91, Tucker Lewis Index = 0.90, Root Mean Square Error of Approximation = 0.06 (CI 0.05-0.07), Standardized Root Mean Square Residual = 0.07 (χ2= 290.72, df = 176)). The ASAD was thus reduced from 45 items to 21 items, which resulted in the ASAD-Short Form (SF). All sub-scales had a high level of internal consistency (> α = .75) and test-retest reliability (ICC > .75).

Discussion The first statistical evaluation of the ASAD indicated a high level of internal consistency and test-retest reliability, and identified three distinctive factors. This could aid patients and professionals’ assessment of types of self-management used by the patient.

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Introduction Anxiety and depressive disorders are among the most prevalent mental health disorders across the globe [1]. Many patients experience a chronic course of symptoms, with chronicity ranging from 24.5% for depressive disorders to 41.9% for anxiety disorders [2]. Anxiety and depressive disorders have been found to often coincide. Out of those patients that reach remission, approximately 57% experience a relapse within the first four years [3]. Both the chronicity of these disorders and the frequency of relapses increase the overall burden of disease [2,4], and are associated with a decreased quality of life [5]. Alongside the significant burden that it places on patients and their relatives, anxiety and depression also cause a tremendous economic burden worldwide [6].

The chronic and recurrent nature of anxiety and depression requires the adoption of a chronic disease approach [7]. The use of self-management skills are generally considered to be essential in managing a chronic disease [8,9], which is why it constitutes a key part of the chronic care model [10]. Self-management has been defined in manifold ways. Barlow et al. [11] define it as “the individual’s ability to manage the symptoms, treatment, physical and psychosocial consequences and life style changes inherent in living with a chronic condition”. According to Lorig and Holman [9], the six core self-management skills, from a patient’s perspective, are: problem solving, decision-making, resource utilization, the formation of a patientprovider partnership, action planning and self-tailoring. With respect to chronic conditions, self-management pertains to practices that patients themselves employ in order to manage their symptoms, avoid relapse, optimize their well-being [9,11], and, ultimately, improve the quality of their lives. Notwithstanding the role of the patient, professionals also have an important role to play in self-management promotion [9].

In recent years, there has been an emergent focus on recovery in mental health care [12,13]. Recovery is not only focused on reducing symptoms, but also signals “a movement towards health and meaning rather than avoidance of symptoms” [14].

From this perspective, recovery also encompasses personal and functional recovery.

Manifold studies have acknowledged that self-management can be critically important in recovering from mental health disorders, due to their often chronic nature [15–17].

However, extant literature has highlighted that there is a complex interaction between anxiety and depressive disorders and the use of self-management skills. For example, prior research has shown that the ability of patients with anxiety and depressive symptoms to perform self-management skills is influenced by the level of their symptoms, and that more severe anxiety and depressive symptoms lead to a decrease in self-management activities [18]. Research has also demonstrated that the effective

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use of self-management strategies by patients suffering from anxiety or depression can reduce the severity of the symptoms for these disorders [19]. Hence, although depression and anxiety likely reduce patients’ ability to utilize self-management strategies, if self-management strategies are utilized, they are likely to decrease patients’ anxiety and depressive symptoms.

There are a number of studies that have investigated the range of self-management strategies utilized by patients with anxiety and depressive disorders, which are often categorized into clusters [20–23]. The clusters that are most often described are: Engaging in activities [20,22,23], Creating a routine [20,23], and Seeking professional treatment [21,23]. Engaging in activities mainly focuses on staying active, while creating a routine pertains to having a sense of structure and routinely planning activities. To the best of our knowledge, there is only one study available that psychometrically evaluates a self-management questionnaire for patients with anxiety, depressive and bipolar disorders, namely the Canadian developed Mental Health Self-Management Questionnaire (MHSQ) [24]. Given the potential cross-cultural differences in selfmanagement [25], not to mention that the MHSQ can be considered incredibly extensive (64 items), there was a need to develop, and subsequently psychometrically assess, a Dutch questionnaire that measured the self-management strategies employed by patients with anxiety and depressive disorders.

Consequently, Zoun et al. [26] constructed a valid questionnaire by using a sample of Dutch patients with chronic anxiety and depressive disorders, which is called the Assessment of Self-management in Anxiety and Depression (ASAD). This questionnaire contains 45 self-management strategies relating to coping with a chronic anxiety and/ or a depressive disorder. However, this questionnaire has hitherto not been psychometrically examined. Psychometric examinations can be carried out by conducting exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

These statistical techniques reveal and confirm the underlying factor structure of a questionnaire, which results in either one or multiple factors explaining the common variance. Moreover, EFA and CFA are also statistical reduction techniques, which can help to determine if the items included in the questionnaire can be reduced, without significantly reducing the level of precision. Simply put, reducing the number of items greatly simplifies the survey administration, which, in turn, makes it less burdensome for patients.

The present study aims to gain insight into the underlying factor structure and psychometric properties of the ASAD, by using two samples of Dutch patients with either partially remitted or chronic anxiety and/or depressive disorders. Furthermore, this study examines whether the number of items in the ASAD can be reduced.

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Methods Study design and participants This is a cross-sectional study that uses data from two separate studies: the GET READY study [27] and the SemCAD study [26]. These two studies were combined to increase the sample size and to assess the ASAD among patients who display the complete range of symptom severity, from mild to severe symptoms.

Sample 1: GET READY study Data from the GET READY study was collected as part of an observational cohort study focused on relapse prevention. The participants in the GET READY study were adults who had undergone treatment for an anxiety and/or a depressive disorder within mental healthcare services in the Netherlands in the prior two-year period, and who were subsequently in full or partial remission. Remission was defined by a score of ≤29 on the Beck Anxiety Inventory (BAI), and a score of ≤38 on the Inventory of Depressive Symptomatology - Self Report (IDS-SR). While measurements of the ASAD took place at baseline and after a nine-month period, only the baseline data was used for this study. A sub-sample completed the ASAD again two weeks after the baseline questionnaire, for test-retest measurements. This data was collected between April 2017 and November 2018. Further details on the GET READY study have been published previously [27].

Sample 2: SemCAD study The data from the SemCAD study was collected as part of a randomized controlled trial (RCT). The participants in the SemCAD study were adults who had been diagnosed with a chronic anxiety and/or depressive disorder, and had undergone treatment in outpatient specialist mental healthcare services in the Netherlands for at least a twoyear period, but who had yet to achieve recovery. The clinicians considered them to be treatment-resistant patients. The measurements took place at baseline (T0), 6 months (T1), 12 months (T2), and 18 months (T3). Given that the ASAD and Patient Health Questionnaire-9 (PHQ-9)/BAI were not collected at the same time, PHQ-9 and BAI data was used from T2, as this was the closest to the assessment of the ASAD. A detailed description of the SemCAD study has also previously been published [26].

Written informed consent was obtained from all participants, and a Medical Ethics Committee approved both study protocols [26,27]. Given that the ASAD was developed for and with patients with chronic anxiety and/or depressive disorders, and we were seeking to psychometrically assess the ASAD among patients who matched these criteria, we included patients with at least mild symptoms in our analyses. Therefore,

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participants who scored less than 10 on the BAI, and less than 5 on the PHQ or less than 14 on the IDS-SR, were ultimately excluded from the EFA and CFA.

Materials Demographic variables Demographic data was collected from all participants, and included age, gender, marital status, educational level and occupational status.

Clinical variables In order to measure the severity of anxiety symptoms, the BAI was used in both samples. The BAI is a questionnaire comprising 21 items. Each item is rated on a 4-point Likert scale from 0 (not at all) to 3 (severely). The BAI has good psychometric properties [28]. In order to measure the severity of depressive symptoms, the IDS-SR was used in the GET READY sample. The IDS-SR is a self-report questionnaire, which consists of 30 items. Each item is rated on a 4-point Likert scale from 0 to 3. The IDS-SR has good psychometric properties [29]. In the SemCAD sample, the PHQ-9 was used to assess depression severity. The PHQ-9 is a questionnaire comprising nine items. Each item is rated on a 4-point Likert scale from 0 (not at all) to 3 (almost every day). The PHQ-9 is a reliable and valid questionnaire [30].

Development of the Assessment of Self-management in Anxiety and Depression questionnaire (ASAD) In a prior study [21], a self-management questionnaire was developed for patients with chronic depression. Using the same methods (concept mapping), the authors of the ASAD developed a questionnaire that focused on patients with chronic depression and chronic anxiety disorders [31].

In phase 1 of concept mapping, patients were asked about helpful self-management strategies they had employed. Two focus groups were formed, consisting of ten and eight patients with chronic anxiety disorders, respectively. In these focus groups, patients completed the statement ‘I can live with a non-recovered anxiety disorder if…’.

This technique allowed for self-management strategies to be explored and discussed together. The patients’ responses were then written on a whiteboard and adjusted until they were clear to all participants. This resulted in a total of 176 self-management strategies. Next, when analyzing the findings of these focus groups, any overlapping strategies were subsequently merged. Ultimately, 91 strategies remained. In phase 2 of concept mapping, these 91 strategies were then sent to the participants, who were requested to prioritize and arrange the strategies accordingly. These strategies were then clustered, based on common features, and prioritized by their relevance. In phase

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3, the strategies were placed in a concept map and divided into different clusters through the use of the program ‘Ariadne’ [32]. In the final phase, the list with the 91 strategies was compared to the existing list of 50 self-management strategies utilized by patients with depression [21]. Once again, any overlapping strategies were removed, and some were merged. This resulted in the Dutch ASAD, which consists of 45 selfmanagement strategies for patients with an anxiety and/or a depressive disorder. Each item can be rated on a 5-point Likert scale, ranging from 1 (not at all) to 5 (very much).

The items in the questionnaire are described in Table 1.

Table 1. Items in the ‘Assessment of Self-management in Anxiety and Depression’ questionnaire.

What do I do to deal with my anxiety and/or depressive disorder as best as I can: 1.

Be aware of my thoughts and cognitive biases.

2.

Acknowledge the signals that tell me I am in danger of relapsing, for example, by using a crisis plan.

3.

Seek out appropriate treatment.

4.

Search for information about my anxiety and/or depression.

5.

Ensure that a professional monitors my medication.

6.

Continue to seek long-term professional help.

7.

Make sure I take my medications regularly, by, for example, either keeping them with me at all times or taking them at a specific place or time.

8.

Stay physically active, by, for example, taking a walk outside, playing sports or doing housework.

9.

Keep busy during the day by doing (volunteer) work.

10.

Find a (creative) hobby.

11.

Go outside regularly.

12.

Use a schedule to stay prepared for upcoming activities.

13.

Tidy the house.

14.

Express my feelings by writing in a diary or via an online blog.

15.

Understand what is going on with me.

16.

Accept my anxiety and/or depression.

17.

Talk with fellow patients.

18.

Be in a trusting environment, where I am accepted for who I am.

19.

Seek support, by, for example, talking about my anxiety and/or depression with people I trust.

20.

Explain to people who are important to me that I am suffering from anxiety and/or depression.

21.

Involve people who are important to me in my treatment.

22.

Ask others for help.

23.

Take care of my personal hygiene, by, for example, showering daily and getting dressed.

24.

Make sure that I have a good day and night rhythm.

25.

Do something for someone else, such as taking care of someone.

26.

Set goals.

27.

Honing my attention through meditation, yoga, mindfulness or breathing exercises, for example.

28.

Be aware of any physical tension in my body, in order to make myself feel relaxed.

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Table 1. Continued 29.

Make sure that I do not take on too many obligations.

30.

Develop or use a talent.

31.

Make sure that I establish a good balance between activities and rest.

32.

Eat and drink healthily.

33.

Reward myself from time to time, for example, buying something nice.

34.

Tell myself that better times lie ahead.

35.

Encourage myself and have perseverance.

36.

Take more and more decisions myself, reducing my dependency on others.

37.

Do my best not to avoid unpleasant situations by facing up to them.

38.

Encourage myself and put things in perspective.

39.

Seek out a professional who I have a connection with.

40.

Distract myself with activities that make me feel good.

41.

Make sure I avoid things I do not want to do.

42.

Make sure I have a professional or another important person to take refuge in.

43.

Keep focused on the present, and stop myself from looking too far ahead.

44.

Make sure I have the freedom to choose what I do and do not want to do.

45.

Make sure that I have control by clearly indicating my boundaries.

Note. This Table comprising the items in the Dutch ASAD has been carefully translated by a professional translator.

Data-analysis In order to assess the factor structure of the ASAD, both an EFA and CFA were conducted. An EFA with principal axis factoring was conducted to examine the underlying factor structure of the ASAD. To test the internal consistency of the ASAD, Cronbach’s alpha was calculated for each factor, while the communalities (common variance) of the items, factor loadings, and overdetermination (factor to variable ratio) were also examined. In order to assess whether the number of items could be reduced, the correlation matrix of the exploratory factor analysis was inspected for extreme multicollinearity (correlations above .80) [33]. Items with a communality below .30, items that cross-loaded on multiple factors with less than 0.2 difference, and items that did not load on any factors were all removed, before the analysis was then subsequently re-run. Given that we anticipated that the factors might correlate, an oblique rotation was chosen (direct oblimin) and the pattern matrix was examined for the factor and item loadings. In order to determine the number of factors that needed to be retained, the scree plot and eigenvalues were inspected. Initially, items with eigenvalues above one were included. The factors deriving from the final factor solution were interpreted and named. The EFA was conducted via SPSS, version 26.

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Upon completion of EFA, CFA was then conducted to both find evidence for the proposed factor structure in EFA, and to examine whether the factors found via EFA were clearly identifiable constructs as measured by the items they contain. To establish the latent structure of items and factors in this way, the CFA was applied with package LAVAAN in R. The input for the CFA were the factors with their items as identified with EFA. Modification index values were also evaluated to see whether it was suitable to free parameters, in order to obtain better values for goodness-of-fit indices [34]. The following criteria were used for the goodness-of-fit of the final model, which was based on a reduced number of items: Comparative Fit Index (CFI) and Tucker-Lewis index (TLI) values > 0.90, Root Mean Square Error of Approximation (RMSEA) values < 0.06 and Standardized Root Mean Square Residual (SRMR) < 0.08 [35]. Missing data, which pertained to ten missing values distributed over six items, were imputed with case means.

Furthermore, psychometric properties were also examined, including internal consistency, test-retest reliability and discriminant validity. Internal consistency indicates the degree of interrelatedness among the items [36]. This was measured using Cronbach’s alpha, and the sub-scales were assumed to be adequate when Cronbach’s alpha was >0.70 [37]. In addition, test-retest reliability was examined using intraclass correlation coefficients (ICC). ICC values were assumed to be excellent if ICC >0.75 [38].

With respect to the test-retest reliability, there were two observations, as ICC values of at least 0.5 were considered to be acceptable, at least 22 participants were required to complete the retest [39]. Discriminant validity concerns the extent to which the factors are diverse and uncorrelated. Therefore, correlations should not exceed 0.7.

Results Participants The 213 participants in this study comprised 113 participants from the GET READY study and 100 participants from the SemCAD study. In total, 42 participants were excluded from the study because their scores indicated that they had no current symptoms (BAI<10 and PHQ<5/IDS-SR<14). This resulted in 171 participants: 88 from the GET READY study and 83 from the SemCAD study. Table 2 presents the demographic and clinical characteristics of these two samples. The total sample consisted of 103 females and 66 males (the gender of two participants was unknown). Out of the 51 participants from the GET READY sample who were invited to re-take the ASAD after a two-week period, 43 (84.3%) responded positively, of which the scores of 12 patients indicated that they were in complete remission. Therefore, the test-retest reliability could be examined for 31 participants.

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Table 2. Demographic and clinical variables for each study.

Variables

GET READY sample (N = 88) Mean (SD)

SemCAD sample (N = 83) Mean (SD)

P

43.4 (12.5)

47.7 (9.0)

0.01

Female

52 (59.1)

51 (61.4)

Male

36 (40.9)

30 (36.1)

Demographic variables Age in years Sex, n (%)

0.61

Missing

2

Marital status, n (%)

0.86

Single

37 (42.0)

36 (43.4)

In a relationship

51 (58.0)

47 (56.6)

Elementary

2 (2.3)

5 (6.0)

High-school

21 (23.9)

23 (27.7)

Secondary vocational education

18 (20.5)

30 (36.1)

Higher professional education or university

45 (51.1)

22 (26.5)

Other

2 (2.3)

3 (3.6)

Employed

57 (64.8)

12 (14.5)

On sick leave

18 (20.5)

42 (50.6)

Retired

0 (0.0)

4 (4.8)

Other

13 (14.8)

25 (30.1)

Anxiety symptoms (BAI)

11.9 (6.4)

21.8 (10.1)

Depressive symptoms (IDS-SR)

24.1 (7.6)

-

Depressive symptoms (PHQ-9)

-

11.5 (5.0)

0.02

Highest educational level, n (%)

<0.001

Occupational status, n (%)

Clinical variables <0.001

As one can discern in Table 2, there were significant differences between the two samples concerning age, educational level, occupational status and the severity of anxiety symptoms. The SemCAD sample was significantly older, had, on average, a lower educational level, were significantly more likely to be unemployed, as well as experiencing more severe anxiety symptoms. The potential difference between the severity of depressive symptoms could not be statistically tested, as both samples utilized different questionnaires. However, the mean IDS-SR score indicates mild depressive symptoms, while the mean PHQ-9 score indicates moderate depressive symptoms.

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Exploratory factor analysis A principal axis factor analysis was conducted on the 45 items of the ASAD with oblique rotation (direct oblimin). The Kaiser-Meyer-Olkin measure verified the sampling adequacy of the analysis, KMO = .85 (‘meritorious’ according to Hutcheson and Sofroniou [40]), and all KMO values for individual items were greater than .54, which is above the acceptable limit of .5 [33]. Bartlett’s test of sphericity [41] was statistically significant (p < .001). Both tests supported the factorability of the correlation matrix.

An initial analysis was run to obtain eigenvalues for each factor in the data. This resulted in 13 factors exceeding Kaiser’s criterion of eigenvalue one, the combination of which explained 67.87% of the variance. Of those 13 factors, three had an eigenvalue above two. The scree plot was ambiguous and showed inflexions that would justify retaining either three or five factors. We opted to retain three factors because this provided the most interpretable solution. Items with factor loadings larger than .3 were included in the factor. In total, 24 items were excluded from the analysis, due to the fact that they did not load on any factor (N = 7), showed cross-loadings between factors with less than 0.2 difference (N = 6), or had a communality below 0.3 (N = 11). Thus, the number of items was reduced from 45 to 21 after the analysis. The 21-item version of the ASAD, the ASAD-Short Form (SF), explained after rotation 51.27% of the variance, with factor one contributing 30.08%, factor two contributing 12.45%, and factor three contributing 8.74%.

Close inspection of the items that were grouped into the same factor (see Table 3) led to the factors being named as follows: factor 1 represents Seeking support; factor 2 represents Daily life strategies; and factor 3 represents Taking ownership. More information about the factors can be found in Table 3.

Table 3. Explanation of the underlying factors.

Factors

Name

Explanation

Factor 1

Seeking support

Seeking and maintaining treatment or support from a professional and significant others

Factor 2

Daily life strategies

Active lifestyle, taking care of yourself, finding balance, structure, setting goals and making plans to achieve them

Factor 3

Taking ownership

Taking ownership and control, having focus, intention and awareness

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Confirmatory factor analysis After EFA, CFA was conducted to examine whether the factors found with EFA were clearly identifiable constructs as measured by the items they contain. This should be expressed in adequate goodness-of-fit measures for the estimated model with three factors. With the 21 items corresponding to the three factors found via EFA as input, the first CFA resulted in suboptimal fit measures: χ2 = 439.35 (df=168), CFI = 0.80, TLI = 0.78, RMSEA = 0.09 (CI 0.08-1.00), SRMR = 0.09, AIC = 10121.75, BIC = 10263.12. Values of the Modification index indicated correlated residuals between seven pairs of items (5 & 6, 8 & 11, 6 & 39, 22 & 21, 24 & 32, 11 & 26, 39 & 21). No compelling theoretical arguments existed to remove the items with correlated residuals, for example by similar wording, so we decided to free the residual correlation parameters, allowing the errors of the items to be correlated. Moreover, one item loaded on two factors.

Item 12 not only loaded on Daily life strategies, but also appeared to load on the factor Taking ownership. The adaptation of the model by freeing parameters resulted in greatly improved fit measures: χ2= 290.72 (df=176), CFI = 0.91, TLI = 0.90, RMSEA = 0.06 (CI 0.05-0.07), SRMR = 0.07, AIC = 9993.12, BIC = 10165.91. See Table 4 for the factor loadings of the EFA and CFA.

Internal consistency To assess the internal consistency of the factors, the communalities (common variance) of the items, overdetermination (factor to variable ratio), and factor loadings were examined. Starting with the communalities, the 21-item ASAD-SF had four items with communality above .50 and a mean communality of .44, which is relatively low.

Overdetermination of factors was high, as high loadings were shown on at least three items for each factor [42]. Therefore, despite low communalities, good recovery of factors was still achieved [42]. Continuing with the factor loadings, factor 1 had five factor loadings above .60 and two factor loadings above .50, factor 2 had four factor loadings above .60 and two factor loadings above .50, while factor 3 had three factor loadings above .60. Therefore, factor 1 and 2 had five or more strongly loading items (.50 or better), thus indicating solid factors [43]. Although factor 3 had only three items, these items could nevertheless still be interpreted in a meaningful way, and, indeed, three items can still indicate a solid factor [43]. Cronbach’s alpha was calculated for the 21-item ASAD-SF, resulting in high internal consistency, α = .88. All sub-scales also had high internal consistency (factor 1: α = .88, factor 2: α = .86, factor 3: α = .76).

Test-retest reliability Test-retest reliability over a two-week period was excellent (factor 1: ICC = .76, 95% CI .49-.89; factor 2: ICC = .88, 95% CI .71-.95; factor 3: ICC = .86, 95% CI .72-.93).

26. Set goals.

11. Go outside regularly.

24. Make sure that I have a good day and night rhythm.

8. Stay physically active, by, for example, taking a walk outside, playing sports or doing housework.

21. Involve people who are important to me in my treatment.

20. Explain to people who are important to me that I am suffering from anxiety and/or depression.

19. Seek support, by, for example, talking about my anxiety and/or depression with people I trust.

42. Make sure I have a professional or another important person to take refuge in.

4. Search for information about my anxiety and/or depression.

39. Seek out a professional who I have a connection with.

22. Ask others for help.

5. Ensure that a professional monitors my medication.

3. Seek out appropriate treatment.

6. Continue to seek long-term professional help.

Table 4. Factor loadings per item of the ASAD questionnaire.

0.652 0.573

0.439 0.392

0.737

0.607

0.472

0.622

0.703

0.519

0.726

0.566

0.590

0.711

0.605

0.612

0.605

0.703

0.622

0.712

0.465

0.635

0.660

0.641

0.650

0.722

0.686

0.796

Factor daily life strategies

Factor taking ownership

Factor seeking support

Factor seeking support

Factor taking ownership

Factor loadings

Factor loadings Factor daily life strategies

Confirmatory factor analysis

Exploratory factor analysis

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6

0.715 0.600

43. Keep focused on the present, and stop myself from looking too far ahead.

0.402

12. Use a schedule to stay prepared for upcoming activities.

44. Make sure I have the freedom to choose what I do and do not want to do.

0.447

10. Find a (creative) hobby

0.768

0.574

32. Eat and drink healthily.

45. Make sure that I have control by clearly indicating my boundaries.

0.576

0.432

0.579

0.510

0.613

Factor daily life strategies

0.566

0.702

0.867

0.340

Factor taking ownership

Factor seeking support

Factor seeking support

Factor taking ownership

Factor loadings

Factor loadings Factor daily life strategies

Confirmatory factor analysis

Exploratory factor analysis

28. Be aware of any physical tension in my body, in order to make myself feel relaxed.

Table 4. Continued

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Discriminant validity As one can see in Table 5, the Seeking support factor correlated with both the Daily life strategies (0.31) and the Taking ownership factor (.31). Furthermore, the Daily life strategies factor also correlated with the Taking ownership factor (.28). The fact that these correlations are well below 0.7 indicates that the variables in the factors were more strongly related to their own factors than other factors.

Table 5. Factor correlation matrix.

Seeking support

Daily life strategies

Seeking support

1.000

Daily life strategies

.310

1.000

Taking ownership

.309

.280

Taking ownership

1.000

Discussion Main findings This study represents the first attempt to evaluate the ASAD questionnaire by performing EFA and CFA, in order to establish the underlying factor structure, psychometric properties, and the possibility of reducing items without sacrificing on precision. Three consistent factors were identified: Seeking support, Daily life strategies, and Taking ownership. Seeking support contained ten items that pertained to seeking and maintaining support from both professionals and significant others. Daily life strategies contained eight items related to maintaining an active lifestyle, healthy habits and engaging in structured activities. Taking ownership contained three items, which pertained to taking control over one’s life and focusing one’s attention on recovery.

The number of items in the questionnaire was subsequently reduced from 45 to 21.

The results thus support the psychometric properties of a short form (SF) of the ASAD. The internal consistency of the 21-item ASAD-SF as well as their sub-scales was high, test-retest reliability indicated excellent reliability on all factors, and discriminant validity was also shown.

Comparisons to previous literature Of those studies that have psychometrically evaluated similar self-management questionnaires, Coulombe et al. [24] and Smith et al.’s [44] research are particularly worthy of comparison to this study.

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The factors identified in this study are similar to the subscales found in Coulombe et al.’s study [24]. They examined the Mental Health Self-Management Questionnaire (MHSQ), which is a 64-item questionnaire developed for patients who are recovering from depression, anxiety or bipolar disorders. The subscale Clinical appears to be similar to the factor Seeking support. However, the clinical subscale does not include support from significant others, whereas the Seeking support factor includes both professional support and support from significant others. The subscale Vitality resembles the factor Daily life strategies, insofar as both focus on engaging in healthy activities. Moreover, the subscale Empowerment bears some similarities with the factor Taking ownership. However, the Empowerment subscale is more extensive, and contains items like ‘loving myself as I am’ and ‘congratulating myself for my successes’.

However, the MHSQ contains almost three times as many items as the 21-item ASADSF, and, hence, is far more burdensome for patients to complete.

There was also some overlap between our study and the Partners in Health (PIH) scale. The PIH scale is an Australian questionnaire, which focuses on the selfmanagement strategies employed by the chronically ill. Smith et al. [44] conducted a CFA to establish the factors of the PIH. When comparing the ASAD-SF to the PIH scale, the same similarities and differences appear as with the MHSQ: the factor Patienthealth professional partnership is similar to the factor Seeking support, albeit it only focuses on professional support, as opposed to support from significant others too.

The factor Coping with a chronic illness is similar to the factor Daily life strategies, insofar as both focus on staying active. The similarities between, on the one hand, the identified factors of the ASAD-SF, and the PIH-factors Knowledge of illness and treatment and Recognition and management of symptoms, on the other, were less obvious, potentially because the PIH scale focuses primarily on self-management of physical illness rather than mental illness. Although, of course, there are many similarities between physical and mental illness, not to mention that the underlying constructs of handling a chronic disease might be comparable, one would expect to see differences between the PIH and the ASAD-SF. Van Grieken et al. [21,22], Villaggi et al. [23] and Schreurs et al. [45] all conducted studies that qualitatively established clusters, dimensions and factors related to selfmanagement.

Given that the ASAD was developed as an expansion of the self-management strategies identified by Van Grieken et al. [21], it is altogether understandable that the factors found in our factor analyses match the sub clusters found by these authors.

The sub clusters identified by Van Grieken et al. [21,22] were clustered using concept mapping. While the authors psychometrically evaluated the 50 self-management strategies that were identified by their participants, no satisfactory EFA could be performed [46]. Our study did partially confirm the sub clusters identified in their

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studies. More specifically, the factor Seeking support is in line with the sub clusters Active coping with professional treatment and Social engagement [21]. Furthermore, the factor Daily life strategies appears to be in accordance with the sub clusters Active self-care, structure and planning, Daily life strategies and rules, Engaging in activities, and Structured attention to oneself [21,22]. In contrast, no sub clusters were described that matched the factor Taking ownership.

There are also similarities between the present study and the factors identified in Villaggi et al.’s study [23]. In their study, self-management strategies were explored among a sample of patients with anxiety disorders, depressive disorders and bipolar disorders. The factor Seeking support resembles the dimension Surrounding myself with people who make me feel better, although this dimension is only focused on informal support, rather than also on professional support. The factor Daily life strategies is in accordance with both the dimension Functional (e.g. Creating a routine and taking action) and the dimension Physical (e.g. Maintaining a healthy lifestyle and Managing one’s energy levels). The factor Taking ownership is in accordance with the sub dimension Empowering oneself. This study from Villaggi et al. further revealed that patients with anxiety, depressive and bipolar disorders utilized similar selfmanagement strategies. This indicates that an approach that is focused on affective disorders might be appropriate for self-management [47].

Finally, the factors identified in this factor analysis can be compared with the Utrecht Coping List (UCL) [45]. The Utrecht Coping List is a 47-item questionnaire that encapsulates seven domains of coping. The domain Seeking social support appears to be very similar to our factor Seeking support. Moreover, the domain Active problem solving is in line with our factor Taking ownership. The other domains were not concordant with the factors found in this factor analysis, most likely because coping is not the same as self-management; while self-management focuses on how one handles a specific disease, coping is more focused on coping with problems in general.

When comparing our findings to the six core self-management skills defined by Lorig and Holman [9], it appears that the skill Formation of a patient-provider partnership overlaps with our factor Seeking support. In addition, the skill Action planning bears some resemblance to our factor Daily life strategies. The other four self-management skills (Problem solving, Decision making, Resource utilization and Self-tailoring) appear to be intertwined in our three factors.

To conclude, most of the overlap between our findings and extant literature pertained to the factors Seeking support and Daily life strategies. Within other self-management questionnaires, the factor Seeking support is primarily focused on seeking support from a professional [24,44], and, indeed, no factors that combined both professional and informal support were found in extant literature. Factors similar to Daily life

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strategies were often identified [21–24,44]. Although less pronounced, we also found a degree of overlap between our third factor Taking ownership, albeit these similar factors focused on empowerment [23,24]. We did not identify any other important factors within extant literature that were not found in our study.

Strengths and limitations There are several strengths to the present study. First, this study is the first to statistically examine the ASAD, and thus provide insight into the underlying factor structure, internal consistency, test-retest reliability and discriminant validity of this questionnaire. Moreover, this study sheds light on how those items that are grouped together are subsequently translated into self-management styles. The 21-item ASADSF has proven to be an internally consistent and reliable measure for assessing selfmanagement strategies among a sample of Dutch patients with (chronic and partially remitted) anxiety and depressive disorders.

The second strength is that the questionnaire focuses on patients suffering from both anxiety and depressive disorders. This is important, because most studies focus solely on either patients with anxiety disorders or patients with depressive disorders, despite the fact that previous research has shown that anxiety and depressive disorders are highly comorbid [48]. Comorbid anxiety and depressive disorders increase chronicity [2], which is one of the reasons for encouraging modes of selfmanagement.

The findings of this study should be interpreted with several limitations in mind. First, the sample of 171 patients is a relatively small sample for factor analysis [49]. However, sample size is also dependent on factor loadings and communalities [33]. As the results demonstrated, the internal consistency of the ASAD-SF and its three factors is high.

Although the communalities show less evidence of internal consistency, the factor loadings and overdetermination indicate that the factors are internally consistent.

Furthermore, the preliminary analysis did indicate that the sample was appropriate for factor analysis. The advantage of a larger sample size is that it would have allowed us to split the sample, and conduct EFA on one sample, while conducting CFA on the other sample, which, in turn, would result in a more stringent assessment of the factor structure [50]. However, this study did not aim to fit the data to suit the EFA and CFA, but rather aimed to provide insight into the covariances between factors, and, in turn, into the factors of the newly developed ASAD. The second limitation of this study pertains to the use of two different datasets.

These datasets were merged to increase the sample size, in order to be able to conduct the EFA and CFA. The participants in this study were screened for depression via two different questionnaires, the PHQ-9 and the IDS-SR, which might be less reliable than

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using a single screening questionnaire. However, both the PHQ-9 and the IDS-SR have been found to be reliable and valid questionnaires for assessing depression. Moreover, these questionnaires were only used to assess the severity of symptoms, in order to exclude those who had no symptoms. Nevertheless, using two datasets could well result in a greater level of heterogeneity. In the SemCAD sample, patients experienced, on average, moderate anxiety and depressive symptoms, while in the GET READY sample the anxiety and depressive symptoms were mild. One explanation for this is that the SemCAD sample comprised patients with chronic anxiety and/or depressive disorders, while the GET READY sample consisted of patients who were in partial remission from anxiety and/or depressive disorders.

Implications for practice and research Several implications for practice can be suggested. First, this study provides a feasible self-management questionnaire that can be offered to patients with (chronic or partially remitted) anxiety and depressive disorders. The use of self-management strategies by patients is likely to be cost-effective for both the prevention and treatment of anxiety and depressive disorders, and could reduce the burden of disease, as well as the economic burden of mental health disorders. The results of this study could also provide guidance for patients regarding which specific selfmanagement strategies to focus on. For example, they could self-manage their disorder by seeking support from professionals and important others (Seeking support), by maintaining a healthy lifestyle and engaging in activities (Daily life strategies), or by taking control and staying focused on their recovery (Taking ownership). Second, the three factors identified in this study could also be considered in the development of relapse prevention programs. With respect to E-health modules, attention should be paid to the themes Seeking support, Daily life strategies and Taking ownership. For example, information on how to engage with important others and MHPs could help patients to seek out support. Third, professionals could advise patients in how best to execute these self-management themes and strategies. One possible approach might be for patients to complete the ASAD-SF during their actual treatment. If they scored low on one or more factors, then this could help guide professionals in advising which self-management strategies to utilize. For example, if patients scored low on the factor Seeking support, the specific attention could be paid to how patients can better involve professionals and important others in their recovery. Fourth, depending on the purpose of completing the ASAD, patients and professionals could choose which version to use. If a detailed description of selfmanagement strategies is required, then patients could complete the 45-item ASAD. Alternatively, if a shorter version is preferred that provides insight into important clusters of self-management, then patients could complete the 21-item ASAD-SF.

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Given that this study indicated that the 21-item ASAD-SF is appropriate, this version should be further explored and validated among a sample of patients with (chronic or partially remitted) anxiety and depressive disorders. Alongside this, to increase generalizability, more studies are required to examine the English version of the ASAD within other settings and countries.

Conclusions This study presents an initial test of a questionnaire that assesses self-management strategies for patients with chronic or partially remitted anxiety and/or depressive disorders. In this respect, the ASAD-SF demonstrated good psychometric properties.

The statistical evaluation conducted here constitutes the first examination of factors of self-management strategies among this sample, and resulted in a stable 3-factor structure. The 21-item ASAD-SF could be offered to patients with (chronic or partially remitted) anxiety and depressive disorders, with the identified factors providing guidance to patients and professionals concerning which specific strategies to focus on. Ultimately, these factors could be incorporated into the development of new relapse prevention programs.

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The primary aim of this thesis was to examine relapse prevention in patients with remitted anxiety and depressive disorders. Three specific aims were formulated: first, to examine – via a systematic review and meta-analysis – the effectiveness of current psychological relapse prevention interventions for patients with remitted anxiety or depressive disorders; second, to evaluate our newly developed GET READY relapse prevention program; and third, to psychometrically test a new measurement instrument for self-management strategies in patients with (chronic or partially remitted) anxiety and depressive disorders.

This chapter presents a summary of the main findings, which will be discussed in relation to extant literature, followed by a reflection on the findings. Methodological considerations are then addressed, before we proceed to delineate the implications of the research for clinical practice and future research. Finally, the chapter ends by providing an overall conclusion to the thesis.

Summary of the main findings In Chapter 2, we conducted a systematic review and meta-analysis in order to examine the effectiveness of current psychological interventions aimed at preventing relapse among patients with remitted anxiety or depressive disorders. We focused on the effectiveness of stand-alone psychological relapse prevention interventions, as well as those interventions combined with maintenance antidepressant treatment (M-ADM) or antidepressant medication (ADM) discontinuation. In total, 7,324 papers were screened, with 40 studies subsequently being included. We demonstrated that for patients with remitted major depressive disorders (MDD), psychological interventions reduced the risk of relapse by 24% within the first 24 months (in comparison to treatment as usual (TAU)), and that this effect persisted for up to three years. When psychological interventions were offered in combination with M-ADM, the risk of relapse was also reduced by 24% within the first 24 months, in comparison to M-ADM alone. Due to the paucity of studies, no meta-analysis could be conducted regarding the effectiveness of psychological relapse prevention interventions that are combined with discontinuation of ADM. Similarly, we found that there was also a relative dearth of studies on relapse prevention for anxiety disorders, which, in turn, meant that no meta-analysis could be conducted for this patient group. In conclusion, psychological interventions were found to be effective for reducing the risk of relapse among patients with remitted MDD. Chapters 3, 4 and 5 described the development, implementation and evaluation of the GET READY relapse prevention program. Chapter 3 outlined the protocol of the GET READY study. The GET READY program was developed based on patient preferences, as well as in collaboration with professionals and a patient panel. The program included regular face-to-face (FTF) contact with a MHP in primary care, online

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E-health modules (including drawing up a personalized relapse prevention plan), and a mood and anxiety diary, which allowed patients to monitor their symptoms. The study protocol describes both the quantitative and qualitative methods that were used to evaluate the GET READY relapse prevention program.

In Chapter 4, the usage of the GET READY program, course of symptoms of participants, and the association between usage intensity and course of symptoms was examined. These factors were investigated through conducting a pre-post study with 113 patients, who were either fully or partially in remission from anxiety and/or depressive disorders. Longitudinal data was collected over a 9-month period. It was observed that the core E-health modules, which focused on relapse psychoeducation and the relapse prevention plan, were used by 70-74% of the patients, while the optional modules were deemed to be elective and, as such, were used by less than 40% of the patients. According to a pre-defined usage intensity measure, around one in four patients were defined as ‘regular users’. Generally speaking, the use of the selfmanagement components of the program, such as online modules and the online ‘mood & anxiety diary’ decreased rapidly over time. Given that the study had a nonexperimental design, no causal effect between the GET READY intervention and the severity of symptoms could be demonstrated. However, it appeared that most patients remained stable while participating in the GET READY intervention: a minority of participants (15%) experienced a relapse in their anxiety symptoms within the 9-month follow-up period, while 10% experienced a relapse in their depressive symptoms.

Having more FTF contact with MHPs was significantly associated with higher anxiety and depressive scores. Other usage variables were not significantly associated with the course of symptoms. In Chapter 5, we described the results of a qualitative study about the implementation and evaluation of the GET READY intervention, from the perspective of both patients and MHPs. Individual interviews were conducted with pairs of patients (N=13) and MHPs (N=12), in order to highlight potential discrepancies between their respective accounts. After reflecting upon the findings of the individual interviews, two focus group interviews were subsequently conducted. These focus groups (comprising both patients and MHPs) showed that users were mostly positive about the GET READY intervention. Specifically, it was said that it created awareness of relapse risks, assigned an active role to patients themselves in relapse prevention, contained relevant components, and provided a sense of security and stability to patients. Alongside this, users also appreciated its usability and accessibility. However, the lack of motivation on the behalf of patients, lack of recognizability of the program due to its focus on both anxiety and depression, and the lack of support from MHPs limited the use of the program. Moreover, the use of the program was also negatively affected by both the number and severity of patients’ symptoms. More specifically, those with few symptoms felt no need to engage in active relapse prevention, while

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those with more severe symptoms experienced a lack of concentration and energy, and therefore made less use of the program. The combination of E-health modules and FTF contact was considered to be essential, and it appeared that MHPs played a crucial role in terms of motivating and supporting patients in the use of the E-health program. There were no marked discrepancies between the paired individual interviews with patients and MHPs. However, the focus group interviews did reveal significant discrepancies, insofar as MHPs expected patients to exercise a certain level of selfmanagement skills when using the relapse prevention program, while patients articulated their limitations in this respect and expressed a desire for more direct and personalized support from their MHPs. In Chapter 6, we assessed the psychometric properties of a new questionnaire for measuring self-management strategies among patients with anxiety and depression: the ‘Assessment of Self-management in Anxiety and Depression’ (ASAD) questionnaire. Given that self-management is an increasingly important aspect in recovering from mental health disorders, focusing on selfmanagement can also be expedient for relapse prevention. However, the burden of anxiety and depressive disorders potentially decreases people’s ability to use selfmanagement strategies, which is problematic given that employing these strategies can lead to a decrease in one’s anxiety and depressive symptoms. Zoun et al. [1] developed the ASAD, because there was no Dutch self-management questionnaire for patients with anxiety and depressive disorders. In our study, the ASAD was completed by 171 participants across two samples. An exploratory and confirmatory factor analysis revealed three solid factors: Seeking support, Daily life strategies and Taking ownership.

Furthermore, the factor analyses revealed that the number of questionnaire items could be reduced from 45 to 21. The evaluation indicated high levels of internal consistency and reliability for the 21 item ASAD short form (ASAD-SF). The identified factors can provide guidance for both patients and professionals with respect to what self-management strategies to apply.

Reflection on the main findings Effectiveness of psychological relapse prevention interventions Our systematic review and meta-analysis indicated that psychological interventions were effective in preventing relapse among patients with remitted MDD when compared to TAU, including when used in combination with M-ADM, leading to a 24% reduction in relapse rates (Chapter 2).

This systematic review and meta-analysis extends the findings of previous research, insofar as it was the first study to demonstrate the additional effect to be gained from providing psychological interventions aimed at relapse prevention to patients using M-ADM up to and including 2 years after remission. This result is highly relevant given that many remitted patients use M-ADM and M-ADM in itself also affects relapse rates

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[2]. We demonstrated that all patients who were receiving M-ADM after completion of their treatment benefited from additional psychological relapse prevention interventions for up to a 2-year period, and that it lowered the risk of relapse even more. This advice is currently not provided in international guidelines [3–6], while only one Dutch guideline suggests that a combination of medication and psychotherapy can be effective in preventing relapse for patients with severe symptoms or patients who have experienced three or more previous episodes [7].

In addition to this, our study revealed that there is a relative dearth of studies on relapse prevention interventions for patients with anxiety disorders. Hence, more research in this field is urgently needed to establish the effectiveness of psychological interventions aimed towards relapse prevention among patients with anxiety disorders.

Evaluation of the GET READY relapse prevention program Our quantitative study (Chapter 4) revealed that – as expected – the core components of the online program were used more intensively than the optional components. This was consistent with data from other studies using E-health treatment programs [8,9].

Within our study, it appeared that the usage of the overall modules was rather low in comparison to other studies [10–13]. However, these other studies were not focused on the prevention of relapse per se, but rather on the treatment of anxiety and depressive disorders. Consequently, over the course of the treatment patients might have been more inclined to engage with the modules, as they felt that there was greater scope for improving their symptoms. In line with other studies, it was shown that the usage intensity of the E-health program decreased rapidly [14,15]. We considered this risk beforehand, which is why we sought to keep patients involved over a longer duration by sending them reminders and asking MHPs to motivate patients to use the program. Unfortunately, it appears that these efforts proved insufficient to keep patients engaged in the program.

At the start of our study, we hypothesized that patients should be able to have access to a relapse prevention program over a significant period of time, as the risk of relapse remains relatively stable over time, even years after reaching remission. Our intention was to provide an easily accessible relapse prevention tool that patients would either use more intensively if they were experiencing a deterioration of their symptoms, or less intensively when they were doing well. In addition, in response to patients’ preferences [16], the GET READY program was offered in a non-committed and flexible way. While patients received recommendations regarding usage of the program and engaged in regular FTF contact with MHPs, they were not obliged to follow a certain protocol. Ultimately, the relatively low usage and rapid decrease of usage intensity is not consistent with the intended use of the program. In this respect, perhaps a more structured and time-intensive program with more frequent FTF contact with

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MHPs might be better suited to keeping patients engaged, thereby increasing the effectiveness of the program. While we believe that it is important to follow patients’ preferences, these findings potentially raise the question of whether following these preferences is necessarily the best way to go in terms of the effectiveness of such programs. Having said that, if patients’ preferences are not sufficiently taken into account, then this is also likely to have a deleterious effect on adherence to the program. These considerations shed light on the difficult choices that must be made during the development of new relapse prevention programs. In conclusion, in order for relapse prevention programs to be effective, one must strike a balance between accounting for patients’ preferences and guaranteeing sufficient exposure to the intervention.

It can be especially difficult to keep patients engaged in the case of relapse prevention. Indeed, previous relapse prevention studies [17–19] have highlighted low rates of participation, on the grounds that patients do not feel the need for such programs, do not feel at risk of relapse, do not expect interventions to be effective, or simply do not want to be confronted with their period of anxiety or depression [18–20].

These reasons were also reported in our qualitative study (Chapter 5).

Although the usage intensity was relatively low and decreased rapidly over time, generally speaking, it appeared that the patients who participated in the GET READY program remained stable over its duration. In fact, the relapse rates in our study were lower than those found in other relapse prevention studies [21,22]. Although no causal pathway could be established in this pre-post study, these results nevertheless may indicate that the GET READY program is equipped to potentially protect patients from relapse. These findings might be explained by the results from our qualitative study (Chapter 5), in which patients expressed that the program functioned as a ‘safety net’ for them, and that they found it comforting that they could easily contact their MHP if they needed to. Indeed, patients routinely mentioned that merely knowing that the MHP was available provided them with a sense of comfort. Patients also positively valued the combination of E-health modules and FTF contact and appreciated the support they received from their MHP. Furthermore, the mere fact that the program increased patients’ awareness of the risk of relapse may have played a role in preventing relapses and keeping patients stable.

A significant positive association was found between the amount of FTF contact that patients had with their MHP and the severity of symptoms. This association remained significant when correcting for the anxiety and depressive symptoms one measurement prior. Since no causality could be established, interpreting this result is a complex issue. The most plausible explanation is that patients adequately responded to their initial symptoms by reaching out to their MHP, which is in accordance with a previous study that showed that patients with more severe symptoms were more likely

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to reach out for help [23]. It is also possible that patients reached out too late, so that ultimately the support offered by the MHP was insufficient for averting relapse. This explanation is supported by findings from the qualitative study (Chapter 5), which showed that patients who experienced high symptom levels were less likely to use the program and, as such, less likely to have FTF contact with their MHP. The results of our qualitative evaluation of the GET READY program (Chapter 5) revealed that patients and MHPs were generally positive about the GET READY program.

The GET READY program was specifically tailored to the preferences of patients: it provided flexible modules, included regular FTF contact with a professional, gave them the opportunity to complete a personal relapse prevention plan, and required a low time investment [16]. It appeared that patients specifically appreciated these aspects of the GET READY program, as well as the ability to personalize their own program.

The perceived increased awareness of relapse risks is consistent with previous research on relapse prevention in depression [24–26]. Several factors were identified that influenced the implementation of the program. In accordance with other studies, program use and implementation were facilitated by patients’ motivation, the perceived effectiveness of the program, the presence of current symptoms and a perceived high risk of future relapse [19,27]. At the same time, we found that a lack of motivation and lack of current symptoms operated as barriers to using the program. In addition, the lack of support from MHPs was also cited as a barrier. Another factor influencing the use and implementation of the program was recognizability, which was also found in Gerhards et al.’s study [27]. That is to say, if patients do not perceive that a program is applicable to them, then this can form a barrier to them using the program. As a result of these factors in particular, implementing the GET READY program proved to be somewhat challenging, as is evidenced by the relatively low usage intensity and rapid decrease of usage described in Chapter 4.

In line with extant literature, this study found that receiving support from MHPs was beneficial in terms of the use and implementation of the relapse prevention program [24,26–29]; in particular, it appeared that the GET READY program was more likely to be successfully implemented if MHPs were accessible and actively engaged in personal contact with their patients. This stressed the importance of the role played

by MHPs, which is discussed in greater detail later in this chapter.

We discovered an interesting mechanism with respect to the association between symptom level and usage, which was that both low and high symptom levels served as a barrier to usage of the program. These results support previous research, which describes that both adult patients with few symptoms of any psychological disorders and those with more severe depressive symptoms often dropout of treatment [30].

Patients with just enough symptoms are perhaps the easiest group to motivate to use the program, although it could also potentially benefit patients that have either a few

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or many symptoms. It might be less important to target patients with only a few symptoms, insofar as they are at a lower risk of relapse [31]. However, patients with many symptoms might possibly be motivated to use the program via the use of persuasive techniques, such as emails, reminders, and additional support and guidance from their MHP. We also identified different perspectives regarding responsibilities: MHPs perceived patients to be remitted and therefore relying on their self-management skills, while patients expected support and ongoing monitoring from their MHPs, especially when their symptoms worsened. Given that a similar finding was also identified in a study concerning patients and GPs [32], this result indicates that patients and health professionals (MHPs in this case) should seek to align their competencies, expectations and needs over the course of their FTF contact, in order to keep patients engaged.

Key themes in the self-management strategies used by patients with anxiety and depressive disorders In the evaluation of the ASAD questionnaire, three consistent factors were identified: Seeking support, Daily life strategies and Taking ownership (Chapter 6).

When comparing our findings to previous studies that have assessed selfmanagement questionnaires, the largest degree of overlap was found with respect to the following factors: Seeking support [33–35] and Daily life strategies [33–37]. Although less obvious, we also found some overlap with our third factor Taking ownership [33,35,38]. No important factors were identified in extant literature that were not found in our study.

The ASAD appeared to be an appropriate assessment tool for assessing the selfmanagement strategies among patients with (chronic or partially remitted) anxiety and depressive disorders. Depending on their purpose for completing the ASAD, patients and professionals can choose which version of the ASAD to use. The 45-item ASAD contains all the self-management strategies of patients that were identified through the method of concept mapping. This version provides detailed insight into the potential self-management strategies that patients can use. However, some may consider the 45-item ASAD to be overly long. Hence, we conducted EFA and CFA to both reduce the number of items and reveal underlying factors, which led to the 21item ASAD-SF. This short form of the ASAD reveals clusters of self-management strategies that patients do and do not apply. Specifically, the clustering of items in factors provides insight into how patients use self-management strategies with respect to ‘Seeking support’, ‘Daily life strategies’, and ‘Taking ownership’, which are considered to be important in self-management [33–38]. In the event of low scores on one or more of these factors on the 21-item ASAD-SF, specific intervention strategies could be employed by both patients and professionals to practice and improve the relevant

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self-management skills from that cluster, or to use external resources in situations in which the further development of these skills is not possible. However, one must realize that when using the 21-item ASAD-SF, one also loses information with respect to the full spectrum of self-management strategies that patients use, insofar as items that did not correspond to the three factors were deleted. In conclusion, both the ASAD and the ASAD-SF can be used during relapse prevention interventions, as selfmanagement strategies are integral to managing a chronic disease such as an anxiety or depressive disorder.

Methodological considerations In this thesis, we adopted a broad perspective on relapse prevention for patients with remitted anxiety and/or depressive disorders by including a systematic review and meta-analysis, a quantitative study, a qualitative study and a psychometric study.

However, the results of this thesis should be interpreted in the context of the following methodological considerations.

During the extraction of the data in our systematic review and meta-analysis (Chapter 2), it became apparent that manifold definitions of relapse and remission are used in the literature. Therefore, patients that are considered to be ‘in remission’ in one study might be considered as ‘not in remission’ in another study. The same issues apply to the term ‘relapse’. Consequently, it is incredibly difficult to compare studies and populations with one another. Although there have been some efforts to establish an international consensus on defining these terms [39,40], these efforts require updating. In particular, an international consensus must be established with respect to the cut-off points for relapse and remission that are widely used in current questionnaires. Moreover, notwithstanding the need to develop a consensus regarding how to define depressive disorders, a consensus should also be reached regarding definitions for relapse and remission in anxiety disorders.

In the protocol paper (Chapter 3), we described the development of the GET READY intervention. Although it is deemed good practice to use a framework in the development of an intervention, such as, for example, the method of Intervention Mapping, no official framework was used in the development process of the GET READY intervention. However, we did adopt a systematic approach in the development process. Specifically, we considered input from a prior study on patient preferences [16], while the initial format and underpinning was discussed with experts, MHPs and patients. Preliminary versions of the E-health modules were reviewed by members of the research team, E-health developers and patients, and adapted accordingly. With respect to developing future relapse prevention programs, the Intervention Mapping method can be considered an appropriate approach, insofar as it facilitates a systematic planning process [41]. However, one should also take into account that Intervention

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Mapping is a time-consuming method, with estimates suggesting that it takes up to 8 months of full-time work to conduct all the necessary steps for developing an intervention [42]. For pragmatic reasons (primarily, issues related to time), we opted to use the aforementioned approach rather than an official framework.

As aforesaid, the GET READY study (Chapters 3, 4 & 5) was a pre-post study. As such, this study provided insight into the acceptability, implementation, and adaptation of the program. In addition, we were able to explore the course of symptoms, as well as their association with the program usage, which, in turn, provided some indications as to the efficacy of the program. However, due to this feasibility design [43], the effectiveness of the intervention could not be established. This study should thus be considered as the first step towards conducting a RCT on the effectiveness of the GET READY intervention.

Another methodological consideration that should be considered is the possibility that selection bias occurred during the GET READY study (Chapters 4 & 5). One would assume that it was predominantly patients with a certain amount of motivation who agreed to participate in the study. At the same time, patients with a more avoidant self-management style might have been less inclined to participate in the study.

Notably, it appeared that the participants in the GET READY study were, overall, highly educated and currently employed (Chapter 4). Although this was also the case in other web-based studies [44,45], it would be expedient to also reach out to patients with lower levels of educational achievement. One way to potentially do this might be to involve patients with lower levels of educational achievement in the developmental phase of relapse prevention programs, in order to ensure that the form and content of the program is feasible for this group. Of course, researchers could also seek to actively recruit these types of patients. Similarly, with respect to the qualitative study (Chapter 5), it is highly probable that those patients who agreed to participate in the interviews and focus group interviews held more positive attitudes towards the program.

Regarding the above consideration, it should be noted that recruiting patients for the GET READY study proved to be difficult, which resulted in a smaller sample size than we hoped for (Chapter 4). In this study, the most prominent method of recruitment was to ask MHPs to recruit their patients. However, it proved difficult to motivate MHPs to recruit patients for research purposes. One reason for this is that over half of the MHPs in the Netherlands experience their workload as being (very) high. On average, they have over 11 consultations a day [46]. Therefore, asking eligible patients to participate in this study was simply not always considered to be a priority for the MHPs. One alternative recruitment method might be to directly recruit patients to take part in the research via specialized mental health care services, as was done in our study and other relapse prevention studies [47]. However, this has become increasingly

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difficult in recent years due to stricter privacy regulations. One way to facilitate this process might be to ask patients at the start of their treatment to consent to participating in research.

As well as this, it appeared that not many eligible patients agreed to participate.

Unfortunately, we were unable to map precisely how many patients were asked to participate, and how many of those agreed to participate, due to the fact that MHPs did not record this information. Based on this, if researchers could directly contact patients themselves, then this would likely provide more insight into these response numbers.

We considered it a strength that we assessed the perspectives of both patients and MHPs on the GET READY program (Chapter 5). We found only two other qualitative studies on relapse prevention among patients with depressive symptoms, and in these cases only the perspective of patients was examined [24,25]. Other qualitative studies on perspectives towards the treatment of depression only included either the perspectives of patients [26,27,48] or therapists [49], but never both. In addition, it appeared that our study was the first to examine perspectives on a relapse prevention program that also focused on anxiety disorders, as other studies primarily focused only on depressive disorders.

Another strength of our study is that our qualitative data allowed for pairwise comparison, because we interviewed both patients and their MHPs. This provided the opportunity to study similarities and differences in their respective viewpoints about the same case. We also combined individual interviews with focus-group interviews, which contributed to data triangulation and thereby enhanced the credibility of our findings [50]. Given that differences in the accounts provided by patients and MHPs especially emerged in the focus-group interviews, this appeared to be a valuable addition to the individual interviews.

In this thesis, both quantitative (Chapter 4) and qualitative methods (Chapter 5) were employed to examine the GET READY program. This mixed-methods approach allowed us a more complete overview of both the use of the program and its evaluation, which, in turn, provided us with relevant suggestions for clinical practice and future research.

Implications for clinical practice Relevance of relapse prevention One of the main implications for clinical practice is that relapse prevention warrants more attention. During this study, it proved difficult to engage patients in the GET READY program. Currently, there appears to be a gap in knowledge and awareness regarding the risk of relapse among remitted patients, while no standard relapse prevention program is currently available for patients in remission from anxiety and

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depressive disorders. Given that we have showed that psychological relapse prevention interventions for remitted depressed patients considerably reduces the risk of relapse (Chapter 2), it is our contention that relapse prevention programs should be available to all these patients. While this is in accordance with current guideline recommendations [3–6], it is far from the case in practice. Although psychological interventions are effective in preventing relapse among patients with depressive disorders, the question remains whether these interventions should be offered to all remitted patients, or only to those at high risk of relapse. Although it might be more cost-effective to specifically target those who are at high risk, clear indicators of precisely who is deemed to be at high risk are currently lacking.

One way to address the relevance of relapse prevention is through psychoeducation.

Specifically, psychoeducation should focus on the risk of relapse and the effectiveness of relapse prevention interventions, in order to increase the motivation of patients to engage in relapse prevention programs. During psychoeducation, particular attention should be paid to engage patients with lower levels of educational achievement. For this purpose, simplified and literacy-adapted psychoeducation materials should be made available, along with using audiovisual methods. Psychoeducation could also be provided by professionals during treatment.

In order for professionals to be able to provide psychoeducation to their patients, they also need to increase their knowledge regarding the risk of relapse and the effectiveness of relapse prevention intervention. In this respect, it appeared that MHPs often lacked such knowledge prior to participating in this study. Therefore, professionals need to receive additional training on these aforesaid subjects. As part of this training, they must also be trained in how to work with existing relapse prevention programs and relapse prevention plans. This training could, for example, also be incorporated within both the initial and advanced education that these professionals undertake. As of June 2021, MHPs in the Netherlands are now obligated to be registered in a ‘quality register’, which requires them to both meet certain criteria for their formal education and to receive a certain amount of training every year. By incorporating relapse prevention into both their initial and advanced education, professionals’ knowledge and skills of relapse prevention will be increased.

Professionals that are involved in guideline development could potentially also play a role in this process, insofar as they have the ability to make clear recommendations regarding relapse prevention. Informal conversations with MHPs during the GET READY study revealed that not all GPs agreed that providing relapse prevention was the task of MHPs. Although the guidelines on anxiety and depressive disorders generally recommend providing relapse prevention to remitted patients, the guidelines should provide more direction regarding the recommended setting for relapse prevention.

Only the Dutch ‘NHG quality standard depression’ [7] clearly states that relapse

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prevention should be provided in primary care settings. In light of the shift in the Netherlands towards providing effective care with the lowest possible level of intensity and as close as possible to the patients’ place of residence, the primary care setting has become increasingly focused on the domain of (relapse) prevention [51]. This should be stressed more explicitly in the current guidelines.

Overall, the process of providing relapse prevention interventions to remitted patients could be enhanced by facilitating appropriate communication between professionals in specialized mental health care services and GPs/MHPs. As described in the Introduction of this thesis, in an ideal situation, the therapist in the mental health care setting should have already discussed the topic of relapse prevention with the patient and composed a relapse prevention plan with the patient during the course of their treatment. If patients complete their treatment in specialized mental health care, then their therapist should send a referral letter to the GP and/or contact the GP to discuss the treatment process and relapse prevention plan. In so doing, patients can be equipped with the right tools for relapse prevention after completion of their treatment. However, professionals in specialized mental health care also lack knowledge on the risk of relapse and relapse prevention. This should be addressed by providing (more) training on these topics to professionals working in specialized mental health care.

Role of the mental health professional Another important implication for clinical practice is that personal support and guidance from MHPs is an essential component of effective relapse prevention (Chapter 5). This is because MHPs have the important task of monitoring and motivating patients to engage in relapse prevention, in order to ensure that patients receive timely support in the event of an impending relapse. In this study, patients appreciated being monitored by their MHP, while those who received less monitoring expressed the need for more intensive monitoring. Although most patients only had one additional FTF meeting after the initial FTF meeting, most patients indicated that regular meetings with their MHP were desirable. During this FTF contact, MHPs can use motivational interviewing techniques to motivate patients to engage in relapse prevention strategies. Indeed, research [24,26–29] has repeatedly shown that E-health based programs are more effective when a MHP is involved.

Most importantly, patients and MHPs should discuss and try to align their needs regarding self-management skills and their desired level of support, both at the beginning of their relationship and over the course of their relationship. Doing so enables each patient to be provided with a personalized and tailored approach, which most likely enhances the implementation and effectiveness of E-health based relapse prevention programs.

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Role of the patient For patients, it is important to focus on self-management strategies that they are actually capable of applying, in order to prevent relapse. According to our psychometric evaluation of the ASAD (Chapter 6), patients can self-manage their disorder by seeking support from professionals and important others (Seeking support), by maintaining a healthy lifestyle and engaging in activities (Daily life strategies), and by taking control and maintaining a focus on recovery (Taking ownership).

Moreover, patients should be aware that MHPs expect them to already possess a certain level of self-management competencies, which may or may not be in accordance with their actual competencies. This can lead patients to feel that they need more support from their MHP. Therefore, as aforementioned, patients should discuss their needs, self-management skills and desired level of support with their MHP.

Role of E-health Our study has several implications for the role of E-health within clinical practice. In a similar vein to Muntingh et al.’s study [16], it appeared to be important to offer E-health in a personalized way. The GET READY program was designed in such a way that patients and MHPs could ‘pick and choose’ their preferred modules, which patients indicated that they valued. However, after completion of the initial module, the modules ‘anxiety’, ‘depression’ and ‘medication’ were automatically offered. As the program was focused on the prevention of both anxiety and depressive disorders, patients with only one of these disorders felt that the program did not completely apply to them (Chapter 5). Therefore, one might suggest that future relapse prevention programs should specifically focus on one diagnosis. However, given that anxiety and depressive disorders often coincide, one might also argue that a transdiagnostic approach is wholly justified [52]. Based on this, we therefore recommend to offer all optional modules without ‘presets’, and to provide patients with the opportunity to personalize the program themselves by choosing a program focused on anxiety, depression or both disorders. One would expect this to strengthen acceptance and adherence to the program, and, ultimately, increase its effectiveness [19]. At the same time, as aforementioned, one should keep in mind that a more structured and time-intensive program might be better suited to keeping patients engaged. Perhaps, patients and MHPs can decide together which modules to choose, along with the required level of support needed from the MHP to remain engaged in these modules.

Therefore, in line with the above recommendations, E-health modules should be tailored to patients’ preferences, as well as to their individual self-management skills.

To create awareness of the available self-management skills and competencies, after they first login, patients should then have the option to either complete the ASAD (if a detailed description of self-management strategies is required) or the ASAD-SF (if a

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shorter version is preferred that provides insight into important clusters of selfmanagement) (Chapter 6). In so doing, it can be identified which self-management skills require specific attention for further development. In line with this assessment, suitable modules can then be set up and the appropriate level of support required from the MHP can also be planned and executed.

This is important because this study clearly indicated that patients prefer professional support in addition to receiving E-health modules (Chapter 5). After completing treatment in specialized mental health care, patients should thus receive guidance in relapse prevention from their MHP. When FTF meetings are combined with E-health modules, these can enhance each other in such a way that ultimately contributes to the effectiveness of the relapse prevention program. This recommendation is supported by both extant literature and the patients in our study who especially valued this combination.

Recommendations for future research The findings of this thesis imply several recommendations for future research. First, this thesis (specifically Chapter 2) has demonstrated that there is a significant lack of studies on relapse prevention among patients with remitted anxiety disorders. We feel that additional studies in this area should be conducted. In addition, this chapter has also shown that there is a relative dearth of studies exploring the use of relapse prevention interventions during the discontinuation of ADM. Given that most patients do not prefer to use medication in the long term [53], and the risk of relapse during discontinuation is high [54], relapse prevention interventions may be able to support patients during the discontinuation of ADM. Second, in order to examine the efficacy of the GET READY intervention, a RCT should be conducted. However, we recommend adapting the GET READY program according to the preferences expressed by patients (Chapter 5). Most importantly, the program should be accessible through a mobile app, as well as having a clear, intuitive and flexible structure for the E-health component, and should allow users to personalize it based on their disorder. To increase patients’ engagement in the program, more frequent FTF contact with MHPs is likely necessary. Preferably, the follow-up duration of this RCT should be at least 2 years, as this will provide greater insight into the course of symptoms over a longer period of time, and allow for greater comparison with other studies. During the patient recruitment phase of the RCT, particular attention should be paid to the variability of patients’ characteristics in the sample, especially regarding their level of educational achievement. In order to gain more insight into the association between course of symptoms and usage, Ecological Momentary Assessment (EMA) could be used in the RCT [55]. In addition, this RCT could be supplemented with a costeffectiveness study, based on our contention that relapse prevention is a cost-effective intervention strategy.

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Third, as outlined in the Introduction of this thesis, self-management can be considered as part of the chronic care model, and, as such, may be essential in preventing relapse. However, one could raise the question of whether self-management is feasible for every patient with remitted anxiety and depressive disorders. In this study, it appeared that self-management could not be expected from every patient, given the low usage intensity and rapid decrease in usage. In particular, patients with low and high symptom levels might require additional guidance and motivation from MHPs to engage in relapse prevention (Chapter 5). Further research into prerequisites for patients with anxiety and depressive disorders to engage self-management strategies is recommended for their effective application.

Fourth, given that the psychometric evaluation of the ASAD indicated that the 21item version was appropriate (Chapter 6), this version should be further explored and validated among a sample of patients with chronic and/or remitted anxiety and depressive disorders. Furthermore, it would be interesting to relate self-management styles, as assessed by the ASAD-SF, to the course of symptoms and the effectiveness of relapse prevention.

Concluding remarks This thesis focused on relapse prevention among patients with remitted anxiety and depressive disorders. As demonstrated in this thesis, patients in remission from depressive disorders should receive psychological relapse prevention interventions.

Greater attention should be paid to developing, implementing and evaluating relapse prevention interventions among patients with anxiety disorders. Although patients were generally positive about the GET READY relapse prevention program, the implementation of the program proved to be challenging, primarily due to a lack of motivation among patients and a lack of support from MHPs. Therefore, psychoeducation focused on the risk of relapse and the effectiveness of psychological relapse prevention interventions should receive more attention in mental health care and the GET READY program may be intensified to attain effectiveness. MHPs appear to have a crucial role to play in implementing relapse prevention programs, and should seek to tailor their support and guidance to the expressed needs and self-management skills of patients. Although usage of the GET READY relapse prevention program was relatively low compared to similar programs, patients mostly remained stable during their participation in the study. This might indicate that the program is capable of potentially protecting patients from relapse. However, a RCT is needed to validate this particular finding.

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NEDERLANDSE SAMENVATTING DUTCH SUMMARY Achtergrond en doelstellingen Veel mensen krijgen in hun leven te maken met angst- of depressieve klachten.

Wanneer deze klachten het leven gaan beheersen, kunnen dit stoornissen worden.

Angststoornissen worden gekenmerkt door het ervaren van ernstige angst en bezorgdheid. In dit proefschrift komen angststoornissen aan bod, die in de ‘Diagnostic and Statistical Manual of Mental Disorders’ (DSM) beschreven zijn: paniekstoornis (met of zonder agorafobie), agorafobie, specifieke fobie, sociale fobie (ook wel sociale angststoornis), gegeneraliseerde angststoornis, obsessieve-compulsieve stoornis en posttraumatische stressstoornis. Naast aandacht voor angststoornissen is er in dit proefschrift ook aandacht voor depressieve stoornissen. Deze kenmerken zich door een sombere stemming en het verlies van interesse of plezier in het leven. In dit proefschrift komen de depressie en dysthyme stoornis aan bod. Een dysthyme stoornis is een langdurige milde depressie.

Wereldwijd behoren angst- en depressieve stoornissen tot de meest voorkomende psychische stoornissen. In Nederland krijgt één op de vijf mensen ooit in het leven te maken met een angst- en/of depressieve stoornis. Dit heeft een grote impact op hun kwaliteit van leven, het functioneren en het welbevinden. Angst- en depressieve stoornissen komen vaak samen voor: mensen die ooit een angststoornis hebben gehad, hebben ook vaak ooit een depressieve stoornis gehad, en andersom.

Er is veel onderzoek verricht naar het behandelen van angst- en depressieve stoornissen. Vaak bestaat de behandeling uit een psychologische en/of medicamenteuze behandeling. Eén van de psychologische behandelingen die veel is onderzocht, is cognitieve gedragstherapie (CGT). CGT blijkt effectief te zijn in het behandelen van angst- en depressieve stoornissen. Behandeling met medicatie blijkt ongeveer even effectief te zijn in het verlagen van angst- en depressieve klachten. Een combinatie van beiden blijkt het meest effectief te zijn. Vaak geven patiënten echter de voorkeur aan psychologische behandeling, bijvoorbeeld vanwege zorgen over bijwerkingen van medicatie. Psychologische behandelingen worden doorgaans via persoonlijk contact gegeven, waarbij de patiënt en hulpverlener elkaar ‘live’ zien. Echter, vanwege COVID-19 lijken er steeds meer van deze behandelingen online gegeven te worden. Online behandelingen kenmerken zich veelal door de inzet van E-health-modules, persoonlijke feedback van een hulpverlener en de mogelijkheid om berichten uit te wisselen. De voordelen van online behandeling kunnen o.a. zijn dat het gemakkelijk toegankelijk is, dat symptomen effectief gemonitord kunnen worden via E-health toepassingen en dat het mogelijk meer kosteneffectief is.

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Wanneer patiënten herstellen van een angst- of depressieve stoornis, wordt gesproken van remissie (remission) of herstel (recovery). Hoewel er veel variatie is in hoe deze termen gebruikt worden in de literatuur, geven beide termen aan dat patiënten niet meer voldoen aan de DSM-criteria voor de stoornis. Maar ook als patiënten hersteld zijn van een angst- of depressieve stoornis, kunnen zij een terugval ervaren. Voor terugval zijn er ook twee termen te vinden in de Engelstalige literatuur: ‘relapse’ en ‘recurrence’. Beide wijzen op een terugkeer van klachten, die zo ernstig zijn dat men (opnieuw) spreekt van een DSM-stoornis. Patiënten die hersteld zijn van een angst- of depressieve stoornis hebben 57% kans om binnen vier jaar een terugval te ervaren.

Dit kan een terugval zijn in dezelfde stoornis, maar mensen die eerst een depressieve stoornis hadden, kunnen ook een angststoornis ontwikkelen (en andersom).

Terugvalcijfers zijn dus hoog. Er zijn enkele risicofactoren bekend die de kans op terugval verhogen. Patiënten die niet geheel maar gedeeltelijk herstellen, hebben meer kans op terugval. Ook is er een grote kans op terugval wanneer men minder goed functioneert in psychosociaal opzicht, en ook wanneer men meerdere en ernstigere episodes van de stoornis heeft ervaren.

Aangezien veel mensen die een behandeling hebben ontvangen voor hun angst- en/ of depressieve stoornis alsnog te maken krijgen met een terugval, is één van de grootste uitdagingen het voorkomen van terugval. Momenteel is er nog te weinig aandacht voor terugvalpreventie in de geestelijke gezondheidszorg. Terugvalpreventie bestaat vaak uit: 1) het continueren van antidepressiva, en 2) psychologische terugvalpreventie-interventies. Het is belangrijk dat patiënt en hulpverlener overeenkomen welke manier van terugvalpreventie gebruikt wordt, aangezien dit de therapietrouw, en daarmee effectiviteit ten goede komt. Er is veel onderzoek gedaan naar psychologische terugvalpreventie-interventies bij depressieve stoornissen, maar in veel mindere mate bij angststoornissen.

In Nederland is de focus de laatste jaren steeds meer verschoven van het behandelen van ziektes naar het voorkomen ervan. Zorg wordt zo laagdrempelig mogelijk aangeboden, wat ook geldt voor psychologische zorg. Bij deze ontwikkeling past de opkomst van de praktijkondersteuner huisarts GGZ (POH-GGZ). Deze hulpverlener ondersteunt de huisarts bij het bieden van psychologische zorg. POH-GGZ zijn dan ook de aangewezen hulpverleners om terugvalpreventie aan patiënten aan te bieden. Daarbij leggen zij een focus op het zelfmanagementvermogen van patiënten, oftewel: wat kunnen patiënten zelf doen om op een constructieve manier met hun symptomen om te gaan?

Huidige terugvalpreventieprogramma’s hebben enkele beperkingen. Ten eerste zijn ze niet toegespitst op zowel angst- en depressieve stoornissen. Ten tweede worden deze programma’s nog nauwelijks aangeboden via de huisartsenpraktijk. Ten slotte zijn ze niet specifiek afgestemd op de voorkeuren van patiënten. Als antwoord op deze

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beperkingen is het GET READY terugvalpreventieprogramma ontwikkeld. Dit is gericht op patiënten die hersteld zijn van een angst- en/of depressieve stoornis. De voorkeuren van patiënten zijn meegenomen in de ontwikkeling van dit programma. Het programma bestaat uit verschillende E-health modules die gepaard gaan met persoonlijke contacten met een POH-GGZ in de huisartsenpraktijk. Daarnaast is er een persoonlijk terugvalpreventieplan. Patiënten kunnen hierbij ook een angst- en stemmingsdagboek invullen. Hun angst- en stemmingsniveau kan zo effectief gemonitord worden.

Het overkoepelende doel van dit proefschrift is om terugval te voorkomen bij patiënten die hersteld zijn van een angst- en/of depressieve stoornis, en daarmee hun kwaliteit van leven te verbeteren. Om dit doel te kunnen bereiken zijn verschillende onderzoeken uitgevoerd Ten eerste werd via een literatuuronderzoek de effectiviteit van psychologische terugvalpreventie-interventies onderzocht. Ten tweede werd het nieuw ontwikkelde GET READY programma en de implementatie ervan geëvalueerd. Als laatste werden de psychometrische eigenschappen van een zelfmanagementvragenlijst voor patiënten met angst- en depressieve klachten onderzocht.

Resultaten In Hoofdstuk 2 wordt een systematische literatuur-overzichtsstudie en meta-analyse beschreven, die is uitgevoerd om de effectiviteit van psychologische terugvalpreventieinterventies voor patiënten met herstelde angst- en depressieve stoornissen te onderzoeken. Er is gekeken naar de effectiviteit van psychologische terugvalpreventieinterventies als aparte interventie, maar ook wanneer deze gecombineerd werden met een onderhoudsbehandeling van antidepressiva, of werden gecombineerd met het afbouwen van antidepressiva. In totaal werden er 7.324 artikelen gescreend, en werden er uiteindelijk 40 artikelen geïncludeerd. Hieruit bleek dat het ontvangen van een psychologische interventie de kans op terugval voor patiënten die hersteld waren van een depressieve stoornis met 24% verminderde ten opzichte van mensen die gebruikelijke zorg ontvingen. Dit effect kwam het duidelijkst naar voren in de eerste 24 maanden, maar het effect bleef zelfs na drie jaar zichtbaar. Wanneer psychologische interventies en antidepressiva werden gecombineerd, leidde dit ook tot 24% minder kans op terugval, vergeleken met wanneer er enkel antidepressiva werden gegeven.

Dit effect was in de eerste 24 maanden zichtbaar. Er kon geen meta-analyse worden uitgevoerd naar het gecombineerde effect van psychologische interventies en het afbouwen van antidepressiva, omdat er te weinig studies over dit onderwerp beschikbaar waren. Tevens kon er, vanwege een gebrek aan studies, geen meta-analyse uitgevoerd worden naar de effectiviteit van psychologische interventies voor patiënten die hersteld zijn van een angststoornis. De conclusie van dit hoofdstuk is dat psychologische interventies effectief zijn in het verminderen van de kans op terugval voor patiënten die hersteld zijn van een depressieve stoornis.

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Hoofdstukken 3, 4 en 5 beschrijven de ontwikkeling, implementatie en evaluatie van het GET READY terugvalpreventieprogramma. Hoofdstuk 3 beschrijft het protocol van de GET READY studie, waarin het GET READY terugvalpreventieprogramma werd aangeboden aan patiënten. Het programma is ontwikkeld in samenspraak met professionals en met een panel van patiënten. Het protocol beschrijft zowel de kwantitatieve als de kwalitatieve methoden die gebruikt zijn om het GET READY programma te evalueren.

In Hoofdstuk 4 wordt het gebruik van het GET READY programma, het beloop van klachten en het verband tussen deze twee factoren beschreven. Deze factoren werden in kaart gebracht bij 113 patiënten die geheel of gedeeltelijk hersteld waren van een angst- en/of depressieve stoornis. Er is longitudinale data verzameld over een periode van negen maanden. De kernmodules in het E-health programma – zijnde het terugvalpreventieplan en de psycho-educatiemodule over terugvalpreventie – werden gebruikt door 70-74% van de patiënten, terwijl de optionele modules gebruikt werden door minder dan 40% van de patiënten. Ongeveer een kwart van de patiënten gebruikte het programma relatief vaak ten opzichte van de rest van de patiënten die er relatief weinig gebruik van maakten. Over het algemeen nam het gebruik van de zelfmanagementonderdelen van het terugvalpreventieprogramma snel af na de start van de follow-up-periode. Aangezien de studie niet experimenteel was, kon er geen oorzakelijk verband worden aangetoond tussen het gebruik van het GET READY programma en de ernst van de symptomen. Wel bleek dat de meeste patiënten die deelnamen aan het programma stabiel bleven: een minderheid van 15% ervaarde een terugval in angstsymptomen in de negen maanden van de studie, en 10% ervaarde een terugval in depressieve symptomen. Patiënten met meer persoonlijke contacten met hun POH-GGZ, hadden significant meer angst- en depressieve klachten. Andere gebruiksvariabelen toonden geen significant verband met het beloop van de klachten.

In Hoofdstuk 5 zijn de resultaten beschreven van een kwalitatieve studie naar de implementatie en evaluatie van het GET READY programma, dit vanuit het perspectief van zowel de patiënt als de POH-GGZ. Daarvoor werden gepaarde individuele interviews afgenomen bij patiënten (N=13) en hun POH-GGZ (N=12). Door deze gepaarde interviews konden eventuele verschillen in de perspectieven aan het licht komen betreffende een en dezelfde casus. Aanvullende op de individuele interviews zijn er ook twee focusgroep-interviews uitgevoerd, één met patiënten en één met POH-GGZ. De interviews toonden aan dat de meeste gebruikers positief waren over het GET READY programma. Specifiek werd genoemd dat het een bewustzijn van risico op terugval teweegbracht en dat het programma bijdroeg aan het innemen van een actieve rol van patiënten in hun eigen herstel. Het werd ervaren als een vangnet voor eventuele terugval in de periode na eerder herstel. Daarnaast waardeerden patiënten de gebruiksvriendelijkheid en toegankelijkheid van het programma. Echter waren er

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ook factoren die het gebruik van het programma belemmerden: het gebrek aan motivatie van patiënten, het gebrek aan herkenbaarheid van het programma (omdat het zich op zowel angst als depressie richtte), en het gebrek aan ervaren steun van de POH-GGZ. Ook bleek dat het gebruik van het programma negatief beïnvloed werd door het aantal en de ernst van de symptomen van patiënten. Patiënten met slechts lichte symptomen hadden er weinig behoefte aan om actief met terugvalpreventie bezig te zijn, terwijl patiënten met meer ernstige symptomen, mede door een gebrek aan concentratie en energie, het programma eveneens minder gebruikten. Het combineren van de E-health modules met de persoonlijke contacten met de POH-GGZ werd als essentieel gezien, door zowel patiënten als POH-GGZ. De POH-GGZ speelde een heel belangrijke rol in het motiveren en steunen van patiënten om met E-health aan de slag te gaan. Uit de gepaarde interviews kwamen geen opvallende verschillen in perspectieven naar voren, maar deze werden in de focusgroepen wel opgemerkt. Zo bleek dat POH-GGZ van patiënten verwachten dat zij een zekere mate van zelfmanagementvaardigheden hadden ten aanzien van het gebruik van het terugvalpreventieprogramma, terwijl patiënten juist aangaven deze vaardigheden niet altijd te bezitten. Zij hadden behoefte aan meer directe en persoonlijke steun van hun POH-GGZ. In Hoofdstuk 6 worden de resultaten gepresenteerd van een onderzoek naar de psychometrische eigenschappen van een nieuwe vragenlijst die gericht is op zelfmanagementvaardigheden van patiënten met angst- en depressieve stoornissen: de ‘Assessment of Self-management in Anxiety and Depression’ (ASAD) vragenlijst.

Deze vragenlijst bestaat uit 45 items en kan gebruikt worden door zowel patiënten als professionals, om zelfmanagementvaardigheden in kaart te brengen. Aangezien zelfmanagement in toenemende mate belangrijk is in het herstel van psychische stoornissen, lijkt een focus op zelfmanagement in het kader van terugvalpreventie gerechtvaardigd. Tegelijkertijd blijkt echter ook dat de last van angst- en depressieve stoornissen mogelijk het gebruik van zelfmanagementvaardigheden juist vermindert.

De ASAD is ontwikkeld omdat er nog geen Nederlandse zelfmanagementvragenlijst beschikbaar was voor patiënten met angst- en depressieve stoornissen. In onze studie werd de ASAD door in totaal 171 mensen ingevuld. Zowel een exploratieve als een confirmatieve factoranalyse lieten zien dat er drie solide factoren aanwezig waren in de vragenlijst: het zoeken van steun, dagelijkse levensstrategieën en het nemen van eigenaarschap. Verder bleek uit de uitgevoerde analyses dat het aantal items verminderd kon worden van 45 naar 21. De evaluatie wees op een hoog niveau van interne consistentie en betrouwbaarheid voor de 21 items van de ASAD ‘short form’ (ASAD-SF).

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Conclusies Eén van de belangrijkste conclusies naar aanleiding van dit proefschrift is dat terugvalpreventie bij angst- en depressieklachten meer aandacht verdient: patiënten die (grotendeels) hersteld zijn van deze stoornissen zouden naast eventuele medicamenteuze ondersteuning (onderhoudsmedicatie) ook psychologische terugvalpreventie-interventies moeten ontvangen. Er is meer aandacht nodig voor de ontwikkeling, implementatie en evaluatie van deze interventies voor deze patiënten.

Hoewel patiënten overwegend positief waren over het GET READY terugvalpreventieprogramma, bleek de implementatie ervan uitdagend, voornamelijk vanwege een gebrek aan motivatie bij patiënten en gebrek aan ervaren steun van de POH-GGZ. Daarom zou er in de gezondheidszorg meer voorlichting gegeven moeten worden over de risico’s op terugval, aan zowel patiënten als de POH-GGZ. POH-GGZ hebben een belangrijke rol in het implementeren van terugvalpreventie­programma’s, waarbij het essentieel is dat zij de mate van ondersteuning en begeleiding afstemmen op de zelfmanagementvaardigheden en behoeften van de patiënt. Hoewel het GET READY terugvalpreventieprogramma relatief weinig gebruikt werd, bleek toch dat de meeste patiënten gedurende het onderzoek stabiel bleven in de klachten. Dit zou kunnen betekenen dat het programma mensen voor terugval zou kunnen behoeden.

Om dit resultaat te bevestigen, zou een gerandomiseerd onderzoek met een controlegroep uitgevoerd moeten worden.

Acknowledgements | Dankwoord | 199

DANKWOORD ACKNOWLEDGEMENTS Wat een voorrecht om een dankwoord te kunnen schrijven, hier heb ik een tijd naar uitgekeken. Iedereen weet immers dat van zo’n proefschrift voornamelijk het dankwoord wordt gelezen. Ik neem daarom graag de ruimte om iedereen te bedanken die heeft bijgedragen aan dit promotietraject.

Als eerste: dank aan mijn promotieteam. Berno, waar moet ik beginnen? Ontzettend bedankt voor je scherpe oog tijdens het lezen, voor de inspirerende oneliners, voor je gave om nog precies te weten wat we 3 weken geleden besproken hebben (ook al begeleidde je op een gegeven punt 20 PhD’s?), voor de pragmatische oplossingen die aangedragen werden en voor de gezelligheid. Ik ervaar het als een voorrecht om verbonden te blijven met het lectoraat GGZ verpleegkunde en samen aan de slag te gaan met het opzetten van leer- en innovatienetwerken waarbij onderwijs, wetenschap en praktijk verbonden worden. Annemieke, dank voor je waardevolle bijdrage aan de overleggen en artikelen. Je scherpe blik en uitgebreide kennis hebben elk deelonderzoek verder geholpen. Ook het feit dat je als POH-GGZ hebt gewerkt kwam goed van pas, en ik heb genoten van de les die je erover gaf, die ik bij mocht wonen. Anna, veel dank voor de ontelbare uren overleg, waarin zaken die voor mij ingewikkeld leken vaak erna opeens een stuk duidelijker waren. Dank voor je positieve woorden, goeie ideeën en praktische antwoorden. Op momenten dat het lastig was, overtuigde je me er altijd van dat ik het wel kon. Neeltje, van alle mee-lezers en co-auteurs denk ik dat ik het vaakst van jou een geheel rood gemarkeerd document terug kreeg. Ik vond dit in het begin lastig, totdat je me vertelde dat enkel als het stuk al goed in elkaar zit, je veel feedback kan geven om het nog beter te maken. Je ontzettend scherpe oog heeft de artikelen stukken beter gemaakt. Dank voor al je positiviteit, creativiteit en praktische oplossingen.

Otto, ook al was je officieel geen onderdeel van mijn promotieteam, toch moet je hier genoemd worden. Als huisarts en onderzoeker had je een enorm waardevolle bijdrage bij de ontwikkeling van het GET READY programma, maar ook zeker daarna. Jouw ideeën voor onderzoeksmethoden, analyses en subsidieaanvragen waren onmisbaar.

Een belangrijk woord van dank wil ik richten aan alle POH-GGZ die meegedaan hebben aan het onderzoek, en aan alle patiënten die deelgenomen hebben. Dank voor jullie tijd, openheid en bereidheid om mee te werken aan het onderzoek. Op deze plek ik wil ook de leden van de leescommissie ontzettend bedanken voor jullie tijd en het beoordelen van mijn proefschrift.

200 | Acknowledgements | Dankwoord

De collega’s van veldwerk wil ik bijzonder bedanken, omdat zonder hen we wel een mooi programma hadden gehad, maar niemand om het bij aan te bieden. In het bijzonder wil ik onderzoeksassistenten Laura, Suzanne, Nancy, Elise en Rochelle bedanken voor hun toewijding aan het werven van respondenten, het versturen van mailings, het bijhouden van de Access database, het meedenken over nieuwsbrieven, het bellen van respondenten voor het invullen van vragenlijsten en nog veel meer dingen. Ook Bianca wil ik bedanken, omdat zij als stabiele factor altijd weer goede ideeën kon aandragen en wilde meedenken over hoe we dingen moesten aanpakken.

Ook de collega’s van datamanagement verdienen een shout-out. Wat een vrij simpele database leek te worden, werd toch een behoorlijk project, en hierbij heeft Esi enorm veel betekend. Telkens als ik weer een aanpassing vroeg, was het binnen no-time geregeld. Ook Denise, Ho-Ming, Lianne, Sanne en Tim wil ik bedanken voor al jullie hulp bij het datamanagen van GET READY. Veel dank ben ik verschuldigd aan Adriaan. Het was enorm fijn dat ik gemakkelijk bij je binnen kon lopen als ik weer een statistische vraag had. Ook in het laatste jaar was je online goed bereikbaar en heb je veel meegedacht, dank daarvoor! Ook wil ik Stasja enorm bedanken, voor je enthousiasme, optimisme en snelle reacties bij het uitvoeren van de factoranalyse. Wie had gedacht dat je zo blij kan worden als er mooie factoren uit een vragenlijst blijken te komen? Daarnaast wil ik op deze plek ook mijn dank uitspreken voor Jeroen. In het begin van mijn promotietraject heeft hij veel meegedacht over mogelijke analyses, en kwam met enorm creatieve ideeën om mijn niet-voor-dehand-liggende-data te tackelen.

Marissa, Sharmila & Carla: bedankt voor jullie administratieve ondersteuning. Margie: dank voor je interesse, gezelligheid, en het ‘bewaken van het fort’.

Stagiaires Aagje, Annabel, Elise en Evelien, jullie hebben allen op een eigen manier een unieke bijdrage geleverd aan het GET READY onderzoek. Ik vond het erg leuk om jullie te begeleiden, zo leuk zelfs dat ik in mijn nieuwe baan ook studenten ga begeleiden bij het uitvoeren van onderzoek.

Daarnaast wil ik mijn dank uitspreken aan alle andere collega’s die op de een of andere manier hebben bijgedragen. Daphne en Eline, dank voor jullie hulp bij het schrijven van content voor de online modules. Ton, dank voor je bijdrages aan enkele artikelen.

Willemijn, ik kijk met een goed gevoel terug op onze úren van screenen en data extractie voor de systematic review & meta-analyse. Dank voor je hulp en gezelligheid. Jasmijn, wat super dat ons kwalitatieve artikel gepubliceerd is. Wat was het veel werk en wat hebben we er ook een leuke exercitie van gemaakt, door een weekje in het Volkshotel te werken met lekkere cappuccino’s. Ook de collega’s van de Academische Werkplaats

Acknowledgements | Dankwoord | 201

Angst wil ik bedanken voor de betrokkenheid, goede overleggen en gezelligheid tijdens de jaarlijkse etentjes.

Niet in de laatste plaats ben ik enorm dankbaar voor mijn roomies van de afgelopen jaren. Laura en Trees, de eerste dag bij GGZ inGeest zaten jullie er, en wat ben ik blij dat ik jullie getroffen heb. We zijn meermaals van kamer gewisseld, maar telkens weer bij elkaar terecht gekomen. Wat zijn we samen over bergen en door dalen gegaan, en wat hebben we veel koffie (en bier) gedronken en plezier gehad! Om de feestvreugde te vergroten kwamen later Claire en Ilja ook als semi-roomies om de hoek kijken. Jullie allen enorm bedankt voor de luisterende oren, koffiemomentjes, slingers als er iets te vieren was en lieve cadeautjes als er verdrietige dingen gebeurden. Ik vind het ongelooflijk jammer dat we geen directe collega’s meer zijn, maar hoop op nog veel etentjes en borrels in de toekomst. Mayke, Lisa, Renske, Melis, Vicky, Afra, Ruth, Carmen, Wicher, Sjors, Moji, Richard en alle andere PhDs en postdocs van GGZ inGeest: dank voor alle gezelligheid tijdens de lunches en koffie/bijpraat momentjes.

Buiten GGZ inGeest zijn er ook veel mensen die ik dankbaar ben. Hilde: dank voor jouw supervisie. Marily: dank voor de heerlijke etentjes en voor het vrijwillig vragen of je mijn proefschrift al mocht lezen. Lotte, Marieke, Judith en Daphne: dank voor jullie interesse in mijn hele promotietraject en de afleiding in heel verschillende vormen.

Emmy: dank voor het meedenken over de inhoud van de E-health modules, dit heb ik erg gewaardeerd. Alle andere vrienden en vriendinnen: dank voor jullie betrokkenheid, lieve berichten en gezellige etentjes in de afgelopen jaren. Ik zie uit naar nog veel meer gezelligheid!

Natuurlijk ook dank aan mijn familie. Speciale dank aan opa die maar bleef vragen wanneer mijn scriptie nou een keer klaar was. Nou opa, hier is ‘tie dan! Dank aan mijn lieve ouders Chris en Alies, die altijd voor me klaar stonden en altijd hebben laten merken enorm trots op me te zijn. Veel dank aan mijn broer Wouter, schoonzus Sarah, en broertje Freek, voor jullie liefde en vriendschap. Ook dank aan de liefste schoonouders Paul en Ina, schoonzus Lydia en zwager Bruno, en lieve kleine Tycho voor jullie betrokkenheid en geloof in mij.

En het belangrijkste plekje van dit dankwoord heb ik bewaard voor Gersom, de liefde van mijn leven. Wat ben ik blij dat wij elkaar – inmiddels alweer 16 jaar geleden – hebben leren kennen, en wat hebben we een mooi leven samen. Zonder jou denk ik dat dit proefschrift er niet was gekomen. Dankjewel voor je liefde, relativeringsvermogen, bereidheid om van alles van me over te nemen als dat nodig was, je motiverende speeches en voor de avonturen die we samen hebben. Ik kan niet wachten om binnenkort het grootste avontuur met jou aan te gaan!

202 | Curriculum vitae

CURRICULUM VITAE Esther Krijnen- de Bruin was born on July 2nd 1989 in Utrecht, the Netherlands. After completing her secondary education at De Passie in Utrecht, she had a gap year, doing voluntary work in Kenya. In 2011 she completed her bachelor’s degree in nursing at Christelijke Hogeschool Ede. From 2011 to 2012 she was a nursing trainee at the department of child and youth psychiatry and at the department for patients with (early) psychosis at UMC Utrecht, and she kept working as a psychiatric nurse until 2015. In addition, she studied Health Sciences at the VU University Amsterdam, with the specialization ‘Prevention and Public Health’. In 2014 she obtained her master’s degree. From 2015 to 2016 she worked as a Clinical Trial Assistant at Julius Clinical in Zeist. In 2016 she started working as a PhD student at GGZ inGeest/Department of Psychiatry of the Amsterdam UMC, location VUmc, also affiliated with Inholland University of Applied Sciences. Her research has been embedded in the ‘Academische Werkplaats Angst’ and focused on relapse prevention for patients with remitted anxiety and depressive disorders. In 2021 she started to work as a lecturer in scientific training at Inholland University of Applied Sciences, in which she also focuses on the development of ‘Leer- en innovatienetwerken’ in mental health care, networks in which science, practice and education is connected.

Dissertation series | 203

DISSERTATION SERIES Department of Psychiatry, Amsterdam University Medical Centers N.M. (Neeltje) Batelaan (2010). Panic and Public Health: Diagnosis, Prognosis and Consequences. Vrije Universiteit Amsterdam. ISBN: 978-90-8659-411-5.

G.E. (Gideon) Anholt (2010). Obsessive-Compulsive Disorder: Spectrum Theory and Issues in Measurement. Vrije Universiteit Amsterdam.

N. (Nicole) Vogelzangs (2010). Depression & Metabolic Syndrome. Vrije Universiteit Amsterdam. ISBN: 978-90-8659-447-4.

C.M.M. (Carmilla) Licht (2010). Autonomic Nervous System Functioning in Major Depression and Anxiety Disorders. Vrije Universiteit Amsterdam. ISBN: 978-90-8659487-0.

S.A. (Sophie) Vreeburg (2010). Hypothalamic-Pituitary-Adrenal Axis Activity in Depressive and Anxiety Disorders. Vrije Universiteit Amsterdam. ISBN: 978-90-8659-491-7.

S.N.T.M. (Sigfried) Schouws (2011). Cognitive Impairment in Older Persons with Bipolar Disorder. Vrije Universiteit Amsterdam. ISBN: 978-90-9025-904-8.

P.L. (Peter) Remijnse (2011). Cognitive Flexibility in Obsessive-Compulsive Disorder and Major Depression – Functional Neuroimaging Studies on Reversal Learning and Task Switching. Vrije Universiteit Amsterdam. ISBN: 978-90-6464-449-8.

S.P. (Saskia) Wolfensberger (2011). Functional, Structural, and Molecular Imaging of the Risk for Anxiety and Depression. Vrije Universiteit Amsterdam. ISBN: 978-90-8659536-5.

J.E. (Jenneke) Wiersma (2011). Psychological Characteristics and Treatment of Chronic Depression. Vrije Universiteit Amsterdam. ISBN: 978-94-9121-150-8.

P.D. (Paul David) Meesters (2011). Schizophrenia in Later Life. Studies on Prevalence, Phenomenology and Care Needs (SOUL Study). Vrije Universiteit Amsterdam. ISBN: 978-90-8659-563-1.

204 | Dissertation series

R. (Ritsaert) Lieverse (2011). Chronobiopsychosocial Perspectives of Old Age Major Depression: a Randomized Placebo Controlled Trial with Bright Light. Vrije Universiteit Amsterdam. ISBN: 978-90-8570-858-2.

A. (Adrie) Seldenrijk (2011). Depression, Anxiety and Subclinical Cardiovascular Disease.

Vrije Universiteit Amsterdam. ISBN: 978-94-6191-052-3.

Y. (Yuri) Milaneschi (2012). Biological Aspects of Late-life Depression. Vrije Universiteit Amsterdam. ISBN: 978-90-8659-608-9.

L. (Lynn) Boschloo (2012). The Co-occurrence of Depression and Anxiety with Alcohol Use Disorders. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-327-2.

D. (Didi) Rhebergen (2012). Insight into the heterogeneity of depressive disorders. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-387-6.

T.M. (Michiel) van den Boogaard (2012). The Negotiated Approach in the Treatment of Depressive Disorders: the impact on patient-treatment compatibility and outcome.

Vrije Universiteit Amsterdam. ISBN: 978-90-8891-495-9.

M. (Marjon) Nadort (2012). The implementation of outpatient schema therapy for borderline personality disorder in regular mental healthcare. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-463-7.

U. (Ursula) Klumpers (2013). Neuroreceptor imaging of mood disorder related systems.

Vrije Universiteit Amsterdam. ISBN: 978-94-6191-575-7.

E. (Ethy) Dorrepaal (2013). Before and beyond. Stabilizing Group treatment for Complex posttraumatic stress disorder related to child abuse based on psycho-education and cognitive behavioral therapy. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-601-3.

K. (Kathleen) Thomaes (2013). Child abuse and recovery. Brain structure and function in child abuse related complex posttraumatic stress disorder and effects of treatment.

Vrije Universiteit Amsterdam. ISBN: 978-94-6191-600-6.

K.M.L.(Klaas) Huijbregts (2013). Effectiveness and cost-effectiveness of the implementation of a collaborative care model for depressive patients in primary care.

Vrije Universiteit Amsterdam. ISBN: 978-90-9027404-1.

Dissertation series | 205

T.O. (Tessa) van den Beukel (2013). Ethnic differences in survival on dialysis in Europe.

The role of demographic, clinical and psychosocial factors. Vrije Universiteit Amsterdam.

ISBN: 978-94-6108410-1.

A. (Agnes) Schrier (2013). Depression and anxiety in migrants in the Netherlands.

Population studies on diagnosis and risk factors. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-719-5.

B. (Barbara) Stringer (2013). Collaborative Care for patients with severe personality disorders. Challenges for the nursing profession. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-809-3.

C.M. (Caroline) Sonnenberg (2013). Late life depression: sex differences in clinical presentation and medication use. Vrije Universiteit Amsterdam. ISBN: 978-94-6191866-6.

Z. (Zsuzsika) Sjoerds (2013). Alcohol dependence across the brain: from vulnerability to compulsive drinking. Vrije Universiteit Amsterdam. ISBN: 978-90-8891-695-3.

V.J.A. (Victor) Buwalda (2013). Routine Outcome Monitoring in Dutch Psychiatry: Measurement, Instruments, Implementation and Outcome. Vrije Universiteit Amsterdam. ISBN: 978-94-6191-905-2.

J.G. (Josine) van Mill (2013). Sleep, depression and anxiety: an epidemiological perspective. Vrije Universiteit Amsterdam. ISBN: 978-94-6108-525-2.

S. (Saskia) Woudstra (2013). Framing depression in a SN[a]Pshot: Imaging risk factors of MDD. Vrije Universiteit Amsterdam. ISBN: 978-90-8891-751-6.

N.C.M. (Nicole) Korten (2014). Stress, depression and cognition across the lifespan.

Vrije Universiteit Amsterdam. ISBN: 978-94-6108-748-5.

M.K. (Maarten) van Dijk (2014). Applicability and effectiveness of the Dutch Multidisciplinary Guidelines for the treatment of Anxiety Disorders in everyday clinical practice. Vrije Universiteit Amsterdam. ISBN: 978-94-92096-00-5.

I.M.J. (Ilse) van Beljouw (2015). Need for Help for Depressive Symptoms from Older Persons Perspectives: The Implementation of an Outreaching Intervention Programme.

Vrije Universiteit Amsterdam. ISBN: 978-94-6259-496-8.

206 | Dissertation series

A.M.J. (Annemarie) Braamse (2015). Psychological aspects of hematopoietic stem cell transplantation in patients with hematological malignancies. Vrije Universiteit Amsterdam. ISBN: 978-94-6259-594-1.

A. (Annelies) van Loon (2015). The role of ethnicity in access to care and treatment of outpatients with depression and/or anxiety disorders in specialised care in Amsterdam the Netherlands. Vrije Universiteit Amsterdam. ISBN: 978-94-90791-34-6.

C. (Chris) Vriend (2015). (Dis)inhibition: imaging neuropsychiatry in Parkinson’s disease.

Vrije Universiteit Amsterdam. ISBN: 978-94-6295-115-0.

A.M. (Andrea) Ruissen (2015). Patient competence in obsessive compulsive disorder.

An empirical ethical study. Vrije Universiteit Amsterdam. ISBN: 978-90-6464-856-4.

H.M.M. (Henny) Sinnema (2015). Tailored interventions to implement guideline recommendations for patients with anxiety and depression in general practice.

Vrije Universiteit Amsterdam. ISBN: 978-94-6169-653-3.

T.Y.G. (Nienke) van der Voort (2015). Collaborative Care for patients with bipolar disorder. Vrije Universiteit Amsterdam. ISBN: 978-94-6259-646-7.

W. (Wim) Houtjes (2015). Needs of elderly people with late-life depression; challenges for care improvement. Vrije Universiteit Amsterdam. ISBN: 978-94-6108-985-4.

M. (Marieke) Michielsen (2015). ADHD in older adults. Prevalence and psychosocial functioning. Vrije Universiteit Amsterdam. ISBN: 978-90-5383-132-8.

S.M. (Sanne) Hendriks (2016). Anxiety disorders. Symptom dimensions, course and disability. Vrije Universiteit Amsterdam. ISBN: 978-94-6259-963-5.

E.J. (Evert) Semeijn (2016). ADHD in older adults; diagnosis, physical health and mental functioning. Vrije Universiteit Amsterdam. ISBN: 978-94-6233-190-7.

N. (Noera) Kieviet (2016). Neonatal symptoms after exposure to antidepressants in utero. Vrije Universiteit Amsterdam. ISBN: 978-94-6169-794-3.

W.L. (Bert) Loosman (2016). Depressive and anxiety symptoms in Dutch chronic kidney disease patients. Vrije Universiteit Amsterdam. ISBN: 987-94-6169-793-6.

Dissertation series | 207

E. (Ellen) Generaal (2016). Chronic pain: the role of biological and psychosocial factors.

Vrije Universiteit Amsterdam. ISBN: 978-94-028-0032-6.

D. (Dóra) Révész (2016). The interplay between biological stress and cellular aging: An epidemiological perspective. Vrije Universiteit Amsterdam. ISBN: 978-94-028-0109-5.

F.E. (Froukje) de Vries (2016). The obsessive-compulsive and tic-related brain. Vrije Universiteit Amsterdam. ISBN: 978-94-629-5481-6.

J.E. (Josine) Verhoeven (2016). Depression, anxiety and cellular aging: does feeling blue make you grey? Vrije Universiteit Amsterdam. ISBN: 978-94-028-0069-2.

A.M. (Marijke) van Haeften-van Dijk (2016). Social participation and quality of life in dementia: Implementation and effects of interventions using social participation as strategy to improve quality of life of people with dementia and their carers. Vrije Universiteit Amsterdam. ISBN: 978-94-6233-341-3.

P.M. (Pierre) Bet (2016). Pharmacoepidemiology of depression and anxiety. Vrije Universiteit Amsterdam. ISBN: 978-94-6299-388-4.

M.L. (Mardien) Oudega (2016). Late life depression, brain characteristics and response to ECT. Vrije Universiteit Amsterdam. ISBN: 978-94-6295-396-3.

H.A.D. (Henny) Visser (2016). Obsessive-Compulsive Disorder; Unresolved Issues, Poor Insight and Psychological Treatment. Vrije Universiteit Amsterdam. ISBN: 978-94-0280259-7.

E.C. (Eva) Verbeek (2017). Fine mapping candidate genes for major depressive disorder: Connecting the dots. Vrije Universiteit Amsterdam. ISBN: 978-94-028-0439-3.

S. (Stella) de Wit (2017). In de loop: Neuroimaging Cognitive Control in ObsessiveCompulsive Disorder. Vrije Universiteit Amsterdam. ISBN: 978-90-5383-225 7.

W.J. (Wouter) Peyrot (2017). The complex link between genetic effects and environment in depression. Vrije Universiteit Amsterdam. ISBN: 978-94-6182-735-7.

R.E. (Rosa) Boeschoten (2017). Depression in Multiple Sclerosis: Prevalence Profile and Treatment. Vrije Universiteit Amsterdam. ISBN: 978-94-028-0474-4.

208 | Dissertation series

G.L.G. (Gerlinde) Haverkamp (2017). Depressive symptoms in an ethnically DIVERSe cohort of chronic dialysis patients: The role of patient characteristics, cultural and inflammatory factors. Vrije Universiteit Amsterdam. ISBN: 978-94-6233-528-8.

T.J. (Tjalling) Holwerda (2017). Burden of loneliness and depression in late life. Vrije Universiteit Amsterdam. ISBN: 978-94-6233-598–1.

J. (Judith) Verduijn (2017). Staging of Major Depressive Disorder. Vrije Universiteit Amsterdam. ISBN: 978-94-6299-597-0.

C.N. (Catherine) Black (2017). Oxidative stress in depression and anxiety disorders.

Vrije Universiteit Amsterdam. ISBN: 978-94-6299-672-4.

J.B. (Joost) Sanders (2017). Slowing and Depressive Symptoms in Aging People. Vrije Universiteit Amsterdam. ISBN: 978-94-6233-650-6.

W. (Willemijn) Scholten (2017). Waxing and waning of anxiety disorders: relapse and relapse prevention. Vrije Universiteit Amsterdam. ISBN: 978-94-6299-606-9.

P. (Petra) Boersma (2017). Person-centred communication with people with dementia living in nursing homes; a study into implementation success and influencing factors.

Vrije Universiteit Amsterdam. ISBN: 978-94-6233-725-1.

T.I. (Annet) Bron (2017). Lifestyle in adult ADHD from a Picasso point of view. Vrije Universiteit Amsterdam. ISBN: 978-94-6299-685-4.

S.W.N. (Suzan) Vogel (2017). ADHD IN ADULTS: seasons, stress, sleep and societal impact. Vrije Universiteit Amsterdam. ISBN: 978-94-6299-673-1.

R.(Roxanne) Schaakxs (2018). Major depressive disorder across the life span: the role of chronological and biological age. Vrije Universiteit Amsterdam. ISBN: 978-94-6299819-3.

J.J. (Bart) Hattink (2018). Needs-based enabling- and care technology for people with dementia and their carers. Vrije Universiteit Amsterdam. ISBN: 978-94-6295-880-7.

F.T. (Flora) Gossink (2018). Late Onset Behavioral Changes differentiating between bvFTD and psychiatric disorders in clinical practice. Vrije Universiteit Amsterdam. ISBN: 978-94-6295-899-9.

Dissertation series | 209

R. (Roxanne) Gaspersz (2018). Heterogeneity of Major Depressive Disorder. The role of anxious distress. Vrije Universiteit Amsterdam. ISBN: 978-94-028-1076-9.

M.M. (Marleen) Wildschut (2018). Survivors of early childhood trauma and emotional neglect: who are they and what’s their diagnosis? Vrije Universiteit Amsterdam. ISBN: 978-94-6332-401-4.

J.A.C. (Jolanda) Meeuwissen (2018). The case for stepped care. Exploring the applicability and cost-utility of stepped-care strategies in the management of depression. Vrije Universiteit Amsterdam. ISBN: 978-90-5383-359-9.

D.S. (Dora) Wynchank (2018). The rhythm of adult ADHD. On the relationship between ADHD, sleep and aging. Vrije Universiteit Amsterdam. ISBN: 978-94-6375-034-9.

M.J.(Margot) Metz (2018). Shared Decision Making in mental health care: the added value for patients and clinicians. Vrije Universiteit Amsterdam. ISBN: 978-94-6332-403-8.

I.(Ilse) Wielaard (2018). Childhood abuse and late life depression. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-072-3.

L.S.(Laura) van Velzen (2019). The stressed and depressed brain. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-062-4.

S. (Sonja) Rutten (2019). Shedding light on depressive, anxiety and sleep disorders in Parkinson’s disease. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-176-8.

N.P.G. (Nadine) Paans (2019). When you carry the weight of the world not only on your shoulders. Factors associating depression and obesity. Vrije Universiteit Amsterdam.

ISBN: 978-94-6380-141-6.

D.J. (Deborah) Gibson-Smith (2019). The Weight of Depression. Epidemiological studies into obesity, dietary intake and mental health. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-144-7.

C.S.E.W. (Claudia) Schuurhuizen ( 2019). Optimizing psychosocial support and symptom management for patients with advanced cancer. Vrije Universiteit Amsterdam. ISBN: 978-94-6323-468-9.

M.X. (Mandy) Hu (2019). Cardiac autonomic activity in depression and anxiety: heartfelt afflictions of the mind. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-206-2.

210 | Dissertation series

J.K.(Jan) Mokkenstorm (2019). On the road to zero suicides: Implementation studies.

Vrije Universiteit Amsterdam. ISBN: 978-94-6361-224-1.

S.Y. (Sascha) Struijs (2019). Psychological vulnerability in depressive and anxiety disorders. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-244-4.

H.W. (Hans) Jeuring (2019). Time trends and long-term outcome of late-life depression: an epidemiological perspective. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-228-4.

R. (Ruth) Klaming Miller (2019). Vulnerability of memory function and the hippocampus: Risk and protective factors from neuropsychological and neuroimaging perspectives.

Vrije Universiteit Amsterdam. ISBN: 978-94-6182-955-5.

P.S.W. (Premika) Boedhoe (2019) The structure of the obsessive-compulsive brain – a worldwide effort. Vrije Universiteit Amsterdam. ISBN: 978-94-6380-329-8.

C.S. (Carisha) Thesing (2020). Fatty acids in depressive and anxiety disorders: fishing for answers. Vrije Universiteit Amsterdam. ISBN: 978-94-6375-846-8.

R.D. (Richard) Dinga (2020). Evaluation of machine learning models in psychiatry.

Vrije Universiteit Amsterdam.

M. (Mayke) Mol (2020). Uptake of internet-based therapy for depression: the role of the therapist. Vrije Universiteit Amsterdam. ISBN: 978-94-6416-150-2.

R.C. (Renske) Bosman (2020). Improving the long-term prognosis of anxiety disorders: Clinical course, chronicity and antidepressant use. Vrije Universiteit Amsterdam. ISBN: 978-94-6375-736-2.

R.W. (Robbert) Schouten (2020). Anxiety, depression and adverse clinical outcomes in dialysis patients. Should we do more? Vrije Universiteit Amsterdam. ISBN: 978-94-6416179-3.

T.T. (Trees) Juurlink (2021). Occupational functioning in personality disorders: a quantitative, qualitative and semi-experimental approach. Vrije Universiteit Amsterdam.

ISBN: 978-94-6421-117-1.

I.P.H. (Ires) Ghielen (2021). Surfing the waves of Parkinson’s disease. Understanding and treating anxiety in the context of motor symptoms. Vrije Universiteit Amsterdam.

ISBN: 978-94-6416-493-0.

Dissertation series | 211

L.K.M. (Laura) Han (2021). Biological aging in major depressive disorder. Vrije Universiteit Amsterdam. ISBN: 978-94-93184-91-6.

E. (Esther) Krijnen-de Bruin (2021). Relapse prevention in patients with anxiety or depressive disorders. Vrije Universiteit Amsterdam. ISBN: 978-94-6423-298-1