Technology in Bipolar disorder

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Letters to the Editors

albeit in its paper version. We are still waiting to see published data about the Palm Life Chart but we believe that this is an equally robust system. We feel that our knowledge about what works best, and for whom, with these technologies is preliminary, and that handheld devices (e.g. PDAs and mobile phones) have considerable promise, especially with younger people who have a lot of experience using such machines. Our experience with young people with bipolar disorders from MDF The Bipolar Organisation,5 the UK advocacy group, suggests that handheld devices can offer the individual a degree of freedom and privacy for recording information and monitoring their illness, which is not possible through either desktop or web-based applications that run on a personal computer. Given that such devices are now relatively cheap, losses for long-term studies can be easily absorbed. Customized software for these devices is not necessarily expensive and there are open source alternatives6,7 that would allow any research group to build their custom forms to monitor their chosen variables of interest. As Dr Bauer suggested, our focus should remain on study processes (and the underlying methodologies) rather than on technology. We hope that the reported studies along with our ongoing study will soon help to increase our field’s knowledge regarding the issues and challenges involved with the rise of machines in clinical research with bipolar disorders. Y Malliaris and J Scott Institute of Psychiatry King’s College, University of London, London, UK References 1.

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Bauer M, Grof P, Rasgon N, Sasse J, Glenn T, Nuuhaus K et al. New technology for longitudinal studies of patients with bipolar disorder. Clin Approach Bipolar Disord 2005; 4: 4–10. Scott J, Malliaris Y, Ferrier N. MDF. Electronic monitoring of day to day symptom variability in individuals with bipolar disorder: feasibility and acceptability of use, and reliability and validity as an outcome measure, 2005; MRC Trial Platform Grant. Further information available at: www.bipolarlab.com (last accessed July 29, 2005). Scharer LO, Hartweg V, Valerius G, Graf M, Hoern M, Biedermann C et al. Life charts on a palmtop computer: first results of a feasibility study with an electronic diary for bipolar patients. Bipolar Disord 2002; 4 (Suppl 1): 107–108. Denicoff KD, Leverich GS, Nolen WA, Rush AJ, McElroy SL, Keck PE et al. Validation of the prospective NIMH-Life-Chart Method (NIMH-LCM super(TM)-p) for longitudinal assessment of bipolar illness. Psychol Med 2000; 30, 6: 1391–1397. MDF The Bipolar Organisation. Available at: www.mdf.org.uk (last accessed July 29, 2005). Weiss HM, Beal DJ, Lucy SL, MacDermid SM. The Purdue Momentary Assessment Tool (PMAT). Available at: www.mfri.purdue.edu/pages/pmat (last accessed August 15, 2005). Barrett DJ, Feldman Barrett L. The Experience-Sampling Program (ESP) (2000). Available at: www2.bc.edu/~barretli/esp/ (last accessed August 1, 2005).

DEAR SIRS, We write in response to the paper ‘New Technology for Longitudinal Studies of Patients with Bipolar Disorder’ by Bauer et al.1 Longitudinal presentation of psychiatric illnesses is a costeffective method with a capacity to excavate otherwise hidden

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information.2,3 Despite the promising potential, we found that in New York City very few providers, patients, or family members are involved in this method. We hope that a computer-focused update1 of the topic will bring new impetus into the methodology. Patients and their loved ones routinely make decisions such as calling in sick, investing, or seeking an additional or new medical provider. While the above issues are likely rooted in psychiatry, and the charts could help in decision making, therapists may not be able to assist patients at this operational level. Existing workforce (from quality engineers to computer specialists) provides many potential patients or family members with advanced know-how and researcher capacity in longitudinal presentation.1 We used the self-rated version of the Life Chart Manual (LCM)4 to introduce mental health patients to the retrospective life chart. Manic and depressive periods were rated as small, medium, or large. To establish reference, patients were instructed to recall their worst depressive and/or manic episodes. While the patients were enthusiastic to learn graphic methods, they were apprehensive about becoming part of a governmentsponsored study – part of the reason being that there were no incentives such as research participation fees or access to new experimental drugs or treatments to motivate participants to forward their charts anonymously to a research database. To illustrate the personal benefits of the LCM we would like to report the case of Mr A, a 49-year-old patient with a 35-year history of psychopathology. Mr A kept LCMs (35 years retrospective; 9 years in prospective forms; 3 in paper and 6 in Excel™ form). His selfrating primarily contained: wake-up status, back pain, anxiety, intermittent explosive disorder (IED) attacks, mood, and physical exercise. Self-rating was entered on a 0–10 scale. The daily rating was an estimate in relation to three reference values: the rating from the day before, common rating, and lifetime best/worst rating. The following are examples of a few common ratings: anxiety, 3; mood, 7; back pain, 0. Wake-up status was rated as bad (–10); neutral (0); or good (10). Comments were noted as needed. Mr A’s symptoms manifested in screaming, hitting himself, and jumping prone onto the floor, while his worst two attacks were accompanied with amnesia. A minor criminal violation deepened his concern about his condition. At age 32 he was started on 100 mg imipramine to treat what appeared to be panic disorder. Shortly after an increase of the imipramine dosage to 150 mg at age 35 he was hospitalized with imipramine-induced mania (flight of thoughts, religious grandiosity, and impaired judgment). No manic episode followed and with the exception of a bipolar depression after the manic episode, Mr A had no signs of clinical depression. His electroencephalogram (EEG) showed mildly diffused slow-ins without epileptiform activity; and his head magnetic resonance image was unremarkable. He had no alcohol or substance abuse problem. IED was diagnosed at age 36. The diagnosis was based on

Clinical Approaches in Bipolar Disorders 2005; 4: 43–45