Research – Published in the Pendulum, Autumn 2003 Issue – The Magazine of the MDF the Bipolar Organisation
Yanni G. Malliaris
Reporting Live from the Bipolar Research Trenches: Life-Chartingtm
Life-Charting: Methodological advances in Bipolar disorder Over the last years we are observing an explosion of research in Bipolar disorder. It is as if we were in a state of Bipolar depression and currently we are experiencing a “manic switch”, which feeds the progress of Bipolar research in all fronts. Gone are the days where Jan Scott1 was complaining about the lack of psychosocial research and the availability of psychological treatments in Bipolar disorders. Amanda’s article2 on the concept of the Bipolar spectrum represents progress on the diagnostic front. But as we are striving to better understand the phenomenology of Manic-Depression, we are also in need of better tools that will help us in our quest to do so. On the methodology front, we are seeing the development and systematic use of methodologies that listen to the name of Life-charting. What all these tools have in common is their goal to graph systematically over time a number of critical variables of Bipolar disorder – the Fantastic 4 include: 1. Episodes, 2. Mood changes (switches), 3. Mood severity, and 4. Sleep. Other variables include medication, life events, social functioning, weight, menstrual cycle and in general whatever else is important to address the research questions at hand. Although the idea of keeping an eye on the course of Bipolar disorder is credited to Emil Kraepelin3, the “infamous” German psychiatrist who made the distinction between Schizophrenia and Manic Depressive illness, the utility of this method should have become apparent to the first homo-sapiens who experienced a manic episode and felt that there is something recurrent about this condition – illness insight permitting! ☺ Currently two validated tools exist and are available for use mainly by researchers but also soon by both consumers and practicing clinicians*. The first tool was developed by researchers at the National Institute of Mental Health (NIMH) and bears the name of LifeCharting (NIMH-LCM)3. The second tool was developed by researchers at UCLA and is called ChronoRecord4. Both systems have begun to be used fruitfully mainly in studies aiming to understand the effects and treatment response of different medications on Bipolar disorder. For example one study5 that used the NIMH Life-charting method, shed some important light on the much debated phenomenon of anti-depressant induced mania. Analysis of the lifecharting data of 42 Depressed Bipolars revealed that anti-depressant medication was more likely to lead to manic switches, if before their current depressed episode they were hypomanic or manic. However, if before they became depressed were in a normal (euthymic) mood state, then anti-depressant medication was more helpful as it was less likely to lead to mania. Unfortunately, the small number of participants did not permit to examine the effects of specific drugs. Yet, in another study6, using the ChronoRecord system this time, researchers revealed some interesting gender differences in Bipolar disorder. Although Bipolar disorder is known to have almost equal prevalence rates in both males and females, both the course and the expression of the disorder seem to be different across the two genders. In this study, 80 participants recruited from the mood disorder clinics at UCLA, Ottawa, and Pennsylvania * the ChronoRecord system is currently being adapted and piloted for use in UK at the Affective Disorders Unit, Institute of Psychiatry – once it is ready it will become freely available to MDF members who wish to participate in research, and to any interested practicing clinicians.
universities were given the ChronoRecord system to use at their homes. The participants were successful in using the system for 3 continuous months, an endeavour which generated 8662 days of data! Although both men and women were most of the time in a well state (79.6% vs 67%), an effect which the authors attributed to medication compliance, interesting differences emerged in the amount of time spent in depression, the severity of symptoms reported, and the mood fluctuations. Women spent significantly more time being depressed (24.8% vs 15.9%), had mood fluctuations twice as often as men, and reported much more severe depressive (17.1% vs. 10.9%) and manic symptoms (18.7% vs. 3.2%). This project is ongoing, and as more participants join and more days of data are gathered, we will learn much more about both gender differences, medication effects and the role of other interesting variables that might affect the development and course of manic depression. Some of you may have already noticed my frequent use of the word “more”. Indeed, this illustrates the power of this approach, which lies on volume and quantity of data to tackle the issues at hand. Nevertheless, an apparent logical caveat of these life charting methodologies is that they can be extremely labour intensive. Again gone are the days were a researcher would be daunted and tortured by the prospect of having to collect and to analyze just one-shot measures. Imagine having to collect data on a number of variables on a daily basis for a number of months or years! However, both the technology itself and most importantly the consumers themselves can come to the rescue of such “feeble minded” researchers. The ChonoRecord system3,7 , mentioned in the previous study, is a computerised version of the Life-charting method* and has been developed for use by the consumers themselves. The system is simple and neat and takes only 2 minutes to complete. Its utility becomes even more apparent by the fact that it can analyse the data and produce graphs that illustrate both mood, sleep, and medications over time. These can be extremely helpful to the user who is interested to maintain a “manicdepressive hygiene”, to the treating therapist who is interested to see how the user responds to different treatments, and finally the researcher who strives to understand the variables that affect the course of the illness. Although there are many things that yet we do not know about the use of Life-charting methodologies (as for example their potential as a therapeutic self-management tool – if any) it is clearly evident that they promote User involvement in the research process. Close to that notion is also the goverments’ recent programme on the development of the “Expert patient” 8 – which is so clearly exemplified in MDF’s Self-management training programme9. Both of which are important developments worthy of discussion in another article. Another benefit of Life-charting methodologies is that they promote prospective research – that is research that looks at things over time. This sort of research is valuable because it can tell us about cause and effect relationships in a naturalistic way (ie. consistent lack of sleep leads to manic relapse and so forth). It can also help experimental research – that is research were cause and effect relationships are revealed by manipulating one set of variables and measuring another (ie. an evil researcher deprives a group of manic depressives of sleep and then measures manic relapses) – by giving to the researcher the ability to know when to test and under what conditions in an ecologically valid way. In closing, it is important to say that Life-charting is not a panacea neither the solution to all the problems faced by people with bipolar disorder, or to clinicians and researchers in the field. However, it is certainly a valuable addition in our arsenal. Intelligent and good use of Life-charting will help to unravel a number of interesting questions in bipolar disorder, which in turn will lead to the development of better and more effective treatment options. * Life-Charting is a trademark name of the NIMH-LCH method; The ChronoRecord system is based on the ChronoSheet – a slightly different Life-charting system than the NIMH-LCM method -- developed in 1975 by Peter Whybrow at UCLA.
Annotated References 1. Scott, J. (1995) Psychotherapy for bipolar disorder. British Journal of Psychiatry. 167, 581-588 -
Jan Scott complains about the lack of psychosocial research and treatments in BD
2. Harris, A. (2003). The Bipolar spectrum. Pendulum. Manic Depression Fellowship -
Amanda Harris presents the recents developments on the diagnosis of BD
3. Bipolar Network News (2002) Special Issue on Life-Charting. -
presents the NIMH-LCM method, its history and development as well as the different versions that are available. It also contains many more good ideas about the use and utility of Life-charting methodologies not discussed here.
4. ChronoRecord Assocation – http://www.chronorecord.org -
the official website of the ChronoRecord system; Contains a useful section explaining in detail the system.
5. MacQueen G.M. et al. (2002) Previous mood state predicts response and switch rates in patients with bipolar depression. Acta Psychiatrica Scandinavica. Vol. 105, 6, 414-418 (5) -
Study that examined the effects of anti-depressant medications on Bipolar depression using the NIMHLCM method
6. Ragson N. et al. (in press) Prospective studies of Bipolar disorder: Influence of Gender -
Study that examined the gender differences in Bipolar disorder using the ChronoRecord system
7. Bauer Michael et al. (2001) A new clinical and research tool for bipolar disorder: ChronoRecord software for daily self-reporting of mood, sleep, and medication. Bipolar disorders. Vol 3 (suppl 1): 26 -
Validation study of the ChronoRecord system
8. Department of Health, “Expert patient” programme – http://www.doh.gov.uk/cmo/progress/expertpatient/epp3.htm 9. Manic Depression Fellowship, Self-Management Training Programme – http://www.mdf.org.uk/services/smt.html
Figure 1. 180 Day Mood Chart From A 34 Year Old Woman With Bipolar I Disorder (source: Bauer et. al. in press, Using technology to improve longitudinal studies: self reporting in bipolar disorder) Weekly Weight
Daily Mood Rating
Life Event Indication Period Indication
Hours In Bed Awake Hours In Bed Asleep
Medication Legend Number
Drug Legend #1 Depakote (divalproex) 250 mg #2 Depakote (divalproex) 500 mg #3 Celexa (citalopram) 20 mg #4 Clonazepam 1.0 mg #5 Zyprexa (olanzapine) 2.5 mg #6 Zyprexa (olanzapine) 5 mg