ASPOFAFF :: Journal - Volume 1 :: Issue 2 :: Vol 1 - Iss 2 - Article - New Computer Based Tool for the Longitudinal Study of Bipolar Disorder


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ASPOFAFF :: Journal - Volume 1 :: Issue 2 :: Vol 1 - Iss 2 - Article - New Computer Based Tool for the Longitudinal Study of Bipolar Disorder

Vol 1 - Iss 2 - Article - New Computer Based Tool for the Longitudinal Study of Bipolar Disorder #11

New Computer Based Tool for the Longitudinal Study of Bipolar Disorder Michael Bauer 1, Paul Grof 2, Natalie Rasgon 3, Laszlo Gyulai 4, Tasha Glenn 5, Peter C Whybrow 6 1Department of Psychiatry and Psychotherapy, Charité - University Medicine Berlin, Campus Charité-Mitte (CCM), Germany, 2 Department of Psychiatry, University of Ottawa, Royal Ottawa Hospital, Ottawa, Canada, 3 Department of Psychiatry, Stanford School of Medicine, Palo Alto, CA, USA, 4 Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA, 5 ChronoRecord Association, Inc., Fullerton, CA, USA, www.chronorecord.org, 6 Neuropsychiatric Institute & Hospital, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles (UCLA), Los Angeles, CA, USA Correspondence and requests for reprints should be addressed to: Michael Bauer, M.D., Ph.D. Professor of Psychiatry Department of Psychiatry and Psychotherapy Charité - University Medicine Berlin Campus Charité-Mitte (CCM) Schumannstr. 20/21 10117 Berlin Germany Tel: +49–30– 450 51 70 70 Fax: +49-30-450-51 79 62 Email: michael.bauer@charite.de Abstract Bipolar disorder is episodic and recurrent with a high degree of inter-individual variation and heterogeneity between patients. Longitudinal studies are an optimal approach to investigating the highly variable course of bipolar disorder, but are expensive and often have a significant amount of missing data. The tools used for daily self-assessment in longitudinal studies of mood disorders are traditionally paper based. This article describes our experience with the development, validation and use of an automated instrument to incorporate technology for long term mood charting. ChronoRecord is software that patients install on a home computer to report mood, medications, sleep, life events, weight and menstrual data. Patients with bipolar disorder showed high acceptance of this computerized approach with 80 of 96 (83%) entering 8662 days of data for a 3-month period during the validation study (mean of 114.7 ± 32.3 SD days). The mean percent of days missing for mood data was 6.1% ± 9.3 SD, equivalent to missing 7.3 day out of the 114.7 days. The widespread acceptance of computer technology by the general public can be leveraged to improve the design of longitudinal studies. Automation of long-term data collection can reduce missing data, eliminate errors associated with data entry, provide ongoing feedback for patients and clinicians and allow the use of interim data for clinical decision support. Key Words: Longitudinal studies, methodology, self-reporting, technology Download the Article for FREE

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