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Longitudinal Digital Mood Charting in Bipolar Disorder: Experiences with ChronoRecord Over 20 Years

Bauer, Michael; Glenn, Tasha; Alda, Martin; Grof, Paul; Bauer, Rita; Ebner-Priemer, Ulrich W. 1; Ehrlich, Stefan; Pfennig, Andrea; Pilhatsch, Maximilian; Rasgon, Natalie; Whybrow, Peter C.
1 Institut für Sport und Sportwissenschaft (IfSS), Karlsruher Institut für Technologie (KIT)

Abstract:

Introduction: Longitudinal study is an essential methodology for understanding disease trajectories, treatment effects, symptom changes, and long-term outcomes of affective disorders. Daily self-charting of mood and other illness-related variables is a commonly recommended intervention. With the widespread acceptance of home computers in the early 2000s, automated tools were developed for patient mood charting, such as ChronoRecord, a software validated by patients with bipolar disorder. The purpose of this study was to summarize the daily mood, sleep, and medication data collected with ChronoRecord, and highlight some of the key research findings. Lessons learned from implementing a computerized tool for patient self-reporting are also discussed.
Methods: After a brief training session, ChronoRecord software for daily mood charting was installed on a home computer and used by 609 patients with affective disorders.
Results: The mean age of the patients was 40.3±11.8 years, a mean age of onset was 22±11.2 years, and 71.4% were female. Patients were euthymic for 70.8% of days, 15.1% had mild depression, 6.6% had severe depression, 6.6% had hypomania, and 0.8% had mania. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000162440
Veröffentlicht am 21.09.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Sport und Sportwissenschaft (IfSS)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2023
Sprache Englisch
Identifikator ISSN: 1439-0795, 0176-3679, 0031-7098, 0720-4280
KITopen-ID: 1000162440
Erschienen in Pharmacopsychiatry
Verlag Thieme Gruppe
Band 56
Heft 05
Seiten 182 – 187
Vorab online veröffentlicht am 07.09.2023
Schlagwörter affective disorders, bipolar disorder, longitudinal tracking, digital mood charting
Nachgewiesen in Scopus
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Web of Science
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