Evidence map›Paper›PMID 37678394›Full record

ArticlePharmacopsychiatry2023

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

Michael Bauer, Tasha Glenn, Martin Alda, Paul Grof, Rita Bauer, Ulrich W Ebner-Priemer, Stefan Ehrlich, Andrea Pfennig, Maximilian Pilhatsch, Natalie Rasgon and 1 more

Abstract read
In one paragraph

Article in Pharmacopsychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Michael BauerDepartment of Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Tasha GlennChronoRecord Association Inc., Fullerton, CA, USA, www.chronorecord.org.
Martin AldaDepartment of Psychiatry, Dalhousie University, Halifax, NS, Canada.
Paul GrofDepartment of Psychiatry, University of Toronto, ON, Canada (retired) and Mood Disorders Center of Ottawa, Ottawa, Canada.
Rita BauerDepartment of Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Ulrich W Ebner-PriemerKarlsruhe Institute of Technology, Institute of Sports and Sports Science, Karlsruhe, Germany.
Stefan EhrlichDivision of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Andrea PfennigDepartment of Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Maximilian PilhatschDepartment of Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Natalie RasgonDepartment of Psychiatry and Biobehavioral Sciences, Stanford School of Medicine, Palo Alto, CA, USA.
Peter C WhybrowDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLongitudinal 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.

methodsAfter a brief training session, ChronoRecord software for daily mood charting was installed on a home computer and used by 609 patients with affective disorders.

resultsThe 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. Among all mood groups, 22.4% took 1-2 medications, 37.2% took 3-4 medications, 25.7 took 5-6 medications, 11.6% took 7-8 medications, and 3.1% took >8 medications.

conclusionThe daily mood charting tool is a useful tool for increasing patient involvement in their care, providing detailed patient data to the physician, and increasing understanding of the course of illness. Longitudinal data from patient mood charting was helpful in both clinical and research settings.

Indexed as

Bipolar DisorderDepressive DisorderAdolescentAdultChildFemaleHumansLongitudinal StudiesMaleManiaMiddle AgedMood DisordersYoung Adult

Identifiers

PMID37678394
PMCPMC10484643

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.