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Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Identifying Mood Instability and Circadian Rest-Activity Patterns Using Digital Remote Monitoring and Actigraphy in
Priyanka Panchal1, Natalie Nelissen2, Niall M McGowan1
1Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.
Bipolar Disorders
|July 17, 2026
Summary
Digital devices can track mood instability and circadian rhythms in individuals at high risk for bipolar disorder (BD). High-risk individuals show more mood instability, but it is not linked to circadian patterns.
Area of Science:
- Psychiatry
- Digital Health
- Chronobiology
Background:
- Mood instability and circadian rhythm disruptions are recognized in psychiatric disorders like bipolar disorder (BD).
- The interrelationship between mood instability and circadian rhythms in BD requires further investigation.
- Longitudinal and remote monitoring methods are desirable for studying these temporal phenomena.
Purpose of the Study:
- To assess the feasibility and value of digital devices for capturing mood/affective instability and rest-activity patterns.
- To compare individuals with high versus low risk for BD based on Mood Disorder Questionnaire (MDQ) scores.
- To explore the relationship between mood instability and circadian activity profiles.
Main Methods:
- A 10-week study involving two groups: high MDQ score (n=37) and low MDQ score (n=37).
- Daily mood ratings, weekly clinical assessments (depression, mania, anxiety), and GENEActiv actigraphy for rest-activity patterns.
- Feasibility and value of digital monitoring for mood and circadian data were assessed.
Main Results:
- MDQ score predicted mood and subjective state instability.
- High MDQ participants exhibited greater negative affect, mood symptoms, and altered circadian activity compared to low MDQ.
- Mood and subjective state instability were not found to be related to circadian indices.
Conclusions:
- Remote monitoring of mood and circadian patterns is feasible and valuable.
- Using MDQ scores for participant selection is effective for studying mood and affective instability.
- This approach holds potential for clinical trials targeting mood dysregulation and affective instability.
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