Accepted for/Published in: JMIR Mental Health
Date Submitted: Dec 8, 2021
Date Accepted: Apr 4, 2022
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Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A longitudinal observational study
ABSTRACT
Background:
Mood disorders are burdensome illnesses that often go undetected and untreated. Sensor technologies within smartphones may provide an opportunity for identifying the early changes in circadian rhythm and social support/connectedness that signify the onset of a depressive or manic episode.
Objective:
Using smartphone sensor data, this study investigated the relationship between circadian rhythm, determined by Global Positioning Systems (GPS) data, and symptoms of mental health among a clinical sample of adults diagnosed with Major Depressive Disorder (MDD) or Bipolar Disorder (BD).
Methods:
A total of 121 participants were recruited from a clinical setting to take part in a ten-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at six timepoints throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (i.e., regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline.
Results:
While we found no association between circadian rhythm and mental health functioning at baseline, there was a positive association between circadian rhythm and the size of participants social support network at baseline (r = .22, p = .030, R2 = .049). In participants with BD, circadian rhythm was associated with change in anxiety from baseline, whereby higher circadian rhythm was associated with an increase in anxiety and lower circadian rhythm was associated with a decrease in anxiety at timepoint five.
Conclusions:
Circadian rhythm, extracted from smartphone GPS data, was associated with social support and predicted changes in anxiety in a clinical sample of adults with mood disorders. Larger studies are required for further validations. However, smartphone sensing may have the potential to monitor early symptoms of mood disorders.
Citation
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Copyright
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