| Autor: |
Taylor A Braund, May The Zin, Tjeerd W Boonstra, Quincy J J Wong, Mark E Larsen, Helen Christensen, Gabriel Tillman, Bridianne O’Dea |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
JMIR Mental Health, Vol 9, Iss 5, p e35549 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2368-7959 |
| DOI: |
10.2196/35549 |
| Popis: |
BackgroundMood 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. ObjectiveUsing smartphone sensor data, this study investigated the relationship between circadian rhythm, which was determined by GPS data, and symptoms of mental health among a clinical sample of adults diagnosed with major depressive disorder or bipolar disorder. MethodsA total of 121 participants were recruited from a clinical setting to take part in a 10-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at 6 time points throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (ie, regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline. ResultsAlthough 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 networks at baseline (r=0.22; P=.03; R2=0.049). In participants with bipolar disorder, circadian rhythm was associated with a change in anxiety from baseline; a higher circadian rhythm was associated with an increase in anxiety and a lower circadian rhythm was associated with a decrease in anxiety at time point 5. ConclusionsCircadian rhythm, which was 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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