TY  - JOUR
AU  - Ren, Benny
AU  - Xia, Cedric Huchuan
AU  - Gehrman, Philip
AU  - Barnett, Ian
AU  - Satterthwaite, Theodore
PY  - 2022
DA  - 2022/9/14
TI  - Measuring Daily Activity Rhythms in Young Adults at Risk of Affective Instability Using Passively Collected Smartphone Data: Observational Study
JO  - JMIR Form Res
SP  - e33890
VL  - 6
IS  - 9
KW  - mobile health
KW  - mHealth
KW  - hidden Markov model
KW  - mental health
KW  - circadian rhythm
KW  - mobile phone
AB  - Background: Irregularities in circadian rhythms have been associated with adverse health outcomes. The regularity of rhythms can be quantified using passively collected smartphone data to provide clinically relevant biomarkers of routine. Objective: This study aims to develop a metric to quantify the regularity of activity rhythms and explore the relationship between routine and mood, as well as demographic covariates, in an outpatient psychiatric cohort. Methods: Passively sensed smartphone data from a cohort of 38 young adults from the Penn or Children’s Hospital of Philadelphia Lifespan Brain Institute and Outpatient Psychiatry Clinic at the University of Pennsylvania were fitted with 2-state continuous-time hidden Markov models representing active and resting states. The regularity of routine was modeled as the hour-of-the-day random effects on the probability of state transition (ie, the association between the hour-of-the-day and state membership). A regularity score, Activity Rhythm Metric, was calculated from the continuous-time hidden Markov models and regressed on clinical and demographic covariates. Results: Regular activity rhythms were associated with longer sleep durations (P=.009), older age (P=.001), and mood (P=.049). Conclusions: Passively sensed Activity Rhythm Metrics are an alternative to existing metrics but do not require burdensome survey-based assessments. Low-burden, passively sensed metrics based on smartphone data are promising and scalable alternatives to traditional measurements. 
SN  - 2561-326X
UR  - https://formative.jmir.org/2022/9/e33890
UR  - https://doi.org/10.2196/33890
UR  - http://www.ncbi.nlm.nih.gov/pubmed/36103225
DO  - 10.2196/33890
ID  - info:doi/10.2196/33890
ER  -