Predicting stress in first-year college students using sleep data from wearable devices.

Autor: Laura S P Bloomfield, Mikaela I Fudolig, Julia Kim, Jordan Llorin, Juniper L Lovato, Ellen W McGinnis, Ryan S McGinnis, Matt Price, Taylor H Ricketts, Peter Sheridan Dodds, Kathryn Stanton, Christopher M Danforth
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: PLOS Digital Health, Vol 3, Iss 4, p e0000473 (2024)
Druh dokumentu: article
ISSN: 2767-3170
DOI: 10.1371/journal.pdig.0000473&type=printable
Popis: Consumer wearables have been successful at measuring sleep and may be useful in predicting changes in mental health measures such as stress. A key challenge remains in quantifying the relationship between sleep measures associated with physiologic stress and a user's experience of stress. Students from a public university enrolled in the Lived Experiences Measured Using Rings Study (LEMURS) provided continuous biometric data and answered weekly surveys during their first semester of college between October-December 2022. We analyzed weekly associations between estimated sleep measures and perceived stress for participants (N = 525). Through mixed-effects regression models, we identified consistent associations between perceived stress scores and average nightly total sleep time (TST), resting heart rate (RHR), heart rate variability (HRV), and respiratory rate (ARR). These effects persisted after controlling for gender and week of the semester. Specifically, for every additional hour of TST, the odds of experiencing moderate-to-high stress decreased by 0.617 or by 38.3% (p
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