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

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Bibliographic Details
Title: Predicting stress in first-year college students using sleep data from wearable devices.
Authors: Bloomfield LSP; Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America.; Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America.; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., Fudolig MI; Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America.; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., Kim J; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., Llorin J; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., Lovato JL; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., McGinnis EW; Department of Social Science and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America.; Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America., McGinnis RS; Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America.; Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America., Price M; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America.; Department of Psychological Science, University of Vermont, Burlington, Vermont, United States of America., Ricketts TH; Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America.; Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, Vermont, United States of America., Dodds PS; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America.; Department of Computer Science, University of Vermont, Burlington, Vermont, United States of America., Stanton K; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America., Danforth CM; Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America.; Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America.; Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America.
Source: PLOS digital health [PLOS Digit Health] 2024 Apr 11; Vol. 3 (4), pp. e0000473. Date of Electronic Publication: 2024 Apr 11 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: PLOS Country of Publication: United States NLM ID: 9918335064206676 Publication Model: eCollection Cited Medium: Internet ISSN: 2767-3170 (Electronic) Linking ISSN: 27673170 NLM ISO Abbreviation: PLOS Digit Health Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2767-3170
DOI:10.1371/journal.pdig.0000473