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This paper is in the following e-collection/theme issue:

mHealth for Wellness, Behavior Change and Prevention (4197) Substance Abuse (649) Alcohol Abuse, Alcoholism Prevention and Recovery (377) Wearable Devices and Sensors (1520) Machine Learning (3043) Digital Biomarkers and Digital Phenotyping (419)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/88223, first published .
Woman with smartwatch drinks juice, checking health data on her wrist.

Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study

Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study

Authors of this article:

Jae Seok Kwak1 Author Orcid Image ;   Hae Kook Lee2 Author Orcid Image ;   Sun-Jin Jo3 Author Orcid Image ;   Jun Hyuk Kwon4 Author Orcid Image ;   Sun Jung Kwon5 Author Orcid Image ;   Yena Kim5 Author Orcid Image ;   Haejung Lee6 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jae Seok Kwak   1 * , PhD ;   Hae Kook Lee   2 * , MD, PhD ;   Sun-Jin Jo   3 * , PhD ;   Jun Hyuk Kwon   4 * , BE ;   Sun Jung Kwon   5 * , PhD ;   Yena Kim   5 * , PhD ;   Haejung Lee   6 * , MSc

1 Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seocho-gu, Seoul, Republic of Korea

2 Department of Psychiatry, The Catholic University of Korea Uijeongbu St. Mary's Hospital, Uijeongbu, Gyeonggi-do, Republic of Korea

3 Department of Addiction Studies, Graduate School, The Catholic University of Korea, Bucheon-si, Gyeonggi-do, Republic of Korea

4 Department of Industrial Engineering, Kongju National University, Cheonan, Chungcheongnam-do, Republic of Korea

5 Department of Counseling Psychology, Korea Baptist Theological University and Seminary, Yuseong-gu, Daejeon, Republic of Korea

6 AI Healthcare Division, PCN, Gangnam-gu, Seoul, Republic of Korea

*all authors contributed equally

Corresponding Author:

  • Hae Kook Lee, MD, PhD
  • Department of Psychiatry
  • The Catholic University of Korea Uijeongbu St. Mary's Hospital
  • 65-1, Geumo-Dong
  • Uijeongbu, Gyeonggi-do 11765
  • Republic of Korea
  • Phone: 82 318203050
  • Email: nplhk@catholic.ac.kr