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

Jae Seok Kwak, Hae Kook Lee, Sun-Jin Jo, Jun Hyuk Kwon, Sun Jung Kwon, Yena Kim, Haejung Lee

Open source

DOI
10.2196/88223
Published
2026-07-10
Container
JMIR mHealth and uHealth
Publisher
JMIR Publications Inc.
Open access
unknown

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BibTeX

@article{allodium:10.2196/88223,
  title = {Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study},
  author = {Jae Seok Kwak and Hae Kook Lee and Sun-Jin Jo and Jun Hyuk Kwon and Sun Jung Kwon and Yena Kim and Haejung Lee},
  year = {2026},
  journal = {JMIR mHealth and uHealth},
  doi = {10.2196/88223},
  url = {https://doi.org/10.2196/88223}
}

RIS

TY  - JOUR
TI  - Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study
AU  - Jae Seok Kwak
AU  - Hae Kook Lee
AU  - Sun-Jin Jo
AU  - Jun Hyuk Kwon
AU  - Sun Jung Kwon
AU  - Yena Kim
AU  - Haejung Lee
PY  - 2026
JO  - JMIR mHealth and uHealth
DO  - 10.2196/88223
UR  - https://doi.org/10.2196/88223
ER  - 

APA

Kwak, J. S., Lee, H. K., Jo, S., Kwon, J. H., Kwon, S. J., Kim, Y., & Lee, H. (2026). Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study. JMIR mHealth and uHealth. https://doi.org/10.2196/88223

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