Developing prediction algorithms for late-life depression using wearable devices: a cohort study protocol

• Published in: BMJ open Vol. 14; no. 6; p. e073290
• Main Authors: Lee, Jin-kyung, Kim, Min-Hyuk, Hwang, Sangwon, Lee, Kyoung-Joung, Park, Ji Young, Shin, Taeksoo, Lim, Hyo-Sang, Urtnasan, Erdenebayar, Chung, Moo-Kwon, Lee, Jinhee
• Format: Journal Article
• Language: English
• Published: England British Medical Journal Publishing Group 13.06.2024; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Protocol
• Subjects: Aged; Aged, 80 and over; aging; Algorithms; Chronic illnesses; Cohort analysis; Cohort Studies; Data collection; depression & mood disorders; Depressive Disorder, Major - diagnosis; Depressive Disorder, Major - epidemiology; Exercise; Female; health informatics; Humans; Interviews; Machine Learning; Male; Mental depression; Mental disorders; Mental Health; Mortality; Older people; Population; Republic of Korea - epidemiology; Research Design; Smartphones; Smartwatches; Substance abuse treatment; Wearable computers; Wearable Electronic Devices; Republic of Korea; South Korea; health informatics; aging; depression & mood disorders; mental health
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2023-073290

IntroductionDespite the high prevalence of major depressive disorder (MDD) among the elderly population, the rate of treatment is low due to stigmas and barriers to medical access. Wearable devices such as smartphones and smartwatches can help to screen MDD symptoms earlier in a natural setting while forgoing these concerns. However, previous research using wearable devices has mostly targeted the younger population. By collecting longitudinal data using wearable devices from the elderly population, this research aims to produce prediction algorithms for late-life depression and to develop strategies that strengthen medical access in community care systems.Methods and analysisThe current cohort study recruited a subsample of 685 elderly people from the Korean Genome and Epidemiology Study—Cardiovascular Disease Association Study, a national large cohort established in 2004. The current study has been conducted over a 3-year period to explore the development patterns of late-life depression. Participants have completed three annual face-to-face interviews (baseline, the first follow-up and the second follow-up) and 2 years of app-based surveys and passive sensing data collection. All the data collection will end at the second follow-up interview. The collected self-report, observational and passive sensing data will be primarily analysed by machine learning.Ethics and disseminationThis study protocol has been reviewed and approved by the Yonsei University Mirae Campus Institutional Review Board (1041849–2 02 111 SB-180-06) in South Korea. All participants provided written informed consent. The findings of this research will be disseminated by academic publications and conference presentations.