Korean longitudinal study on digitally optimized mental healthcare: a cohort profile
J. Lee1, J. Lee2, T. Kim3, T. Choi1
1School of Medicine, Catholic University of Daegu, Department of Psychiatry, Daegu, Korea, Republic of, 2College of Medicine, Dankook University, Department of Psychiatry, Cheonan 31116, Korea, Republic of, 3Yonsei University Wonju Severance Christian Hospital, Department of Psychiatry, Wonju, Korea, Republic of
Background: The Korean Longitudinal Study on Digitally Optimized Mental Healthcare (KLOSDOM) is an innovative multicenter trial-ready cohort study.
Aims & Objectives: It aims to develop a digitally integrated mental healthcare platform that integrates robots, artificial intelligence, and local community services.
Method: A total of 3,100 participants, including 1,000 from the previous Chungnam Province cohort and 700 of each from Chungnam, Gangwon, and Daegu, will be recruited between December 2024 and the end of 2025.
Sociodemographic factors and physical health data are collected at enrolment using questionnaires.
Every four months, formal tools are used to conduct psychiatric diagnoses and determine mental and physical health conditions, such as depression, anxiety, suicidality, stress, insomnia, and loneliness, quality of life, and disability.
We assessed smartphone overdependence at regular intervals.
Passive data on phone usage, life patterns, and health monitoring from smart band are collected in real time.
Weekly ecological momentary assessments monitor daily life and mood and detect risk situations early.
A subset of 500 participants engages in a Living Lab, collecting multi-modal data through robots and sleep radar sensors, while evaluating the usability and satisfaction with these devices.
Sociodemographic factors and physical health data are collected at enrolment using questionnaires.
Every four months, formal tools are used to conduct psychiatric diagnoses and determine mental and physical health conditions, such as depression, anxiety, suicidality, stress, insomnia, and loneliness, quality of life, and disability.
We assessed smartphone overdependence at regular intervals.
Passive data on phone usage, life patterns, and health monitoring from smart band are collected in real time.
Weekly ecological momentary assessments monitor daily life and mood and detect risk situations early.
A subset of 500 participants engages in a Living Lab, collecting multi-modal data through robots and sleep radar sensors, while evaluating the usability and satisfaction with these devices.
Results: This study will show how tailored digital applications and web-based platforms can facilitate personalized self-help interventions, enhance expert-user interaction, and promote active user engagement.
Discussion & Conclusions: This approach can potentially reduce stigma and improve public awareness of mental health care by shifting from a treatment-centered model to a community-based prevention framework.
In sessions