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

Digital Biomarkers and Digital Phenotyping (284) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) Wearable Devices and Sensors (1133) mHealth for Wellness, Behavior Change and Prevention (3315) Mobile Devices and Apps for Seniors and Healthy Aging (265) Mental Health Issues in Elderly Patients and Geriatric Psychiatry (149) Internet of Things (98) Depression and Mood Disorders; Suicide Prevention (1691)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55842, first published .
Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study

Authors of this article:

Sunmi Song1, 2, 3 Author Orcid Image ;   YoungBin Seo4, 5 Author Orcid Image ;   SeoYeon Hwang3, 5 Author Orcid Image ;   Hae-Young Kim3, 4, 5, 6 Author Orcid Image ;   Junesun Kim1, 2, 3, 5 Author Orcid Image
Article Authors Cited by (12) Tweetations (3) Metrics

Journals

  1. Luo Y, Wang J, Gan G, Liu M, Lu Z, Jia S, Huang M, Wang S, Gan M, Xie J, Cheng A. Effectiveness of digital modified behavioral activation treatment program for rural older adults with depressive symptoms in Western Hunan: study protocol for a multi-center randomized controlled trial. BMC Psychology 2024;12(1) View
  2. Heckler W, Feijó L, de Carvalho J, Barbosa J. Digital phenotyping for mental health based on data analytics: A systematic literature review. Artificial Intelligence in Medicine 2025;163:103094 View
  3. Nejadshamsi S, Karami V, Ghourchian N, Armanfard N, Bergman H, Grad R, Wilchesky M, Khanassov V, Vedel I, Abbasgholizadeh Rahimi S. Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study. JMIR Aging 2025;8:e67715 View
  4. de Sousa R, Zagalo D, Costa T, de Almeida J, Canhão H, Rodrigues A. Exploring depression in adults over a decade: a review of longitudinal studies. BMC Psychiatry 2025;25(1) View
  5. Zakai J, Alharthi S. Harnessing Digital Phenotyping for Early Self-Detection of Psychological Distress. Healthcare 2025;13(16):2008 View
  6. Jung H, Kim D, Lee I, Kim O, Lee S, Lee S, Chung U, Kim J, Kim S, Kim J, Shin A, Lee J. Key Features of Digital Phenotyping for Monitoring Mental Disorders: Systematic Review. Journal of Medical Internet Research 2025;27:e77331 View
  7. Nalkar S, Chandak A. Telemedicine for specific populations: evaluating effectiveness and barriers in enhancing healthcare access and outcomes. Journal of Public Health 2025 View
  8. Zhang C, Lin L, Wang L, Hu H, Zhang H. The Double-Edged Sword of Digital Engagement—How Digital Access and Internet Use Reshape Sleep Schedules and Underlying Mechanisms in Older Adults: Longitudinal Observational Study. JMIR Aging 2025;8:e79731 View
  9. Gong X, Cheng Q, Wu Y, Wang S, Xu K, Qin L, He F, Cheng J. Influencing factors of depressive symptoms in middle-aged and elderly people and its regional differences in china: a study based on Bayesian network model. Journal of Health, Population and Nutrition 2025;44(1) View
  10. Alsalloum G, Dalibalta S, Hadijat Y. Harnessing digital health interventions to address the heterogeneity of depression: a systematic review. Frontiers in Digital Health 2025;7 View

Books/Policy Documents

  1. Thirupathi L, Kaashipaka V, Dhanaraju M, Katakam V. Intelligent Systems and IoT Applications in Clinical Health. View

Conference Proceedings

  1. Jin S, Kim B, Han K. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. "I Don't Know Why I Should Use This App": Holistic Analysis on User Engagement Challenges in Mobile Mental Health View