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

Formative Evaluation of Digital Health Interventions (3606) Web-based and Mobile Health Interventions (4342) mHealth for Wellness, Behavior Change and Prevention (3507) Depression and Mood Disorders; Suicide Prevention (1805) Mobile Health in Psychiatry (564) Anxiety and Stress Disorders (1401)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51334, first published .
iPhone screen showing a mental health forecast app with daily activity and mood data.

mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial

mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial

Authors of this article:

Kazuhiro Watanabe1 Author Orcid Image ;   Shoichi Okusa2 Author Orcid Image ;   Mitsuhiro Sato3 Author Orcid Image ;   Hideki Miura4 Author Orcid Image ;   Masahiro Morimoto5 Author Orcid Image ;   Akizumi Tsutsumi1 Author Orcid Image
Article Authors Cited by (12) Tweetations (3) Metrics

Journals

  1. Ohta T, Osuka Y, Shida T, Daimaru K, Kojima N, Maruo K, Iizuka A, Kitago M, Fujiwara Y, Sasai H. Feasibility, Acceptability, and Potential Efficacy of a Mobile Health Application for Community-Dwelling Older Adults with Frailty and Pre-Frailty: A Pilot Study. Nutrients 2024;16(8):1181 View
  2. Santos L, Guimarães L, Soares A, Figueiredo J, Pimentel J, Oliveira A. Características das intervenções efetivas de exercício físico conduzidas no ambiente de trabalho: uma revisão de escopo. Revista Brasileira de Atividade Física & Saúde 2024;29:1 View
  3. WATANABE K. Promoting Physical Activity Among Workers for Better Mental Health: An mHealth Intervention With Deep Learning. Journal of UOEH 2024;46(1):119 View
  4. Watanabe K, Sato M, Okusa S, Tsutsumi A. Effectiveness and Implementation Outcomes of an mHealth App Aimed at Promoting Physical Activity and Improving Psychological Distress in the Workplace Setting: Cluster-Level Nonrandomized Controlled Trial. JMIR mHealth and uHealth 2025;13:e70473 View
  5. Leightley D, Williamson C, Korbacz A, Curcin V, Marshall I, Greenberg N. Effectiveness of AI-based interventions in workplace mental health: a systematic review and narrative synthesis. British Medical Bulletin 2026;157(1) View
  6. Yousefi F, Naye F, Ouellet S, Yameogo A, Sasseville M, Bergeron F, Ozkan M, Cousineau M, Amil S, Rhéaume C, Gagnon M. Artificial Intelligence in Health Promotion and Disease Reduction: Rapid Review. Journal of Medical Internet Research 2025;27:e70381 View
  7. Jiang L, Zhang J, Wong Y. Digital technology in occupational health of manufacturing industries: a systematic literature review. Discover Applied Sciences 2024;6(12) View
  8. Giebel G, Speckemeier C, Schrader N, Abels C, Plescher F, Hillerich V, Wiedemann D, Börchers K, Wasem J, Blase N, Neusser S. Quality assessment of mHealth apps: a scoping review. Frontiers in Health Services 2024;4 View
  9. Rahimi M, Abrishamifar K, Hazhir S, Valizadeh H, Nourani A, Rahimi B. Sensor‐Equipped Digital Technologies for Monitoring and Detecting Depressive Disorders: A Systematic Review. Health Science Reports 2026;9(3) View
  10. Baldwin T, Cadar D, Sigala N. Mobile apps to promote behavioural change in occupational settings: a systematic review and meta-analysis. BMC Digital Health 2026;4(1) View
  11. Morouço P, Ramadas E. Digital Physical Activity Interventions for Mental Health Promotion of and Reduction in Addictive Behaviors: Integrative Comprehensive Review with a Focus on Personalization and Implementation. International Journal of Environmental Research and Public Health 2026;23(6):703 View

Books/Policy Documents

  1. Prakash A, Malagatti D, Pai A, Damodar P. Transforming Organizational Culture Through Meta-Driven Human Resources. View