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

Reviews in Digital Mental Health (243) Artificial Intelligence (1371) Machine Learning (1465) Natural Language Processing (692) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1514) Users' and Patients' Needs for Mental Health Services (403)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49577, first published .
Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis

Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis

Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis

Authors of this article:

Jessica Rogan1, 2 Author Orcid Image ;   Sandra Bucci1, 2 Author Orcid Image ;   Joseph Firth1 Author Orcid Image
Article Authors Cited by (3) Tweetations (7) Metrics

Journals

  1. Bidargaddi N, Leibbrandt R, Paget T, Verjans J, Looi J, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. DIGITAL HEALTH 2024;10 View
  2. Hoose S, Králiková K. Artificial Intelligence in Mental Health Care: Management Implications, Ethical Challenges, and Policy Considerations. Administrative Sciences 2024;14(9):227 View
  3. Cormier M, Orr M, Kaser A, MacDonald H, Chorney J, Meier S. Sleep well, worry less: A co-design study for the development of the SMILE app. DIGITAL HEALTH 2024;10 View