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

Reviews in Digital Mental Health (289) Artificial Intelligence (2128) Machine Learning (2075) Natural Language Processing (917) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) Users' and Patients' Needs for Mental Health Services (502)

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 (29) 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
  4. Wu W, Zuo E, Zhang W, Meng X. Multi-physiological signal fusion for objective emotion recognition in educational human–computer interaction. Frontiers in Public Health 2024;12 View
  5. Levkovich I, Rabin E, Brann M, Elyoseph Z. Large language models outperform general practitioners in identifying complex cases of childhood anxiety. DIGITAL HEALTH 2024;10 View
  6. Mosolova E, Alfimov A, Kostyukova E, Mosolov S. Prospects of machine learning applications in affective disorders. Digital Diagnostics 2025;6(1):97 View
  7. Rony M, Das D, Khatun M, Ferdousi S, Akter M, Khatun M, Begum M, Khalil M, Parvin M, Alrazeeni D, Akter F. Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy. DIGITAL HEALTH 2025;11 View
  8. Gülırmak Güler K, Albayrak Günday E. Hemşirelik Öğrencilerinin Psikiyatri Hemşireliğinde Yapay Zekâ Kullanımına Yönelik Algı, Beklenti Ve Endişelerinin Derinlemesine İncelenmesi: Nitel Çalışma. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi 2025;14(1):214 View
  9. Zhang X, Berry N, Di Basilio D, Richardson C, Eisner E, Bucci S. Mental Health Professionals’ Technology Usage and Attitudes Toward Digital Health for Psychosis: Comparative Cross-Sectional Survey Study. JMIR Mental Health 2025;12:e68362 View
  10. Anaduaka U, Oladosu A, Katsande S, Frempong C, Awuku-Amador S. Leveraging artificial intelligence in the prediction, diagnosis and treatment of depression and anxiety among perinatal women in low- and middle-income countries: a systematic review. BMJ Mental Health 2025;28(1):e301445 View
  11. Ball H, Eisner E, Ainsworth J, Bagg E, Beattie L, Cella M, Chalmers N, Clifford S, Drake R, Faulkner S, Greenwood K, Gumley A, Haddock G, Kendall K, Kenny A, Lees J, Lewis S, Maclean L, Nicholas J, O’Hare K, Oluwatayo A, Punchihewa S, Richardson C, Richardson L, Schwannauer M, Sherborne J, Turner R, Vogel E, Walters J, Warner A, Wilson P, Wykes T, Zahid U, Zhang X, Bucci S. Mental Health Professionals’ Perspectives on Digital Remote Monitoring in Services for People with Psychosis. Schizophrenia Bulletin 2025 View
  12. McKenna S, Chong M, Poulsen A, Turner A, Gorban C, Crouse J, Capon W, Varidel M, Aji M, Scott E, Hickie I, Iorfino F. Weighing Costs and Benefits of Delay and the Acceptance of Two Decision Support Tools in Mental Health Care: Scoping Study Using Quantitative and Qualitative Data. JMIR Human Factors 2025;12:e71678 View
  13. Rech H, Vitta A, Freires E, Semolini F, Silva L. Aplicações da Inteligência Artificial (IA) na Regulação Emocional (RE): Uma Revisão Integrativa. Cuadernos de Educación y Desarrollo 2025;17(6):e8542 View
  14. Semenova N, Martynyuk K. Classification of risks of using artificial intelligence systems in the field of mental health. Медицинская этика 2025;(2025(2)) View
  15. Antonini A, Coşar S, Naja I, Haleem M, Macdonald J, Innominato P, Barresi G. Smartphone as a Sensor in mHealth: Narrative Overview, SWOT Analysis, and Proposal of Mobile Biomarkers. Sensors 2025;25(12):3655 View
  16. Zhang X, Eisner E, Di Basilio D, Richardson C, Firth J, Bucci S. Healthcare professionals’ views on implementing digital health tools in psychosis: a national survey in the UK. BMJ Digital Health & AI 2025;1(1):e000005 View
  17. Zhang W, Zhang Q, Wang P, Zhou X, Wu Y. The application of Generative Artificial Intelligence in mental health care: A bibliometric and visualized analysis. Asian Journal of Psychiatry 2025;110:104596 View
  18. Tuncer G, Çetinkaya Duman Z. The Exploration of Psychiatric Nurses' Perspectives on the Applications of Artificial Intelligence in Supporting Care: ‘Patients Prefer Seeing a Human Over AI’. Journal of Psychiatric and Mental Health Nursing 2025;32(5):1053 View
  19. Shen S, Qi W, Zeng J, Li S, Liu X, Zhu X, Dong C, Wang B, Shi Y, Yao J, Wang B, Lou X, Gu S, Li P, Wang J, Jiang G, Cao S. Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review. Journal of Medical Internet Research 2025;27:e77066 View
  20. Goldie J, Dennis S, Hipgrave L, Coleman A. Practitioner Perspectives on the Uses of Generative AI Chatbots in Mental Health Care: Mixed Methods Study. JMIR Human Factors 2025;12:e71065 View
  21. Yıldız E. Ethical Big Data for Personalised Mental Health Nursing: A P4 and Systems View. Journal of Psychiatric and Mental Health Nursing 2025;32(6):1404 View
  22. Martin C, Wittkowski A, Agass R, Camacho E, Falana A, Hale R, Hann M, Ifezue A, Lemetyinen H, Lewis S, Myers H, Nicholas J, Stockton-Powdrell C, Tower C, Watson K, Whelan P, Eisner E. Digital screening for postnatal depression: A qualitative study and framework analysis exploring the views of healthcare professionals. SSM - Mental Health 2025;8:100549 View
  23. Yeasmin S, Saha S, Khan Rony M, Akter Semi M, Das S, Rahman R, Khan R, Tasnim A, Hosen A. The role of AI-driven art therapy in supporting autism, mental health, and emotional well-being: An umbrella review. DIGITAL HEALTH 2025;11 View
  24. Bucci S, Zhang X, Di Basilio D, Berry N, Berry K, Edge D, Haddock G. Clinicians’ experience of a digital intervention for psychosis in the context of a randomised controlled trial: a qualitative study. Psychosis 2025:1 View

Books/Policy Documents

  1. Menon V. Chatbots and Mental Healthcare in Psychology and Psychiatry. View
  2. Buzila E, Gil F. Digital Maturity in Hospitals. View
  3. Alqaidoom M, Ateeq A, Aljazrawi Z. Sustainable Data Management. View
  4. Efthymiou E, Katsarou D, Sofologi M, Megari K, Papadopoulou S, Mantsos E, Argyriadis A, Argyriadi A. AI in Learning, Educational Leadership, and Special Education. View

Conference Proceedings

  1. Azam U, Razzak I, Vishwakarma S, Hacid H, Zhang D, Jameel S. Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining. BAKER: Bayesian Kernel Uncertainty in Domain-Specific Document Modelling View