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

Psychological, Behavioral, Social, and/or Cultural Experiments and Interventions (95) Artificial Intelligence (2129) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) Design, Usability, and Evaluation of Research Instruments, Scales, and Measures (85) Attitudes, Beliefs, and Health Behaviours in Human Factors Research (73)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46859, first published .
Attitudes Toward the Adoption of 2 Artificial Intelligence–Enabled Mental Health Tools Among Prospective Psychotherapists: Cross-sectional Study

Attitudes Toward the Adoption of 2 Artificial Intelligence–Enabled Mental Health Tools Among Prospective Psychotherapists: Cross-sectional Study

Attitudes Toward the Adoption of 2 Artificial Intelligence–Enabled Mental Health Tools Among Prospective Psychotherapists: Cross-sectional Study

Authors of this article:

Anne-Kathrin Kleine1 Author Orcid Image ;   Eesha Kokje1 Author Orcid Image ;   Eva Lermer1, 2 Author Orcid Image ;   Susanne Gaube1 Author Orcid Image
Article Authors Cited by (22) Tweetations (4) Metrics

Journals

  1. Huang A, Ozturk A, Zhang T, de la Mora Velasco E, Haney A. Unpacking AI for hospitality and tourism services: Exploring the role of perceived enjoyment on future use intentions. International Journal of Hospitality Management 2024;119:103693 View
  2. Roy M, Jamwal M, Vasudeva S, Singh M. Physicians behavioural intentions towards AI-based diabetes diagnostic interventions in India. Journal of Public Health 2025;33(12):2605 View
  3. Dingel J, Kleine A, Cecil J, Sigl A, Lermer E, Gaube S. Predictors of Health Care Practitioners’ Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology. Journal of Medical Internet Research 2024;26:e57224 View
  4. Hassan M, Kushniruk A, Borycki E. Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review. JMIR Human Factors 2024;11:e48633 View
  5. Kleine A, Schaffernak I, Lermer E. Exploring predictors of AI chatbot usage intensity among students: Within- and between-person relationships based on the technology acceptance model. Computers in Human Behavior: Artificial Humans 2025;3:100113 View
  6. Nelson J, Kaplan J, Simerly G, Nutter N, Edson-Heussi A, Woodham B, Broman-Fulks J. The balance and integration of artificial intelligence within cognitive behavioral therapy interventions. Current Psychology 2025;44(9):7847 View
  7. Bhuiyan M, Husain T, Islam S, Amin A. Exploring the prospective influence of artificial intelligence on the health sector in Bangladesh: a study on awareness, perception and adoption. Health Education 2025;125(3):279 View
  8. Creswell Báez J, Victor B, Dysart C, Goldkind L. “I Don’t Understand It, but Okay”: An Empirical Study of Mental Health Practitioners’ Readiness to Use Large Language Models. Journal of Technology in Human Services 2025;43(2):142 View
  9. Pérez-Sobrino P, Ibarretxe-Antuñano I. Firebreak, circuit break, or water break? The impact of metaphor on people’s perception and attitudes towards lockdown measures. Applied Linguistics 2025 View
  10. Cecil J, Kleine A, Lermer E, Gaube S. Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study. BMC Health Services Research 2025;25(1) View
  11. Fritz B, Eppelmann L, Edelmann A, Rohrmann S, Wessa M. How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis. BMC Psychology 2025;13(1) View
  12. Wagner J, Schwind A. Investigating psychotherapists’ attitudes towards artificial intelligence in psychotherapy. BMC Psychology 2025;13(1) View
  13. Lam T, Hu Y, Yi Y, Schulz P, Lwin M, Kee K, Goh W, Cheung M, Lee H, Fan A, Lam P, Lam S, Zhou L, Chen Y, Li F, Lau Y, Wu J, Chiu H, Xu H, Sung J. A Model Predicting Artificial Intelligence Use by Gastroenterology Nurses in Clinical Practice: A Cross‐Sectional Multicenter Survey. Journal of Gastroenterology and Hepatology 2025;40(9):2275 View
  14. 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
  15. 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
  16. Bewersdorff A, Nerdel C, Zhai X. How AI literacy correlates with affective, behavioral, cognitive and contextual variables: A systematic review. Computers and Education: Artificial Intelligence 2025;9:100493 View
  17. Winarto P, Nugroho E, Tadee P, Safira B. What factors drive digital marketing adoption among smallholder poultry egg farmers in Indonesia? A case study in Blitar Regency, East Java. Cogent Food & Agriculture 2025;11(1) View
  18. Hessel H, Hynes K, He Y, Gizzi S. A Framework for Ethical Considerations in the Integration of AI and Systemic Therapy. International Journal of Systemic Therapy 2025:1 View

Books/Policy Documents

  1. Vidanage K, Gunesekera A. Corporate Social Responsibility Approaches to Ethical AI in Business. View
  2. Menon V. Chatbots and Mental Healthcare in Psychology and Psychiatry. View
  3. Moyano M, Narváez J, Olmedo A, Guerrero G, Chiliquinga C. Advanced Research in Technologies, Information, Innovation and Sustainability. View

Conference Proceedings

  1. Yang Y, Viranda T, Van Meter A, Choudhury T, Adler D. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Exploring Opportunities to Augment Psychotherapy with Language Models View