Cecil, Julia;
Kleine, Anne-Kathrin;
Lermer, Eva;
Gaube, Susanne;
(2025)
Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study.
BMC Health Services Research
, 25
, Article 556. 10.1186/s12913-025-12715-8.
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Abstract
BACKGROUND: As mental health disorders continue to surge, exceeding the capacity of available therapeutic resources, the emergence of technologies enabled by artificial intelligence (AI) offers promising solutions for supporting and delivering patient care. However, there is limited research on mental health practitioners' understanding, familiarity, and adoption intentions regarding these AI technologies. We, therefore, examined to what extent practitioners' characteristics are associated with their learning and use intentions of AI technologies in four application domains (diagnostics, treatment, feedback, and practice management). These characteristics include medical AI readiness with its subdimensions, AI anxiety with its subdimensions, technology self-efficacy, affinity for technology interaction, and professional identification. METHODS: Mixed-methods data from N = 392 German and US practitioners, encompassing psychotherapists (in training), psychiatrists, and clinical psychologists, was analyzed. A deductive thematic approach was employed to evaluate mental health practitioners' understanding and familiarity with AI technologies. Additionally, structural equation modeling (SEM) was used to examine the relationship between practitioners' characteristics and their adoption intentions for different technologies. RESULTS: Qualitative analysis unveiled a substantial gap in familiarity with AI applications in mental healthcare among practitioners. While some practitioner characteristics were only associated with specific AI application areas (e.g., cognitive readiness with learning intentions for feedback tools), we found that learning intention, ethical knowledge, and affinity for technology interaction were relevant across all four application areas, underscoring their relevance in the adoption of AI technologies in mental healthcare. CONCLUSION: In conclusion, this pre-registered study underscores the importance of recognizing the interplay between diverse factors for training opportunities and consequently, a streamlined implementation of AI-enabled technologies in mental healthcare.
| Type: | Article |
|---|---|
| Title: | Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s12913-025-12715-8 |
| Publisher version: | https://doi.org/10.1186/s12913-025-12715-8 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. |
| Keywords: | Artificial intelligence, Learning intention, Mental healthcare, Technology implementation, Use intention, Humans, Artificial Intelligence, Male, Female, Adult, Attitude of Health Personnel, United States, Middle Aged, Germany, Intention, Mental Health Services, Qualitative Research, Mental Disorders, Psychiatry, Psychotherapists |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10207700 |
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