NDLI: Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study

Content Provider	Springer Nature : BioMed Central
Author	Cecil, Julia Kleine, Anne-Kathrin Lermer, Eva Gaube, Susanne
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.
Related Links	https://bmchealthservres.biomedcentral.com/counter/pdf/10.1186/s12913-025-12715-8.pdf
Ending Page	18
Page Count	18
Starting Page	1
File Format	HTM / HTML
ISSN	14726963
DOI	10.1186/s12913-025-12715-8
Journal	BMC Health Services Research
Issue Number	1
Volume Number	25
Language	English
Publisher	BioMed Central
Publisher Date	2025-04-16
Access Restriction	Open
Subject Keyword	Public Health Health Administration Health Informatics Nursing Research Mental healthcare Artificial intelligence Technology implementation Use intention Learning intention
Content Type	Text
Resource Type	Article
Subject	Health Policy

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Assistive technologies in healthcare: utilization and healthcare workers perceptions in Germany

The role of champions in the implementation of technology in healthcare services: a systematic mixed studies review

Women's perspectives on the use of artificial intelligence (AI)-based technologies in mental healthcare.

Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden

Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

Mixed-methods evaluation of mental healthcare integration into tuberculosis and maternal-child healthcare services of four South African districts

Patient perceptions and predictors of intention to use telehealth for follow-up care: a mixed methods study among adults living with HIV in Kampala, Uganda

Innovation in healthcare: leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden

Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study

Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study

Similar Documents

Assistive technologies in healthcare: utilization and healthcare workers perceptions in Germany

The role of champions in the implementation of technology in healthcare services: a systematic mixed studies review

Women's perspectives on the use of artificial intelligence (AI)-based technologies in mental healthcare.

Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden

Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

Mixed-methods evaluation of mental healthcare integration into tuberculosis and maternal-child healthcare services of four South African districts

Patient perceptions and predictors of intention to use telehealth for follow-up care: a mixed methods study among adults living with HIV in Kampala, Uganda

Innovation in healthcare: leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden

Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study

Mental health practitioners’ perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study