Asset Details
Do you wish to reserve the book?
Barriers and enablers for generative artificial intelligence in clinical psychology: a qualitative study based on the COM-B and theoretical domains framework (TDF) models
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Barriers and enablers for generative artificial intelligence in clinical psychology: a qualitative study based on the COM-B and theoretical domains framework (TDF) models
Do you wish to request the book?
Barriers and enablers for generative artificial intelligence in clinical psychology: a qualitative study based on the COM-B and theoretical domains framework (TDF) models
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Barriers and enablers for generative artificial intelligence in clinical psychology: a qualitative study based on the COM-B and theoretical domains framework (TDF) models
2025
Overview
Background
This study investigated the perceptions of care psychologists regarding the adoption of generative artificial intelligence (GenAI) in therapeutic practice. As AI continues to be integrated into various sectors, including healthcare, understanding how psychologists perceive its implementation in therapeutic settings is essential. The study explores the factors that act as barriers and facilitators to GenAI adoption and examines their impact on the future of therapeutic interventions.
Methods
A qualitative study design was adopted, involving semistructured, in-depth interviews with 14 private care psychologists in Spanish cities. The study focused on urban private care settings. The interviews were designed based on TDF domains to identify barriers and enablers. All sessions were recorded and transcribed. Data were analysed using a content approach, with the identified topics mapped onto the TDF and COM-B components.
Results
Eighteen factors were identified that influenced the decision to accept or reject GenAI in therapy, with 12 factors acting as barriers and 6 acting as facilitators. These factors are classified within the TDF domains. Highlighted barriers included a lack of understanding of AI and concerns about the confidentiality and privacy of information shared in therapy, while the main facilitators were training in AI skills and the possibility of having a digital assistant.
Conclusion
This study reveals the need for greater understanding of training in AI among psychologists. The acceptance of AI varies depending on the training and experience of professionals; some show concern for the future of their profession, while others highlight that it is an opportunity to improve interventions. Information privacy concerns are significant and have been identified as key factors for enabling AI deployment.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
