Accepted for/Published in: JMIR Mental Health
Date Submitted: Aug 6, 2025
Date Accepted: Dec 4, 2025
Physician Perspectives Regarding the Impact of Artificial Intelligence on the Therapeutic Relationship in Mental Health Care: Qualitative Study
ABSTRACT
Background:
The therapeutic relationship is the professional partnership between clinicians and patients that supports open communication and clinical decision-making. This relationship is critical to the delivery of effective mental health care. Integration of artificial intelligence (AI) into mental health care has the potential to support accessibility and personalized care; however, less is known about how AI might affect the dynamic of the therapeutic relationship.
Objective:
Our objective was to ascertain how physicians anticipate AI tools will impact the therapeutic relationship in mental health care.
Methods:
We conducted 42 in-depth interviews with psychiatrists and family medicine practitioners to investigate physician perceptions regarding the impact of AI on mental health care.
Results:
Physicians identified several disruptions from AI use, noting that these tools could impact the dyad of the patient-physician relationship in ways that are both positive and negative. They suggested that AI tools could create efficiencies that allow for relationship building as well as avoid issues with miscommunication during psychotherapeutic interactions. However, they also expressed concerns that AI tools might not adequately capture aspects of the therapeutic relationship, such as empathy, that are vital to mental health care. Physicians also raised issues related to the impact AI tools will have on shared decision-making as well as the role of transparency of AI tool use in maintaining relationships with patients.
Conclusions:
As AI applications become increasingly integrated into mental health care, it is crucial to assess how this integration may support or disrupt the therapeutic relationship.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.