Investigating psychotherapists' attitudes towards artificial intelligence in psychotherapy

Area of Science:

• Mental Health
• Psychotherapy
• Artificial Intelligence

Background:

• Rising mental health disorders and therapist shortages necessitate innovative solutions like AI and Machine Learning (ML).
• AI/ML show promise in diagnostics, personalized treatment, and therapy optimization.
• Understanding psychotherapists' attitudes towards AI/ML is crucial for its integration but remains underexplored.

Purpose of the Study:

• Investigate psychotherapists' attitudes toward AI/ML in Germany.
• Identify factors influencing AI acceptance and perceived usefulness.
• Explore the relationship between technical affinity and AI perception.

Main Methods:

• Cross-sectional survey of 181 licensed psychotherapists in Germany.
• Assessed attitudes towards AI/ML, technical affinity, and perceived utility.
• Hierarchical regression analyses identified predictors of AI acceptance.

Main Results:

• Perceived usefulness in diagnostics and personalized treatment plans significantly predicted positive AI/ML attitudes.
• Empathic support was a significant predictor across groups, though rated lower for enhancement.
• Technically affine therapists focused on AI benefits in diagnostics; non-affine therapists highlighted empathic support and relapse prediction.

Conclusions:

• Negative attitudes stem from fears of professional replacement and limited AI/ML understanding.
• A significant portion of therapists (40%) lack technical inclination, indicating a potential knowledge gap.
• Education and emphasizing human qualities are vital to address fears and facilitate AI/ML adoption in psychotherapy.