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From innovation to implementation: Artificial intelligence in cognitive behaviour therapy training and supervision.
Roz Shafran1, Laura Bond2, Per Carlbring3
1Great Ormond Street Institute for Child Health, University College London, United Kingdom.
Artificial intelligence (AI) can enhance mental health care training by simulating patients and offering real-time feedback. This technology promises greater efficiency and accessibility in evidence-based psychotherapy supervision, despite facing challenges.
Area of Science:
- Mental Health
- Artificial Intelligence
- Psychotherapy Training
Background:
- Mental health care globally faces challenges in training and supervision for evidence-based psychotherapies.
- Cognitive and behavioral therapies (CBT) require consistent and effective training protocols.
Purpose of the Study:
- To describe the potential role of AI in clinician training and supervision for evidence-based psychotherapies.
- To outline the gains, challenges, and risks associated with AI implementation in this field.
Main Methods:
- The paper reviews the potential applications of AI in simulating patient interactions for assessment and therapy.
- It discusses AI's capability to provide real-time, personalized feedback on treatment fidelity.
- AI's role in developing cultural sensitivity among trainees is also explored.
Main Results:
- AI can significantly improve the efficiency, consistency, effectiveness, and accessibility of psychotherapy training.
- Simulated patients and real-time feedback offer novel training modalities.
- AI can aid in developing crucial clinical skills like cultural sensitivity.
Conclusions:
- AI holds transformative potential for global mental health care training and supervision.
- Key challenges include data quality, ethical considerations, low-resource implementation, and the need for rigorous research.
- Guidelines are proposed for the responsible development and deployment of AI in CBT training to maximize benefits and minimize risks.
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