Can AI Technologies Support Clinical Supervision? Assessing the Potential of ChatGPT
Clinical supervision is essential for trainees, preventing burnout and ensuring the effectiveness of their interventions. AI technologies offer increasing possibilities for developing clinical practices, with supervision being particularly suited for automation. The aim of this study is to evaluate...
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/12/1/29 |
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| Summary: | Clinical supervision is essential for trainees, preventing burnout and ensuring the effectiveness of their interventions. AI technologies offer increasing possibilities for developing clinical practices, with supervision being particularly suited for automation. The aim of this study is to evaluate the feasibility of using ChatGPT-4 as a supervisory tool in psychotherapy training. To achieve this, a clinical case was presented to three distinct groups (untrained AI, pre-trained AI, and qualified human supervisor), and their feedback was evaluated by Gestalt psychotherapy trainees using a Likert scale rating of satisfaction. Statistical analysis, using the statistical package SPSS version 25 and applying principal component analysis (PCA) and one-way analysis of variance (ANOVA), demonstrated significant differences in favor of pre-trained AI feedback. PCA highlighted four components of the questionnaire: relational and emotional (C1), didactic and technical quality (C2), treatment support and development (C3), and professional orientation and adaptability (C4). The ratings of satisfaction obtained from the three kinds of supervisory feedback were compared using ANOVA. The feedback generated by the pre-trained AI (f2) was rated significantly higher than the other two (untrained AI feedback (f1) and human feedback (f3)) in C4; in C1, the superiority of f2 over f1 but not over f3 appears significant. These results suggest that AI, when appropriately calibrated, may be an appreciable tool for complementing the effectiveness of clinical supervision, offering an innovative blended supervision methodology, in particular in the area of career guidance. |
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| ISSN: | 2227-9709 |