A Meta-Analysis of the Acceptance of Artificial Intelligence in Psychotherapy

Abstract

In recent years, artificial intelligence (AI) technology has demonstrated potential in psychotherapy. However, there is currently a lack of systematic research that comprehensively assessed public acceptance of AI-based psychotherapy. The purpose of this study is to use meta-analysis to explore public acceptance of AI in psychotherapy and the sources of heterogeneity. A random-effects model was employed, using Hedges' g as the effect size, to pool the differences in acceptance between the AI group and the conventional psychotherapy group. Subgroup analysis and meta-regression were used to explore the sources of heterogeneity. The review included a total of 10 studies involving 1967 participants. Meta-analysis revealed no statistically significant overall difference in acceptance between AI-based psychotherapy and conventional therapy; however, substantial heterogeneity was observed across studies, indicating that this pooled estimate should be interpreted cautiously. Subgroup analysis suggested that the type of conventional psychotherapy, cultural background, and AI type may contribute to variations in acceptance; however, these findings should be interpreted cautiously due to the limited number of studies in some subgroups. Meta-regression analysis indicated that studies with later publication dates and larger sample sizes reported relatively lower AI acceptance. Public acceptance of AI-based psychotherapy may be influenced by multiple factors, including AI type, cultural background, and characteristics of comparison conditions. Future research should focus on cultural differences, the professionalism of AI tools, and the quality of research methodology to more clearly define the appropriate contexts for AI in psychotherapy.

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