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TRUVACE RECORD VERSION
record: TRV-2026-2732
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:16:08.501446Z
status: published
lens: p_space
sector: science
headline: A Meta-Analysis of the Acceptance of Artificial Intelligence in Psychotherapy
dek: 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 conven…
gain_title: (none)
problem_title: A meta-analysis of 10 studies with 1,967 participants found no statistically significant difference in acceptance between AI psychotherapy and conventional therapy (g = −0.171, 95% CI −0.908 to 0.566), and later and larger studies reported lower acceptance of AI.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A meta-analysis of 10 studies with 1,967 participants found no statistically significant difference in acceptance between AI psychotherapy and conventional therapy (g = −0.171, 95% CI −0.908 to 0.566), and later and larger studies reported lower acceptance of AI.
problem_evidence: The meta-analysis results showed that the overall effect size was g = −0.171 (95% CI: [−0.908, 0.566], p = 0.649) | studies with later publication dates and larger sample sizes reported relatively lower AI acceptance
quick_read: A meta-analysis in Behavioral Sciences pooled 10 studies published between 2017 and 2025, covering 1,967 participants (981 in AI groups, 986 in control groups), to compare acceptance of AI-based psychotherapy with conventional therapy. The pooled effect was g = −0.171 (95% CI −0.908 to 0.566, p = 0.649), so the data gave no clear advantage or disadvantage to AI.

Results varied enormously between studies (I² = 98%). Acceptance of AI was similar to acceptance of human therapists but higher than for bibliotherapy. Studies using general chatbots such as ChatGPT leaned toward conventional therapy, while those using specialised tools such as Woebot leaned toward AI.

The authors rated the certainty of evidence as very low. Later and larger studies reported lower acceptance of AI, which the authors link to fading novelty or small-study effects, and the funnel plot was asymmetric, so publication bias cannot be ruled out.
limitation: The meta-analysis included only 10 studies with very high heterogeneity (I² = 98%) and very low certainty of evidence. Possible publication bias and an unregistered protocol add further uncertainty, and the moderator findings are exploratory.
tag: Evidence-backed problem
key_points: The review searched Web of Science, PubMed, Google Scholar, CNKI and Wanfang up to January 2026, found 2,735 articles and included 10. | Included studies enrolled between 8 and 428 participants, including college students, older adults and patients with mental disorders. | Leave-one-out checks gave Hedges' g values from −0.312 to 0.035, all non-significant. | Acceptance of AI was no different from acceptance of human therapists but higher than for bibliotherapy. | Studies of general chatbots such as ChatGPT favoured conventional therapy; studies of specialised tools such as Woebot favoured AI. | Meta-regression linked later publication year and larger sample size to lower AI acceptance, but the authors call this exploratory. | Certainty of evidence was rated very low under the GRADE framework; Egger's test gave p = 0.055 and the funnel plot was asymmetric.
rundown: The authors included studies that compared acceptance of conversational AI, such as ChatGPT and Woebot, with conventional treatment such as human therapists or bibliotherapy. Acceptance was measured on Likert-type scales covering willingness to use, attitudes, satisfaction and trust, and converted to Hedges' g so different scales could be pooled. Two researchers screened and extracted data independently, and the Kmet checklist rated all 10 studies as low risk of bias.

Subgroup analysis suggested that the type of control therapy, cultural background and AI type might explain some of the variation, while population, baseline distress and participant source did not. The cultural findings rest on single studies in some groups: Southern European and Middle Eastern samples showed different patterns, and the authors call these preliminary.

The authors note the review was not registered in a public registry, that questionnaire reliability was rarely reported, and that older AI models studied years ago may not reflect current capabilities. They conclude that AI could complement human therapists, but that the evidence does not show either approach is better.
sources:
- peer_reviewed | Behavioral Sciences | https://doi.org/10.3390/bs16091552 | 2026-09-02
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