Currently accepted at: Journal of Medical Internet Research
Date Submitted: Apr 18, 2026
Date Accepted: Oct 14, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/98450
The final accepted version (not copyedited yet) is in this tab.
Effects of AI Conversational Agents on Emotion Regulation: A Systematic Review and Meta-Analysis
ABSTRACT
Background:
Background:
AI conversational agents (AICA) are increasingly being used to support emotion regulation. However, their overall effectiveness, the populations for whom they are most effective, and the sources of between-study heterogeneity remain unclear.
Objective:
Objective:
This study systematically reviewed and meta-analyzed the literature on AICA to estimate their pooled effects on emotion regulation and examine variability across regulatory pathways.
Methods:
Methods:
Following the PRISMA 2020 guidelines, we searched PubMed, Embase, Web of Science, Scopus, and major Chinese databases (CNKI, Wanfang, and VIP) from inception to November 4, 2025, with an updated search conducted on March 12, 2026. Eligible studies reported quantitative outcomes related to emotion regulation following interactions with AICA. Random-effects meta-analyses were performed using standardized mean differences. Robust variance estimation and three-level models were used to address statistical dependence among multiple effect sizes. Subgroup and strategy-specific analyses were conducted to explore potential sources of heterogeneity.
Results:
Results:
Nineteen studies met the inclusion criteria, of which fifteen were included in the meta-analysis. Overall, AICA showed a moderate positive effect on adaptive emotion regulation. Evidence for reductions in maladaptive emotion regulation strategies was weaker and less consistent. Effects varied across emotion regulation strategies, with interventions targeting response modulation and cognitive change showing relatively stable effects.
Conclusions:
Conclusions:
AICA may modestly enhance adaptive emotion regulation, whereas evidence for reducing maladaptive strategies remains limited. Their effectiveness appears to vary across regulatory pathways and implementation contexts. Future research should prioritize mechanism-focused designs and transparent reporting of intervention components to clarify how conversational agents support emotion regulation. Clinical Trial: Trial Registration: PROSPERO CRD420251231468; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251231468
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.