Document Type

Article

Source of Publication

Human Behavior and Emerging Technologies

Publication Date

1-1-2025

Abstract

Recent decades have witnessed a rise in the prevalence of common mental health problems coupled with an increasing demand for talk‐based psychological therapies. This has coincided with the rise of mental health chatbots (MHCs), a corollary of which is the use of MHCs, AI‐driven, conversational agents, to provide interactive support, guidance, and therapeutic engagement for persons experiencing mental health challenges. There has been a growing research interest in MHCs, and this study provides a much‐needed systematic review that examines this expanding research literature, identifying themes, trends, and areas worthy of further exploration. This review identified and systematically explored 97 published papers on MHCs. Most studies explored MHC design and evaluation, emphasizing empathy‐based chatbots and their relative efficacy compared with conventional delivery modes (e.g., in‐person human therapists). Text‐based communication was the most frequently utilized modality over and above the use of audio, graphical, or mixed modes. The most commonly used therapeutic orientation among MHCs was cognitive behavioral therapy (CBT), with far less focus on third‐wave evidence‐based approaches such as dialectical behavior therapy and acceptance and commitment therapy. The most frequently targeted mental health condition was depression, although there were several other conditions also considered. Most MHC research has not considered cultural appropriateness or cultural adaptation of interventions. Further, limited attention to severe or high‐risk symptomatology has been given. Meanwhile, we noted that most of the studies used quantitative and mixed evaluation methods. Evaluation shows persistent challenges around personalization, privacy, and technical reliability. Future research should focus on integrating human‐in‐the‐loop mechanisms, advancing cultural adaptation, incorporating thought‐challenging CBT techniques, embedding ethics into design, and exploring large language models (LLMs) for more adaptive and empathetic support.

ISSN

2578-1863

Publisher

Wiley

Volume

2025

Issue

1

Disciplines

Computer Sciences | Medicine and Health Sciences

Keywords

Digital Mental Health Interventions, Social Robot Interaction and HRI, Emotion and Mood Recognition

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexed in Scopus

no

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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