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Cited by 11Digital Mental Health InterventionsSocial Robot Interaction and HRIEmotion and Mood Recognition

A Systematic Review on Mental Health Chatbots: Trends, Design Principles, Evaluation Methods, and Future Research Agenda

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Kuhail, Mohammad Amin, Al-Shamaileh, Ons, Farooq, Shahbano, Shahin, Hana, Abdelzaher, Fatema, Thomas, Justin·2025·Human Behavior and Emerging Technologies
DOI 10.1155/hbe2/9942295
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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.

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  • Existing reviews and meta-analyses of LLM-CBs for mental health focus on applications of LLM-CBs as clinical intervention tools, often under research-protocol conditions.

    “Although reviews and meta-analyses of LLM-CBs for mental health exist13,14,29,30, as well as scoping reviews on the implementation of LLM-CBs in mental health31,32, their focus is narrowed to applications of LLM-CBs as clinical intervention tools.”

    From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [30]

    Section 3 (Related Work; page not available) says prior mental-health-chatbot reviews examine intervention effectiveness, but also lists design, user experience, technology, ethics, and other objectives. Section 6.2.5 discusses LLMs but does not establish that reviews of LLM-based chatbots are narrowly focused on clinical intervention tools or research-protocol conditions. (LLM, conf=0.78)

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Cited by

Sorted by citations

Authors
Kuhail, M. A., Al-Shamaileh, O., Farooq, S., Shahin, H., Abdelzaher, F., & Thomas, J.
Affiliations
  • Zayed University (AE)
  • University of Alberta (CA)
  • University of Liverpool (GB)
Corresponding author
Kuhail, Mohammad Amin
ORCID
Venue
Human Behavior and Emerging Technologies
Publisher
Wiley
Published
2025-01
Volume
2025
Issue
1
ISSN
2578-1863 (ISSN-L)
DOI
10.1155/hbe2/9942295
OpenAlex
W7106712149
Cited by
11
References
43
Citations by year
2026: 11
FWCI
1.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Human Behavior and Emerging Technologies (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Zayed University (R23014)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
Keywords
mental health chatbots, chatbots, chatbot evaluation, cognitive behavioral therapy, depression, cultural adaptation, human-in-the-loop, large language models, third-wave therapies

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