Application of Synchronous Text-Based Dialogue Systems in Mental Health Interventions: Systematic Review
Open accessAbstract
BACKGROUND: Synchronous written conversations (or "chats") are becoming increasingly popular as Web-based mental health interventions. Therefore, it is of utmost importance to evaluate and summarize the quality of these interventions. OBJECTIVE: The aim of this study was to review the current evidence for the feasibility and effectiveness of online one-on-one mental health interventions that use text-based synchronous chat. METHODS: A systematic search was conducted of the databases relevant to this area of research (Medical Literature Analysis and Retrieval System Online [MEDLINE], PsycINFO, Central, Scopus, EMBASE, Web of Science, IEEE, and ACM). There were no specific selection criteria relating to the participant group. Studies were included if they reported interventions with individual text-based synchronous conversations (ie, chat or text messaging) and a psychological outcome measure. RESULTS: A total of 24 articles were included in this review. Interventions included a wide range of mental health targets (eg, anxiety, distress, depression, eating disorders, and addiction) and intervention design. Overall, compared with the waitlist (WL) condition, studies showed significant and sustained improvements in mental health outcomes following synchronous text-based intervention, and post treatment improvement equivalent but not superior to treatment as usual (TAU) (eg, face-to-face and telephone counseling). CONCLUSIONS: Feasibility studies indicate substantial innovation in this area of mental health intervention with studies utilizing trained volunteers and chatbot technologies to deliver interventions. While studies of efficacy show positive post-intervention gains, further research is needed to determine whether time requirements for this mode of intervention are feasible in clinical practice.
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Of extant systematic reviews on AI chatbots, 6 targeted assessing efficacy in enhancing mental health outcomes, 2 examined feasibility in health care settings, and 1 described technical architectures and characteristics in chronic conditions.
“Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].”
From Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. (2023) · cites this paper as [11]
The Abstract (Objective; page unavailable) identifies this as a systematic review of the effectiveness of synchronous text-based mental health interventions, so it fits the cited group of efficacy-focused reviews. But the Results (Feasibility and Acceptability Studies; page unavailable) say interventions were mostly delivered by professionals, with chatbots among the technologies studied. The review is therefore not specifically an assessment of AI-chatbot efficacy. (LLM, conf=0.87)
Experimental — accuracy not yet measuredOverall, our mixed results regarding feasibility, acceptability, and usability are partially aligned with the findings of the existing systematic reviews that reported heterogeneity in these secondary outcome measures and results across studies.
“Overall, our mixed results regarding feasibility, acceptability, and usability are partially aligned with the findings of the existing systematic reviews that reported heterogeneity in these secondary outcome measures and results across studies [1,2,7,9-11].”
From Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. (2023) · cites this paper as [11]
The Results > Study Selection section reports significant heterogeneity across studies in conditions, psychological outcomes, intervention design, and subjective ratings; Results > Feasibility and Acceptability Studies also describes a wide range of studies. The cited review does not specifically report heterogeneous usability measures or mixed feasibility, acceptability, and usability results, so it supports the broader point but not all of the attributed detail. No page numbers are available in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredExisting systematic and scoping reviews of conversational agent interventions in mental health have focused on a subset of conversational agents with a visual character (embodied) or are now outdated.
“Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health.”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [8]
Conversational agents or chatbots that deliver CBT via a text-based, semiautomated algorithm are known to reduce mild-to-moderate depressive symptoms in nonclinical populations.
“Conversational agents or “chatbots” that deliver CBT via a text-based, semiautomated algorithm are known to reduce mild-to-moderate depressive symptoms in nonclinical populations [17,20-23].”
From Chatbot-Delivered Cognitive Behavioral Therapy in Adolescents With Depression and Anxiety During the COVID-19 Pandemic: Feasibility and Acceptability Study (2022) · cites this paper as [23]
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- Authors
- Hoermann, S., McCabe, K. L., Milne, D. N., & Calvo, R. A.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Calvo, Rafael A
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2017-08-07
- Volume
- 19
- Issue
- 8
- Pages
- e267
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC5595406
- OpenAlex
- W2744519557
- Cited by
- 263
- References
- 42
- Citations by year
- 2026: 20 · 2025: 28 · 2024: 24 · 2023: 33 · 2022: 55 · 2021: 34 · 2020: 39 · 2019: 16 · 2018: 12 · 2017: 2
- FWCI
- 2.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, other-oa)
- Funders
- Australian Research Council (LP130100453, FT140100824)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- digital mental health interventions, chatbots, text messaging, feasibility, intervention effectiveness, usual care, anxiety, depression, eating disorders, addiction, psychological outcomes
- MeSH terms
- Feasibility Studies, Humans, Mental Health, Text Messaging
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