Identifying key user experience and technical features for sustained use of unguided chatbots for health-related behavior change: a systematic review

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Abstract
Objective: This review aims to identify the contribution of user experience features and underlying technical features to sustained engagement in unguided chatbots for improving health-related behaviors. Materials and Methods: Following PRISMA-2020 guidelines, we conducted a systematic review, searching PubMed, ACM, APA PsycINFO, Cochrane, Web of Science, and IEEE Xplore from June to September 2022 and updated in April 2025. Data was analyzed via Synthesis without Meta-Analysis (SWiM), to understand the relationship between user engagement overall and individual experience metrics. Results: Customizable avatars and flexible input interactions may enhance overall user engagement. Conversely, pre-scripted content that lacks personalization and emotional support negatively impacts user satisfaction and adherence to health interventions. Other features contributing to sustained engagement are in-app technical assistance, user learning features, and crisis support systems. A strong positive correlation (r = 0.808, n = 16) was observed between user satisfaction and engagement, specifically for satisfaction dimensions including need fulfillment (r = 0.872, n = 6), willingness to recommend chatbot (r = 0.817, n = 4) and user enjoyment (r = 0.971, n = 3) in SWiM analysis. The limited application of large language models and retrieval augmented generation techniques may constrain the quality of support available to users and overall sustained engagement. Conclusion: Effective unguided chatbot design requires an emphasis on interactive educational elements, in-app technical assistance and crisis support, and personalized content. This can be achieved with high context awareness, input understanding, and quality content generation. Our findings suggest that user satisfaction is a primary driver of sustained engagement, though further research is needed to validate individual user satisfaction features for sustained engagement.

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