ArticleDigital health
Effects of personalization and source expertise on users' health beliefs and usage intention toward health chatbots: Evidence from an online experiment.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Leveraging chatbots for enhanced decision-making: a comprehensive literature review.Frontiers in artificial intelligence · 2026Pooled it
- Effectiveness of Communication Competence in AI Conversational Agents for Health: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- A Systematic Review of Factors Affecting Utilization of Decision Support Systems: The Interplay Between Technology, Users, and the Healthcare Environment.Health science reports · 2026Review
- Examining Artificial Intelligence Chatbots' Responses in Providing Human Papillomavirus Vaccine Information for Young Adults: Qualitative Content Analysis.JMIR public health and surveillance · 2026Article
- Feasibility and Preliminary Impacts of a Diabetes Education Chatbot Simulation on Glycemic Targets, Loneliness, and Health Beliefs in Indonesia: An Explanatory Mixed-methods Study.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2026Article
- Neurocognitive mechanisms of source credibility: how work experience and patient ratings modulate the processing of medical veracity cues.Frontiers in human neuroscience · 2026Article
- Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis.Journal of medical Internet research · 2025Article
- Psychological, economic, and ethical factors in human feedback for a chatbot-based smoking cessation intervention.NPJ digital medicine · 2025Article
- How Do Consumers Trust and Accept AI Agents? An Extended Theoretical Framework and Empirical Evidence.Behavioral sciences (Basel, Switzerland) · 2025Article
- Factors influencing perceived benefits and behavioral intention to use mental health chatbots among professional employees: an empirical study.Frontiers in digital health · 2025Article
- Usability, Engagement, and Report Usefulness of Chatbot-Based Family Health History Data Collection: Mixed Methods Analysis.Journal of medical Internet research · 2024Article
- Article
- From clinics to clicks: Investigating the motivations and competency framework of healthcare professionals on social media.Digital healthArticle
- Article
- How the affordance and psychological empowerment promoting AI-based medical consultation usage: A mixed-methods approach.Digital healthArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Based on the heuristic-systematic model (HSM) and health belief model (HBM), this study aims to investigate how personalization and source expertise in responses from a health chatbot influence users' health belief-related factors (i.e. perceived benefits, self-efficacy and privacy concerns) as well as usage intention. Methods: A 2 (personalization vs. non-personalization) × 2 (source expertise vs. non-source expertise) online between-subject experiment was designed. Participants were recruited in China between April and May 2021. Data from 260 valid observations were used for the data analysis. Results: Source expertise moderated the effects of personalization on health belief factors. Perceived benefits and self-efficacy mediated the relationship between personalization and usage intention when the source expertise cue was presented. However, the privacy concerns were not influenced by personalization and source expertise and did not significantly affect usage intention toward the health chatbot. Discussion: This study verified that in the health chatbot context, source expertise as a heuristic cue may be a necessary condition for effects of the systematic cue (i.e. personalization), which supports the HSM's arguments. By introducing the HBM in the chatbot experiment, this study is expected to provide new insights into the acceptance of healthcare AI consulting services.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.