ArticleFrontiers in psychology2024
Unpacking public resistance to health Chatbots: a parallel mediation analysis.
Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Can Medical Chatbots Trigger Disinhibition and Encourage Health Information Disclosure?Healthcare (Basel, Switzerland) · 2026Article
- Users' intentions to use medical escort service platforms: Based on technology trust and psychological resistance.iScience · 2026Article
- Understanding Chinese Consumers' Purchase Resistance in Virtual Live Streaming Rooms: The Role of Negative Anthropomorphism Disconfirmation and Service Guarantees.Behavioral sciences (Basel, Switzerland) · 2026Article
- Trauma-informed conversational agents for mental health: understanding user perspectives and experiences.Frontiers in digital health · 2026Article
- Media amplification, model source cues, and expectancy violation in public acceptance of generative AI: evidence from a health-consultation experiment.Frontiers in psychology · 2026Article
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Authors and funding
4 authors.
Funding
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Abstract
Introduction: Despite the numerous potential benefits of health chatbots for personal health management, a substantial proportion of people oppose the use of such software applications. Building on the innovation resistance theory (IRT) and the prototype willingness model (PWM), this study investigated the functional barriers, psychological barriers, and negative prototype perception antecedents of individuals' resistance to health chatbots, as well as the rational and irrational psychological mechanisms underlying their linkages. Methods: Data from 398 participants were used to construct a partial least squares structural equation model (PLS-SEM). Results: Resistance intention mediated the relationship between functional barriers, psychological barriers, and resistance behavioral tendency, respectively. Furthermore, The relationship between negative prototype perceptions and resistance behavioral tendency was mediated by resistance intention and resistance willingness. Moreover, negative prototype perceptions were a more effective predictor of resistance behavioral tendency through resistance willingness than functional and psychological barriers. Discussion: By investigating the role of irrational factors in health chatbot resistance, this study expands the scope of the IRT to explain the psychological mechanisms underlying individuals' resistance to health chatbots. Interventions to address people's resistance to health chatbots are discussed.
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