Stigma Reduction, Anonymity, and the Attitude–Intention Link in Medical Chatbot Use

Abstract

This study advances technology acceptance theory by introducing identity risk as a boundary condition on the link between attitude toward medical chatbots and intention to use. Drawing on the unified theory of acceptance and use of technology (UTAUT), the model positions performance expectancy, effort expectancy, social influence, facilitating conditions, and perceived cost saving as antecedents of attitude and intention, and tests perceived anonymity and perceived reduction of stigma as moderators of the attitude–intention relation. Evidence from recent users in Malaysia, analyzed with structural modeling, shows that performance expectancy, effort expectancy, social influence, and perceived cost saving are associated with more favorable attitudes, and that attitude is the central pathway to intention, while facilitating conditions show no direct association with intention in this context. Perceived anonymity does not change how attitude relates to intention. Perceived reduction of stigma changes this relation by lifting baseline willingness yet weakening the added effect of more favorable attitudes. Theoretical implications follow. Identity risk specifies when classic acceptance pathways hold in health care and reframes anonymity as a hygiene factor rather than a differentiator. The results clarify the distinct roles of stigma and anonymity in adoption judgment and temper expectations about facilitating conditions in the use of medical chatbots. For human-computer interaction and service design, the findings support designs that make clinical competence and provenance salient, allow first contact without identification, provide clear escalation to clinicians, and use stigma-sensitive language without eroding perceived clinical authority.

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