Unpacking public resistance to health Chatbots: a parallel mediation analysis

Front Psychol. 2024 Apr 10:15:1276968. doi: 10.3389/fpsyg.2024.1276968. eCollection 2024.

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.

Keywords: health chatbots; innovation resistance theory; parallel mediation analysis; partial least squares structural equation modeling; prototype willingness model; resistance behavioral tendency.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research is supported by the Fundamental Research Funds for the Central Universities (23JNQMX50).