How incidental exposure shapes continued use of AI chatbots in healthcare: A multigroup analysis.

OBJECTIVE: This study aims to examine the linkage between incidental information exposure and individuals' continuous intention to use AI chatbots in healthcare, and whether this process varies by pre-existing attitudes toward human doctors. METHOD: Data were collected through a cross-sectional survey (N = 779) from June 11 to June 16, 2025. Structural equation modeling and multigroup comparison analysis were conducted to test the hypothesized relationships and group differences. RESULT: Incidental exposure to information about AI chatbots in healthcare was positively linked to both subjective (β = .378, p < .001) and objective knowledge (β = .095, p < .05). Both subjective (β = .222, p < .001) and objective knowledge (β = .224, p < .001) about AI chatbots in healthcare were positively linked to positive attitudes toward these technologies, which was subsequently associated with continuous intention (β = .468, p < .001). Multigroup analysis showed that the link between objective knowledge and positive attitudes toward AI chatbots in healthcare was stronger among those with high (β = .299, p < .001) versus low (β = .135, p = .014) positive attitudes toward human doctors, as was the link between positive attitudes and continuous intention (high: β = .506; low: β = .271, ps < .001). CONCLUSION: Incidental exposure to media information about AI chatbots in healthcare was positively linked to continuous usage intention through knowledge acquisition and attitude formation. Individuals with divergent levels of pre-existing attitudes toward human doctors performed differently within the mechanism.