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Parents of children admitted to the PICU face an overwhelming informational landscape, necessitating accessible, patient-specific information. Large Language Models (LLMs) powering AI chatbots offer a promising solution for simplifying complex medical information. We aimed to characterize parental online health information-seeking (OHIS) behaviors and attitudes toward AI chatbots by conducting a cross-sectional survey of 139 English-speaking parents of children admitted to a large academic PICU between April-August 2024. We assessed OHIS behaviors, knowledge of and experience with AI chatbots, and attitudes regarding their potential healthcare utility. Most parents (87%) engaged in OHIS using search engines (86%). Parents with higher income and education sought information more frequently (OR 3.3, 95% CI 1.8-6.2; OR 2.9, 95% CI 1.5-5.7, respectively); those with higher education were less satisfied with online resources (OR 0.5, 95% CI 0.25-0.97). Parents expressed openness toward AI chatbots in healthcare applications (median 4/6). Significant socioeconomic disparities in current AI chatbot use favored male (OR 2.5, 95% CI 1.1-6.0) and higher income (OR 3.8, 95% CI 1.1-12.7) parents. Parents of critically ill children show high OHIS behaviors and positive attitudes toward AI chatbots. Addressing significant socioeconomic disparities in AI chatbot use is crucial for developing equitable implementation strategies in the PICU.
Hunter et al. (Mon,) studied this question.
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