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Examining Preferences for Human vs. AI Sources in Online Health Information Seeking: Integrating the RISP and Source
1Department of Communication, Cornell University.
Health Communication
|August 5, 2026
Summary
Individuals prefer human doctors over AI chatbots for health information, influenced by social norms and AI
Area of Science:
- Digital Health Communication
- Health Information Seeking Behavior
- Human-Computer Interaction
Background:
- Growing use of AI chatbots and online consultations for health information.
- Individuals face choices between AI and human sources for medical advice.
- Need to understand factors influencing source preference in digital health environments.
Purpose of the Study:
- Examine how risk motivations and source credibility influence preferences for AI chatbots versus human doctors.
- Integrate the Risk Information Seeking and Processing (RISP) framework with source credibility concepts.
- Clarify evaluation of human and AI sources in contemporary health information seeking.
Main Methods:
- Online experimental survey with 248 participants.
- Random assignment to higher (STDs) or lower (allergies) sensitivity topics.
- Regression analyses to identify predictors of source choice.
Main Results:
- Overall preference for online human doctors over AI chatbots.
- Informational subjective norms strongly predicted preference for human doctors.
- Positive beliefs in AI predicted preference for AI agents.
- Higher perceived AI information-gathering capacity increased AI preference in low-sensitivity contexts.
Conclusions:
- RISP motivations explain the salience of health information seeking.
- Source credibility evaluations guide the translation of motivations into source preferences.
- Topic sensitivity indirectly influences source preference via subjective norms.
- Affective and knowledge factors had limited impact on source choice.
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