Exploring the influence of privacy concerns, AI literacy, and perceived health stigma on AI chatbot use in healthcare: An uncertainty reduction approach
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Summary
This summary is machine-generated.AI chatbots are valued for health information and lifestyle guidance, but privacy concerns can hinder their use. AI literacy and addressing health stigma are key to increasing trust and patient engagement with AI in healthcare.
Area Of Science
- Human-Computer Interaction
- Health Informatics
- Artificial Intelligence Ethics
Background
- AI chatbots are increasingly explored for healthcare applications.
- Understanding user perceptions is crucial for effective AI integration.
- Uncertainty Reduction Theory provides a framework for analyzing human-AI interactions.
Purpose Of The Study
- To investigate the impact of AI privacy concerns, AI literacy, and perceived health stigma on the preference for AI chatbots in Chinese healthcare.
- To examine how these factors influence the acceptance of AI chatbots for various healthcare functions.
Main Methods
- Survey data from 1487 participants were analyzed.
- Descriptive statistics were generated using frequency analyses.
- Regression modeling was employed to assess variable relationships.
Main Results
- AI chatbots are preferred for health information and lifestyle guidance.
- Privacy concerns reduce AI's perceived substitutability for doctors, especially for sensitive issues.
- AI literacy mitigates privacy concerns, while health stigma increases acceptance of AI for sensitive topics and exacerbates privacy concerns.
Conclusions
- AI chatbots play a significant role in healthcare, influencing personal information disclosure.
- Findings extend Uncertainty Reduction Theory to human-AI interactions.
- Prioritizing privacy, AI literacy, and stigma reduction is vital for patient trust and engagement with AI healthcare tools.
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