Patient-centered Evaluation of AI Answers to Genetic Counseling Questions

Abstract

Abstract The growing use of large language models for health communication raises important questions about patient preferences, trust, and satisfaction with AI-generated content. We conducted a qualitative survey comparing patient perceptions of clinician versus AI answers to questions about Alzheimer’s disease and genetics. Twenty-six participants scored responses on relevance, trustworthiness, and coherence, and additionally selected a preferred response and provided free-text comments. We found that participants generally preferred AI responses over human-written ones and rated them higher on all evaluation axes. Qualitative analysis of free-text comments identified key factors influencing patient preferences, including clarity, verbosity, certainty, empathy, and numeracy, with patients showing diverse and sometimes contradictory preferences along these dimensions. These findings suggest the AI-generated responses were well-received by patients and may have a role in triaging patients with information-seeking queries. Future work should focus on dynamically identifying patient communication preferences and tailoring communication styles accordingly.

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