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From Readability to Fidelity: A Design-Constrained LLM for Health-Literacy-Aligned Patient Education
One-line summary
An AI research paper on From Readability to Fidelity: A Design-Constrained LLM for Health-Literacy-Aligned Patient Education.
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Chinese explanation / 中文解读
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Original abstract
Large language models (LLMs) offer transformative potential for personalized patient education, yet their clinical utility is restricted by misinformation and a failure to align with Health Literacy (HL) principles. This paper presents a blueprint for a Design-Constrained LLM (DC-LLM). We translate Nutbeam’s HL constructs - functional, interactive, and critical - into technical constraints, including readability gating, contextual adaptation, and evidence of provenance. We outline a four-phase evaluation plan to validate the system’s comprehension, trust, and clinical adherence. This framework moves generative AI beyond mere text simplification toward a safe, interactive, and evidence-based patient education tool.
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