To evaluate whether large language model (LLM)-generated plain-language summaries improve patient understanding of lung cancer screening reports compared to standard radiology reports.
Key Findings:
Participants receiving LLM-generated summaries reported higher comprehension levels than those with standard reports.
Perceived clarity and satisfaction were also significantly higher in the summary group.
The improvement in comprehension persisted after adjusting for age, education, and health literacy.
Anxiety levels did not significantly differ between the two groups.
Interpretation:
LLM-generated summaries may enhance patient understanding of lung cancer screening results, suggesting potential benefits for patient communication.
Limitations:
The study used hypothetical scenarios rather than real clinical reports.
Outcomes were based on self-reported measures rather than objective assessments.
Online recruitment may limit generalizability to broader populations undergoing lung cancer screening.
Conclusion:
LLM-generated plain-language summaries could support patient understanding of lung cancer screening results, warranting further evaluation in clinical settings.
