Self-reported comprehension of large language model-generated summaries of lung cancer screening reports: a vignette survey

Abstract Background Patients access radiology reports without delay, which can cause anxiety and misunderstanding. While large language models (LLMs) can generate patient-friendly summaries (PS) to mitigate this, their potential to address literacy-based disparities remains unquantified. Purpose To measure the effect of LLM-generated PS on the objective comprehension and subjective experiences of individuals reading lung cancer screening computed tomography reports, and to determine the differential impact with respect to self-rated English and health literacy. Materials and Methods This cross-sectional survey (July 24–28, 2025) used a within-subjects design. Participants from the online research platform Prolific, self-enrolled from the general U.S. population, viewed 3 lung cancer screening reports (negative; negative with complex incidentals; suspicious for malignancy), first in their original format and then with an LLM-generated PS. Objective comprehension, subjective experiences (including anxiety, via a 5-point Likert scale), and hypothetical communication intent were assessed after each viewing. Univariate and multivariate analyses, including demographic subgroup comparisons, were performed. Results A total of 1815 participants (mean age, 46 years ± 16 [SD]; 919 women) who completed the survey were evaluated. The addition of a PS improved objective comprehension (P < .001) and reduced anxiety (P < .001) for all scenarios. This effect was most pronounced for respondents with low self-rated English literacy, who had greater comprehension gain (P < .001) and anxiety reduction (P = .012) than those with high literacy. Individuals with low self-rated health literacy also experienced more anxiety reduction (P < .001). PS also increased the proportion of participants reporting that they would be willing to wait for a scheduled appointment to discuss their results (P < .001). Conclusion LLM-generated PS of lung cancer screening reports increase comprehension and reduce anxiety, most notably among individuals with lower self-rated English and health literacy. If validated in a patient population, they represent a potential tool to improve communication.

Authors

Institutions

Publication Details

Journal
Radiology Advances
Published
2026-02-16
DOI
https://doi.org/10.1093/radadv/umag008
Primary Topic
Health Literacy and Information Accessibility
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self-reported comprehension of large language model-generated summaries of lung cancer screening reports: a vignette survey

Alison S Rustagi, Yang Yu, Jae Ho Sohn, Parris Diaz et al.
Radiology Advances
Health Literacy and Information Accessibility
article

Self-reported comprehension of large language model-generated summaries of lung cancer screening reports: a vignette survey

Alison S Rustagi, Yang Yu, Jae Ho Sohn, Parris Diaz, Meng Ye, Koharu Sakiyama, Juan A Serna
article en

Abstract

Abstract Background Patients access radiology reports without delay, which can cause anxiety and misunderstanding. While large language models (LLMs) can generate patient-friendly summaries (PS) to mitigate this, their potential to address literacy-based disparities remains unquantified. Purpose To measure the effect of LLM-generated PS on the objective comprehension and subjective experiences of individuals reading lung cancer screening computed tomography reports, and to determine the differential impact with respect to self-rated English and health literacy. Materials and Methods This cross-sectional survey (July 24–28, 2025) used a within-subjects design. Participants from the online research platform Prolific, self-enrolled from the general U.S. population, viewed 3 lung cancer screening reports (negative; negative with complex incidentals; suspicious for malignancy), first in their original format and then with an LLM-generated PS. Objective comprehension, subjective experiences (including anxiety, via a 5-point Likert scale), and hypothetical communication intent were assessed after each viewing. Univariate and multivariate analyses, including demographic subgroup comparisons, were performed. Results A total of 1815 participants (mean age, 46 years ± 16 [SD]; 919 women) who completed the survey were evaluated. The addition of a PS improved objective comprehension (P < .001) and reduced anxiety (P < .001) for all scenarios. This effect was most pronounced for respondents with low self-rated English literacy, who had greater comprehension gain (P < .001) and anxiety reduction (P = .012) than those with high literacy. Individuals with low self-rated health literacy also experienced more anxiety reduction (P < .001). PS also increased the proportion of participants reporting that they would be willing to wait for a scheduled appointment to discuss their results (P < .001). Conclusion LLM-generated PS of lung cancer screening reports increase comprehension and reduce anxiety, most notably among individuals with lower self-rated English and health literacy. If validated in a patient population, they represent a potential tool to improve communication.

Radiology AdvancesVol. 3(2)
San Francisco General Hospital (US), SRI International (US), University of California, San Francisco (US), California Pacific Medical Center (US), San Francisco VA Health Care System (US), University of California, Berkeley (US)
Quality Education
Openalex Percentile: Top 54%
Health Literacy and Information Accessibility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.