ArticleRadiology advances2026
Self-reported comprehension of large language model-generated summaries of lung cancer screening reports: a vignette survey.
Article in Radiology advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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 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 ( 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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.