ArticleScientific reports2024
Conclusiveness, readability and textual characteristics of plain language summaries from medical and non-medical organizations: a cross-sectional study.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Use of chat GPT for sentiment and readability analysis of nutrition articles in legacy media.JAMIA open · 2026Article
- Feeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer.Journal of translational medicine · 2025Article
- Practical guidance on publishing plain-language summaries for scientific manuscripts with an Asia-Pacific audience.BMC research notes · 2025Article
- Using ChatGPT to Improve the Presentation of Plain Language Summaries of Cochrane Systematic Reviews About Oncology Interventions: Cross-Sectional Study.JMIR cancer · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
This cross-sectional study compared plain language summaries (PLSs) from medical and non-medical organizations regarding conclusiveness, readability and textual characteristics. All Cochrane (medical PLSs, n = 8638) and Campbell Collaboration and International Initiative for Impact Evaluation (non-medical PLSs, n = 163) PLSs of latest versions of systematic reviews published until 10 November 2022 were analysed. PLSs were classified into three conclusiveness categories (conclusive, inconclusive and unclear) using a machine learning tool for medical PLSs and by two experts for non-medical PLSs. A higher proportion of non-medical PLSs were conclusive (17.79% vs 8.40%, P < 0.0001), they had higher readability (median number of years of education needed to read the text with ease 15.23 (interquartile range (IQR) 14.35 to 15.96) vs 15.51 (IQR 14.31 to 16.77), P = 0.010), used more words (median 603 (IQR 539.50 to 658.50) vs 345 (IQR 202 to 476), P < 0.001). Language analysis showed that medical PLSs scored higher for disgust and fear, and non-medical PLSs scored higher for positive emotions. The reason for the observed differences between medical and non-medical fields may be attributed to the differences in publication methodologies or disciplinary differences. This approach to analysing PLSs is crucial for enhancing the overall quality of PLSs and knowledge translation to the general public.
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Registered trials
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