医学和非医学组织提供的通俗易懂摘要的结论性、可读性和文本特征：一项横断面研究。

Conclusiveness, readability and textual characteristics of plain language summaries from medical and non-medical organizations: a cross-sectional study.

机构信息

Department of Research in Biomedicine and Health, University of Split School of Medicine, Šoltanska 2A, 21000, Split, Croatia.

Department of Psychology, Faculty of Humanities and Social Sciences, University of Split, Split, Croatia.

出版信息

Sci Rep. 2024 Mar 12;14(1):6016. doi: 10.1038/s41598-024-56727-6.

DOI:10.1038/s41598-024-56727-6

PMID:38472285

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10933350/

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.

摘要

这项横断面研究比较了医学和非医学组织的通俗语言摘要（PLS）在结论性、可读性和文本特征方面的差异。分析了截至 2022 年 11 月 10 日发表的最新版本系统评价的所有 Cochrane（医学 PLS，n=8638）和 Campbell 协作和国际影响评估倡议（非医学 PLS，n=163）的 PLS。使用机器学习工具对医学 PLS 进行分类，并由两位专家对非医学 PLS 进行分类，将 PLS 分为三个结论性类别（结论性、非结论性和不明确）。非医学 PLS 的结论性比例更高（17.79%比 8.40%，P<0.0001），可读性更高（轻松阅读文本所需的受教育年限中位数为 15.23（四分位距（IQR）14.35 至 15.96）比 15.51（IQR 14.31 至 16.77），P=0.010），使用的词汇更多（中位数 603（IQR 539.50 至 658.50）比 345（IQR 202 至 476），P<0.001）。语言分析表明，医学 PLS 在厌恶和恐惧方面得分较高，而非医学 PLS 在积极情绪方面得分较高。医学和非医学领域之间观察到的差异的原因可能归因于出版方法或学科差异。这种分析 PLS 的方法对于提高 PLS 的整体质量和向公众进行知识转化至关重要。