CNRS, Univ. Lille, UMR 8163 - STL - Savoirs Textes Langage, F-59000 Lille, France.
Stud Health Technol Inform. 2022 May 25;294:634-638. doi: 10.3233/SHTI220546.
The reduction of the linguistic complexity of medical texts to make them more understandable to a larger population is an important task. The simplification of texts involves several steps, among which our study focuses on the definition of complex constructions and on study of the impact of the simplification. For this study, we selected 20 texts from the medical domain on different topics, namely drugs, diseases, substances, and medical institutions. We identified complex linguistic constructions and carried out their manual simplification at syntactic, lexical and semantic levels. We then designed a questionnaire to test comprehension of the texts and conducted a study with 26 participants. The results of this study shows that simplified texts obtained higher number of correct answers than technical texts. This difference is statistically significant. The self-evaluation questionnaire, done at the beginning of the test, indicates that the participants tend to overestimate their understanding of medical information. Besides, there is no correlation between the time taken to complete the interview and the correct answers provided.
将医学文本的语言复杂性降低，使其更容易被更多人理解是一项重要任务。文本的简化涉及多个步骤，我们的研究集中在定义复杂结构和研究简化的影响上。在这项研究中，我们选择了 20 篇来自不同主题的医学领域的文本，包括药物、疾病、物质和医疗机构。我们确定了复杂的语言结构，并在句法、词汇和语义层面上进行了手动简化。然后，我们设计了一份问卷来测试对文本的理解，并对 26 名参与者进行了研究。这项研究的结果表明，简化后的文本比技术文本获得了更多的正确答案。这种差异具有统计学意义。测试开始时进行的自我评价问卷表明，参与者往往高估了自己对医学信息的理解。此外，完成访谈所花费的时间与提供的正确答案之间没有相关性。
