首页> 外文期刊>Journal of cancer education: the official journal of the American Association for Cancer Education >Computer-Based Readability Testing of Information Booklets for German Cancer Patients
【24h】

Computer-Based Readability Testing of Information Booklets for German Cancer Patients

机译:德国癌症患者信息小册子的基于计算机的可读性测试

获取原文
获取原文并翻译 | 示例
           

摘要

Understandable health information is essential for treatment adherence and improved health outcomes. For readability testing, several instruments analyze the complexity of sentence structures, e.g., Flesch-Reading Ease (FRE) or Vienna-Formula (WSTF). Moreover, the vocabulary is of high relevance for readers. The aim of this study is to investigate the agreement of sentence structure and vocabulary-based (SVM) instruments. A total of 52 freely available German patient information booklets on cancer were collected from the Internet. The mean understandability level L was computed for 51 booklets. The resulting values of FRE, WSTF, and SVM were assessed pairwise for agreement with Bland-Altman plots and two-sided, paired t tests. For the pairwise comparison, the mean L values are L-FRE = 6.81, L-WSTF = 7.39, L-SVM = 5.09. The sentence structure-based metrics gave significantly different scores (P < 0.001) for all assessed booklets, confirmed by the Bland-Altman analysis. The study findings suggest that vocabulary-based instruments cannot be interchanged with FRE/WSTF. However, both analytical aspects should be considered and checked by authors to linguistically refine texts with respect to the individual target group. Authors of health information can be supported by automated readability analysis. Health professionals can benefit by direct booklet comparisons allowing for time-effective selection of suitable booklets for patients.
机译:可以理解的健康信息对于治疗依从性和改善的健康结果至关重要。对于可读性测试,几种仪器分析了句子结构的复杂性,例如氟氯虫读取容易(FRE)或维也纳配方(WSTF)。此外,词汇表对读者具有高相关性。本研究的目的是调查句子结构和基于词汇(SVM)工具的协议。从互联网中收集了总共52种可自由的德国患者信息小册子。为51个小册子计算了平均可理解等级L.由Bland-Altman图和双面配对T测试进行评估FRE,WSTF和SVM的结果。对于成对比较,平均值值是L-FE = 6.81,L-WSTF = 7.39,L-SVM = 5.09。基于句子结构的指标对于所有评估的书夹给出了显着不同的分数(P <0.001),由Bland-Altman分析确认。研究结果表明,基于词汇的仪器不能与FRE / WSTF互换。但是,应由作者考虑和检查分析方面,以对各个目标组进行语言上的文本。可以通过自动可读性分析来支持健康信息的作者。卫生专业人员可以通过直接的小册子比较来利用,允许有时间有效地选择适合患者的小册子。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号