Computer-Based Readability Testing of Information Booklets for German Cancer Patients.
Christian KeinkiRichard ZowallaMonika PobiruchinJutta HuebnerMartin WiesnerPublished in: Journal of cancer education : the official journal of the American Association for Cancer Education (2020)
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 LFRE = 6.81, LWSTF = 7.39, LSVM = 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.
Keyphrases
- health information
- social media
- healthcare
- patient reported outcomes
- end stage renal disease
- newly diagnosed
- deep learning
- high resolution
- type diabetes
- insulin resistance
- working memory
- adipose tissue
- mass spectrometry
- computed tomography
- magnetic resonance imaging
- young adults
- magnetic resonance
- single cell
- human milk
- weight loss
- replacement therapy