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

  • Christian Keinki
  • Richard Zowalla
  • Monika Pobiruchin
  • Jutta Huebner
  • Martin Wiesner
Article

Abstract

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.

Keywords

Evidence-based health information Patient information booklets Readability Understandability Support vector machine 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© American Association for Cancer Education 2018

Authors and Affiliations

  1. 1.Department of Hematology and Medical OncologyUniversity Hospital JenaJenaGermany
  2. 2.Department of Medical InformaticsHeilbronn UniversityHeilbronnGermany
  3. 3.GECKO InstituteHeilbronn UniversityHeilbronnGermany

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