| Title |
Computer-Based Readability Testing of Information Booklets for German Cancer Patients
|
|---|---|
| Published in |
Journal of Cancer Education, April 2018
|
| DOI | 10.1007/s13187-018-1358-0 |
| Pubmed ID | |
| Authors |
Christian Keinki, Richard Zowalla, Monika Pobiruchin, Jutta Huebner, Martin Wiesner |
| 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. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 21% |
| Student > Master | 3 | 13% |
| Student > Postgraduate | 3 | 13% |
| Researcher | 3 | 13% |
| Student > Bachelor | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 6 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 4 | 17% |
| Psychology | 3 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Computer Science | 2 | 8% |
| Other | 3 | 13% |
| Unknown | 8 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 July 2020.
All research outputs
#13,900,608
of 23,043,346 outputs
Outputs from Journal of Cancer Education
#491
of 1,151 outputs
Outputs of similar age
#176,459
of 329,221 outputs
Outputs of similar age from Journal of Cancer Education
#11
of 25 outputs
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We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.