Evidence map›Paper›PMID 29651761›Full record

ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2019

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

Christian Keinki, Richard Zowalla, Monika Pobiruchin, Jutta Huebner, Martin Wiesner

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Christian KeinkiDepartment of Hematology and Medical Oncology, University Hospital Jena, Am Klinikum 1, 07747, Jena, Germany. christian.keinki@med.uni-jena.de.ORCID http://orcid.org/0000-0001-9569-7346
Richard ZowallaDepartment of Medical Informatics, Heilbronn University, Max-Planck-Str. 39, 74081, Heilbronn, Germany.
Monika PobiruchinGECKO Institute, Heilbronn University, Max-Planck-Str. 39, 74081, Heilbronn, Germany.
Jutta HuebnerDepartment of Hematology and Medical Oncology, University Hospital Jena, Am Klinikum 1, 07747, Jena, Germany.
Martin WiesnerDepartment of Medical Informatics, Heilbronn University, Max-Planck-Str. 39, 74081, Heilbronn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 L

Indexed as

Health LiteracyReadingVocabularyComprehensionGermanyHumansInformation DisseminationInternetNeoplasmsPatient Education as TopicEvidence-based health informationPatient information bookletsReadabilitySupport vector machineUnderstandability

Identifiers

PMID29651761

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.