Literature DB >> 18999150

Creating a gold standard for the readability measurement of health texts.

Sasikiran Kandula1, Qing Zeng-Treitler.   

Abstract

Developing easy-to-read health texts for consumers continues to be a challenge in health communication. Though readability formulae such as Flesch-Kincaid Grade Level have been used in many studies, they were found to be inadequate to estimate the difficulty of some types of health texts. One impediment to the development of new readability assessment techniques is the absence of a gold standard that can be used to validate them. To overcome this deficiency, we have compiled a corpus of 324 health documents consisting of six different types of texts. These documents were manually reviewed and assigned a readability level (1-7 Likert scale) by a panel of five health literacy experts. The expert assigned ratings were found to be highly correlated with a patient representatives readability rating (r = 0.81, p<0.0001).

Entities:  

Mesh:

Year:  2008        PMID: 18999150      PMCID: PMC2655974     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  2 in total

1.  Assessing readability of consumer health information: an exploratory study.

Authors:  Darren Gemoets; Graciela Rosemblat; Tony Tse; Robert Logan
Journal:  Stud Health Technol Inform       Date:  2004

2.  Beyond surface characteristics: a new health text-specific readability measurement.

Authors:  Hyeoneui Kim; Sergey Goryachev; Graciela Rosemblat; Allen Browne; Alla Keselman; Qing Zeng-Treitler
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11
  2 in total
  13 in total

1.  Readability assessment of online patient education materials provided by the European Association of Urology.

Authors:  Patrick Betschart; Valentin Zumstein; Maico Bentivoglio; Daniel Engeler; Hans-Peter Schmid; Dominik Abt
Journal:  Int Urol Nephrol       Date:  2017-09-13       Impact factor: 2.370

2.  Improving Patient Education Materials: A Practical Algorithm from Development to Validation.

Authors:  Patrick Betschart; Sergej E Staubli; Valentin Zumstein; Christa Babst; Rafael Sauter; Hans-Peter Schmid; Dominik Abt
Journal:  Curr Urol       Date:  2019-10-01

3.  Readability Assessment of Commonly Used German Urological Questionnaires.

Authors:  Pavel Lyatoshinsky; Manolis Pratsinis; Dominik Abt; Hans-Peter Schmid; Valentin Zumstein; Patrick Betschart
Journal:  Curr Urol       Date:  2019-10-01

4.  Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

Authors:  Renu Balyan; Scott A Crossley; William Brown; Andrew J Karter; Danielle S McNamara; Jennifer Y Liu; Courtney R Lyles; Dean Schillinger
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

5.  An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study.

Authors:  Biyang Yu; Zhe He; Aiwen Xing; Mia Liza A Lustria
Journal:  J Med Internet Res       Date:  2020-05-21       Impact factor: 5.428

6.  Internet-Based Patient Education Materials Regarding Diabetic Foot Ulcers: Readability and Quality Assessment.

Authors:  David Michael Lee; Elysia Grose; Karen Cross
Journal:  JMIR Diabetes       Date:  2022-01-11

7.  Predicting the readability of physicians' secure messages to improve health communication using novel linguistic features: Findings from the ECLIPPSE study.

Authors:  Scott A Crossley; Renu Balyan; Jennifer Liu; Andrew J Karter; Danielle McNamara; Dean Schillinger
Journal:  J Commun Healthc       Date:  2020-09-24

8.  Health recommender systems: concepts, requirements, technical basics and challenges.

Authors:  Martin Wiesner; Daniel Pfeifer
Journal:  Int J Environ Res Public Health       Date:  2014-03-03       Impact factor: 3.390

9.  Readability of written medicine information materials in Arabic language: expert and consumer evaluation.

Authors:  Sinaa Al Aqeel; Norah Abanmy; Abeer Aldayel; Hend Al-Khalifa; Maha Al-Yahya; Mona Diab
Journal:  BMC Health Serv Res       Date:  2018-02-27       Impact factor: 2.655

10.  Readability assessment of commonly used urological questionnaires.

Authors:  Patrick Betschart; Dominik Abt; Hans-Peter Schmid; Pascal Viktorin; Janine Langenauer; Valentin Zumstein
Journal:  Investig Clin Urol       Date:  2018-08-02
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