Evidence map›Paper›PMID 28710681›Full record

ArticleThe patient2018

Evaluating the European Health Literacy Survey Questionnaire in Patients with Stroke: A Latent Trait Analysis Using Rasch Modeling.

Yi-Jing Huang, Cheng-Te Chen, Gong-Hong Lin, Tzu-Yi Wu, Sheng-Shiung Chen, Li-Fong Lin, Wen-Hsuan Hou, Ching-Lin Hsieh

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in The patient, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 5% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  9. Patients' understanding of health information in Germany.Patient preference and adherence · 2019
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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

8 authors at 6 institutions in 1 country.

Yi-Jing HuangSchool of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.
Cheng-Te ChenDepartment of Educational Psychology and Counseling, National Tsing Hua University, Hsinchu, Taiwan.
Gong-Hong LinSchool of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.
Tzu-Yi WuInstitute of Economics, Academia Sinica, Taipei, Taiwan.
Sheng-Shiung ChenDepartment of Physical Medicine and Rehabilitation, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan.
Li-Fong LinDepartment of Physical Medicine and Rehabilitation, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.
Wen-Hsuan HouSchool of Gerontology and Health Management, College of Nursing, Taipei Medical University, Taipei, Taiwan. houwh@tmu.edu.tw.
Ching-Lin HsiehSchool of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.
National Taiwan University · TWE-Da Hospital · TWInstitute of Economics, Academia Sinica · TWNational Tsing Hua University · TWTaipei Medical University Hospital · TWTaipei Medical University-Shuang Ho Hospital · TW

Funding

E-Da Hospital EDAHT104015Ministry of Science and Technology, Taiwan NSC-102-2314-B-038-007-MY3 and MOST-105-2314-B-038-012National Health Research Institutes NHRI-EX104-10207PI
6 · The paper itself

Abstract

backgroundThe effective self-management and treatment of long-term disability after stroke depends greatly on the health literacy of patients. The European Health Literacy Survey Questionnaire (HLS-EU-Q) is a comprehensive and theory-based measure that captures multiple self-perceived competencies of health literacy and covers a diverse range of health contexts. However, there is no psychometric evidence on the HLS-EU-Q in the stroke population.

objectiveThe aim of this study was to examine the validity of the HLS-EU-Q in patients with stroke using Rasch analysis.

methodsWe compared the model deviance among the one-domain, three-domain, four-domain, and 12-domain structures using likelihood ratio tests to determine the dimensionality of the HLS-EU-Q. Thereafter, we examined the unidimensionality of each domain, local independence, item fit, response categories, and differential item functioning (DIF) for the best fitting structure.

resultsA total of 311 patients with stroke participated in this study. Rasch analysis revealed that the 12-domain HLS-EU-Q demonstrated the best data-model fit. The original 4-point scales showed disordering, which can be corrected by rescaling them as 3-point scales with the two middle categories collapsed. All 47 items in the rescaled HLS-EU-Q fit the 12-domain Rasch model, demonstrated local independence, assessed the 12 unidimensional domains respectively, and had invariant difficulties between different age or education groups of the patients with stroke.

conclusionWe recommend using the 12-domain scores of the rescaled HLS-EU-Q to comprehensively and accurately capture the competencies to access, understand, appraise, and apply health information within the three health contexts of healthcare, disease prevention, and health promotion for patients with stroke.

Indexed as

Health Knowledge, Attitudes, PracticeHealth LiteracyAgedChronic DiseaseCommunicationFemaleHospitals, TeachingHumansMaleMiddle AgedPatient Education as TopicProspective StudiesPsychometricsReproducibility of ResultsSelf-ManagementStroke

Identifiers

PMID28710681
OpenAlexW2735825644

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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.