Abstract
Background: The 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. Objective: The aim of this study was to examine the validity of the HLS-EU-Q in patients with stroke using Rasch analysis. Methods: We 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. Results: A 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. Conclusion: We 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.
| Original language | English |
|---|---|
| Pages (from-to) | 83-96 |
| Number of pages | 14 |
| Journal | Patient |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Feb 1 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- Nursing (miscellaneous)
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