The COVID-19 vaccination health literacy questionnaire (CVHL-Q): Design and validation according to classic psychometric and Rasch analyses
Résumé fourni par la source
Objectives This study aimed to describe the COVID-19 vaccination health literacy questionnaire (CVHL-Q) and test its psychometric properties in the Spanish general population using Classic Test Theory (CTT) and Rasch measurement analysis. Study design A cross-sectional, observational study was conducted among the Spanish general population in February 2022. Methods An online survey was administered to a nationally representative sample of 1067 people aged 18 years or older. To measure COVID-19 Vaccination Health Literacy (CVHL) a short questionnaire was developed by the research team. The psychometric properties of the CVHL-Q were explored using Rasch analysis and CTT, following recommended practices for validation of rating scales. Results The CVHL index mean was 34.3 (SD: 11.6, range: 0–50) with 39.7 % of participants showing limited COVID-19 vaccine literacy (score ≤33 points). The instrument exhibited satisfactory internal consistency. Regarding discriminative validity, not all the a-priori hypotheses were confirmed: younger individuals had lower CVHL-Q scores, and no association was found with education level. A final model based on a random subsample of 300 participants showed a good fit to the Rasch model (χ 2 = 31.9, p = 0.044 with Benferroni correction) and satisfactory reliability (PSI = 0.718). All items displayed ordered thresholds and acceptable residual fit. Conclusions The CVHL-Q is a short, questionnaire with robust measurement properties that allow assessing the ability of population to find, understand, use and appraise the information on COVID-19 vaccines. It might be useful in designing communication campaigns and to assess pandemic preparedness.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- The COVID-19 vaccination health literacy questionnaire (CVHL-Q): Design and validation according to classic psychometric and Rasch analyses
- Date Crossref
- 01/10/2025
- Éditeur
- Elsevier BV
- Type
- journal-article
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