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Psychometric properties of the Hungarian version of the eHealth Literacy Scale

Author

Listed:
  • Zsombor Zrubka

    (Corvinus University of Budapest
    Corvinus University of Budapest)

  • Ottó Hajdu

    (Eötvös Loránd University)

  • Fanni Rencz

    (Corvinus University of Budapest
    Hungarian Academy of Sciences)

  • Petra Baji

    (Corvinus University of Budapest)

  • László Gulácsi

    (Corvinus University of Budapest)

  • Márta Péntek

    (Corvinus University of Budapest)

Abstract

Background We adapted the eHealth Literacy Scale (eHEALS) for Hungary and tested its psychometric properties on a large representative online sample of the general population. Methods The Hungarian version of eHEALS was developed using forward–backward translation. For the valuation study, 1000 respondents were recruited in early 2019 from a large online panel by a survey company. We tested internal consistency, test–retest reliability and construct and criterion validity using classical test theory, as well as item characteristics using an item-response theory (IRT) graded response model (GRM). Results 55% of respondents were female, and 22.1% were ≥ 65 years old. Mean eHEALS score was 29.2 (SD: 5.18). Internal consistency was good (Cronbach’s α = 0.90), and test–retest reliability was moderate (intraclass correlation r = 0.64). We identified a single-factor structure by exploratory factor analysis, explaining 85% of test variance. Essential criteria for GRM analysis were met. Items 3 and 4 (search of health resources) were the least difficult, followed by items 5 and 8 (utilisation of health information), and then items 1 and 2 (awareness of health resources). Items 6 and 7 (appraisal of health resources) were most difficult. The measurement properties of eHEALS were not affected by gender, age, education or income levels. Female gender, older age, intensity of health information seeking, formal health education and visit at the electronic health-record website were associated with higher eHEALS scores, as well as best and worst self-perceived health states, BMI

Suggested Citation

  • Zsombor Zrubka & Ottó Hajdu & Fanni Rencz & Petra Baji & László Gulácsi & Márta Péntek, 2019. "Psychometric properties of the Hungarian version of the eHealth Literacy Scale," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(1), pages 57-69, June.
    • Handle: RePEc:spr:eujhec:v:20:y:2019:i:1:d:10.1007_s10198-019-01062-1
    DOI: 10.1007/s10198-019-01062-1
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    References listed on IDEAS

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    1. Judith Aponte & Kathleen M. Nokes, 2017. "Validating an electronic health literacy scale in an older hispanic population," Journal of Clinical Nursing, John Wiley & Sons, vol. 26(17-18), pages 2703-2711, September.
    2. Rizopoulos, Dimitris, 2006. "ltm: An R Package for Latent Variable Modeling and Item Response Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i05).
    3. Leonard Feldt, 1969. "A test of the hypothesis that cronbach's alpha or kuder-richardson coefficent twenty is the same for two tests," Psychometrika, Springer;The Psychometric Society, vol. 34(3), pages 363-373, September.
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    Cited by:

    1. Óscar Brito Fernandes & Márta Péntek & Dionne Kringos & Niek Klazinga & László Gulácsi & Petra Baji, 2020. "Eliciting preferences for outpatient care experiences in Hungary: A discrete choice experiment with a national representative sample," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    2. Amit S. Malhan & Kiarash Sadeghi-R & Robert Pavur & Lou Pelton, 2024. "Healthcare information management and operational cost performance: empirical evidence," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(6), pages 963-977, August.

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    More about this item

    Keywords

    eHEALS; eHealth literacy; Item-response theory; Validation; Hungary; EQ-5D-5L;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General

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