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Psychometric properties of the Hungarian version of the eHealth Literacy Scale
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 re...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544600/ https://www.ncbi.nlm.nih.gov/pubmed/31098883 http://dx.doi.org/10.1007/s10198-019-01062-1 |
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author | Zrubka, Zsombor Hajdu, Ottó Rencz, Fanni Baji, Petra Gulácsi, László Péntek, Márta |
author_facet | Zrubka, Zsombor Hajdu, Ottó Rencz, Fanni Baji, Petra Gulácsi, László Péntek, Márta |
author_sort | Zrubka, Zsombor |
collection | PubMed |
description | 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 < 25 and participation at health screenings over the past year. CONCLUSIONS: The Hungarian eHEALS is a useful and valid tool for measuring subjective eHealth literacy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10198-019-01062-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6544600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-65446002019-06-19 Psychometric properties of the Hungarian version of the eHealth Literacy Scale Zrubka, Zsombor Hajdu, Ottó Rencz, Fanni Baji, Petra Gulácsi, László Péntek, Márta Eur J Health Econ Original Paper 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 < 25 and participation at health screenings over the past year. CONCLUSIONS: The Hungarian eHEALS is a useful and valid tool for measuring subjective eHealth literacy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10198-019-01062-1) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2019-05-16 2019 /pmc/articles/PMC6544600/ /pubmed/31098883 http://dx.doi.org/10.1007/s10198-019-01062-1 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Zrubka, Zsombor Hajdu, Ottó Rencz, Fanni Baji, Petra Gulácsi, László Péntek, Márta Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title | Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title_full | Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title_fullStr | Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title_full_unstemmed | Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title_short | Psychometric properties of the Hungarian version of the eHealth Literacy Scale |
title_sort | psychometric properties of the hungarian version of the ehealth literacy scale |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544600/ https://www.ncbi.nlm.nih.gov/pubmed/31098883 http://dx.doi.org/10.1007/s10198-019-01062-1 |
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