Psychometric properties of the Hungarian version of the eHealth Literacy Scale

• Published in: The European journal of health economics Vol. 20; no. Suppl 1; pp. S57 - S69
• Main Authors: Zrubka, Zsombor, Hajdu, Ottó, Rencz, Fanni, Baji, Petra, Gulácsi, László, Péntek, Márta
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer 01-06-2019; Springer Berlin Heidelberg; Springer Nature B.V
• Subjects: Adolescent; Adult; Age Factors; Aged; Aged, 80 and over; Classical test theory; Consumer Health Information - methods; Cross-Sectional Studies; Economic Policy; Education; Electronic Health Records - statistics & numerical data; Factor analysis; Female; Health Behavior; Health Care Management; Health Economics; Health Knowledge, Attitudes, Practice; Health Literacy - statistics & numerical data; Humans; Hungary; Information Seeking Behavior; Item response theory; Literacy; Male; Medicine; Medicine & Public Health; Middle Aged; Original Paper; Pharmacoeconomics and Health Outcomes; Psychometrics; Public Finance; Public Health; Quantitative psychology; Reproducibility of Results; Sex Factors; Socioeconomic Factors; Surveys and Questionnaires - standards; Telemedicine - statistics & numerical data; Young Adult; Hungary; eHealth literacy; Validation; Item-response theory; Hungary; eHEALS; I10; EQ-5D-5L
• ISSN: 1618-7598; 1618-7601
• DOI: 10.1007/s10198-019-01062-1

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 a = 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 healthrecord 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.