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Assessment of eHealth Literacy in Healthcare Service Users: Construction and Validation of a Measurement Instrument
Abstract
Introduction
eHealth literacy is influenced by Internet access and is associated with health status. The aim of this study was to develop and validate an instrument called eHealth-Much to measure eHealth literacy in users of healthcare services.
Methods
An instrumental research design was used. Content validity was assessed by expert judgment and quantified using Aiken’s V coefficient. A polychoric correlation matrix was used for the items. Sample adequacy was assessed through the Kaiser-Meyer-Olkin (KMO) index and Bartlett's test of sphericity before conducting exploratory factor analysis (EFA). The EFA was conducted using the Weighted Least Squares (WLS) extraction method with Oblimin rotation. Reliability was assessed using Cronbach’s Alpha (α) and McDonald’s Omega (ω) coefficients.
Results
Twelve experts from five different countries participated in the content validation process, obtaining a V coefficient of 0.93 (95% CI: 0.79–0.97). A total of 1,068 health service users of both sexes participated in the construct validity testing. The median age was 32 years (IQR: 13, Q1: 26, Q3: 39; Min: 17, Max: 78). The KMO index was 0.92 (Bartlett's test, p < 0.001). The EFA suggested four factors labeled “Digital Literacy” (WLS1), “Digital Self-Management” (WLS4), “Digital Skill” (WLS3), and “Scientific Empowerment” (WLS2), which together explained 59.3% of the total variance. The reliability coefficients obtained were 0.86 for Cronbach’s alpha and 0.90 for McDonald’s omega. Percentile ranks and normative scores were also established for the sample.
Discussion
The factorial structure obtained theoretically supports the multidimensionality of the construct, aligning with previous models of digital health literacy.
Conclusion
The scale demonstrates adequate levels of validity and reliability. It may be considered a viable option for use in both primary care settings and hospital environments. Further studies are recommended to expand the psychometric analysis.
