A psychometric analysis of the Italian version of the ehealth literacy scale using item response and classical test theory methods

Nicola Diviani, Alexandra Lelia Dima, Peter Johannes Schulz

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42 Scopus citations


Background: The eHealth Literacy Scale (eHEALS) is a tool to assess consumers' comfort and skills in using information technologies for health. Although evidence exists of reliability and construct validity of the scale, less agreement exists on structural validity. Objective: The aim of this study was to validate the Italian version of the eHealth Literacy Scale (I-eHEALS) in a community sample with a focus on its structural validity, by applying psychometric techniques that account for item difficulty. Methods: Two Web-based surveys were conducted among a total of 296 people living in the Italian-speaking region of Switzerland (Ticino). After examining the latent variables underlying the observed variables of the Italian scale via principal component analysis (PCA), fit indices for two alternative models were calculated using confirmatory factor analysis (CFA). The scale structure was examined via parametric and nonparametric item response theory (IRT) analyses accounting for differences between items regarding the proportion of answers indicating high ability. Convergent validity was assessed by correlations with theoretically related constructs. Results: CFA showed a suboptimal model fit for both models. IRT analyses confirmed all items measure a single dimension as intended. Reliability and construct validity of the final scale were also confirmed. The contrasting results of factor analysis (FA) and IRT analyses highlight the importance of considering differences in item difficulty when examining health literacy scales. Conclusions: The findings support the reliability and validity of the translated scale and its use for assessing Italian-speaking consumers' eHealth literacy.

Original languageEnglish
Article numbere114
JournalJournal of Medical Internet Research
Issue number4
StatePublished - Apr 2017


  • Classical test theory
  • Italian
  • Item response theory
  • Validation
  • eHEALS
  • eHealth literacy


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