Validation of the COVID-19 Digital Health Literacy Instrument in the Italian Language: A Cross-Sectional Study of Italian University Students

Chiara Lorini, Veronica Velasco, Guglielmo Bonaccorsi, Kevin Dadaczynski, Orkan Okan, Patrizio Zanobini and Luca P. Vecchio
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Chiara Lorini: Department of Health Science, University of Florence, 50134 Florence, Italy
Veronica Velasco: Department of Psychology, University of Milano-Bicocca, 20123 Milan, Italy
Guglielmo Bonaccorsi: Department of Health Science, University of Florence, 50134 Florence, Italy
Kevin Dadaczynski: Department of Health Science, Fulda University of Applied Sciences, 36037 Fulda, Germany
Orkan Okan: Department of Sports and Health Science, Technical University Munich, 80992 Munich, Germany
Patrizio Zanobini: Department of Health Science, University of Florence, 50134 Florence, Italy
Luca P. Vecchio: Department of Psychology, University of Milano-Bicocca, 20123 Milan, Italy

IJERPH, 2022, vol. 19, issue 10, 1-17

Abstract: The Coronavirus Disease 19 (COVID-19) pandemic and the associated “infodemic” have shown the importance of surveillance and promotion of health literacy, especially for young adults such as university students who use digital media to a very high degree. This study aimed to assess the validity and reliability of the Italian version of the COVID-19 adapted version of the Digital Health Literacy Instrument (DHLI). This cross-sectional study is part of the COVID-19 University Students Survey involving 3985 students from two Italian universities. First, item analysis and internal consistency were assessed. Then, Principal Component Analysis (PCA) and Confirmatory Factor Analyses (CFA) were performed comparing different models. The Italian DHLI showed good psychometric characteristics. The protecting privacy subscale was excluded, given the criticalities presented in the validation process. CFA confirmed the four-factor structure, also including a high-order factor. This result allows using the scale to measure a global level of digital health literacy and consider its levels separately for each construct component: searching the web for information, evaluating reliability, determining personal relevance, and adding self-generated content.

Keywords: digital health literacy; COVID-19; university students; infodemic; measurement; scale validation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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