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Translation and Validation of Digital Competence Indicators in Greek for Health Professionals: A Cross-Sectional Study

Alexandra Karvouniari, Dimitris Karabetsos, C. Kleisiaris, Savvato Karavasileiadou, Nadiah A. Baghdadi, Virginia-Athanasia Kyrarini, Evangelia Kasagianni, Afroditi Tsalkitzi et al.

Healthcare, 2024

8 citations

Abstract

Background: it is widely accepted that living in the digital transformation era, the need to develop and update new professional skills and tools in health sectors is crucially important. Therefore, this study aimed to explore the reliability and validity of the Digital Competence Indicators tool in assessing the digital skills of Greek health professionals. Methods: in this cross-sectional study, 494 health professionals, including doctors (175) and registered nurses (319) working in four Greek hospitals were recruited and willingly participated using a convenience-sampling method. The original framework of Digital Competence Indicators was translated from English to Greek based on guidelines for cross-cultural adaptation of questionnaires. The validity of the tool was explored using confirmatory factor analysis (CFA) to verify the fit of the model using inductive techniques. The instrument reliability was confirmed using Cronbach’s alpha (α) and McDonald’s Omega coefficients. Results: the reliability was estimated at 0.826 (Cronbach’s-α) and 0.850 (McDonald’s Omega-ω). The indicators of CFA were all calculated within an ideal range of acceptance. Specifically, the CFA comparative fit index produced the following adjustment indices: x2/df = 1.152 (p = 0.037), CFI = 0.997, Lewis index (TLI) = 0.966, and root mean square error of approximation (RMSEA) = 0.018. Conclusions: The present study demonstrated that the Digital Competence Indicator instrument has high reliability,…

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Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

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