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Translation and Validation of Digital Competence Indicators in Greek for Health Professionals: A Cross-Sectional Study.
- Source :
- Healthcare (2227-9032); Jul2024, Vol. 12 Issue 14, p1370, 12p
- Publication Year :
- 2024
-
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: x<superscript>2</superscript>/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, internal consistency, and construct validity and, therefore, it is suitable for measuring digital skills of health professionals. [ABSTRACT FROM AUTHOR]
- Subjects :
- DIGITAL technology
CROSS-sectional method
MULTITRAIT multimethod techniques
CRONBACH'S alpha
RESEARCH funding
RESEARCH methodology evaluation
RESEARCH evaluation
DESCRIPTIVE statistics
CHI-squared test
COMPUTER science
RESEARCH methodology
INFORMATION science
FACTOR analysis
DATA analysis software
PROFESSIONAL competence
Subjects
Details
- Language :
- English
- ISSN :
- 22279032
- Volume :
- 12
- Issue :
- 14
- Database :
- Complementary Index
- Journal :
- Healthcare (2227-9032)
- Publication Type :
- Academic Journal
- Accession number :
- 178691204
- Full Text :
- https://doi.org/10.3390/healthcare12141370