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Translation and psychometric validation of instruments assessing healthcare professionals' digital competence and
Erika Jarva1, Marco Tomietto2, Wilson Tam3
1Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
Background:
As healthcare systems worldwide become increasingly digitalised, the skills, knowledge, and attitudes of healthcare professionals toward digital technologies are now recognised as essential for both everyday clinical practice and as part of broader competence framework. Previous research has studied digital competence among healthcare professionals through instrument development, yet it has lacked international scope across diverse healthcare settings. The purpose of this study was to conduct a cultural and linguistic validation of the Digital Health Competence (DigiHealthCom) and Aspects Associated with Digital Health Competence (DigiComInf) instruments. The aim was to verify the structure of the factor model in the instruments across 19 different countries and healthcare systems.
Methods:
An international multisite instrument translation, content validity assessment and survey data collection on healthcare professionals' self-evaluated digital competence were conducted between March 2022 and September 2024. The data (n = 6440) was analysed with exploratory factor analysis and confirmatory factor analysis to test the factorial structure of the DigiHealthCom and DigiComInf instruments measuring healthcare professionals' digital competence and educational and organisational factors associated.
Findings:
Scale level content validity ranged from 0.83 to 1.00 in DigiHealthCom and 0.73 to 1.00 in DigiComInf. Minor cultural adjustments were made to the items across healthcare countries. Both instruments showed high internal consistency (α = 0.95 - ω = 0.95) and the items' internal consistency varied between 0.59 and 0.86 in item-to-total correlations. Exploratory factor analysis confirmed the construct validity with five factors in DigiHealthCom and two factors in DigiComInf. Confirmatory factor analysis revealed adequate model fit in the five-factor structure in DigiHealthCom and three factor structure in DigiComInf.
Interpretation:
The findings provide preliminary support for the reliability and factorial validity of the instruments across diverse healthcare contexts and languages. However, cross-cultural measurement invariance should be established before instrument scores are compared directly between countries.
