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

DIGCOMP framework digital skills healthcare professionals instrument

Journal

Healthcare (Basel, Switzerland)
ISSN: 2227-9032
Titre abrégé: Healthcare (Basel)
Pays: Switzerland
ID NLM: 101666525

Informations de publication

Date de publication:
09 Jul 2024
Historique:
received: 05 06 2024
revised: 05 07 2024
accepted: 05 07 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 26 7 2024
Statut: epublish

Résumé

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. 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. 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 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.

Sections du résumé

BACKGROUND 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 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 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
CONCLUSIONS 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.

Identifiants

pubmed: 39057513
pii: healthcare12141370
doi: 10.3390/healthcare12141370
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
ID : Supporting Project number (PNURSP2024R293)

Auteurs

Alexandra Karvouniari (A)

Department of Nursing, School of Health Science, Hellenic Mediterranean University, 71410 Heraklion Crete, Greece.

Dimitrios Karabetsos (D)

Department of Neurosurgery, University Hospital of Heraklion, 71500 Heraklion Crete, Greece.

Christos F Kleisiaris (CF)

Department of Nursing, University of Thessaly, Gaiopolis, 41500 Larissa, Greece.

Savvato Karavasileiadou (S)

Department of Community Health Nursing, College of Nursing, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

Nadiah Baghdadi (N)

Nursing Management and Education Department, College of Nursing, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

Virginia-Athanasia Kyrarini (VA)

Department of Mathematics, University of Patras, 26504 Rio, Greece.

Evangelia Kasagianni (E)

424 General Army Training Hospital, 56429 Thessaloniki, Greece.

Afroditi Tsalkitzi (A)

401 General Military Hospital of Athens, 11525 Athens, Greece.

Maria Malliarou (M)

Department of Nursing, University of Thessaly, Gaiopolis, 41500 Larissa, Greece.

Christos Melas (C)

Department of Nursing, School of Health Science, Hellenic Mediterranean University, 71410 Heraklion Crete, Greece.

Classifications MeSH