Evidence map›Paper›PMID 41029270›Full record

ArticleBMC nursing2025

Reliability and validity of the Turkish version of the digital competence questionnaire for nurses.

Arzu Bulut, Reyhan İnce Kasap, Nuray Yılmaz

Abstract read
In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Arzu BulutFaculty of Health Sciences, Department of Health Management, Bandirma Onyedi Eylul University, Bandirma, Balikesir, 10200, Türkiye. abulut@bandirma.edu.tr.ORCID https://orcid.org/0000-0001-7362-5667
Reyhan İnce KasapDirector of Health Care Services, Republic of Turkiye Ministry of Health, Bulancak State Hospital, Giresun, Türkiye.ORCID https://orcid.org/0009-0004-7067-3144
Nuray YılmazDirector of Health Care Services, Republic of Turkiye Ministry of Health, Giresun Training and Research Hospital, Giresun, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital competence is crucial for nurses adapting to technological advancements and ensuring effective patient care. The purpose of this study was to evaluate the reliability and validity of the Turkish version of the Digital Competence Questionnaire (DCQ), thus providing a scientific basis for its study application among Turkish nurses.

methodsA cross-sectional validation study was conducted with 423 registered nurses from two hospitals in the Black Sea region Turkiye using convenience sampling. Two independent samples were collected: 208 participants for exploratory factor analysis (EFA) and 215 participants for confirmatory factor analysis (CFA). The data were collected through online surveys, assessing demographic characteristics, digital competence, attitudes towards digital technology, and affinity for technology interaction. The Turkish version of DCQ was created by translating and revising the original scale, conducting item and factor analysis, and validating it with validation factor analysis.

resultsThe Turkish version of the DCQ demonstrated a two-factor structure: Knowledge and Skills, and Attitude. EFA and CFA confirmed the scale's construct validity. The CFA model fit indices indicated an excellent fit with the data. Reliability measures were high, with internal consistency and test-retest reliability. Scores on the Turkish version of the DCQ were significantly associated with technology interaction and attitudes toward digital technology. The Turkish DCQ showed robust psychometric properties, aligning with the theoretical framework of digital competence.

conclusionsThe Turkish adaptation of the DCQ is a valid and reliable instrument for assessing nurses' digital competence. It provides a valuable resource for identifying gaps in digital skills and designing targeted interventions in clinical practice. The tool also supports efforts to enhance digital literacy and integration of digital technologies within nursing education and practice in Turkiye. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AttitudeDigital competenceDigital health skillsKnowledgeNursing digital proficiencyNursing educationPsychometric validationSkills

Identifiers

PMID41029270
PMCPMC12486577

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.