Digital Leadership Scale for Clinical Nurses (DLS-CN) : Development and Validation of Instrument (Preprint)
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Résumé
<sec> <title>BACKGROUND</title> The rapid advancement of digital technologies, combined with the evolving complexity of healthcare environments, has introduced a new paradigm in nursing practice. Clinical nurses are now required not only to deliver safe and effective patient care but also to demonstrate competencies in digital literacy and innovation. Among these emerging competencies, digital leadership has become a critical attribute—enabling nurses to lead digital transformation, ensure patient safety, enhance care quality, and support system-level change within healthcare organizations. Despite its increasing relevance, there is a notable absence of validated measurement tools tailored to assess digital leadership in clinical practice. </sec> <sec> <title>OBJECTIVE</title> This study aimed to develop and psychometrically validate a Digital Leadership Scale for Clinical Nurses (DLS-CN) to systematically evaluate the digital leadership of nurses working in clinical settings. </sec> <sec> <title>METHODS</title> The scale development process followed a rigorous multi-step procedure. Initial items were derived from previous qualitative research involving a literature review and in-depth interviews, complemented by an additional literature review in this study. The content validity of 38 preliminary items was evaluated by nine experts over two rounds. A pilot test was conducted with 30 nurses, followed by cognitive interviews with five nurses to refine item clarity and relevance. The final set of items was administered to 446 clinical nurses across various healthcare institutions. Data were randomly split for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Additional analyses were conducted to evaluate item discrimination, convergent validity, and internal consistency using IBM SPSS 25.0 and AMOS 23.0. </sec> <sec> <title>RESULTS</title> The finalized DLS-CN consists of 29 items grouped under four domains: (1) ability to utilize digital technology, (2) digital safety management, (3) digital collaboration mindset, and (4) organizational influence. These four factors explained 56.9% of the total variance. The scale showed strong internal consistency (Cronbach’s α = .95). Convergent validity was demonstrated through strong positive correlations with the Nursing Informatics Competency Scale (r = .82, p < .001) and the Self-Leadership Scale (r = .83, p < .001). </sec> <sec> <title>CONCLUSIONS</title> The DLS-CN is a valid and reliable instrument for measuring digital leadership among clinical nurses. It offers a practical tool for educators, administrators, and researchers to assess and enhance digital leadership capabilities—ultimately supporting the digital transformation of healthcare systems. </sec> <sec> <title>CLINICALTRIAL</title> <p/> </sec>
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle