MétaCan
Menu
Retour à la cohorte
Enregistrement W4396633626 · doi:10.2196/58170

Digital Health Education and Training for Undergraduate and Graduate Nursing Students: Scoping Review

2024· article· en· W4396633626 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
fundUn bailleur canadien est enregistré sur le travail.
venuePublié dans une revue dont le pays d'attache est le Canada.

Notice bibliographique

RevueJMIR Nursing · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueHealth Education and Validation
Établissements canadiensMcGill UniversityUniversity of New BrunswickUniversity of Alberta
Organismes subventionnairesSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
Mots-clésPreprintMedical educationTraining (meteorology)Graduate educationPeer reviewPsychologyNursingMedicineComputer sciencePolitical scienceGeography

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: As technology will continue to play a pivotal role in modern-day health care and given the potential impact on the nursing profession, it is vitally important to examine the types and features of digital health education in nursing so that graduates are better equipped with the necessary knowledge and skills needed to provide safe and quality nursing care and to keep abreast of the rapidly evolving technological revolution. OBJECTIVE: In this scoping review, we aimed to examine and report on available evidence about digital health education and training interventions for nursing students at the undergraduate and graduate levels. METHODS: This scoping review was conducted using the Joanna Briggs Institute methodological framework and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search strategy was developed and applied to identified bibliographic databases including MEDLINE (Ovid; 1946 to present), Embase (Ovid; 1974 to present), CINAHL (EBSCOhost; 1936 to present), ERIC (EBSCOhost; 1966 to present), Education Research Complete (EBSCOhost; inception to present), and Scopus (1976 to present). The initial search was conducted on March 3, 2022, and updated searches were completed on January 11, 2023, and October 31, 2023. For gray literature sources, the websites of select professional organizations were searched to identify relevant digital health educational programs or courses available to support the health workforce development. Two reviewers screened and undertook the data extraction process. The review included studies focused on the digital health education of students at the undergraduate or graduate levels or both in a nursing program. Studies that discussed instructional strategies, delivery processes, pedagogical theory and frameworks, and evaluation strategies for digital health education; applied quantitative, qualitative, and mixed methods; and were descriptive or discussion papers, with the exception of review studies, were included. Opinion pieces, editorials, and conference proceedings were excluded. RESULTS: A total of 100 records were included in this review. Of these, 94 records were identified from database searches, and 6 sources were identified from the gray literature. Despite improvements, there are significant gaps and limitations in the scope of digital health education at the undergraduate and graduate levels, consequently posing challenges for nursing students to develop competencies needed in modern-day nursing practice. CONCLUSIONS: There is an urgent need to expand the understanding of digital health in the context of nursing education and practice and to better articulate its scope in nursing curricula and enforce its application across professional nursing practice roles at all levels and career trajectories. Further research is also needed to examine the impact of digital health education on improving patient outcomes, the quality of nursing care, and professional nursing role advancement. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.11124/JBIES-22-00266.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,938
Score d'incertitude au seuil0,581

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,221
Tête enseignante GPT0,575
Écart entre enseignants0,354 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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