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Enregistrement W4407610033 · doi:10.1186/s12909-025-06780-0

Factors related to professional commitment of nursing students: a systematic review and thematic synthesis

2025· review· en· W4407610033 sur OpenAlexaboutno aff
Hengxi Chen, Yali Chen, Ai Zheng, Tan Xin, Ling Han

Notice bibliographique

RevueBMC Medical Education · 2025
Typereview
Langueen
DomaineNursing
ThématiqueNursing education and management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésThematic analysisMedical educationPsychologyNursingMedicineQualitative researchSociology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: To identify the factors related to nursing students' professional commitment. Such research can assist in identifying strategies that can be used to cultivate and strengthen professional commitment among nursing students, which can ultimately help address nursing shortages and improve the overall quality of care. METHODS: A systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). PubMed, EMBASE, MEDLINE, CINAHL, Cochrane Library, Web of Science were searched for English-language articles from inception and July 1, 2024.Studies were systematically screened for inclusion based on predetermined eligibility criteria. The studies were quality assessed using Non-Randomized Studies (RoBANS), the JBI Critical Appraisal Checklist, the Newcastle-Ottawa Scale (NOS), Mixed-Method Appraisal Tool (MMAT), and data were analyzed using thematic analysis. A thematic synthesis was performed to identify descriptive themes across all included studies. The process involved intensive reading of the literature, followed by the extraction of qualitative data, which was organized into topically similar codes. Researchers collaborated to merge related codes into subthemes, which were then consolidated into main themes for the final report. RESULTS: A total of 1,165 studies were identified from the search, and 16 met the predetermined inclusion criteria. Three key themes emerged from the synthesis: individual factors (age, gender, region, psychological well-being, motivation, self-efficacy, career choice and individual perception), educational factors (educator impact, academic achievement, clinical experience and learning environment) and family and social factors (family influence, influence from others and social perception).Key findings indicate that age, gender, and region significantly impact professional commitment, with female students displaying greater growth post-internship. Psychological well-being is a crucial factor, with perceived stress adversely affecting commitment levels. Motivation, self-efficacy, and pre-internship commitment are pivotal in fostering long-term engagement in the profession. Additionally, involuntary career choices correlate with lower commitment, highlighting the importance of informed decision-making. Educators play a vital role, as supportive teaching practices enhance student well-being and commitment. Academic achievement and clinical experiences further influence professional dedication. Family support and social perceptions, including occupational stigma, are also crucial in shaping commitment levels. Collectively, these findings underscore the necessity of a supportive educational environment and societal perceptions to enhance nursing professional commitment. CONCLUSIONS: This review identifies key factors influencing nursing students' professional commitment, including individual, educational, family, and social influences. To enhance commitment, it is essential to foster psychological well-being, motivation, and self-efficacy within supportive educational environments. Implementing mentorship programs and addressing societal perceptions can mitigate stigma and strengthen commitment. These findings highlight the need for targeted interventions in nursing education and policy to improve workforce retention and care quality. Future research should assess the long-term impact of these strategies. REGISTRATION: The protocol for the conduct of this study was registered on the International Prospective Register of Systematic Reviews (PROSPERO) with the registration number CRD42024564848.

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.

Comment cette classification a été obtenuedéplier

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)0,011
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,172
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
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 Opus0,064
Tête enseignante GPT0,467
Écart entre enseignants0,403 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations17
Publié2025
Routes d'admission1
Résumé présentoui

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