Rural nursing education: a photovoice perspective
Notice bibliographique
Résumé
INTRODUCTION: For many rural Canadians nursing care is the primary and often the sole access point to health care. As such, rural nurses are an invaluable resource to the health and wellbeing of rural populations. However, due to a nursing workforce that is aging and retiring, limited resources and support, healthcare reform issues, and other factors, these rural professionals are in short supply. Because of limited opportunities to learn about rural practice settings, nursing students may be reluctant to select rural practice locations. Relevant and effective educational initiatives are needed to attract nursing students to underserved rural and remote communities so that rural people receive the health care they require. The purpose of this study was to explore the use of the innovative research approach called photovoice as an educational strategy to foster learning about and interest in rural locations and rural nursing as future practice settings. Fostering of interest in rural may help to address nursing workforce shortages in rural settings. METHODS: Thirty-eight third and fourth year nursing and health sciences students enrolled in an elective 'Rural Nursing' course used the qualitative research method photovoice to take photographs that represented challenges and facilitators of rural nursing practice. They then engaged in written reflection about their photos. Photos were to be taken in rural settings of their choice, thus fostering both urban and rural student exposure to diverse rural communities. RESULTS: One hundred forty-four photos and reflections were submitted, representing students' appreciation of diverse facilitators and challenges to rural nursing practice. Facilitators included technology, a generalist role, strong sense of community, and slower pace of life. Challenges included inadequate rural education in undergraduate nursing programs, professional isolation, safety issues, few opportunities for professional development, lack of anonymity, and insider/outsider status. Exemplar photos and reflections are provided. CONCLUSIONS: The photovoice research approach used in this rural education endeavour proved to be very useful in fostering students' exposure to, interest in, and understanding of rural settings and their influence on rural nursing practice. Photovoice is also recommended for use in rural courses other than nursing. Suggested strategies include group photovoice experience and the expansion of reflection to enhance rural health research.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,007 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».