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Enregistrement W2966411141 · doi:10.22605/rrh5347

'We have to drive everywhere': rural nurses and their precepted students

2019· article· en· W2966411141 sur OpenAlexaffabout
Olive Yonge, Deirdre Jackman, Florence Luhanga, Florence Myrick, Tracy Oosterbroek, Vicki Foley

Notice bibliographique

RevueRural and Remote Health · 2019
Typearticle
Langueen
DomaineNursing
ThématiqueNursing Education, Practice, and Leadership
Établissements canadiensUniversity of Prince Edward IslandUniversity of ReginaUniversity of LethbridgeUniversity of Alberta HospitalUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésSnowball samplingPhotovoiceNursingQualitative researchParticipant observationPsychologyRural areaMedicineMedical educationSociology

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Travel safety culture is a vital aspect of nursing in rural western Canada, where long distances and severe weather are commonplace. However, this culture is poorly understood owing to the absence of official policy, and the tendency of rural nurses to take travel risks and burdens in stride, rather than advocating for change. Travel risks and burdens include extreme weather events such as tornadoes and blizzards; unmarked routes and hazards; distance, time and expense; and driver fatigue. In such rural settings, the safety and health of visitors, novices and students are of particular concern. The researchers sought to elicit the tacit knowledge of rural registered nurses, and their students undertaking rural nursing preceptorships, pertaining to rural travel issues and best practices for safety and wellbeing. METHODS: Through purposive and snowball sampling, the researchers recruited seven senior nursing students and five nurse preceptors. Seven rural acute and community care sites, between 42 km and 416 km distant from the students' primary place of study, were covered by the study. Photovoice, a participant action modality, was employed to collect photographic and qualitative interview data from participants over 10 weeks, between February and April 2016. The data were analyzed thematically, in collaboration with participants, who in turn validated the results. A digital storytelling initiative was attempted, to further involve participants in dissemination of findings, but only one participant took part in this phase of the project. RESULTS: The central finding of the study was that nursing students learn to accept and manage limitations - and to recognize and capitalize on opportunities - when undertaking rural preceptorships. With regard to road safety, the students were found to be particularly vulnerable to long distances, hazardous conditions, fuel and cellular data expenses, and fatigue. These issues were compounded by the students' reluctance to speak up, or to miss shifts, when they felt unsafe or unwell. Their preceptors role modeled autonomy and community ethos as the foundations of a frontline, extemporaneous road safety culture. This entailed personal safety measures borne from rural experience and background, familiarity with the countryside, and community connectedness with other healthcare sites in place of any official public alert system. The preceptors furthermore benefited from strong union protection for occupational health and safety concerns, but students being taught in rural settings had no such advantage. CONCLUSIONS: Nursing students should have the same occupational health and safety protections as their rural preceptors, especially the right to refuse travel, without penalty, in unsafe circumstances. Better travel subsidies and road safety measures during rural preceptorship may help increase the likelihood of students considering a rural career path. Furthermore, the frontline, community-based road safety experience of rural nurses is an untapped source of information for educators and policymakers. Such information will become more and more vital as a diminishing number of rural nurses are called upon to care for an aging client base.

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)0,000
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: Empirique
Score de désaccord entre enseignants0,759
Score d'incertitude au seuil0,644

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
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 Opus0,021
Tête enseignante GPT0,343
Écart entre enseignants0,323 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

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

En bref

Citations6
Publié2019
Routes d'admission2
Résumé présentoui

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