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Enregistrement W4405192624 · doi:10.1111/jan.16667

Interpreting Context in Rural and Remote Aged Care Facilities in Readiness for a New Care Model: A Mixed Method Study

2024· article· en· W4405192624 sur OpenAlexaboutno aff
Alison Craswell, Karen Watson, Marianne Wallis, Janet Baker, Katharina Merollini, Kaye Coates, Alison Mudge

Notice bibliographique

RevueJournal of Advanced Nursing · 2024
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGeriatric Care and Nursing Homes
Établissements canadiensnon disponible
Organismes subventionnairesHealth Innovation, Investment and Research Office
Mots-clésAged careContext (archaeology)NursingMedicineMedical emergencyGeography

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Geographical isolation compounds limited access to healthcare services and skilled workforce for the provision of rural aged care. Residents have complex chronic disease management and end-of-life care needs. An undersupply of general medical practitioners due to retirement, attrition or unfilled training places in Australia has impacted recruitment to rural areas. Nurse practitioners have been identified as a potential solution. AIM: To describe and explore the inner (local and organisational) and outer (wider health system) contexts of healthcare, from the perspective of care staff and residents' families. This, in turn, aims to inform the planned implementation of a nurse practitioner model, in several aged care facilities, operating within rural and remote settings, in Queensland Australia. DESIGN: A convergent mixed methods design. METHODS: Qualitative data were collected, in 2022-2023, using semistructured interviews with staff focusing on role, knowledge development, workplace culture and care relationships with local community. Resident's family's perspectives were obtained as a secondary analysis of organisational feedback data. Quantitative data were collected from direct care workers using the Alberta Context Tool for Long-Term Care. Data were analysed according to type and integrated. RESULTS: Relational care for residents and families is highly valued but provision of quality is challenging where time-poor staff are perceived to be doing the best they can. Scarce local healthcare services make it difficult to meet resident healthcare needs. Despite the supportive organisational culture, evolving policy requirements have impacted already difficult staff recruitment in rural settings. CONCLUSION: Identifying contextual needs of organisations in readiness for change highlights geographical and sectoral nuances influencing any future implementation. As government policy changes to improve the older adult care sector, rural and remote facilities are forced to increasingly adapt. IMPLICATIONS FOR THE PROFESSION: Context-specific needs extend far beyond a nurse practitioner providing additional expertise in care provision. IMPACT STATEMENTS: What problem did the study address? Nurse practitioners have been successfully implemented into residential aged care facilities in metropolitan and major regional centres but translating this role into rural and remote Australia requires being cognisant of the needs, unique challenges and context of this setting. What were the main findings? In an organisational culture of support, the importance of staff providing relational care and having connection with older adult residents and families was a central driver. It was challenging for staff to meet complex care requirements in the absence of local healthcare options and support. Time pressures, from inadequate staffing and changing structural aged care sector, force the prioritising of care requirements. Where and on whom will the research have an impact? Older adults, policy makers and aged care providers will benefit from understanding the context of rural and remote settings, particularly in identifying potential solutions when there are gaps in primary and secondary healthcare. REPORTING METHOD: The GRAMMS checklist was followed in reporting of this study. PATIENT OR PUBLIC CONTRIBUTION: Two lived experience consumers were involved as research team members. One was involved during the development and submission of the funding application and another during project activities including data collection and analysis and the development of publications.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,021
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,021
Score d'incertitude au seuil0,110

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0210,015
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0050,002
Communication savante0,0050,003
Science ouverte0,0020,004
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,038
Tête enseignante GPT0,448
Écart entre enseignants0,410 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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Même revueJournal of Advanced NursingMême sujetGeriatric Care and Nursing HomesTravaux en français237 207