Growing the peer workforce in rural mental health and social and emotional well‐being services: A scoping review of the literature
Notice bibliographique
Résumé
INTRODUCTION: Growing the mental health peer workforce holds promise for rural communities, but we currently lack an understanding of the guidance available to support the development, implementation and sustainability of this workforce in rural settings. OBJECTIVE: Study aims are to: (1) determine the extent and nature of the literature that provides guidance for growing the peer workforce in rural mental health services; and (2) identify and explore any guidance relevant to rural peer work services dedicated to First Nations communities, including those promoting social and emotional well-being within this body of literature. DESIGN: A scoping review method was employed to identify relevant peer-reviewed and grey literature published between 2013 and 2022 across PsychInfo, Medline, Embase and CINAHL, Scopus and Informit HealthInfoNet databases, as well as targeted organisation websites and Google Advanced Search. FINDINGS: A total of 26 unique studies/projects were included from the US, UK, Canada and Australia with public mental health, non-government/for purpose and private sector service settings represented in the literature. Grey literature, such as reports of evaluations and frameworks, formed the majority of included texts. While there is a lesser volume of rurally focused literature relative to the general peer work literature, this is a rich body of knowledge, which includes guidance concerning services dedicated to First Nations communities. Via synthesis critical considerations were identified for the development, implementation and sustainability of peer work in rural mental health services across six domains: 'Working with community members and stakeholders', 'Organisational culture and governance', Working with others and in teams, Professional expertise and experience, Being part of and working in the community and 'Local mental health services capacity'. DISCUSSION: While there are considerations relevant across a range of settings, the domains of: 'working with community members and stakeholders', 'being part of and working in the community' and 'local mental health services capacity', capture additional, distinct and nuanced challenges and opportunities for growing the peer work in rural services. CONCLUSION: The literature offers insights valuable for service planning, policy development and the allocation of resources to support rural peer workforce growth.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».