Interventions for health workforce retention in rural and remote areas: a systematic review
Notice bibliographique
Résumé
BACKGROUND: Attracting and retaining sufficient health workers to provide adequate services for residents of rural and remote areas has global significance. High income countries (HICs) face challenges in staffing rural areas, which are often perceived by health workers as less attractive workplaces. The objective of this review was to examine the quantifiable associations between interventions to retain health workers in rural and remote areas of HICs, and workforce retention. METHODS: The review considers studies of rural or remote health workers in HICs where participants have experienced interventions, support measures or incentive programs intended to increase retention. Experimental, quasi-experimental and observational study designs including cohort, case-control, cross-sectional and case series studies published since 2010 were eligible for inclusion. The Joanna Briggs Institute methodology for reviews of risk and aetiology was used. Databases searched included MEDLINE (OVID), CINAHL (EBSCO), Embase, Web of Science and Informit. RESULTS: Of 2649 identified articles, 34 were included, with a total of 58,188 participants. All study designs were observational, limiting certainty of findings. Evidence relating to the retention of non-medical health professionals was scant. There is growing evidence that preferential selection of students who grew up in a rural area is associated with increased rural retention. Undertaking substantial lengths of rural training during basic university training or during post-graduate training were each associated with higher rural retention, as was supporting existing rural health professionals to extend their skills or upgrade their qualifications. Regulatory interventions requiring return-of-service (ROS) in a rural area in exchange for visa waivers, access to professional licenses or provider numbers were associated with comparatively low rural retention, especially once the ROS period was complete. Rural retention was higher if ROS was in exchange for loan repayments. CONCLUSION: Educational interventions such as preferential selection of rural students and distributed training in rural areas are associated with increased rural retention of health professionals. Strongly coercive interventions are associated with comparatively lower rural retention than interventions that involve less coercion. Policy makers seeking rural retention in the medium and longer term would be prudent to strengthen rural training pathways and limit the use of strongly coercive interventions.
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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 | 0,007 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,006 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 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 ».