The effectiveness of ethno-specific and mainstream health services: an evidence gap map
Notice bibliographique
Résumé
Abstract Background People of culturally and linguistically diverse (CALD) background face significant barriers in accessing effective health services in multicultural countries such as the United States, Canada, Europe and Australia. To address these barriers, government and nongovernment organisations globally have taken the approach of creating ethno-specific services, which cater to the specific needs of CALD clients. These services are often complementary to mainstream services, which cater to the general population including CALD communities. Methods This systematic review uses the Evidence Gap Map (EGM) approach to map the available evidence on the effectiveness of ethno-specific and mainstream services in the Australian context. We reviewed Scopus, Web of Science and PubMed databases for articles published from 1996 to 2021 that assessed the impact of health services for Australian CALD communities. Two independent reviewers extracted and coded all the documents, and discussed discrepancies until reaching a 100% agreement. The main inclusion criteria were: 1) time (published after 1996); 2) geography (data collected in Australia); 3) document type (presents results of empirical research in a peer-reviewed outlet); 4) scope (assesses the effectiveness of a health service on CALD communities). We identified 97 articles relevant for review. Results Ninety-six percent of ethno-specific services (i.e. specifically targeting CALD groups) were effective in achieving their aims across various outcomes. Eighteen percent of mainstream services (i.e. targeting the general population) were effective for CALD communities. When disaggregating our sample by outcomes (i.e. access, satisfaction with the service, health and literacy), we found that 50 % of studies looking at mainstream services’ impact on CALD communities found that they were effective in achieving health outcomes. The use of sub-optimal methodologies that increase the risk of biased findings is widespread in the research field that we mapped. Conclusions Our findings provide partial support to the claims of advocacy stakeholders that mainstream services have limitations in the provision of effective health services for CALD communities. Although focusing on the Australian case study, this review highlights an under-researched policy area, proposes a viable methodology to conduct further research on this topic, and points to the need to disaggregate the data by outcome (i.e. access, satisfaction with the service, health and literacy) when assessing the comparative effectiveness of ethno-specific and mainstream services for multicultural communities.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,063 | 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 ».