A scoping review of the levels, implementation strategies, enablers, and barriers to cervical, breast, and colorectal cancer screening among migrant populations in selected English-speaking high-income countries
Notice bibliographique
Résumé
BACKGROUND: Cancer remains one of the leading causes of mortality and morbidity worldwide with colorectal, cervical, and breast cancers accounting for significant proportion of preventable deaths. Early screening, diagnosis, and treatment could prevent many of these deaths. However, migrants face persistent disparities in the screening, early diagnosis, and treatment of these cancers. This study synthesizes evidence on cancer screening uptake, implementation strategies, as well as their enablers and barriers among migrants in English-speaking high-income countries (Australia, the USA, the UK, Canada, and New Zealand). METHODS: We conducted a scoping review of studies published in any language between 1 January 2015 and 31 December 2024. Studies were retrieved from four databases: PubMed, Scopus, Embase, and Web of Science. Search terms were developed based on four domains: types of cancer (colorectal, cervical, and breast), migrant populations, screening coverage, and country of residence. The uptake of cancer screening among migrants in selected countries was determined. A thematic analysis was conducted to analyze the data and identify key themes related to the implementation of cancer screening strategies, as well as their enablers and barriers. RESULTS: A total of 80 studies were included in the review. Migrants exhibited varied levels of utilization of cancer screening such as cervical cancer (41% - 84%), breast cancer (24%-87%), and colorectal cancer (4%-55%). Four themes related to the implementation of cancer screening strategies were identified: i) culturally tailored health education and communication, ii) trust-building initiatives with providers and health systems, iii) family and community support for acculturation and engagement, iv) awareness and knowledge on increased risk perception. Several barriers to the implementation of cancer screening strategies were identified, including lack of insurance, transportation challenges, difficulty in speaking and understanding English, inflexible work hours of health services, cultural taboos, stigma, poverty, and undocumented (illegal) status of migrants. Enablers of the implementation of cancer screening strategies included faith-based messaging on cancer screening, community partnerships, home-based fecal immunochemical test kits, availability of after-hours services, gender-concordant care, social networks, acculturation, and trust-building. CONCLUSIONS: The uptake of cancer screening (breast, cervical, colorectal) varied and had low among migrants (e.g., refugees, culturally and linguistically diverse populations). Targeted, culturally tailored approaches, expanding interpreter services, and fostering cross-sector collaborations (e.g., linking screenings to cultural events) are essential for addressing disparities in cancer screening among migrants. Culturally sensitive and adaptive, equity-focussed interventions on cancer screening should be prioritized by ensuring sustained funding, disaggregated data collection on the uptake of cancers screening and design and implementation of programs on targeting diverse population groups.
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 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 | 0,021 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,006 |
| Bibliométrie | 0,020 | 0,024 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».