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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".