Somali’s perceptions, beliefs and barriers toward breast, cervical and colorectal cancer screening: a socioecological scoping review
Bibliographic record
Abstract
Purpose While there is literature that examines factors associated with low participation in cancer screening among Canadian ethnic groups, there is limited understanding of black visible minorities, particularly Somalis. Thus, the purpose of this study is to synthesize knowledge pertaining to the perceptions, beliefs and barriers of Somali women and men toward screening for breast, cervical and colorectal cancers in countries such as Canada. Design/methodology/approach The scoping review methodology was used to search for peer-reviewed articles that explicitly examined perceptions, beliefs and barriers among Somalis toward screening for breast, cervical and colorectal cancers in developed countries. The following electronic databases were searched without time frame restrictions, namely, OVID Medline, Embase, CINHAL, PubMed, Scopes and ProQuest. A total of 402 peer-reviewed articles were identified and screened. Three articles were identified through reference list screening (one eligible) and consultation with experts in the networks (two eligible). In total, 12 studies met the inclusion criteria for synthesis. Thematic analysis was used to analyze the selected articles for key themes and the synthesis was informed by the socio-ecological model. Findings The majority of studies originated from the USA and focused primarily on Somali women and cervical cancer screening. Themes that emerged from the literature include individual-level negative experiences and socio-cultural perceptions/beliefs; community-level barriers in cancer screening; and systemic challenges in navigating the health-care system. Many of the studies focused on individual and community-level determinants of cancer screening, with little attention to systemic level determinants. Other gaps identified include factors influencing Somali men’s low participation in cancer screening; limited studies on colorectal cancer and Somali women; and specific cancer-screening barriers faced by Somalis within the Canadian context. Originality/value The findings of the review reveal multiple cancer screening challenges for Somali communities and the gained insights should inform both health and social care practitioners and policymakers.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".