Barriers to and facilitators of breast, cervical and colorectal cancer screening and cancer screening histories of Métis people in Alberta, Canada
Bibliographic record
Abstract
Comprehensive evaluation of cancer screening activities based on individual experiences is urgently needed to address the burden of cancer among Métis people. In this co-designed and co-led study, a cancer screening questionnaire developed for Métis people to evaluate their cancer screening histories and to explore barriers and facilitators to cancer screening was used. Adult Métis Albertans were invited to participate in the anonymous survey through a multi-modal strategy used for community consultations. Descriptive analyses compared responses between regions, age groups and geographic locations. In total, 370 participants who identified as Métis consented and contributed responses between 12 September and 2 December 2022. Female respondents reported higher rates of cervical and breast cancer screening (>94%) and lower rates of colorectal cancer screening (67-78%). Most of the barriers and facilitators were rated as very important, especially access to reliable and accurate information on screening, risks and benefits of cancer screening, explanation of the test results or procedures, trust in their health care provider(s) and health care system and access to a primary health care provider. This study fills a crucial gap that can inform targeted interventions to increase cancer screening awareness and rates among Métis Albertans and reduce their cancer burden.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".