When the Data Does Not Match the Story: Do Trauma Histories and Addiction Issues Really Characterize Poor Cervical Cancer Screening Uptake Among Manitoba First Nation Women Living On-Reserve?
Bibliographic record
Abstract
First Nations women have historically used cervical Papanicolaou (Pap) screening services less than non-First Nations women, and have correspondingly higher rates of cervical cancer compared to non-Aboriginal women. It has been suggested that trauma/mental health histories and addiction behaviours may present barriers and result in less use of Pap screening. This study examined the potential influence of trauma/mental health histories and addiction on self-reports of Pap screening. Data from the Manitoba First Nations Regional Longitudinal Health Survey 2002/2003 were used to explore the association of social demographic characteristics, trauma history, and addiction behaviours with Pap screening among a sample of 1,707 First Nations adult women living on-reserve in Manitoba, Canada. Women younger than 50 years, those who reported suicidal thoughts and/or attempts over their lifetime, and those with polysubstance addictions were more likely to have been screened in the three years prior to the survey. Contrary to the perceptions of some older First Nations women, women with a challenging past were indeed engaging in Pap screening. Trauma histories and addiction behaviours did not reduce the use of cervical screening for First Nations women in this study. Screening uptake, however, is still less than optimal for older women and women with less than high school education. Culturally appropriate and gender-sensitive communication and health service efforts are required to undo existing misperceptions, and to encourage women, regardless of age or current or past circumstances, to participate in cancer screening for their own wellbeing.
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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 | 0.015 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".