Why many visible minority women in Canada do not participate in cervical cancer screening
Bibliographic record
Abstract
OBJECTIVE: To determine a high-risk group of visible minority women in Canada who do not participate in cervical cancer screening and the reasons why they do not participate. DESIGN: We combined two cycles of a large Canadian health survey, Canadian Community Health Survey (CCHS), to obtain a large sample size of visible minority women. Proportions of 'never having a Papanicalaou (Pap) test' and 'not having a Pap test within the last three years' were then calculated for different ethnic groups using sampling weights advised by Statistics Canada to account for the complex sampling procedure used in CCHS. A logistic regression model was developed to test the association between demographic and health-related variables and not having a Pap test. To identify visible minority women who were at a high risk of not having a Pap test, we stratified these women simultaneously on three variables that were significant in the logistic regression model. RESULTS: Visible minority women were more than twice as likely never to have had a Pap test. Among visible minority women, those who recently immigrated to Canada and did not have a regular physician had the highest risk for not having a Pap test. Common reasons reported for not having a Pap test included believing it was not necessary and simply not getting around to it. CONCLUSION: Visible minority women in Canada may not be participating in regular Pap testing because of cultural beliefs and a lack of an understanding of the importance of Pap testing. A culturally appropriate cervical cancer screening intervention program that involves members of visible minority communities may increase participation of this subgroup of Canadian women. This study provides preliminary information on why visible minority women in Canada do not participate in cervical cancer screening. However, the lumping together of all visible minority may obscure differences between different ethnic groups. Therefore, further research on each ethnic group is required to develop tailored culturally appropriate intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".