Inuit women's attitudes and experiences towards cervical cancer and prevention strategies in Nunavik, Quebec
Bibliographic record
Abstract
OBJECTIVES: To describe the attitudes about and experiences with cervical cancer, Pap smear screenings and the HPV vaccine among a sample of Inuit women from Nunavik, Quebec, Canada. We also evaluated demographic and social predictors of maternal interest in HPV vaccination. STUDY DESIGN: A mixed method design was used with a cross-sectional survey and focus group interviews. METHODS: Women were recruited through convenience sampling at 2 recruitment sites in Nunavik from March 2008 to June 2009. Differences in women's responses by age, education, and marital status were assessed. Unconditional logistic regression was used to determine predictors of women's interest in HPV vaccination for their children. RESULTS: Questionnaires were completed by 175 women aged 18-63, and of these women a total of 6 women aged 31-55 participated in 2 focus groups. Almost half the survey participants had heard of cervical cancer. Women often reported feelings of embarrassment and pain during the Pap smear and older women were more likely to feel embarrassed than younger women. Only 27% of women had heard of the HPV vaccine, and 72% of these women were interested in vaccinating their child for HPV. No statistically significant predictors of maternal interest in HPV vaccination were found. CONCLUSIONS: Our findings indicate that health service planners and providers in Nunavik should be aware of potential barriers to Pap smear attendance, especially in the older age groups. Given the low awareness of cervical cancer, the Pap smear and the HPV vaccine, education on cervical cancer and prevention strategies may be beneficial.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 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) | 0.003 | 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".