The Role of Primary Care Nurse Practitioners in Reducing Barriers to Cervical Cancer Screening: A Literature Review
Bibliographic record
Abstract
Nearly all cases of cervical cancer (CC) are caused by persistent infection by human papillomavirus (HPV). CC remains the second most prevalent carcinoma among women and, in 2017, Canada's screening rates were off target by 19%. For example, screening rates as low as 57.6% were observed in low-income neighbourhoods in Ontario, compared to 70% in highest-income neighbourhoods. Complex, multifactorial barriers affect women's participation in cervical cancer screening (CCS). The most common barriers to screening are directly linked to disparities within determinants of health, including belonging to a minority ethnic group, low socioeconomic status, lack of education, and lack of access to healthcare. Nurse Practitioners (NPs) can reduce these barriers by providing innovative, evidence-based, culturally competent women-friendly care while building trusting relationships with patients and, thus, play a greater role in preventing the disease. The objective of this literature review is to summarize barriers to CCS and the role Canadian NPs can have in reducing them.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".