Association between cancer stigma and cervical cancer screening uptake among women of Dhulikhel and Banepa, Nepal
Bibliographic record
Abstract
BACKGROUND: Cervical cancer ranks as the most common cancer among Nepalese women with a high incidence and mortality. Despite evidence that effective screening programs reduce disease burden, screening services are under-utilized. Cancer stigma can be a major barrier to cervical cancer screening uptake among Nepalese women. OBJECTIVES: This study assessed the association between cancer stigma and cervical cancer screening uptake among women residing in semi-urban areas of Kavrepalanchok district (Dhulikhel and Banepa), Nepal. METHODS: We conducted a cross-sectional study among 426 women aged 30-60 years using telephone interview method from 15th June to 15th October 2021. A validated Cancer Stigma Scale (CASS) was used to measure cancer stigma and categorized women as presence of cancer stigma if the mean total score was greater than three. We obtained information on cervical cancer screening uptake through self-reported responses. Univariable and multivariable logistic regression were performed to assess the association between cancer stigma and cervical cancer screening uptake. We adjusted socio-demographic: age, ethnicity, occupation, religion and education, and reproductive health variables: parity, family planning user, age of menarche and age at first sexual intercourse during multivariable logistic regression. RESULTS: Twenty-three percent of women had cancer stigma and 27 percent reported that they had ever been screened for cervical cancer. The odds of being screened was 0.23 times lower among women who had stigma compared to those who had no stigma (95% CI: 0.11-0.49) after adjusting for confounders: age, ethnicity, occupation, religion, education, parity, contraceptive use, age of menarche and age at first sexual intercourse. CONCLUSION: Women residing in semi-urban areas of Nepal and had cancer stigma were less likely to have been screened for cervical cancer. De-stigmatizing interventions may alleviate cancer stigma and contribute to higher uptake of cervical cancer screening.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".