Socio-Economic Factors Associated with Cancer Stigma among Apparently Healthy Women in Semi-urban Nepal
Bibliographic record
Abstract
Abstract Cancer is the primary cause of death globally, and despite the significant advancements in treatment and survival rates, it is still stigmatized in many parts of the world. However, there is limited public health research on cancer stigma among general population (non-patient) women in Nepal. Therefore, this study aims to determine the prevalence of cancer stigma and its associated factors in this group. Methods We conducted a cross-sectional study among 426 healthy women aged 30 – 60 years who were residents of Dhulikhel and Banepa in central Nepal. We measured cancer stigma using the Cancer Stigma Scale (CASS). CASS measures cancer stigma in six subdomains (awkwardness, avoidance, severity, personal responsibility, policy opposition, financial discrimination) on a 6-point Likert scale (strongly disagree to agree strongly) with higher mean stigma scores correlating with higher levels of stigma. We used univariable and multivariable linear regression to identify the socio-demographic factors associated with the CASS score. Results Overall, the level of cancer stigma was low (mean total stigma score: 2.6 ± 0.6) but still present among participants. Stigma related to personal responsibility had the highest levels (mean stigma score: 3.9 ± 1.3), followed by severity (mean stigma score: 3.2 ± 1.3) and financial discrimination (mean stigma score: 2.9 ± 1.6). There was a significant association of mean CASS score with older age (the mean difference is stigma score: 0.01 points; 95% CI: 0.01-0.02) and lower education (difference -0.02 points; 95% CI: -0.03, -0.003) after adjusting for age, ethnicity, education, marital status, religion, occupation, and parity. Conclusion While overall cancer stigma was low in Nepal, some subdomains were increased in the general population of women in Nepal. Because stigma may impact engagement in cancer screening efforts, programs should aim to counteract stigma, particularly among older and less educated women.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".