Socio-economic factors associated with cancer stigma among apparently healthy women in two selected municipalities Nepal
Bibliographic record
Abstract
INTRODUCTION: 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 the general female population 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 to 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 domains (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 utilized Generalized Estimating Equations (GEE) with multivariable linear regression to identify the socio-demographic factors associated with the CASS score. RESULTS: Overall, the level of cancer stigma was low, with a mean stigma score of 2.6 (0.6), but it was still present among participants. Stigma related to personal responsibility had the highest levels, with a mean score of 3.9 (1.3), followed by severity with a mean score of 3.2 (1.3), and financial discrimination with a mean score of 2.9 (1.6). There was a significant association between the mean CASS score and older age (mean difference in stigma score: 0.11 points; 95% CI: 0.02-0.20) as well as lower education (difference: -0.02 points; 95% CI: -0.03 to -0.003), after adjusting for age, ethnicity, education, marital status, religion, occupation, and parity. CONCLUSION: While overall cancer stigma was low, some domains of stigma were higher among women in a suburban area in central Nepal; thus, indicating that cancer stigma persists in this region despite its low overall prevalence.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".