Knowledge and practice of breast self-examination and associated factors among women with breast cancer in Kabul, Afghanistan
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the leading cause of cancer-related mortality among women worldwide, and it has poor prognosis if diagnosed at late stages. Common breast cancer detection methods include mammography, clinical breast exams (CBE), and breast self-examination (BSE). Breast self-examination is the most cost-effective strategy for early detection in low- and middle-income countries. OBJECTIVE: To evaluate the knowledge and practice of breast self-examination, along with associated factors, among women with breast cancer visiting Ali Abad Teaching Hospital in Kabul, Afghanistan in 2025. METHODS: This cross-sectional study was conducted among 290 Afghan women aged 20-80 who were either currently or previously admitted to the Oncology department of Ali Abad Teaching Hospital for regular follow-ups or treatment. Data was collected using an interviewer-administered questionnaire between January and February 2025. Chi-square tests were conducted to examine the associations between BSE knowledge, BSE practice, and potential explanatory factors. Those that showed significant associations in the bivariate analyses were considered potential confounders and included in multivariable logistics regression analysis. RESULTS: The mean age of participants was 42.9 ± 14.7. Majority of the participants were illiterate (83.8%) and unemployed (95.9%). Women with education of secondary level or higher were more likely to practice BSE than those who were illiterate (AOR: 3.65, 95% CI: 1.06-12.76). Participants with good knowledge level were more likely to practice BSE than those who had a poor knowledge of BSE (AOR: 5.28, 95% CI: 2.45-12.48). In addition, women who had heard of BSE were more likely to practice it compared to those who had not (AOR: 4.31, 95% CI: 1.37-19.25). CONCLUSIONS: In this study, education, knowledge score, and awareness of BSE (i.e., having heard of BSE) were selected as important predictors for practice of BSE via both bivariate and multivariate logistic regression analysis. While about 50% of participants demonstrated good knowledge of BSE, only 18% were practicing it, and among those who did, only about 30% were performing it at the right time and frequency. These findings highlight the importance of educational programs with an aim to increase breast cancer awareness among women in Afghanistan, and to promote breast self-examination as a low-cost, accessible tool for early detection - helping to alleviate cancer burden in the country.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".