Knowledge, Attitude and Performance Regarding Breast Self-examination among Students of Medical Institutes
Bibliographic record
Abstract
Objectives: The aim of this study was to assess knowledge, attitude and practice related to BSE among female students of Ibn Sina, Mellat and Jamal al-Shafa medical institutes in Kabul, Afghanistan. Breast cancer is the second most common cancer among women worldwide. Breast self-examination (BSE) is an affordable and easy way to detect breast cancer early. In developing countries with existing unfavourable social, economic and cultural conditions, BSE may be the most effective tool for the prevention and timely diagnosis of breast cancer. Material and Methods: This cross-sectional study was conducted between August and December 2023. It included a sample of 354 students selected using a stratified and systematic sampling method. Data were collected using a standard questionnaire derived from a literature review. The Statistical Package for the Social Sciences version 26 software was used for analysis and descriptive statistics, and Chi-square tests were also performed. Results: Out of 354 students, 347 students (98%) participated in the study. The age range was between 17 and 40 years, with a mean of 21.0 and a standard deviation of 2.9. This study found that only 28.8% had good knowledge, 25.9% had average knowledge, and 76.7% had average attitudes toward BSE. In addition, 22.8% of the participants had performed BSE, and 11.5% had a family history of breast cancer. The majority (66.3%) had heard about BSE before. Statistically significant relationships were found between the patterns of knowledge and the field of study and academic semester (P = 0.001) and between the level of attitude and the field of study (P = 0.008), academic semester (0.003) and type of knowledge (0.001). Conclusion: This study showed that the participants had poor knowledge and average attitudes regarding BSE. Therefore, it is important to fill the gap between knowledge and practice through effective and systematic educational and media programs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".