Knowledge and Practice Regarding Breast Self-Examination (BSE) among Nursing Students Working in A Tertiary Care Hospital Lahore, Pakistan: An Observational Descriptive Cross Sectional Study
Bibliographic record
Abstract
Background: Breast self-examination (BSE) is a simple, quick, and cost-free method crucial for the early detection of breast cancer, which significantly reduces morbidity and mortality. Health Sciences students, particularly those in nursing, are ideally positioned to serve as role models and educators on this practice. Objective: The objective of this study was to assess the knowledge and practice of BSE among nursing students at a tertiary care hospital in Lahore, with a view to identifying gaps that could be addressed through targeted educational programs. Methods: This observational descriptive cross-sectional study engaged nursing students from various academic levels at a tertiary care hospital in Lahore. Participants were selected through convenience sampling. Adherence to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement was ensured. Data were collected via a self-administered structured questionnaire and analyzed using SPSS software version 26, focusing on frequencies and percentages of categorical variables. Results: Of the participants, 63.76% demonstrated a high level of knowledge about BSE, scoring ≥75%. In contrast, 36.23% scored below 75%, indicating a low level of knowledge. Practice of BSE was limited, with only 47% (n=65) of the participants engaging in the practice, and the majority, 53% (n=73), not practicing at all. Conclusion: Although nursing students show a good understanding of BSE, a significant gap exists between their knowledge and actual practice. This discrepancy highlights the need for enhanced educational interventions to encourage regular BSE practice, which is essential for the effectiveness of breast cancer screening and early detection efforts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".