Describing the practice of breast self-examination and associated factors among female healthcare workers in Saint Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
Bibliographic record
Abstract
Background: Breast cancer is the most frequently occurring cancer in women and is a global health problem. Yet, it can be a manageable disease with early diagnosis and sufficient treatment protocols, such as advanced surgical intervention, chemotherapy, and radiation therapies. Breast self-examination (BSE) is a screening technique that involves examining one's breasts for lumps, distortions, or swelling, and contributes to early diagnosis of the disease. Objectives: The aim of this study was to assess the practice of BSE and associated factors among female healthcare workers in Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia, 2022. Methods: An institution-based cross-sectional study was carried out at St. Paul's Hospital Millennium Medical College. A stratified and systematic random sampling technique was utilized to obtain respondents for the study. The data for this study were collected by professional nurses using a structured questionnaire. Data were analyzed using SPSS (version 20) software. Logistic regression analysis was utilized to assess relevant factors. Predictors with a p-value of < 0.05 were considered as statistically significant. Results: Four hundred respondents participated giving a 100% response rate. The median age of study participants was 28 years, with an inter-quartile range of six years. About two-thirds (63.8%) of the study participants had good knowledge about BSE, 46.3% had a positive attitude toward BSE, and 76.25% reported they practised BSE. Significant associations were observed with the practice of BSE and the factors of age, monthly income, and knowledge about BSE. Compared to participants 40 years and above, participants between 25-29 years [AOR=0.10; 95%CI: 0.01, 0.88] and 35-39 years [AOR=0.09; 95%CI: 0.01, 0.92] were less likely to practise BSE; those with monthly income less than 5250 ETB [AOR=0.19; 95%CI: 0.035, 0.996], and between 5251-7800 [AOR=0.16; 95%CI: 0.032, 0.78], and 7801-10900ETB [AOR=0.18; 95%CI: 0.04, 0.83] were less likely to practise BSE; and those with good knowledge about BSE [AOR=2.08; 95%CI: 1.23, 3.53] were more apt to practise BSE. Conclusion: The study showed that about three-quarters of the health workers practised BSE. Statistically significant associations were observed between BSE and the factors of age in years, monthly income, and knowledge about BSE.
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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 | 0.001 |
| 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".