Breast self-examination among older women in Ireland: The Irish Longitudinal Study on Ageing -TILDA
Bibliographic record
Abstract
Abstract Background Regular breast self-examination (BSE) is a simple, cost-effective way of early breast cancer detection, particularly for women outside eligible screening age and for interval cancers. Although mammographic screening is the current most effective breast screening tool, the importance of regular BSE and breast awareness may be overlooked. The study aimed to identify socio-demographic, lifestyle and health-related factors associated with BSE practice among women in Ireland. Methods This study was conducted using Wave 4 data from The Irish Longitudinal Study on Ageing (TILDA), which collects health-related information from people aged 50 plus in biennial data collection waves. Those women aged 50-64 (eligible breast screening age in 2016) were selected. Following univariate analysis, logistic regression analysis was performed on selected variables to determine the factors independently associated with BSE practice. Results The prevalence of BSE was 70.7%. There was no significant association found between socio-demographic, lifestyle or health related factors and BSE. On logistic regression analysis, family history of cancer was not found to be associated with increased practice of BSE (Adjusted Odds Ratio (OR) 1.02, 95% Confidence Interval (CI) 0.79-1.31, p = 0.86). Having attended for mammogram showed a non-significant reduction in the likelihood of doing BSE (Adjusted OR 0.77, 95% CI 0.58-1.02, p = 0.07). Conclusions There are few studies on BSE from developed countries and this is the first from Ireland. BSE prevalence was 61%, 22.6% and 46.8% from Canada, United Kingdom and United States respectively, and was considerably lower from Asian and African countries. Women in this study were more educated than the general population counterparts, this might have overestimated BSE prevalence and obscured true associations. While we did not identify significant associations there is a suggestion that attending for mammography reduces women's interest in BSE. Key messages Being ‘Breast Aware’ and BSE are important alongside mammography for early detection of breast cancer. In countries where screening mammography is unavailable, BSE is an important detection tool.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".