Patterns and predictors of adherence to breast cancer screening recommendations in Alberta’s Tomorrow Project
Bibliographic record
Abstract
Breast cancer screening is an important prevention component as it can reduce cancer mortality and improve survival. Understanding patterns of adherence to screening recommendations is essential to guide health promotion strategies and policy implementation efforts. The 1999 Alberta screening guidelines were used to determine screening status for eligible female participants in Alberta's Tomorrow Project (n = 4,972), a longitudinal province-based cohort. Screening patterns were derived based on screening status assessed at enrollment (2001-2008) and follow-up (2008-2011). Information on reason for screening was also collected at each time point. Multinomial logistic regression was used to assess potential predictors of adherence to screening recommendations. The majority of participants were up-to-date with screening at enrollment (79.3 %), and follow-up (75.2 %). Among all participants, 66.3 % were up-to-date at both time points (considered 'regular screeners'), 8.9 % were not up-to-date or never at enrollment but up-to-date at follow-up (considered 'new screeners'), 21.6 % were not up-to-date at follow-up (considered 'episodic screeners') and 3.2 % had never participated in screening (considered 'non-screeners'). Having a family doctor was the strongest factor associated with being a regular screener (OR (95 % CI): 0.37 (0.24 0.57) when compared with new screeners. Current smokers were more likely to be non-regular screeners. The primary reason for screening was routine screening or age. In conclusions, non-regular screening patterns were more prevalent among women without a family doctor. This finding suggests having a family doctor is an important mechanism to encourage screening. Further work is required to raise awareness of current recommendations and to understand and address reasons for non-adherence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".