Organizational challenges to equity in the delivery of services within a new personalized risk-based approach to breast cancer screening
Bibliographic record
Abstract
Emerging evidence opens new possibilities to improve current breast cancer mammography screening programs. One promising avenue is to tailor mammography screening according to individual risk. However, some factors could challenge the implementation of such approach, specifically its potential impact on the equitable delivery of services. This study aims to identify the barriers and facilitators to the equitable delivery of services within a future integration of a personalized approach in the Québec screening program. We then propose different means to address them. We conducted 16 semi-structured interviews with stakeholders with a role in the management, implementation or assessment of the Québec screening program. The barriers and facilitators identified by respondents were regrouped in two themes: 1) Reproduction of social inequities, and 2) Amplification of regional disparities in access to services. We consider that fostering inclusion through communication strategies and relying on electronic communication technologies could help in addressing these issues.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".