Canadian Women’s Attitudes Toward Receiving Personalized Breast Cancer Risk Information: Insights From the PERSPECTIVE I&I Project
Bibliographic record
Abstract
BACKGROUND: Risk-stratified breast cancer screening has been proposed as an alternative to the age-based approach currently used by most screening programs. This study, part of the Canadian PERSPECTIVE I&I project, examined perceived advantages and disadvantages of learning your breast cancer risk category and associated screening plans. METHOD: Women aged 40 to 69 from Ontario and Quebec (N = 3319) had multifactorial risk assessments using the CanRisk tool. Risk categories (average [78.9%], higher than average [16.4%], high [4.6%]) were communicated along with screening plans. Participants completed questionnaires on attitudes toward learning their risk before, at the time of, and 1 year later risk communication. Participant characteristics associated with these attitudes were assessed using multinomial logistic regression. RESULTS: At the time of risk communication, most participants (72.9%) perceived ``Easing worry'' as an advantage of learning their risk. However, participants at higher risk were more likely to report that it did not ease their worry. Visible minority participants (OR = 1.86, 95% CI, 1.16, 2.98) and those with lower education attainment were more likely to view "complicated information" as a disadvantage (College/Apprenticeship/Trades: OR = 1.54, 95% CI, 1.24, 1.92; High School or below: OR = 1.77, 95% CI, 1.29, 2.42). Ontario participants were more likely to view risk communication as "information I do not want to know" (OR = 0.44, 95% CI, 0.32, 0.59) compared to Quebec participants. CONCLUSION: Most women responded positively to learning their breast cancer risk category and screening plan. Successful implementation of risk-stratified screening will require clear communication, healthcare provider support, and adaptation to regional resources.
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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 | 0.001 | 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".