Nurses' Intention to Support Informed Decision-Making about Breast Cancer Screening with Mammography: A Survey
Bibliographic record
Abstract
There is growing interest in informed decision-making about breast cancer screening with mammography and growing advocacy for the provision of balanced information about potential benefits and harms. The authors report on a survey evaluating nurses' intention to support women targeted by the Quebec Breast Cancer Screening Program in making informed decisions about breast cancer screening with mammography. Of the 840 questionnaires completed, 618 were included in the data analysis. The mean +/- standard deviation score for intention was 1.7 +/- 1.2 on a 6-point Likert scale ranging from -3 to +3, indicating strong intention to support the targeted women. Perceived behavioural control was the theory-based variable most strongly associated with intention, followed by attitude and social norm. These results can be used to develop interventions to train nurses in integrating informed decision-making about breast cancer screening with mammography into their practice and to design relevant decision support tools.
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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 | 0.005 | 0.018 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".