The association between religiosity, spirituality, and breast cancer screening: A cross-sectional analysis of Alberta’s Tomorrow Project
Bibliographic record
Abstract
Breast cancer is the leading cause of cancer-related mortality among women. Screening permits the early detection and treatment of malignancies, thereby reducing mortality. A woman's religiosity and spirituality (R/S) may facilitate screening through encouragement of healthy behaviors. Population-level data from Alberta's Tomorrow Project (ATP) were used to explore the cross-sectional association between R/S and breast cancer screening among women aged 50 to 69 years who did not have a history of breast cancer. Two variables were used to measure R/S: (1) R/S Salience was defined as the importance of religion and spirituality in one's life; (2) R/S Attendance was defined as the frequency of attendance at religious or spiritual services. We regressed breast cancer screening (mammogram: yes/no) on each R/S variable in separate multivariable logistic regression models. At baseline (n = 2569), 94% of women reported receiving a mammogram. Greater R/S Salience was not associated with receipt of mammogram: the adjusted odds ratio (aOR) was 1.04 (95% confidence interval [CI]: 0.71-1.51. R/S Attendance also showed no association with mammogram: attending at least once monthly versus never attending (aOR: 1.10; 95% CI: 0.71-1.69); attending one to four times yearly versus never attending (aOR: 0.95, 95% CI: 0.57-1.58). Further research could examine specific subgroups of the population, e.g., whether use of R/S to promote breast cancer screening may be more effective among females with strong pre-existing connections to faith.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".