Individual and regional determinants of mammography uptake.
Bibliographic record
Abstract
BACKGROUND: Analysis of mammography utilization has traditionally been performed from an individual-level perspective. The purpose of this study was to explore the combined influence of individual- and regional-level determinants of mammography utilization. METHODS: Logistic hierarchical multilevel modelling was used to investigate the influences of region of residence and individual characteristics on mammography utilization. Socioeconomic status information about health planning regions was derived from the 1996 Canadian Census. Individual-level information was extracted from the 1996 National Population Health Survey. RESULTS: After controlling for individual-level education, regions with fewer high school graduates had lower levels of mammography utilization. A cross-level interaction between regional-level education and individual-level social involvement was found. Other individual-level variables associated with screening confirmed previous literature findings. CONCLUSION: Our findings suggest that higher levels of participation in social activities modify the detrimental influence on mammography utilization of living in a less educated region. This challenges the current focus of mammography screening research on individual-level determinants of uptake. Multilevel, synergistic strategies to possibly achieve higher levels of screening should be considered by health promotion program planners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".