GENDER AND OSTEOPOROSIS SELF-EFFICACY AMONG OLDER ADULTS PRESENTING FOR BONE DENSITY TESTING
Bibliographic record
Abstract
A number of studies have shown gender differences in osteoporosis care such that men have lower rates of diagnosis, treatment, and poorer outcomes than women. In our analysis, we evaluated gender differences in self-reported confidence in one’s ability to engage in bone health behaviors (i.e. consuming adequate dietary calcium and engaging in exercise), as measured by the Osteoporosis Self-Efficacy Scale (OSES). OSES was measured in 7,749 older adults presenting for bone densitometry at three U.S. medical centers. Overall, the calcium and exercise sub-scale scores are generally high and do not significantly differ by gender. OSES, however, has poor measurement model fit both overall and within gender groups, although the gender differences in the measurement model are minor, reflecting factorial invariance across genders. Given their generally high OSES sub-scale scores, greater attention to men’s barriers to preventive care as an underlying factor in their poorer outcomes may be warranted.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".