Gendered perceptions of osteoporosis: implications for youth prevention programs
Bibliographic record
Abstract
The presentation of osteoporosis as a woman's disease in prevention information influences how osteoporosis is perceived and how prevention information is internalized and applied. Using the Health Belief Model as a framework, gendered perceptions of osteoporosis were investigated in Canadian young adults to inform the design of prevention programs. A combination of the Osteoporosis Health Belief Scale (OHBS) and semi-structured interviews were used to explore participants' perceptions of osteoporosis severity, susceptibility, and motivation to engage in prevention activities. Sixty multiethnic men and women aged 17-30 years living in Hamilton, Ontario, Canada participated in the study. While the findings from the OHBS indicated that both genders scored high for self-efficacy, the results from the qualitative interviews showed ambivalent attitudes toward prevention behaviors, indicating a disconnect between quantitative and qualitative findings. Perceptions related to severity and susceptibility revealed that while osteoporosis was generally viewed as a woman's disease, perceived individual risk of disease was a negotiation between larger gender constructs of osteoporosis and a variety of risk factors. This study indicates that osteoporosis prevention programs should consider actively acknowledging gendered and youth-based conceptions of osteoporosis in order to increase prevention behaviors in the whole population to reduce future disease.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".