Comparing measured calcium and vitamin D intakes with perceptions of intake in Canadian young adults: insights for designing osteoporosis prevention education
Bibliographic record
Abstract
OBJECTIVE: To identify the relationship between perceptions of Ca and vitamin D consumption and actual intakes to inform the design of osteoporosis prevention education. DESIGN: An FFQ was used to approximate usual monthly Ca and vitamin D intakes among a group of young Canadians. Qualitative interviews and a food card pile sort activity explored individuals' perceptions of nutrient intakes. The FFQ was used to assess nutrient adequacy for individual participants and the qualitative interviews and pile sort were analysed using thematic content analysis. SETTING: Hamilton, Canada. SUBJECTS: Sixty participants aged 17-30 years, representing varying levels of educational attainment. RESULTS: Seventy-eight per cent of young adults who consumed inadequate vitamin D perceived their intake as adequate, compared with 57 % for Ca. Thematic analysis revealed three major themes that contributed to young adults' understandings of intake: belief their diet was correct, absence of symptoms and confusion over nutrient sources. CONCLUSIONS: The majority of participants perceived themselves as consuming adequate amounts of Ca and vitamin D, when they were actually consuming inadequate amounts according to FFQ findings. These perceptions were related to low engagement in prevention activities. Prevention education must motivate young adults to question the adequacy of their micronutrient intakes and design tailored programmes that are geared to a young adult audience.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".