Is a ‘healthy diet’ and a ‘calcium‐rich diet’ the same thing? Qualitative study examining perceptions of a calcium‐rich diet in individuals who have received bone health education
Bibliographic record
Abstract
BACKGROUND: In the present study, we aimed to (i) examine perceptions of achieving calcium and vitamin D recommended dietary allowance (RDA) and (ii) determine how participants talked about food in relation to RDA recommendations. METHODS: Participants aged ≥50 years who were prescribed osteoporosis medication and received two modes of bone health education were eligible. Relying on a qualitative description design, we interviewed participants 1 month after they had attended an education session and received a self-management booklet. Calcium and vitamin D intakes were estimated by in-depth questions about diet and supplements and compared with perceptions of achieved RDA levels. Interview transcripts were analysed based on an analytic hierarchical process. RESULTS: Forty-five participants (29 reporting previous fragility fractures) were included. Calcium and vitamin D RDA appeared to be potentially achieved by 64% and 93% of participants, respectively, primarily because of reliance on supplements. Few participants talked about vitamin D in relation to food intake and 49% of participants were unclear about the calcium content of food. Most considered that a healthy diet was equivalent to a calcium-rich diet. We noted no differences in our findings in the subset of individuals with fragility fractures. CONCLUSIONS: Despite reporting a prescription for osteoporosis medication and receiving bone health education, a substantial number of individuals appeared to have sub-optimal calcium levels. This may be attributed to the challenge of achieving RDA with diet alone and the misconception of a healthy diet as a calcium-rich diet.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".