Barriers and facilitators to following dietary recommendations for bone health: a qualitative study
Bibliographic record
Abstract
BACKGROUND: An estimated one in two women and one in five men will experience a low-trauma fracture after age 50. Diet is an important mediator of bone health but individuals with or at risk of osteoporosis do not always meet recommended intake of specific nutrients (protein, calcium, vitamin D) and whole foods. We aimed to identify barriers and facilitating factors to following dietary recommendations for bone health among adults with or at risk of osteoporosis. METHODS: Adults aged ≥ 45 years who had been referred to a specialty osteoporosis clinic were recruited to participate in 4 virtual focus groups exploring barriers and facilitators to following dietary recommendations for bone health. Interest in a practical, bone-health focused Culinary Medicine program was also assessed. RESULTS: A total of 29 individuals were enrolled, 26 completed a pre-survey which asked about demographics and dietary habits, and 24 (age range 56-89 years, 21 female) attended one of four virtual focus groups. Principle barriers to following dietary recommendations for bone health highlighted by the focus group participants were: (1) living alone and cooking for one, (2) low motivation to prepare meals, and (3) dietary restrictions. Principal facilitators were: (1) preparing meals in advance, (2) online grocery shopping, and (3) engaging in exercise. Focus group participants expressed enthusiasm about participating in a Culinary Medicine program for bone health. CONCLUSION: Our findings indicate that adults with or at risk of osteoporosis face multiple barriers to adhering with dietary recommendations. Bone-focused Culinary Medicine programming merits further study as a possible method of overcoming these barriers.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".