Increasing dietary calcium intake of children and their parents: a randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: Approximately 25 % of Canadian children aged 4-8 years fail to meet the recommended dietary allowance (RDA) of calcium (Ca). Young children's food choices are primarily determined by their parents. No interventions have directly targeted parents as a medium through which to increase children's Ca consumption. This study compared the effectiveness of a Ca-specific intervention targeted towards parents, with generic dietary advice on the Ca consumption of children aged 4-10 years. DESIGN: A parallel two-arm randomised controlled trial was conducted. SETTING: The study was conducted across Canada. Both conditions received information on the RDA of Ca and an index of intake requirements. Material sent to the intervention condition included behavioural strategies to increase dietary Ca consumption, information on the benefits of dietary Ca intake and messages addressing perceived barriers to the consumption of Ca-rich foods. PARTICIPANTS: A total of 239 parents (93 % mothers) of children aged 4-10 years who consumed less than the RDA of Ca were randomly assigned in a 1:1 allocation ratio. RESULTS: There was a significant increase in total Ca intake and Ca from dairy for children at weeks 8, 34 and 52 (P ≤ 0·001) in both conditions. Parental Ca intake and amount spent on dairy products did not significantly increase following the intervention. CONCLUSIONS: Provision of daily Ca requirements with regular reminders could impact parents' delivery of Ca-rich foods to their children. This finding is important for public health messaging as it suggests that parents are a potent medium through which to promote Ca intake in children.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".