Interventions Aimed at Increasing Dairy and/or Calcium Consumption of Preschool-Aged Children: A Systematic Literature Review
Bibliographic record
Abstract
Dairy product consumption is important during childhood, as dairy products provide nutrients to support growth and development. However, a high proportion of children globally are not meeting recommended daily intakes, which may have long-term health implications. Accumulating evidence suggests that interventions aimed at instilling healthy lifestyle habits are most effective when initiated during the preschool years. Therefore, the purpose of the review was to identify the characteristics of effective dairy and/or calcium interventions targeting preschool-aged children. A systematic literature review identified 14 intervention studies published between 1998⁻2018 addressing dairy/calcium intakes in the preschool population (1.5 to 5 years). Intervention reporting was assessed using intervention intensity, behavior change techniques and Workgroup for Intervention Development and Evaluation Research (WIDER), with the quality of studies evaluated using risk of bias and Grades of Recommendation, Assessment, Development and Evaluation (GRADE). Five of the 14 studies included in the review reported significant improvements in children's dairy (4/5) or calcium (1/5) intake. Characteristics that may enable intervention effectiveness include the delivery of interventions in one setting (preschool facility), using specific behavior change techniques (environmental restructuring and teach to use prompts/cues), and targeting both parent and child. Overall, the interventions assessed demonstrated variable success and highlighted the need for developing effective interventions designed to increase dairy and/or calcium intakes in preschool-aged 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".