A qualitative study to understand parent and physician perspectives about cow’s milk fat for children
Bibliographic record
Abstract
OBJECTIVE: Consensus guidelines recommend that children consume reduced-fat (0·1-2 %) cow's milk at age 2 years to reduce the risk of obesity. Behaviours and perspectives of parents and physicians about cow's milk fat for children are unknown. Objectives were to: (i) understand what cow's milk fat recommendations physicians provide to 2-year-old children; (ii) assess the acceptability of reduced-fat v. whole cow's milk in children's diets by parents and physicians; and (iii) explore attitudes and perceptions about cow's milk fat for children. DESIGN: Online questionnaires and individual interviews were conducted. Questionnaire data were analysed using descriptive statistics. Interview transcripts were analysed using a general inductive approach and thematic analysis. SETTING: The TARGet Kids! practice-based research network in Toronto, Canada. PARTICIPANTS: Questionnaire respondents included fifty parents and fifteen physicians; individual interviews were conducted with with fourteen parents and twelve physicians. RESULTS: Physicians provided various milk fat recommendations for 2-year-old children. Parents also provided different cow's milks: eighteen (36 %) provided whole milk and twenty-nine (58 %) provided reduced-fat milk. Analysis of qualitative interviews revealed three themes: (i) healthy eating behaviours, (ii) trustworthy nutrition information and (iii) importance of dietary fat for children. CONCLUSIONS: Parents provide, and physicians recommend, a variety of cow's milks for children and hold mixed interpretations of the role of cow's milk fat in children's diets. Clarity about its effect on child adiposity is needed to help make informed decisions about cow's milk fat for 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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".