Parent and physician beliefs, perceptions and knowledge of plant milks for children
Bibliographic record
Abstract
Background: Parent and physician perceptions of plant milk are unclear. Aim: To explore parent and physician perceptions of plant milk for children and to gain a better understanding of why parents and physicians might choose plant milk for children. Methods: A mixed methods study was conducted using a questionnaire and interviews with parents and physicians participating in the TARGet Kids! cohort study. Questionnaire data were analyzed using descriptive statistics. Interview transcripts were analyzed using thematic analysis. Results: Parents reported a variety of reasons for choosing plant milk for their children including concerns around allergies, the environment, animal welfare, plant-based diet, health benefits, taste and hormones in cow's milk. Parents gave their children various types of plant milks and physicians provided various recommendations to parents of children not consuming cow's milk. Our study identified that 79% of parents and 51% of physicians were unaware that soy milk is the recommended cow's milk substitute for children. Additionally, 26% of parents did not know some plant milks are not fortified and can contain added sugar. Three main themes were identified from interviews about why parents and physicians may choose plant milk for children: (i) healthiness of plant milk; (ii) concerns about hormones; and (iii) environmental impacts. Conclusions: Parents and physicians choose the milk that they believe is healthiest for their child or patient. However, a lack of clarity on the effects of plant milk consumption on children's health resulted in conflicting views on whether plant milk or cow's milk is healthier 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".