How and Where Parents of Infants and Young Children Want to Receive Nutrition Information
Bibliographic record
Abstract
PURPOSE: To understand how and where parents of infants and young children (children ≤5 years old) prefer to receive nutrition information. METHODS: A 1-page survey was developed and pilot tested at 2 community agencies. The final survey was distributed at 18 community health centres (CHCs) in Calgary and surrounding rural areas. Any parent attending a well-child visit (child ≤5 years old) was able to participate. RESULTS: Five hundred and twenty-nine surveys were completed. The majority of respondents at every CHC identified online reading (79.2%) in their home (86.0%) as the preferred method and location to receive nutrition information. Almost all (99.4%) participants had internet access. Handouts (38.6%) were the second most popular way to receive nutrition information. In-person and online classes were only a preferred method by a small percentage of respondents, 10.6% and 8.1%, respectively. CONCLUSIONS: Appropriate, evidence-based nutrition websites should be promoted to parents with young children. Health professionals should be aware that parents likely access nutrition information online, and they need to provide an opportunity for parents to discuss what they found. Future research is needed to understand which websites parents access for online nutrition information and how they discern whether it is credible.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".