<i>Preschoolers’ Dietary Behaviours:</i>Parents’ Perspectives
Bibliographic record
Abstract
PURPOSE: Preschoolers' dietary intake behaviours are described from the perspective of their parents. METHODS: A maximum variation sample of 71 parents of preschoolers participated in this qualitative study. Ten semi-structured focus group interviews were conducted. Two experienced moderators facilitated all focus groups, which were audio-recorded and transcribed verbatim. Strategies to ensure trustworthiness of the data were employed throughout the study. Two team members independently performed inductive content analysis. NVivo software was used to code the emerging themes. RESULTS: Parents identified food and food issues as key health-related behaviours among preschoolers. Parents discussed challenges to healthy eating, including time limitations and societal pressures, as well as methods for facilitating healthy food choices, including bribery, education, and being creative with food. CONCLUSIONS: Dietary intake is on the minds of preschoolers' parents. Unfortunately, some methods that parents currently use to promote healthy food choices may be more detrimental than beneficial for children in the long term. Parents' keen interest in their preschoolers' eating habits may make them particularly receptive to learning about and facilitating healthy choices in more behaviourally appropriate ways. Widespread educational messages about the benefits and detriments of various strategies to facilitate healthy eating among preschoolers therefore seem warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".