Perceptions of Employed Parents About Early Childhood Obesity and the Need for Prevention Strategies
Bibliographic record
Abstract
Responses to the increased prevalence of childhood obesity are merging, and employed parents will become targets for strategies designed to prevent childhood obesity. This study aimed at describing their perceptions of employed parents about childhood obesity and determining which prevention strategies they would need the most. In this cross-sectional study, 504 employed parents were recruited from 33 child care centers in Sherbrooke (Quebec, Canada) who completed a self-administered questionnaire on their perceptions about childhood obesity and the need for prevention strategies. Logistic regression was used to explore differences in needs for prevention strategies according to participant characteristics. Most participants were female, aged 32.9 ± 4.9 years, and perceived childhood obesity was an important problem. The prevention strategies that seemed most needed were the implementation of (a) physical and nutrition education programs in child care settings and (b) measures that give employed parents more time to cook for and be physically active with their children. Support for specific strategies differed across genders and education levels. Moreover, they depended on the perceived relationship between work and meal preparation. Policy makers should be aware of the needs of employed parents to develop policies that would have the greatest likelihood of success in this population.
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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 | 0.006 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".