Parental Perception, Concern, and Dissatisfaction With Preschool Children's Weight and Their Associations With Feeding Practices in a Chinese Sample: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between parental perception, concern, and dissatisfaction with child weight and their feeding practices among Chinese families. DESIGN: A cross-sectional study. SETTING: Four public kindergartens in Yangzhou, China. PARTICIPANTS: Chinese parents of preschool children (n = 1,779). MAIN OUTCOME MEASURES: Three responsive feeding practices (i.e., encouragement of healthy eating, monitoring, and modeling) and 3 nonresponsive feeding practices (i.e., pressure to eat, restriction, and use of food as a reward). ANALYSIS: Hierarchical multiple regression analysis was performed to examine their associations. The agreement was evaluated with kappa statistics. RESULTS: Parents who perceived children as overweight or obese reported less pressure to eat (P = 0.04); parents who were concerned about children with underweight reported more pressure to eat (P = 0.01); parents who rated children's body weight size as underweight were less likely to encourage children to eat healthy food (P = 0.04) and restrict food intake (P = 0.02); parents who desired a slimmer child's body size reported less modeling (P < 0.001) and more restriction (P = 0.04). The disagreements between parental self-reported and visual perception of child weight and actual child weight were statistically significant, respectively (P < 0.01). CONCLUSIONS AND IMPLICATIONS: The results suggested the significant influence of parental perception, concern, and dissatisfaction with child weight on feeding practices. Our findings may inform public health practitioners and primary care providers in designing interventions to enhance parental accurate weight perception and optimize feeding practices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".