Child Involvement in Choosing a Recipe, Purchasing Ingredients, and Cooking at School Increases Willingness to Try New Foods and Reduces Food Neophobia
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of involving children in their feeding process (choosing a recipe, purchasing the ingredients, and cooking) on their lunch food choice in a school environment. DESIGN: Quasi-experimental. SETTING: Two schools in Bilbao, Spain. PARTICIPANTS: A total of 202 children (aged 8-9 years) participated in the study (43% girls), with 99 in the nutrition education (NE) group and 103 in the hands-on (HO) group. INTERVENTION: Three 1-hour workshops (1 workshop/wk), different for each group: HO, cooking-related activities, and NE, healthy habits promotion through nutrition education activities. MAIN OUTCOME MEASURES: Food neophobia, diet quality, cooking self-efficacy and attitudes toward cooking, and food intake and selection of the experimental lunches. ANALYSIS: Chi-square test of independence, ANCOVA, and t tests were performed. RESULTS: Students from the HO group selected and ate more spinach/broccoli (P < 0.001 and P = 0.02, respectively) for the first lunch; and selected more spinach/broccoli (P = 0.04) for the second lunch. After the intervention, improvements were observed for spinach liking and neophobia for the HO group and cooking self-efficacy and KidMed score for both groups. CONCLUSIONS AND IMPLICATIONS: Both interventions succeeded in improving children's diet quality, but only the HO group reduced food neophobia levels. Therefore, involving children in choosing a recipe, purchasing ingredients, and cooking may promote changing eating behaviors toward healthy habits such as increasing vegetable consumption.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".