Eating Behaviour Correlates in Children Referred to a Telehealth Program for Overweight and Obesity Treatment
Bibliographic record
Abstract
PURPOSE: To describe the relationships between emotional eating behaviours and demographic, anthropometric, and behavioural characteristics of children referred to a comprehensive telehealth program for the treatment of overweight and obesity. METHODS: Correlational analyses were conducted using baseline scores from self-reports on the Dutch Eating Behavior Questionnaire for Children (DEBQ-C), the Dutch Eating Behavior Questionnaire (DEBQ), the Godin Leisure-Time Exercise Questionnaire (GLTEQ), and physician-reported anthropometric/demographic measures obtained from referrals to the program. RESULTS: Data from girls (n = 20), age 8-17 yr, revealed a significant positive correlation between the Emotional Eating subscale of the DEBQ-C and DEBQ and age (r = 0.70, p = 0.0006), a non-significant negative correlation with standardized BMI score (r = -0.19, p = 0.4), and a significant negative correlation with total physical activity (r = -0.54, p = 0.01), as reported through the GLTEQ. Data from boys (n = 21), age 8-18 yr, revealed a significant positive correlation between the Emotional Eating subscale of the DEBQ-C and DEBQ and age (r = 0.62, p = 0.003), a non-significant negative correlation with standardized BMI score (r = -0.08, p = 0.7), and a significant negative correlation with total physical activity (r = -0.60, p = 0.004), as reported through the GLTEQ. CONCLUSION: In both boys and girls, emotional eating behaviors were reported to increase with age, decrease with higher levels of physical activity, and show no significant correlation with standardized BMI scores. This provides further evidence for the protective effect of physical activity in children. This research has important implications for the future treatment of children with overweight and obesity. Funding was provided by the Childhood Obesity Foundation and the Provincial Health Services Authority.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".