‘I want to lose weight’: Early risk for disordered eating?
Bibliographic record
Abstract
The present study examined the risk of disordered eating and its relation to attempts to lose weight by surveying a Maritime Canadian sample of 247 girls and boys in grades 6, 7 and 8. Current attempts to lose weight were highest in grade 8 girls (41% of girls and 9% of boys) compared with grade 6 (14% of girls and 24% of boys) and grade 7 (21% of girls and 13% of boys) children. Of those trying to lose weight, 71.4% were in the average range for weight and height, 12.2% were overweight and 16.3% were obese. The Children's version of the Eating Attitudes Test (ChEAT) was used to assess eating attitudes and behaviours, and the Rosenberg Self-Esteem Scale was used as a measure of self-esteem. The results showed that 8.5% of the children fell in the high-risk group for disordered eating (ChEAT score 20 or higher). Those in the high-risk group were significantly more likely to fear being overweight (90%), to have tried to lose weight in the past (81%), to be currently trying to lose weight (76%), and to have engaged in binge eating (38%) and self-induced vomiting (24%). The best predictor of membership in the high-risk group for girls was current attempts at weight loss and having lower self-esteem. Only two boys fell in the high-risk group. Body mass index and current weight category (underweight, average, overweight and obese) could not explain the differences between the low- and high-risk groups. Knowing that a child is trying to lose weight can aid in identifying youth at risk for disordered eating, and can provide an opportunity for preventive education.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".