Associations between dieting practices and eating disorder attitudes and behaviors: Results from the Canadian study of adolescent health behaviors
Bibliographic record
Abstract
This study aimed to describe the frequency of dieting practices among adolescents and young adults in Canada, as well as determine the association between dieting and eating disorder attitudes and behaviors. Data from 2762 Canadian adolescents and young adults from the Canadian Study of Adolescent Health Behaviors were analyzed. Frequencies were used to determine the prevalence of 11 different diets among the sample, and chi-square tests were used to assess gender differences. Multiple modified Poisson and linear regression analyses were conducted to determine the associations between any dieting and eating disorder attitudes and behaviors. Among the sample, 15.7 % of girls and women, 10.4 % of boys and men, and 13.0 % of transgender/gender expansive (TGE) participants reported any dieting in the past 12 months, with the Ketogenic diet being most common among all genders. Results from regression analyses showed that engaging in any dieting in the past 12 months was associated with greater eating disorder psychopathology among girls, women, boys, and men, but not TGE participants. There were varying trends in association between specific types of dieting practices and eating disorder behaviors among girls, women, boys, and men. Dieting is relatively common among a national sample of Canadian adolescents and young adults, and engagement is associated with greater eating disorder psychopathology and behaviors. Healthcare and public health professionals should consider screening for eating disorders among adolescents and young adults who report engaging in dieting 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".