Characterizing cheat meals among a national sample of Canadian adolescents and young adults
Bibliographic record
Abstract
BACKGROUND: "Cheat meals", described as brief eating episodes that depart from established dietary practices to consume prohibited foods, represent a novel and increasingly common eating behavior with particular salience in adolescence and young adulthood. However, knowledge gaps remain regarding the frequency and characterization of foods and calories consumed during cheat meals, and their associations with eating disorder behaviors and psychopathology. Thus, the aims of this study were to delineate engagement in cheat meals among a large, national sample of Canadian adolescents and young adults. METHODS: Participants (N = 2,717) were from the Canadian Study of Adolescent Health Behaviors. Frequencies of engagement in cheat meals, and associated foods and calories consumed, in the past 12 months and 30 days were determined. The associations between engagement in cheat meals and eating disorder behaviors and psychopathology were determined using modified Poisson regression analyses. RESULTS: Engagement in cheat meals in the past 12 months was highest among men (60.9%) compared to women (53.7%) and transgender/gender non-conforming (TGNC; 52.5%) participants. Cheat meals consisting between 1,000 and 1,499 cal were those most frequently reported among all participants. Mean number of cheat meals in the past 12 months was equivalent to > 1 per week, which was similar to engagement in the past 30 days. Finally, engagement in cheat meals in the past 12 months and 30 days was associated with patterns of eating disorder behaviors and psychopathology among all participants, including binge-eating-related behaviors. CONCLUSIONS: This study further characterized and extended knowledge of cheat meal engagement across genders, aligning with prior research by demonstrating that engagement is associated with greater eating disorder psychopathology. Findings from this study add to the growing characterization of the novel behavioral phenomenon of cheat meals. Specifically, over half of adolescents and young adults across all 13 provinces and territories in Canada reported engaging in > 1 cal dense cheat meal per week, over the past 12 months. Despite the normalization and promotion of cheat meal engagement among the general public and unique fitness communities, engagement in this behavior is linked to greater eating disorder behaviors and psychopathology, including binge-eating episodes. Our findings emphasize the need for further research, public awareness, and clinical interventions aimed at addressing this potentially harmful eating behavior.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".