Examining Predictors of Breakfast Skipping and Breakfast Program Use Among Secondary School Students in the COMPASS Study
Bibliographic record
Abstract
BACKGROUND: Many Canadian schools offer breakfast programs; however, students' engagement in these programs is low, while breakfast skipping is highly prevalent among youth. This study examined whether the availability of breakfast programs supports adolescents' regular breakfast eating, and identified characteristics of breakfast skippers who are not using these programs. METHODS: Data from 30,771 secondary school students from Ontario and Alberta, Canada, participating in Year 3 (2014-2015) of the COMPASS study were used for descriptive and logistic regression analyses. Participants were categorized by self-reported breakfast eating and school breakfast program use. RESULTS: Sixteen percent of participants reported using school breakfast programs. Breakfast skipping was highly prevalent among participants, regardless of their breakfast program use. Characteristics significantly associated with program use included traveling to school via public transit or a school bus, being a bullying victim, and having a high school connectedness score. A desire to lose weight and non-involvement in school sports were significantly associated with being a "breakfast skipper/nonprogram user." CONCLUSIONS: School breakfast programs do not consistently support regular breakfast eating, even among adolescents actively engaged in these programs. Future research should identify and evaluate practices to bolster participation in breakfast programs and promote regular breakfast eating among adolescents.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".