Trajectories of Eating Behaviour Changes during Adolescence
Bibliographic record
Abstract
Adolescence represents a critical transition phase during which individuals acquire eating behaviours that can track into adulthood. This study aims to characterise trends in eating behaviours throughout adolescence by investigating the presence of sub-groups of individuals presenting distinct trajectories of vegetable and fruit, sugary beverage, breakfast and fast-food consumption. Data from 744 MATCH study Canadian participants followed from 11 to 18 Years old (2013-2019) were included in the analyses. Participants reported how often they ate breakfast and consumed vegetables and fruits, sugary beverages and fast foods. Trajectories of eating behaviours over seven years were identified using group-based multi-trajectory modelling. For girls, three different groups were identified, namely 'stable food intake with a decline in daily breakfast consumption' (39.9%), 'moderate food intake and worsening in overall eating behaviours' (38.0%) and 'stable high food intake' (22.1%). For boys, five different groups were identified, namely 'low food intake with stable daily breakfast consumption' (27.3%), 'breakfast-skippers and increasing fast food intake' (27.1%), 'low food intake with a decline in daily breakfast consumption' (23.9%), 'high food intake with worsening of eating behaviours' (13.3%) and 'average food intake with consistently high breakfast consumption' (8.4%). Eating behaviours evolve through various distinct trajectories and sub-group-specific strategies may be required to promote healthy eating behaviours 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".