Investigating the Links Between Food Addiction, Emotional Dysregulation, Impulsivity and Quality of Life in Brazilian and Canadian College Students: A Network Analysis
Bibliographic record
Abstract
INTRODUCTION: Food addiction (FA) has been associated with emotional dysregulation, impulsivity and reduced quality of life, but its interrelationships remain underexplored. This cross-sectional descriptive study aimed to examine these connections using network analysis. METHODS: Data were collected from 1777 university students in Brazil and Canada through an online survey. Participants were classified into three groups based on the modified Yale Food Addiction Scale 2.0 (mYFAS 2.0): No food addiction (NFA), mild food addiction (MFA) and moderate/severe food addiction (MSFA). RESULTS: The MSFA group reported significantly higher levels of depression, anxiety, stress, impulsivity and emotional dysregulation, as well as lower quality of life compared to the other groups. Network analysis identified stress as the most influential variable in both samples, whereas impulsivity played a key role in connecting FA with emotional problems, particularly, in the MSFA group. CONCLUSIONS: This study addresses this gap by identifying impulsivity as central to the co-occurrence of FA and emotional dysfunction, thereby offering insights for future research and interventions targeting FA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".