COVID-19 pandemic lockdown and problematic eating behaviors in a student population
Bibliographic record
Abstract
BACKGROUND AND AIMS: Since mid-March 2020, over 3 billion people have been confined as a result of the COVID-19 pandemic. Problematic eating behaviors are likely to be impacted by the pandemic through multiple pathways. This study examined the relationships between stress related to lockdown measures and binge eating and dietary restriction in a population of French students during the first week of confinement. METHODS: A sample of undergraduate students (N = 5,738) completed an online questionnaire 7 days after lockdown measures were introduced. The survey comprised variables related to lockdown measures and the COVID-19-pandemic, mood, stress, body image, binge eating and dietary restriction during the past 7 days, as well as intent to binge eat and restrict in the following 15 days. RESULTS: Stress related to the lockdown was associated with greater likelihood of binge eating and dietary restriction over the past week and intentions to binge eat and restrict over the next 15 days. Greater exposure to COVID-19-related media was associated with increased eating restriction over the past week. Binge eating and restriction (past and intentions) were associated with established risk factors, including female gender, low impulse regulation, high body dissatisfaction, and having a concurrent probable eating disorder. DISCUSSION AND CONCLUSION: The higher the stress related to the first week of confinement, the higher the risk of problematic eating behaviors among students, particularly those characterized by eating-related concerns. Screening for risk factors and providing targeted interventions might help decrease problematic eating behaviors among those who are most vulnerable.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".