Food Values, Food Purchasing, and Eating-Related Outcomes Among a Sample of Quebec Adults During the COVID-19 Pandemic
Bibliographic record
Abstract
Purpose: This investigation evaluated food values, food purchasing, and other food and eating-related outcomes during the COVID-19 pandemic in Quebec, Canada. The role of stress in eating outcomes was also examined. Methods: An online household survey was conducted among Quebec adults aged ≥18 years (n = 658). Changes in outcomes during, as compared to before, the pandemic were evaluated using descriptive statistics and thematic analysis of free text responses. Eating outcomes by daily stress level (low, some, high) were assessed using Cochran–Armitage test for trend. Results: Most respondents reported increased importance and purchasing of local food products (77% and 68%, respectively) and 60% reported increased grocery spending (mean ± standard deviation: 28% ± 23%). Respondents with a higher daily stress level had a higher frequency of reporting eating more than usual compared to before the pandemic (low stress 21%, some stress 34%, high stress 39%, p-trend <0.0001). Free text responses described more time spent at home as a reason for eating more than usual. Conclusions: To support healthy eating during and post-pandemic, dietitians should consider patients’ mental/emotional well-being and time spent at home. Moreover, support of local food products may provide opportunities to promote healthy eating, sustainability, and post-pandemic resiliency of food systems.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".