Portrait of Post-Pandemic Lifestyle Habits of Canadian Students Entering Post-Secondary Education
Bibliographic record
Abstract
Numerous studies have reported a disruption in the lifestyle habits (LsHs) of post-secondary students during the COVID-19 pandemic. Given the importance of LsHs for these young adults’ physical and mental health and academic success, it is pertinent to examine whether these changes were maintained beyond the public health crisis. As post-pandemic data on the LsHs of post-secondary students in Canada remain limited, the aim of this study is to provide an overview. In October 2023, data on six LsHs (physical activity, sedentary behaviour, diet, sleep, screen time, drug and alcohol use) were collected from 2,283 students at 14 post-secondary institutions in Quebec, Canada. The resulting portrait suggests that habits relating to physical activity, sedentary behaviours and alcohol and drug consumption are healthier than before and during the pandemic. However, eating habits and screen time appear to be less healthy than before and during the pandemic. Sleep patterns, which were disrupted during the pandemic, seem to be returning to pre-pandemic levels. These results are discussed in the light of plausible explanations and suggest possible interventions to consider.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".