Associations between youth lifestyle habits, sociodemographic characteristics, and health status with positive mental health: A gender-based analysis in a sample of Canadian postsecondary students
Bibliographic record
Abstract
Objective: This study aims to estimate associations between lifestyle habits, sociodemographic characteristics, health status, and positive mental health (i.e., flourishing, languishing, moderate) and anxiety and depression symptoms in postsecondary students. Methods: This cross-sectional study used a convenience sample of 2165 Canadian first-semester postsecondary students (59 % female, 41 % men). Participants reported positive mental health using the Mental Health Continuum-Short Form and completed the Hospital Anxiety and Depression Scale to screen for probable cases of anxiety and depression in the Fall of 2023. Participants reported lifestyle habits including recreational screen time (hours/day), physical activity (minutes/week), in-person social interaction (frequency/week), and homework (hours/week). Participants reported age, gender, race/ethnicity, socioeconomic status, and health status (presence of a disability or health problem). Results: Women's weekend screen time was associated with an 11 % reduction in the odds of experiencing flourishing mental health (odds ratio [OR]: 0.89, 95 % CI, 0.83-0.95), and never engaging in in-person socializing increased the odds of women experiencing languishing mental health (OR: 3.80, 95 % CI, 1.45-9.96). More frequent engagement in physical activity and homework were each associated with an increased odds of men experiencing flourishing mental health (OR: 1.00, 95 % CI, 1.00-1.00; OR: 1.03, 95 % CI, 1.00-1.05). Conclusions: These findings highlight modifiable lifestyle habits including screen time, physical activity, in-person socializing, and homework which can be leveraged for mental health promotion among postsecondary students.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".