Modifiable behavioural factors and their association with depression and anxiety in Canadian undergraduate post-secondary students
Bibliographic record
Abstract
Background: The mental health of post-secondary students is important for academic success and overall wellness. If post-secondary students are struggling with mental health concerns, these concerns can affect various aspects of university life including transitioning to post-secondary education, socialization and making connections, physical health, academic success, and student retention. Certain lifestyle behaviours identified as modifiable behavioural factors, or behaviours that are within the students’ control, such as sleep, physical activity, and substance use, may be valuable commodities to explore to proactively and positively improve the mental health and academic achievements of post-secondary students. \n \nObjective: This thesis explored the associations between depression and anxiety, and six modifiable behavioural factors (sleep, physical activity, cigarette smoking, e-cigarette use, marijuana use, and alcohol consumption) among female and male Canadian undergraduate post-secondary students. \n \nMethod: Data from the 2019 National College Health Assessment (NCHA) Canadian Reference Group was analyzed using logistic regression models. Models, stratified by sex at birth, explored the association between depression as a mental health indicator and six modifiable behavioural factors (sleep, physical activity, cigarette smoking, e-cigarette use, marijuana use, and alcohol consumption) while controlling for relevant covariates. The same approach, also stratified by sex at birth, explored the association between anxiety as a mental health indicator and the six modifiable behavioural factors and covariates. \n \nResults: In this sample of Canadian undergraduate students, 53% of students reported depression and 71% of students reported anxiety. The main predictors of depression for female and male students were insufficient sleep, cigarette use, and marijuana use, but insufficient physical activity predicted depression only for female students. The main predictors of anxiety for female and male students were insufficient sleep, insufficient physical activity, cigarette use, and marijuana use. Alcohol consumption including binge drinking was either not significant or was found to have an inverse association with depression and anxiety for both sexes. \n \nConclusion: Mental health is a serious problem among Canadian undergraduate post-secondary students. Both depression and anxiety are linked to several modifiable behaviours: sleep, physical activity, cigarette use, and marijuana use. These finding warrant the need for effective health campaigns, programming, and institutional policies that support student well-being and decrease mental health prevalence at post-secondary institutions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".