Symptoms of mental illness among university student-athletes during the second wave of the COVID-19 pandemic lockdown in Canada
Bibliographic record
Abstract
The COVID-19 pandemic lockdown disrupted the university sports season and had negative consequences on the academic and personal life of university student-athletes, resulting in several psychological challenges. The goal of this study is to document the symptoms of mental illness among university student-athletes during the second wave of the COVID-19 pandemic lockdown in Canada. It aims to (a) assess the prevalence of mental illness symptoms (anxiety, depression, disordered eating, and dangerous drinking) among university student-athletes and (b) identify which sociodemographic and sports characteristics, pandemic impacts, and levels of perceived stress most influence these symptoms. A total of 424 university student-athletes completed an online survey, which included questions on mental illness and the impact of the pandemic lockdown. The results revealed a notable prevalence of the symptoms of mental illness; depressive symptoms are reported by 37.9% of the participants, anxiety symptoms by 24.9%, dangerous drinking symptoms by 10.1%, and disordered eating by 8.6%. In addition, being female [OR = 0.56, 95% CI (0.33, 0.95)] or a member of a visible minority group [OR = 2.63, 95% CI (1.02, 6.78)] are significantly associated with the presence of depressive symptoms. Low academic motivation has a significant negative influence on the presence of depressive [OR = 3.37, 95% CI (1.82, 6.25)] and anxiety symptoms [OR = 2.75, 95% CI (1.35, 5.62)]. However, the presence of perceived stress was strongly associated with depressive [OR = 7.07, 95% CI (3.26, 15.35)], anxiety [OR = 6.51, 95% CI (3.30, 12.84)], and dangerous drinking symptoms [OR = 5.74, 95% CI (2.51, 13.14)]. This study advocates for specific mental illness prevention and treatment resources tailored to the unique needs of university student-athletes. Accordingly, partnerships and practical interventions to support university student-athletes' mental health are presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".