The COVID-19 Pandemic: A Cross Sectional Analysis of Canadian University Students' and Student-Athletes' Mental Health
Bibliographic record
Abstract
Student-athletes have shown to display poorer mental health than student non-athletes, typically due to the unique stressors of participating in collegiate sport. During the COVID-19 pandemic and with the implementation of public health response measures Şenışık et al. (2020) discovered that depression and anxiety symptoms were significantly lower in Turkish professional athletes than non- athletes, and similar among genders and sport types. Further research is required, and this study aims to identify differences among Canadian university student-athletes and non-athletes, males and females, and team and individual sport athletes on symptoms of depression, anxiety, stress, and distress during the 2019/2020 academic year. The Depression Anxiety Stress Scale – 21 and Impact of Events Scale – Revised were completed by 349 student-athletes (241 male and 108 female) and 142 non-athletes (77 male and 65 female). There were no main effects for gender or sport type, but student-athletes scored significantly higher than student non-athletes in depression (p < .001), anxiety (p = .014), stress (p < 0.001), and distress (p = .001). Interestingly, female team sport athletes reported greater levels of each measure than female individual sport athletes (p = .011). In conclusion, Canadian university student- athletes reported significantly higher levels of mental distress than student non-athletes during the 2019/2020 academic year, and there were no differences by gender or sport type. Although, female team sport athletes reported higher symptoms of depression, anxiety, stress, and distress than female individual sport athletes. This data was inconsistent with Şenışık et al. (2020), highlighting the need for more research to be done comparing post-secondary students and student-athletes to identify how the COVID-19 pandemic affected them, and how academic institutions can mitigate, and aid mental health disturbances caused by events of this nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".