Difference in sleep and mental distress between in-season and out of season university athletes
Bibliographic record
Abstract
According to OCHA (2009), university students are more than twice as likely to report mental health concerns than non-university students. It has been found that university student-athletes have substantially higher levels of mental distress than student non-athletes in Canada (Sullivan et al., 2017). The stage of year (i.e., in-season, out of season) has been demonstrated to have a significant effect on student-athlete behavior (Scott et al., 2008). Furthermore, evidence suggests that 46.5% of student-athletes had sleep disorders (Monma et al., 2017), and sleep quality and mental distress have been found to be interrelated (Joao, Becker, de Neves Jesus, 2016). The current study extended this literature by examining differences in mental well-being and sleep between student athletes who are in season and those who are not. A sample of 60 student-athletes, 30 in-season (27 females ; 3 males) and 30 out of season (6 females ; 24 males) completed the Kessler Psychological Distress Scale (K6) and the Pittsburgh Sleep Quality Index (PSQI). Comparisons between stages of season were conducted using t-test for K6 scores and Mann-Whitney U on the PSQI scores, because they are ordinal variables. All results were insignificant, indicating that there were no differences between in-season and out of season student-athletes on their perceived levels of mental distress and the quantity and quality of their sleep. Although future research is needed on mental health in this population, it appears that time of season may not be a relevant factor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".