The Impact of Perceived Sleep, Mood and Alcohol Use on Verbal, Physical and Sexual Assault Experiences among Student Athletes and Student Non-Athletes
Bibliographic record
Abstract
Previous research has shown that student athletes are more likely to be involved in a physical altercation or be a victim of verbal, physical and/or sexual abuse than student non-athletes, which can have long-lasting negative effects on mood, behavior and quality of life. In addition, among college students, sleep difficulties are ubiquitous and may deteriorate the unique life experience that university represents. The influences of poor sleep quality, mood and alcohol consumption related to these events are examined here between student athletes and student non-athletes. A series of hierarchical logistic regressions explored the relationship between verbal, physical and sexual assault risk factors. Results suggest that poor sleep, alcohol consumption and mood are all associated with exposure to a physical altercation or episode of abuse, irrespective of athlete status. Results also show that variables targeting self-reported difficulty sleeping and experiences of verbal, physical and sexual assault were positively associated. However, given the cross-sectional nature of the study, it is impossible to establish the direction of these relationships.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".