Gender differences in concussion-related knowledge, attitudes and reporting behaviors of varsity athletes
Bibliographic record
Abstract
BACKGROUND: Concussion is a pathophysiological process that occurs due to a traumatic biomechanical force. Concussions are an "invisible" and common traumatic brain injury with symptoms that may be underestimated. This necessitates fundamental improvements in public knowledge specifically addressing young university athletes and different genders. This cross-sectional study aimed to explore the possibility of gender differences with respect to university student athletes' concussion knowledge, attitude and reporting behaviors. We hypothesized that there should be no significant difference in concussion knowledge among male and female student athletes; however, females would show a more positive attitude and more reporting behaviors than male student athletes. METHODS: Overall, 115 university athlete students completed a survey questionnaire; we eliminated some participants based on required inclusion criteria of Rosenbaum Concussion Knowledge and Attitude Survey-student version (RoCKAS-ST). Our final analysis consisted of 96 participants: 20 males (mean age 21.15 years) and 75 females (mean age 22.36 years). This study included questions about the athletes' given reasons for reporting or not reporting a concussion. Additionally, 33 RoCKAS-ST questions on Concussion Knowledge Index (CKI) with fair test-retest reliability (r=0.67) and 15 items on Concussion Attitude Index (CAI) with satisfactory test-retest reliability (r=0.79) were provided. RESULTS: Males reported more sources for learning about concussions and more sport-related reasons for reporting a concussion than females (P<0.05). Both genders provided equal numbers of reasons for neglecting a concussion report or not disclosing a concussion for the sake of others (i.e., family, teammates or the coach). Out of 16 given reasons for not reporting a concussion, males significantly chose sport-related reasons over female athletes (P<0.05). Additionally, by looking at the two components of RoCKAS-ST, the independent t-test results showed no significant gender-based differences in concussion knowledge and attitude indices (P>0.05). Nevertheless, females were less optimistic about evaluating other athletes' attitude over concussion reporting (P<0.05). CONCLUSIONS: Our study indicated that concussion knowledge is not gender biased among Canadian university athletes; however, more investigation is required to learn how safe environments for concussion disclosure could encourage reporting the symptoms in varsity athletes, especially in males who are more susceptible to not reporting a concussion to not miss their sport-related goals.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".