Relationship Between Severe Injuries And Current Physical Activity Levels In Former Collegiate Softball Athletes
Bibliographic record
Abstract
Collegiate softball participation may positively influence long-term physical activity (PA) levels; however, future activity levels may be impacted by sustaining a severe injury during sport. PURPOSE: 1) Describe PA levels among former collegiate softball athletes and 2) investigate association between sustaining a severe injury during a player’s career and current PA levels. METHODS: This was a cross-sectional survey-based study. PA levels were continuously measured in total metabolic equivalents of task (METs) and categorically by PA volume (low, moderate, high), using the International Physical Activity Questionnaire-short form (IPAQ). A severe injury was defined as injury resulting in 3+ weeks of time-loss from sport. Missing data was absent at random and managed using multiple imputation using chained equations. Descriptive statistics were reported as mean (standard deviation) and count (%). Chi-square analysis was performed to assess the differences between severe injury and PA category. Crude and adjusted (confounders: body mass index, age, years played, and position) multivariable linear regressions were used to determine the association between a history of a severe injury and current total PA levels (METs). RESULTS: 129 former collegiate softball athletes participated (Age: 28.7 ± 7.4; BMI: 28.5 ± 6.1; softball seasons played: 16.7 ± 7.4). 67% (95% CI: 60%, 74%) of participants reported a severe injury during their playing careers. Within the sample, 64% (54.8, 73.0) of participants were categorized as high activity while only around 5% (1.6, 10.5) were part of the low PA category. No association was observed between sustaining a severe injury and current PA levels in METs for total METs for crude (-105.0, 95% CI: -862.0-652.0, p = 0.703) or adjusted (-181.7, -944.3, 580.9, p = 0.638) models. No association was observed between severe time loss injury and current PA by category (X2 = 2.2071, df = 2, p = 0.331). CONCLUSION: Following retirement former collegiate softball athletes demonstrate high levels of physical activity regardless of previous severe injury status after retiring. Further research is warranted in larger samples to determine if differences arise by injury type, body location, or playing position.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".