Internal and External Workload in Youth Basketball Players Who Are Symptomatic and Asymptomatic for Patellar Tendinopathy
Bibliographic record
Abstract
Objective To examine the differences in external and internal workload in players with and without patellar tendinopathy. Design Nested case-control study. Methods Workload was monitored in 152 players (aged 13–18 years) for a 1-week period, including all practices, games, and conditioning sessions. Players were prescreened into patellar tendinopathy cases and controls without patellar tendinopathy, using the previously validated Oslo Sports Trauma Research Center-patellar tendinopathy questionnaire. Simple linear regression analysis, with adjustment for clustering by team and Bonferroni correction, was used to examine mean differences in measures of external workload (cumulative jump counts and sessions completed) and internal workload (session rating of perceived exertion in arbitrary units) between cases and controls. Results A total of 144 players (19 cases, 125 controls) met the inclusion criteria for final analysis. No significant differences were found between players with patellar tendinopathy and those without patellar tendinopathy in the 3 outcomes: jump count (mean difference, 45 jumps; 98.3% confidence interval [CI]: −41, 130; P = .177), basketball sessions completed (mean difference, 0.9; 98.3% CI: −0.3, 2.2; P = .067), and session rating of perceived exertion (mean difference, 346 arbitrary units; 98.3% CI: −459, 1151; P = .260). Conclusion In the current study, a significant difference in workload was not detected between youth basketball players with patellar tendinopathy and players without patellar tendinopathy. Efforts toward identifying players at early stages of patellar tendinopathy and applying relevant interventions are warranted. J Orthop Sports Phys Ther 2020;50(7):402–408. Epub 6 Sep 2019. doi:10.2519/jospt.2020.9094
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".