Factors affecting the shoulder functional profile in elite judo athletes
Bibliographic record
Abstract
ABSTRACT The aim was to investigate the effects of sex, age, preferred judo technique, dominance, and injury history on the shoulder functional status of elite judo athletes. Sixty‐one elite judo athletes (38 males, age: 18.1 ± 1.2 years, body mass: 69.3 ± 13.3 kg, body height: 172.2 ± 9.8 cm, brown belt to second‐degree black belt) completed three questionnaires: Western Ontario Shoulder Instability, Western Ontario Rotator Cuff, and Shoulder Instability‐Return to Sport after Injury. They performed four physical tests: the glenohumeral rotator isometric strength test, upper quarter Y‐balance test, unilateral seated shot put test, and modified Closed Kinetic Chain Upper Extremity Stability Test. The results showed that the female athletes had less shoulder functional abilities than the male athletes (p < 0.001 to p = 0.02). The younger athletes had poorer shoulder stability and upper extremity power than the older athletes (p < 0.001 to p = 0.02), but their glenohumeral muscles were stronger in both internal (p = 0.03) and external (p = 0.005) rotations. All the judo athletes had similar bilateral differences in shoulder functional status, except for judokas who preferred throwing techniques (p = 0.01). Injury history affected self‐perceived functional status (p < 0.001), as well as upper extremity muscle capacity and neuromuscular control (p = 0.01 to p = 0.05). This study provides new insight into the shoulder functional status of elite judo athletes, which may aid in the development of sports‐specific injury prevention and return‐to‐sport programmes to reduce the risk of shoulder injury occurrence and recurrence. Highlights Normalized levels of upper extremity abilities must be sex‐ and age‐specific in prevention programmes. Prevention programmes may focus on muscle bilateral and anteroposterior symmetry. Prevention programmes may include psychological training tailored to the sex of judo athletes.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".