HIGH PREVALENCE OF SUBSTANTIAL SHOULDER PROBLEMS AMONG ELITE ADOLESCENT HANDBALL PLAYERS: THE KAROLINSKA HANDBALL STUDY
Bibliographic record
Abstract
Background Recent studies report a high prevalence of shoulder problems in senior team handball players but studies in adolescent players are lacking. Objective To measure the season prevalence of substantial shoulder problems (SSP) in elite adolescent handball players. Design Longitudinal cohort study with weekly online follow-ups. Setting Elite adolescent male and female handball players at handball-profiled high schools in Sweden. Participants 471 (54% females, mean age 16) were recruited from 10 of 15 national handball-profiled high schools. Assessment of Risk Factors The prevalence of SSP, stratified by age, was assessed through repeated online questionnaire data. Main Outcome Measurements Season prevalence of SSP during the previous handball season was measured during the pre-season (baseline), and was studied prospectively during the current season via weekly reports using the OSTRC Overuse Injury Questionnaire. SSP was defined as problems leading to moderate or severe reductions in handball participation or performance, or to time-loss. Results The weekly response rate was 86–96% and 83% of the players responded to at least 90% of the weekly reports. The previous season prevalence measured at baseline was 8% (95% CI 5–11%) among players in the 1st grade and 20% (95% CI (15–26%) in the 2nd and 3rd grades. During the prospective season, 22% (95% CI 17–27%) of players in the 1st grade reported having SSP, and 27% of players in the 2nd and 3rd grades. Of those with SSP at some point during the previous season, 67% (95% CI 54–77%) also reported SSP at least once during the prospective season. Conclusions The season prevalence of SSP is high among adolescent handball players and the prevalence increases when the players start high school. A majority of players with previous SSP also report subsequent SSP problems indicating that the pre-high school period is where prevention strategies preferably should be implemented.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".