Under-reporting of sport-related concussions by adolescent athletes: a systematic review
Bibliographic record
Abstract
The objective of this systematic review was to examine and synthesize the current literature on sport-related concussion under-reporting in adolescent athletes. In addition, the review addresses perceived barriers for reporting, and identifies sex or gender differences in reporting behaviours. Eight databases were searched for articles that explore sport-related concussion under-reporting in adolescent athlete populations (13–18 years old). Articles were screened at the title/abstract level followed by full-text review by independent reviewers. In total, 5390 articles were screened for inclusion, and 26 articles were included in the review. All studies found evidence for athletes failing to disclose concussion symptoms. Barriers for disclosure included athletes’ desires to remain in games and interpersonal dynamics among the athlete, teammates and coaches. Both male and female athletes were found to under-report symptoms, with limited evidence suggesting male athletes under-report more frequently. Concussion education does not appear to be an effective deterrent for under-reporting, and prior concussion knowledge does not appear to predict sustained improvements in under-reporting behaviours. Future work needs to address more context and sport-specific education initiatives to target athletes who may be at high-risk for under-reporting.
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 | 0.011 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".