CONCUSSION REPORTING IN YOUTH SPORTS: A GROUNDED THEORY APPROACH
Bibliographic record
Abstract
Objective The purpose of this study was to generate a grounded theory that explained concussion reporting in youth sports from the perspective of the young athletes. Background Participation in youth sports is increasingly popular with estimates of 35 – 40 million U.S. children playing an organized sport each year. Current concussion education has not been shown to be consistently effective. The risk of concussion exposure is present in a number of youth sports. Much of the research surrounding concussion reporting has targeted older adolescents. A better understanding of the reporting process among younger athletes is needed. Design/Methods A grounded theory approach was used to gather and analyze data from semi-structured interviews with soccer players ages 5 to 12. The sample consisted of eleven athletes (8 male, 3 female) from non-elite soccer leagues in two counties; Maricopa, Arizona and Santa Barbara, California. Results Data analysis induced four conceptual categories; trusted environment, self-monitoring, being a player and incentive structure. The resultant theoretical model explains injury reporting from the perspective of young athletes. This study suggests that there is an incentive structure related to injury reporting, that young athletes have a good understanding of the incentives in relation to their perception of self as a player. Athletes demonstrate self-agency in terms of self-monitoring, however important adult others provide a trusted environment that makes children feel safe with their decisions. Conclusions This study suggests that a better understanding of the incentive structure embedded in the reporting process is needed to design effective prevention and education strategies. Important other adults such as parents and coaches may play a pivotal role in injury reporting among younger athletes when compared to adolescents.
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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 | 0.029 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".