Exploring Children’s Experiences Following Sport-Related Concussions
Bibliographic record
Abstract
Objectives: To gain a better understanding of the emotional and mental experiences of child and adolescent athletes following a sport-related concussion, in order to better support these athletes throughout recovery. Methods: Adolescents (n=21) ages 15-24 years who self-reported experiencing a sport-related concussion under the age of 18, participated in a retrospective, single group, qualitative analysis based on semi-structured interviews. Thematic Content Analysis was used to identify themes amongst participants’ responses. Results: The results indicated three overarching domains with underlying themes and subthemes within: (1) Acute Challenges Post-Concussion (i.e., difficulty accepting unknowns, self-image and mattering, school, missing out and isolation, feelings of hopelessness), (2) Coping with Acute Challenges Post-Concussion (i.e., support, previous concussions, prioritizing mental health), and (3) Take-Aways Post-Concussion (i.e., learning about injury, self-growth, long lasting impacts on overall health). Conclusion: Child and adolescent athletes face numerous emotional challenges post-concussion and following recovery; however, there are many ways in which children are resilient and cope with these challenges. Implications: It is critical that the knowledge of child and adolescent athletes’ challenges post-concussion, as well as the successful coping mechanisms and protective factors utilized throughout recovery are used to develop better preventative and interventive strategies, in order to support the athletes’ well-being post-concussion.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".