The lived experience of sport-related concussion: A collaborative inquiry in elite sport
Bibliographic record
Abstract
Sport-related concussion(s) (SRCs) pose a complex problem to researchers and practitioners alike. The psychological and emotional experience of these injuries requires individualized and multidisciplinary intervention to promote wellbeing and effective recovery. These interventions require a thorough understanding of the SRC experience. Thus, collaborative inquiry, a novel approach in the SRC domain, was employed to give athletes a voice in how their experience is portrayed and understood within the research and applied communities. Data were generated over two years through on-going discussion and reflection between the researchers and twelve elite athletes who experienced SRCs. Athletes advocated for a broader view of their injury that considers the interplay of sociocultural factors and the individual’s psychosocial experience. Mutual engagement through interviews, member reflections, focus groups, follow-up emails, and further reflective conversations generated two composite narratives. These narratives are interpreted using Bronfenbrenner’s Ecological Systems Theory to underline the interplay of factors: (1) microsystem (athletic identity), (2) mesosystem ((dis)trust in relationships), (3) exosystem (concussion protocols), (4) macrosystem (sport culture), and (5) chronosystem (timing related to major events and recovery). Through this unique combination of methodology and theory within SRC research, we aim to highlight opportunities for applied intervention, multidisciplinary collaboration, and future scientific explorationLay summary: Elite athletes who experienced concussions collaboratively created stories which highlight the complexity of concussions. These stories and accompanying analysis are intended to help practitioners and researchers further understand some of the psychological, social, and cultural factors that contribute to injury experience and recovery.Implications for PracticeThis article aims to facilitate an understanding of some of the complex and interacting factors that impact an elite athlete’s experience with concussion. Through a narrative exploration of athletes’ experiences and a multi-systems theory, this article highlights potential targets for applied sport psychology and rehabilitative interventions. Specifically, psychological, social, and cultural barriers and factors are identified as potential intervention areas, all of which have been largely ignored in existing return-to-sport protocols.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.023 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".