Factors that contribute to the process of reporting concussion symptoms experienced by Canadian Football League players
Bibliographic record
Abstract
Background: Concussions continue to be at the forefront of research today and are still an ongoing problem for athletes across sporting domains. Further investigation is warranted to achieve a greater understanding of concussions. Purpose: The purpose of this dissertation was to explore research related to sports-related concussions, how concussions affect athletes and those surrounding the athletes at all levels of sport, with a particular focus on Canadian Football League players and the underreporting of concussions. This dissertation also reviews qualitative research methodologies, and how they are applied within concussion research. Research Questions: a) What is my own personal relationship with concussions? In particular, what was my experience with the culture of the CFL while I was playing professional football, and later, during my transition out of professional football? b) What is the extent, range, and nature of the peer-reviewed qualitative research literature on concussions in sport? c) What factors contribute to the process of reporting concussion symptoms in Canadian Football League players? Methodology: I utilized an autoethnography to for the first question, a scoping review to address the second question, and a constructivist grounded theory study (in a sample of ten current and retired CFL players) to approach the third question. Findings: Within the autoethnography presented herein, several factors were identified as influencing the way I interpreted my experiences throughout my playing career, and my subsequent transition from professional sport. The scoping review of qualitative research in sport-related concussion suggested that qualitative research is useful for exploring all levels and types of sports. It further suggested that qualitative methodologies provide researchers with a lens that can be used to view the athletes going through the concussions, and also the other people in their lives such as physicians, parents, coaches, care-takers, teammates and equipment personnel. Different methodologies highlighted several different areas such as barriers to reporting concussions, lived experiences, media portrayal of concussions, coping strategies and effected relationships. Finally, the empirical data collected within the grounded theory study that formed the primary study within this dissertation suggested several factors that influenced the underreporting of concussions in the CFL, within three contexts: a) premeditated thoughts during the pre-game b) assessing the hit on the field and c) during the recovery process of a concussion. Implications: Findings show the current state of concussion research and highlights several factors that influence professionals to underreport their concussions. Implications for future research are discussed.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 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".