Exploring the Implications of Injury on Athlete Experiences with Positional Competition in Sport
Bibliographic record
Abstract
Background: Positional competition is an omnipresent and variable occurrence between athletes who occupy the same position within a team. Athletic injury has also been positioned as an inevitability in sport, with proposed implications for both the athlete and their team more generally. Interestingly, despite the salience of these two constructs, researchers have yet to explore their intersection in any detail. The current study leveraged athlete perceptions from Canadian football, which is a sport rich with both positional hierarchy and likelihood of injury. Objective: The aim of this study was to explore the impact of injury on experiences of positional competition within a USports football context and see how athletes described their interactions with the various social agents involved in playing time decisions across the injury experience. Methods: A two-phase qualitative study was conducted which involved individual semi-structured interviews and focus groups. In Phase 1, 12 USports OUA football athletes (Mage = 21.50; SD = 1.57) participated in individual semi-structured interviews. Positions of Phase 1 participants included Offensive Line, Receiver, H-Back, Running Back, Defensive Line, Linebacker, and Defensive Back, and in varying years of eligibility (Meligibility = 3.42; SD = 1.16). In Phase 2, 8 CWUAA and AUS USports football athletes (Mage = 22.25; SD = 1.49) participated in two focus groups. Positions of Phase 2 athletes included Quarterback, Offensive Line, Receiver, Linebacker, Defensive Back, and Long Snapper, and in varying years of eligibility (Meligibility = 3.5; SD = 1.41). Data were analyzed using a critical realist analysis approach, involving the identification of demi-regularities and the processes of abduction and retroduction. Results: Three key themes were created to represent athlete experiences with positional competition while injured. The first theme, “injury is inevitable in football”, revealed athlete experiences playing while injured and the relationship between injury status and competitive evaluation by coaches. The second theme, “athlete status is a key feature of positional competition while injured”, described high status as a mitigating factor in the relationship between injury and positional competition. The third theme, "injury creates and takes away opportunities", depicted the impact of an injury for other athletes to then compete for playing time opportunities. Conclusion and Recommendations: An athlete’s desire to garner playing time and not lose their position on the Depth Chart, as well as additional pressure in a team sports setting to not let their teammates and coaches down, motivates athletes to hide injury symptoms. This contributes to harmful cultural norms of maladaptive injury management in football programs. Higher status athletes have more access to resources for appropriate injury management and transparent social support, mitigating the relationship between injury and positional competition. Injury, while jeopardizing an athletes position on the Depth Chart, created opportunity for heightened competition for other athletes to fill the space, altering team cohesion. These findings have implications for athletes managing their own injury and recovery process, coaches seeking to maintain group cohesion in a complex environment, and all sport stakeholders hoping to enhance athlete experiences with injury and positional competition.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".