Sport psychology and concussion: new impacts to explore
Bibliographic record
Abstract
In recent years, there has been great interest in examining the psychological effects of athletic injuries. This has also extended to interventions in which coping strategies have been suggested to enhance recovery. Concussive injuries, which are common to many sports, hold particular problems in this regard. For example, a concussed athlete may be prone to experience isolation, pain, anxiety, and disruption of daily life as a result of the injury. This may be a problem for individual sport athletes—for example, professional skiers—who do not have the support of team mates to help them through their rehabilitation and recovery, as well as team sport athletes whose team mates may inadvertently pressure them to return to play. Besides the physical loss resulting from an injury, there may also be psychological distress. Commonly reported emotion responses resulting from athletic injury have included anger, denial, depression, distress, bargaining, shock, and guilt.1–5 These are particularly seen in career ending injuries. Such emotional distress can negatively affect the athletes’ recovery process. “…concussed athletes in team sports seem to have fewer long term problems” Injured athletes have also reported feelings of isolation and loneliness. Researchers found that athletes prevented from participating in their activity have lost contact with their team, coach, and friends.6,7 For example, Gould et al 6 examined the emotional reactions of US national team skiers to season ending injuries and found that 66.6% cited lack of attention and isolation as a source of stress during their injury. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".