Self-Compassion and Willingness to Adhere to Return-to-Play Protocol Following Sport-Related Concussions
Bibliographic record
Abstract
CONTEXT: Athletes who do not follow proper concussion recovery protocols are likely to experience their symptoms for longer while putting themselves at risk of further health issues. It is, therefore, critical to identify the types of athletes who may be more or less likely to follow the guidance of medical professionals following concussions. In this research, we tested the hypothesis that athletes with higher levels of self-compassion would be more willing to follow concussion recovery protocols. DESIGN: Cross-sectional study. METHODS: We collected data from 2 samples of combat sport athletes (sample 1, N = 173 and sample 2, N = 172). All participants completed online surveys assessing self-compassion, the likelihood that they would follow 10 recovery recommendations if they were to experience a concussion in their sport, and scales assessing 3 covariates: self-esteem, conscientiousness, and sport competitiveness. RESULTS: After controlling for self-esteem, conscientiousness, and sport competitiveness, the results of multiple regression analyses in both samples showed that self-compassion was positively associated with willingness to follow concussion recovery recommendations (sample 1: β = 0.19, 1-tailed P = .039; sample 2: β = 0.20, 1-tailed P = .025). The results of a mini meta-analysis of these effects supported this positive association, Mean r = .144, Z = 2.666, 1-tailed P = .004. CONCLUSIONS: Athletes who are highly self-compassionate reported a greater willingness to follow the advice of medical professionals and adhere to return-to-play protocol. This finding has implications for the rehabilitation of sport concussions; it may be advantageous to encourage athletes to be kind and compassionate toward themselves throughout the concussion recovery process.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".