8.3 Psychological readiness to return to performance following a concussion: the perspective of athletes, coaches and mental performance consultants
Bibliographic record
Abstract
Objective To explore the psychological readiness to return to performance following a concussion through the perspectives of three key sports actors: athletes, coaches, and mental performance consultants. Design Qualitative research using interpretative phenomenological epistemology, underpinned by relativist ontology. Setting Semi-structured interviews. Participants 18 athletes (9 females; Mdnage=22.5, IQR=4.2 years), 10 coaches (2 females, Mdnage=37.5, IQR=16.2 years), and 11 mental performance consultants (9 females; Mdnage=32.0, IQR=8.0 years) competing or working for the university, provincial, or national level in a variety of individual or team sports. All athletes had suffered at least one concussion in the past two years, had fully recovered from it, and had returned to sport competition at the time of the interview. Coaches and mental performance consultants had all worked with at least one athlete who met those same criteria. Main Results Confidence, control, and commitment emerged as main factors for psychological readiness to return to performance following a concussion. These factors are not fixed, rather they are evolving across three milestones of psychological readiness: recovery, return to sport, return to performance. The data enable the generation of a model and guidelines for the Progressive Psychological Readiness to Return to Performance After a Concussion. Conclusions Thus far, return to sport protocols have mainly considered physical readiness while disregarding psychological readiness. Our work highlights the importance of psychological progression that mirrors physical progression to promote optimal readiness to return to performance following a concussion. Future research should create and validate protocols aimed at promoting confidence, control, and commitment.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".