Canada-based sports chiropractors' attitudes, beliefs, and practical application of sport psychology in the injury rehabilitation process: a mixed-methods study.
Bibliographic record
Abstract
Objective: To understand Canada-based sports chiropractors' attitudes, beliefs, and practical application of sport psychology in the sports injury rehabilitation process. Methods: A cross-sectional, mixed-methods study design was employed. A questionnaire was emailed to 144 eligible participants including Fellows and Residents of the Royal College of Chiropractic Sports Sciences (Canada) (RCCSS(C)). Fifty-two surveys were returned fully completed. Fifteen respondents completed semi-structured interviews to further examine attitudes and beliefs in sport psychology training, delivery, and referrals. Results: Approximately two-thirds of Canada-based sports chiropractors felt that athletes were affected psychologically 100% of the time when injured. Sports chiropractors reported using some basic psychological techniques during the sports injury rehab process and expressed interest in having more training in more advanced techniques and practical application of these skills, as well as developing a referral network with sport psychology professionals in Canada. Conclusions: Sports chiropractors in Canada reported receiving entry level training in sports psychology and understood the importance of addressing the psychological aspects of sports injury. Further research is warranted to explore the effectiveness of current and future sports psychology education interventions for sports chiropractors.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".