Student Athletic Therapists' Knowledge of Pain-Relieving Medications: A Nationwide Study
Bibliographic record
Abstract
Purpose: Misuse of pain-relieving medications (PRMs), including opioids, is high among injured athletes. Athletes are increasingly relying on PRMs and as a result, it is likely that student athletic therapists (SATs) have managed athletes who have misused PRMs and may have potentially missed important symptoms placing athletes in harm. While dispensing PRMs is not within the scope of practice of the SAT, recognition and referral are. Previous research has found that SATs feel ill prepared to recognize PRM misuse and feel tremendous pressure to provide correct health information to the athlete. The purpose of this study was to expand on previous pilot work and uncover SATs knowledge on PRMs nationally. Method: A survey was sent to SATs currently studying in accredited Athletic Therapy programs and recent graduates (AATP). Results: A total of 57 surveys were completed. Results indicated that SATs believed they lacked sufficient knowledge related to PRMs and opioids however their personal knowledge of PRMs and opioids empowered them to provide athlete education on such medications. Over half of the SATs indicated that they have been approached by athletes and coaches to provide PRMs. SATs reported experiencing considerable pressure to provide athletes with correct information and showed stigma towards athletes misusing opioids. Conclusions: Although SATs reported the ability to recognize an athlete misusing opioids, they were unsure of how to make a quick decision when faced with potential opioid misuse situations. Recommendations: We recommend that curriculum, as well as clinical educators, address the pressure SATs experience and reinforce education to help identify and manage athletes who potentially misuse PRMs. Our study provides insight into the current level of knowledge of Canadian SATs regarding PRMs and opioids to help educators and others who work with SATs in a field setting.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".