Multi-method proof-of-concept evaluation for R2Play: a novel multi-domain return-to-play assessment tool for concussion
Bibliographic record
Abstract
Return-to-play (RtoP) clearance after concussion typically involves single- and dual-task assessments that do not reflect the speed or complexity of sport. We developed R2Play, a dynamic multi-domain assessment tool for concussion. This study aimed to (1) demonstrate proof of concept for R2Play by evaluating alignment with design objectives (easy to use, fun, sport-like, clinically valuable, resource efficient, and flexible); and (2) document subsequent iterations to R2Play design. A multi-method evaluation was performed wherein clinicians were paired with youth to test R2Play together and complete separate semi-structured interviews. Quantitative metrics included the System Usability Scale (SUS), heart rate (HR), ratings of perceived exertion (RPE), assessment durations, and R2Play completion times, errors, and multi-task cost scores (changes in performance with the introduction of new challenges). Interviews explored perspectives on design objectives, analyzed using content analysis. Participants included five clinicians (n = 2 occupational therapy; n = 1 physiotherapy; n = 1 athletic therapy; n = 1 medicine) and 10 youth (ages 10-22 years). Assessments took 30-40 minutes despite minor technical challenges (e.g., unresponsive equipment). Clinician-rated usability was good-to-excellent (SUS = 81 ± 8.4; 95% CI: 73.6, 88.4) and youth reported that instructions were easy to follow. Moderate-to-high-intensity exertion was achieved (peak HR = 80 ± 11% age-predicted maximal; 95% CI: 77.4%, 88.5%). Multi-task cost scores reflected some aspects of hypothesized level demand loading. Clinicians described R2Play as potentially valuable to assess sport tolerance and enable rich observations of multi-domain skill integration. Tables were constructed to map study findings onto design iterations. This study supports proof-of-concept for R2Play, a new multi-domain concussion assessment tool, and identified areas for improvement, which has informed changes to the design of R2Play before broader evaluation among youth post-concussion.
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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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".