Evaluating R2Play, A Novel Multidomain Return-to-Play Assessment Tool for Concussion: Mixed Methods Feasibility and Face Validity Study
Notice bibliographique
Résumé
Background: Return-to-play guidelines for concussion recommend a multimodal approach to assess recovery, symptoms, exertion tolerance, and cognition. However, existing assessments do not reflect the speed or complexity of multidomain skill integration in sport. We developed R2Play, a dynamic multidomain return-to-play assessment tool, and previously established proof of concept by demonstrating design objectives alignment. Objective: We aim to (1) assess the feasibility of R2Play according to usability, reliability, practicality, and safety; (2) examine physical exertion levels during R2Play as a preliminary marker of face validity; and (3) understand clinician and youth perspectives on the feasibility, face validity, potential value, and challenges associated with R2Play. Methods: A convergent parallel mixed methods design was used. Rehabilitation clinicians were paired with youth cleared to return-to-play postconcussion to complete R2Play together and provide feedback through semistructured interviews. Feasibility was assessed on predefined criteria for usability (clinician ratings on System Usability Scale), practicality (assessment duration), reliability (technical issues), and safety (adverse events). Face validity was evaluated with a target of youth achieving ≥80% of age-predicted maximal heart rate or rating of perceived exertion ≥7/10. Interviews explored perspectives on feasibility and face validity, analyzed using content analysis. Quantitative and qualitative results were merged via joint display to identify areas of convergence, divergence, and complementarity. Results: Participants included 10 youth (ages 13-20 y) with a history of concussion and 5 clinicians (n=2 physiotherapists, n=2 occupational therapists, and n=1 kinesiologist). Success criteria were met or approached for all feasibility domains. Clinician-rated usability was good-to-excellent (System Usability Scale=84.00±6.02), and youth reported that instructions were easy to learn. There were no catastrophic technical or user errors interrupting assessments. Configuration was completed in 5.74 (SD 1.09) minutes, and assessments took 26.50±6.02 minutes. There were no safety or symptom exacerbation incidents requiring assessment modification. R2Play elicited vigorous intensity physical exertion (peak heart rate=90.10±5.78% age-predicted maximal heart rate, peak rating of perceived exertion=5.50±1.72), with target exertion criteria met for 9/10 youth. Clinician and youth feedback confirmed that R2Play reflects elements of sport across physical, cognitive, and perceptual domains, making it a valuable tool for assessing readiness to return-to-play and informing rehabilitation planning for unresolved issues. Mixed methods meta-inferences provided enhanced insights regarding how to improve the usability, practicality, safety, and face validity of R2Play. Conclusions: Findings support the potential feasibility and face validity of R2Play, a multidomain assessment tool for youth with concussion, demonstrating excellent usability, vigorous physical exertion demands, and promising feedback regarding its potential to fill gaps in the return-to-play process among this initial sample from a single site. Future work is underway to establish the cross-site feasibility of R2Play and evaluate its content validity by establishing the physical, cognitive, and perceptual loading of assessment levels.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,065 | 0,069 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».