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Record W4404183157 · doi:10.1123/jsr.2024-0106

Return-to-Play With R2Play: Protocol for Evaluating Cross-Site Feasibility, Face Validity, and Content Validity of a Multidomain Concussion Assessment Tool for Youth

2024· article· en· W4404183157 on OpenAlexaff
Shannon E. Scratch, Josh Shore, Danielle DuPlessis, Andrew Lovell, Andrea Hickling, Pavreet K. Gill, Kylie D. Mallory, Emily Lam, Fanny Hotzé, Roger Zemek, Carolyn A. Emery, Kathryn Schneider, Michael G. Hutchison, Isabelle Gagnon, Jeffrey G. Caron, Nick Reed, Elaine Biddiss

Bibliographic record

VenueJournal of Sport Rehabilitation · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationMcGill UniversityUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversity of OttawaHolland Bloorview Kids Rehabilitation HospitalYork UniversityMcGill University Health CentreToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsContent validityConcussionFace validityProtocol (science)Context (archaeology)PsychologyApplied psychologyComputer sciencePhysical medicine and rehabilitationPoison controlMedicineClinical psychologyInjury preventionPsychometricsMedical emergency

Abstract

fetched live from OpenAlex

CONTEXT: Clinical concussion assessments do not typically simulate the speed or complexity of sport. Performance changes arising from combined physical, cognitive, and sensory demands of sport may thus remain undetected during rehabilitation. We developed R2Play, a multidomain return-to-play assessment tool for youth with concussions. R2Play involves levels and conditions that vary in physical, cognitive, and sensory load to simulate the multidomain demands of sport. OBJECTIVES: To explore cross-site feasibility, face validity, and content validity of R2Play by integrating quantitative and qualitative data. METHODS: Convergent mixed-methods feasibility study. Five sites will each recruit 5 clinicians (total nc = 25) and 10 youth sport participants (ages 10-25 y) with a history of concussion in the previous year (total ny = 50). Feasibility will be evaluated using quantitative criteria for acceptability, demand, implementation, practicality, and integration, and qualitative investigated data from content analysis of postassessment interviews with youth and clinician participants. Face validity will be investigated in postassessment interviews. Content validity will be established through (1) changes in performance metrics (time to completion, errors, and heart rate) across R2Play levels, (2) youth-perceived physical and cognitive exertion for each level, and (3) overall clinician perceptions determined through postassessment interviews. Qualitative and quantitative data will be merged through joint display to identify areas of convergence, divergence, and complementarity, and to establish meta-inferences about feasibility, face validity, and content validity. DISCUSSION: This study aims to demonstrate the face and content validity of R2Play, and its feasibility for cross-site implementation. Findings will guide further iteration of R2Play and establish the foundation for a larger multicenter validation study to establish the psychometric properties of R2Play. This work represents an important first step toward the implementation of an ecologically valid multidomain assessment tool designed to support a safe and efficient return-to-play after concussion, ultimately reducing the risk of recurrent concussion and subsequent injury.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.276
GPT teacher head0.500
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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