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Record W4414979008 · doi:10.32396/usurj.v10i2.871

The Refinement of a Previously Tested Concussion Protocol to Improve Its Clinical Utility

2025· article· en· W4414979008 on OpenAlexaffvenue
Amy Meyer, Alison Oates

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsConcussionIntraclass correlationConcordanceBalance (ability)Reliability (semiconductor)Protocol (science)Balance problems

Abstract

fetched live from OpenAlex

College of Kinesiology Research Theme: Human Performance Background: Concussions are a complex pathophysiological process that can affect balance control, emphasizing the importance of measuring balance during concussion rehabilitation. Previous research evaluated the feasibility of a balance assessment protocol comprised of 24 standing tasks (e.g., one/two legs, eyes open/closed, on/off foam, with/without a figure 8 head movement, with/without a reaction time task). Fifteen of the 24 tasks were deemed feasible; however, the reliability, clinical implementation, and clinical utility of those tasks are unknown. This research examined the reliability of those 15 tasks, gathered clinician insights, and evaluated the clinical utility to develop a refined balance assessment protocol for people undergoing concussion rehabilitation. We hypothesized that the clinical utility index (CUI) would increase after our refinements. Methods: Participants completed the standing balance tasks while standing on force plates (VALD Force Decks) to measure Centre of Pressure (COP) movement. Reliability of the COP data for participants without a history of concussion who completed the tasks twice 2-20 days apart was examined using Intraclass correlation coefficients (ICCs) for normally distributed data and Lin’s Concordance Coefficient (Rc) for non-normally distributed data (α =.05). Tasks with ≥ moderate reliability were compared between participants with and without a history of concussion using independent t-tests (α =.05). We shared results with four practicing clinicians (physiotherapists at a local clinic) to gather their clinical input and determine which tasks would be clinically useful. Clinical utility was calculated for the original and refined protocols. Results: Six of the 15 feasible tasks had significant (p<.05), moderate-good reliability, including quiet standing eyes closed, quiet standing single leg, quiet standing single leg eyes closed, figure 8 single leg, figure 8 on foam single leg, and a lower extremity reaction time test. The quiet standing eyes closed and quiet standing single leg tasks differentiated between groups with and without a history of concussion. Clinicians chose the quiet standing eyes closed, figure 8 single leg, and lower extremity reaction time tasks as tasks they could incorporate into their current concussion rehabilitation protocol. The CUI changed from 1 (original protocol) to 5 (refined protocol). Discussion: Using the previously established feasibility results and calculated reliability results changed the number of tasks from 15 to 3, which increased the CUI and represents a more clinically useful protocol. The feasibility and reliability results allowed clinicians insight into which tests are best to implement into their current protocol. The quiet standing eyes closed task serves as a simple baseline test, while the figure 8 single leg task incorporates vestibular activation, and the lower extremity reaction time task adds a cognitive challenge to balance. Future research could implement these three tasks in people undergoing concussion rehabilitation to determine if they are beneficial in detecting changes in balance and for clinical decision-making.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.052
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.102
GPT teacher head0.423
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes2
Has abstractyes

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