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Record W3096343493 · doi:10.4103/0028-3886.299149

The Implementation of “McGill's Big 3” in an Individual with an Acquired Brain Injury who Ambulates Independently: A Case Report

2020· article· en· W3096343493 on OpenAlexaboutno aff
Stephen Cousins, SarahM Craig, Brett Gordon

Bibliographic record

VenueNeurology India · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMcGill Pain QuestionnaireBalance (ability)Physical therapyTest (biology)Physical medicine and rehabilitationPsychological interventionRehabilitationHeelIntervention (counseling)Acquired brain injuryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Improved function, through balance and mobility, has been demonstrated in individuals with an acquired brain injury (ABI) following various exercise interventions; however, the feasibility of implementing "McGill's Big 3" exercises, typically prescribed for people with back pain, to improve function in people with ABI requires investigation. OBJECTIVE: The aim of this case report was to determine the feasibility of implementing "McGill's Big 3" exercises on balance and mobility when prescribed to an individual with an ABI who ambulates independently. METHODS AND MATERIALS: A 40-year-old female with an ABI completed an 8-week exercise intervention consisting of "McGill's Big 3" exercises. Balance and mobility testing were completed pre and post intervention, including, heel-to-toe standing; the foot tap test; forward reach test; pick-up test; stand-to-floor test; and three-meter timed up-and-go. RESULTS: The results demonstrated improvement across all tests. CONCLUSIONS: These findings support the use of "McGill's Big 3" exercises in a rehabilitation program, for individuals with neurological impairments such as an ABI.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.084
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.070
GPT teacher head0.377
Teacher spread0.307 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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