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Record W4293567095 · doi:10.3138/ptc-2021-0025

Clinical Motor Coordination Tests in Adult Neurology: A Scoping Review

2022· review· en· W4293567095 on OpenAlexafffundvenue
Elka Schwartz, Kathryn Guidry, Amanda Lee, Danny D. Dinh, Mindy F. Levin, Marika Demers

Bibliographic record

VenuePhysiotherapy Canada · 2022
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in RehabilitationJewish Rehabilitation Hospital
FundersMcGill University
KeywordsMotor coordinationPhysical medicine and rehabilitationLower limbTrunkPhysical therapyPsychologyMEDLINEMetric (unit)MedicineSurgeryNeuroscience

Abstract

fetched live from OpenAlex

Purpose: This scoping review aimed to identify which clinical tests are used to assess upper limb, lower limb, and trunk motor coordination, and their metric and measurement properties for adult neurological populations. Method: MEDLINE (1946–) and EMBASE (1996–) databases were searched using keywords such as movement quality, motor performance, motor coordination, assessment, and psychometrics. Data regarding the body part assessed, neurological condition, psychometric properties, and scored metrics of spatial and/or temporal coordination were independently extracted by two reviewers. Alternate versions of some tests such as the Finger-to-Nose Test were included. Results: Fifty-one included articles yielded 2 tests measuring spatial coordination, 7 tests measuring temporal coordination, and 10 tests measuring both. Scoring metrics and measurement properties differed between tests, with a majority of tests having good-to-excellent measurement properties. Conclusions: The metrics of motor coordination scored by current tests vary. Since tests do not assess functional task performance, the onus falls on clinicians to infer the connection between coordination impairments and functional deficits. Clinical practice would benefit from the development of a battery of tests that assesses the metrics of coordination related to functional performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.413
Teacher spread0.363 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2022
Admission routes3
Has abstractyes

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