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Record W2145896162 · doi:10.1186/s12984-015-0070-0

Test–retest reliability of KINARM robot sensorimotor and cognitive assessment: in pediatric ice hockey players

2015· article· en· W2145896162 on OpenAlexafffund
C. Elaine Little, Carolyn A. Emery, Amanda M. Black, Stephen H. Scott, Willem Meeuwisse, Alberto Nettel‐Aguirre, Brian W. Benson, Sean P. Dukelow

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2015
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAlberta Children's HospitalQueen's UniversityUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Children's Hospital Research Institute
KeywordsSession (web analytics)ConcussionPsychologyPhysical medicine and rehabilitationReliability (semiconductor)Test (biology)Physical therapyMotor skillCognitionMedicineDevelopmental psychologyPoison controlInjury preventionComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Better diagnostic and prognostic tools are needed to address issues related to early diagnosis and management of concussion across the continuum of aging but particularly in children and adolescents. The purpose of the current study was to evaluate the reliability of robotic technology (KINARM robot) assessments of reaching, position sense, bimanual motor function, visuospatial skills, attention and decision making in youth ice hockey players (ages 10-14). METHODS: Thirty-four male children attended two testing days, one week apart. On day one, each subject completed five tasks on the robot with two examiners (alternating examiner sequence); the 2(nd) examiner followed the same procedure as the 1(st) immediately afterwards. One consistent examiner tested subjects one week later. This is a test-retest reliability study. The robotic tasks characterize sensorimotor and/or cognitive performance; 63 parameters from 5 tasks are reported. Session 1 was the 1(st) time the subject performed the 5 tasks, session 2 the 2(nd) time on day 1, and session 3 one week following. RESULTS: Intra-class correlation coefficients ranged from 0.06 to 0.91 and 0.09 to 0.90 for session 1 to 2 and 2 to 3, respectively. Bland-Altman plots showed agreement in a majority of the parameters and a learning effect in 25 % and 24 % of parameters in session 1 vs 2 and 1 vs 3, respectively but none for session 2 vs 3. Of those that showed a learning effect, only 8 % of parameters in session 1 vs 2 and 10 % in session 1 vs 3 had a clinical relevance measure ≥ 0.8. CONCLUSIONS: The relative homogeneity of the sample and the effect of learning seen in some of the task parameters appears to have negatively impacted the intra-class correlation coefficients from session 1 to 2, with less impact for 2 to 3. The Bland-Altman analysis supports good absolute reliability in healthy male children with no neurological impairment ranging in age from 10 to 14. The clinically relevant learning effect seen, in a small number of parameters could be addressed by creating a learning effect adjustment factor and/or implementing a practice session, which would eliminate the learning effect.

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)0.007
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 score0.008
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.321
Teacher spread0.292 · 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

Citations45
Published2015
Admission routes2
Has abstractyes

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