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Record W3171795849 · doi:10.1177/20556683211014023

Reliability and validity of a computer game-based tool of upper extremity assessment for object manipulation tasks in children with cerebral palsy

2021· article· en· W3171795849 on OpenAlexaff
Anuprita Kanitkar, Sanjay Tejraj Parmar, Tony Szturm, Gayle Restall, Gina Rempel, Nilashri Naik, Neha Gaonkar, Nariman Sepehri, Bhavana Ankolekar

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2021
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCerebral palsyReliability (semiconductor)CorrelationPhysical medicine and rehabilitationTest (biology)PsychologyObject (grammar)Computer sciencePhysical therapyArtificial intelligenceMathematicsMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: A computer game-based upper extremity (CUE) assessment tool is developed to quantify manual dexterity of children with Cerebral Palsy (CP). The purpose of this study was to determine test-retest reliability of the CUE performance measures (success rate, movement onset time, movement error, and movement variation) and convergent validity with the Peabody Developmental Motor Scale version 2 (PDMS-2) and the Quality of Upper Extremity Skills Test (QUEST). METHODS: Thirty-five children with CP aged four to ten years were tested on two occasions two weeks apart. RESULTS: CUE performance measures of five chosen object manipulation tasks exhibited high to moderate intra-class correlation coefficient (ICC) values. There was no significant difference in the CUE performance measures between test periods. With few exceptions, there was no significant correlation between the CUE performance measures and the PDMS-2 or the QUEST test scores. CONCLUSIONS: The high to moderate ICC values and lack of systematic errors indicate that the CUE assessment tool has the ability to repeatedly record reliable performance measures of different object manipulation tasks. The lack of a correlation between the CUE and the PDMS-2 or QUEST scores indicates that performance measures of these assessment tools represent distinct attributes of manual dexterity.

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)0.001
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 score0.047
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Rehabilitation and Assistive Technologies EngineeringSame topicCerebral Palsy and Movement DisordersFrench-language works237,207