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Record W4400651759 · doi:10.1080/01942638.2024.2378050

Reliability of the Test of Gross Motor Development Third Edition Among Children with Developmental Coordination Disorder

2024· article· en· W4400651759 on OpenAlexaff
Laine Roczniak, M Jutras, Caroline Lévesque, Carole Fortin

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsGross motor skillReliability (semiconductor)Test (biology)PsychologyMotor skillDevelopmental psychologyClinical psychologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Aim The Test of Gross Motor Development Third Edition (TGMD-3) is used to assess the development of fundamental movement skills in children from 3 to 10 years old. This study aimed to evaluate the intra-rater, inter-rater, and test-retest reliability and to determine the minimal detectable change (MDC) value of the TGMD-3 in children with developmental coordination disorder (DCD).Methods The TGMD-3 was administered to 20 children with DCD. The child’s fundamental movement skills were recorded using a digital video camera. Reliability was assessed at two occasions by three raters using the generalizability theory.Results The TGMD-3 demonstrates good inter-rater reliability for the locomotor skills subscale, the ball skills subscale, and the total score (φ = 0.77 − 0.91), while the intra-rater reliability was even higher (φ = 0.94 − 0.97). Test-retest reliability was also shown to be good (φ = 0.79-0.93). The MDC95 was determined to be 10 points.Conclusion This study provides evidence that the TGMD-3 is a reliable test when used to evaluate fundamental movement skills in children with DCD and suggests that an increase of 10 points represents a significant change in the motor function of a child with DCD.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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