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Record W2152314328 · doi:10.3109/01942638.2014.980928

Psychometric Properties of the Canadian Little Developmental Coordination Disorder Questionnaire for Preschool Children

2014· article· en· W2152314328 on OpenAlexafffundabout
Brenda N. Wilson, Dianne Creighton, Susan Crawford, Jennifer Heath, Lisa Semple, Benjamin Tan, Shannon Hansen

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2014
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsProvidence Health CareMount Royal UniversityAlberta Health ServicesAlberta Children's HospitalUniversity of Calgary
FundersMount Royal UniversityUniversity of CalgaryAlberta Health Services
KeywordsCronbach's alphaConstruct validityMovement assessmentLogistic regressionPsychologyDiscriminant validityTest (biology)Clinical psychologyMotor coordinationMotor functionReceiver operating characteristicMotor skillInternal consistencyDevelopmental psychologyPsychometricsMedicinePhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

AIMS: Test the psychometric properties and cut-off scores for the Canadian Little Developmental Coordination Disorder Questionnaire (Little DCDQ), which screens for coordination difficulties in children aged 3 to 4 years. METHODS: Parents of children with typical development (n = 108) and children at risk for motor problems (n = 245) completed the questionnaire. A subgroup (n = 119) of children was tested with the Movement Assessment Battery for Children-2 (MABC-2) and the Beery-Buktenica Developmental Test of visual-motor integration (VMI) to determine motor impairment (MI). RESULTS: Test-retest reliability (r = 0.956, p < .001) and internal consistency (Cronbach's alpha = 0.94) were high. Construct validity was supported by a factor analysis and significant difference in scores of children who were typically developing and were at risk. Concurrent validity was evaluated for the children who received standardized motor testing, with significant difference between children with and without MI. Discriminant function analysis showed that all 15 items were able to distinguish the two groups. The questionnaire correlated well with the MABC-2 and VMI. Validity as a screening tool was assessed using logistic regression modeling (X(2)(5) = 25.87, p < .001) and receiver operating curves, establishing optimal cut-off values with adequate sensitivity. CONCLUSIONS: The Little DCDQ is a reliable, valid instrument for early identification of children with motor difficulties.

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 score0.051
Threshold uncertainty score0.999

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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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

Citations69
Published2014
Admission routes3
Has abstractyes

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