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Description of children identified by physicians as having developmental coordination disorder

2008· article· en· W2022530905 on OpenAlexaff
Cheryl Missiuna, Robin Gaines, Jennifer McLean, Denise DeLaat, Mary Egan, Helen Soucie

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2008
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsIzaak Walton Killam Health CentreDalhousie UniversityChildren's Hospital of Eastern OntarioMcMaster University
Fundersnot available
KeywordsMedical diagnosisIncidence (geometry)PediatricsMultidisciplinary approachMedicinePsychologyPhysical therapy

Abstract

fetched live from OpenAlex

The aim of this study was to describe in detail a large group of children aged 4 to 12 years who were diagnosed with developmental coordination disorder (DCD) by physicians following a rigorous multidisciplinary procedure. As part of a community-based DCD knowledge translation program, physicians received specialized training and were invited to identify children with probable DCD who were referred for further investigation to help confirm the diagnosis. Of 116 children (87 males, 29 females; age range 4y 1mo - 12y 11mo, mean age 8y) identified as having probable DCD by physician participants, 88 (76%) were subsequently diagnosed with DCD and 77.3% of these demonstrated a high degree of motor impairment. All children who were diagnosed experienced difficulties in self-care and/or academic or leisure activities. The male:female ratio was 3:1 and the incidence of preterm births among this sample was 12.5%. We conclude that, given the expense involved with ruling out differential diagnoses, it can be difficult to adhere rigorously to diagnostic criteria for DCD in clinical practice and research. This description of a group of children actually diagnosed with DCD helps to clarify the characteristics of these children as well as issues related to the refinement of diagnostic criteria.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.246
Teacher spread0.231 · 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 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

Citations72
Published2008
Admission routes1
Has abstractyes

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