MétaCan
Menu
Back to cohort
Record W2760840533 · doi:10.1093/pch/pxx086.012

DIFFERENTIAL DIAGNOSES FOR DEVELOPMENTAL COORDINATION DISORDER

2017· article· en· W2760840533 on OpenAlexaff
Jill G. Zwicker, Elizabeth C. R. Mickelson

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicForeign Language Teaching Methods
Canadian institutionsUniversity of British ColumbiaSunny Hill Health Centre for Children
Fundersnot available
KeywordsMedical diagnosisNeurodevelopmental disorderPsychologyPediatricsAttention deficit hyperactivity disorderPsychiatryIntellectual disabilityPervasive developmental disorderMedicineDevelopmental disorderClinical psychologyAutism

Abstract

fetched live from OpenAlex

BACKGROUND: The diagnosis of developmental coordination disorder (DCD) is based on four criteria outlined in the Diagnostic and Statistical Manual-5th ed. (American Psychiatric Association, 2013). One of these criteria is that the motor difficulties are not better explained by other diagnoses, such as intellectual disability, visual impairment, or neurological condition. Yet, few studies of children with DCD report how or if other medical conditions have been ruled out, with only 22/176 studies (12.5%) reporting that the children had been assessed by a physician (Smits-Engelsman et al., Hum Mov Sci, 2015:42; 293–306). OBJECTIVES: The purpose of this study was to determine what other conditions could present like DCD. DESIGN/METHODS: A prospective cohort of children referred for suspicion of DCD was assessed by a developmental pediatrician and an occupational therapist. Clinical assessment included developmental history, neurological exam, parent and child interview, standardized motor assessment, and the Developmental Coordination Disorder Questionnaire (Wilson et al., 2007 www.dcdq.ca) completed by a parent or caregiver. Diagnosis of DCD was based on DSM-5 criteria (American Psychiatric Association, 2013) and the European Academy for Childhood Disability guidelines (Blank et al., Dev Med Child Neurol, 2012:54;53–93). RESULTS: Of the 111 children assessed as of July 2016, 79 (71%) received a DCD diagnosis. The remaining 32 (29%) were suspected of having DCD but met the diagnostic criteria for other disorders. Of these 32 children, 16 (50%) were diagnosed with another neurodevelopmental disorder (e.g. fetal alcohol spectrum disorder, learning disability, attention deficit hyperactivity disorder), 8 (25%) were diagnosed with a neurological condition (e.g., cerebral palsy, hypotonia, seizure disorder, Chiari I malformation), and 8 (25%) were diagnosed with a genetic or other medical condition (e.g., microdeletion syndromes, Neurofibromatosis Type 1, Ehlers-Danlos syndrome). CONCLUSION: Results of this study underscore the importance of having children suspected of DCD to be assessed by a pediatrician to determine if there are other diagnoses to explain the child’s motor difficulties. Future directions include increasing awareness of DCD and paediatricians’ role in making a DCD diagnosis, as well as differential diagnoses to consider.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.032
GPT teacher head0.377
Teacher spread0.344 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicForeign Language Teaching MethodsFrench-language works237,207