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Record W2581279248

Developmental coordination disorder, self-regulation, and executive functioning in preschool-aged children: Implications for research

2016· article· en· W2581279248 on OpenAlexaffabout
Jeffrey D. Graham, Yao‐Chuen Li, Sara King‐Dowling, Christine Rodriguez, John Cairney

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2016
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologyDevelopmental psychologyCognitionAggressionAssociation (psychology)Executive functionsEmotional regulationSelf-controlMental healthClinical psychologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Developmental Coordination Disorder (DCD) is one of the most prevalent childhood neurodevelopmental disorders and is characterized by impaired gross and fine motor skills (American Psychiatric Association, 2013). DCD has been linked to lower levels of physical and mental health, executive functioning (EF), and several self-regulation problems (for a review see Cairney et al., 2015), yet the data pertaining to preschool-aged children remains limited. Self-regulation broadly refers to the process of exerting control over one's thoughts, emotions or behaviours (Baumeister, 2014). Importantly, childhood self-regulation is predictive of several adaptive cognitive, physical and health related outcomes over the life course (Mischel et al., 2011). Participants (n = 211, 89 girls, Mage = 4.56±0.50 years) in the current study are part of a larger longitudinal study. Presently, 110 (76 boys) children are classified as at risk for DCD (DCDr). DCDr children were found to experience a greater amount of internalizing (e.g., emotional control; p = .001, d = 0.46) and externalizing (e.g., aggression; p Acknowledgments: This study is funded by the Canadian Institutes for Health Research (CIHR award #126015) and supported by a CIHR Postdoctoral Fellowship

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)0.001
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 score0.033
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.306
Teacher spread0.285 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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