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Record W3127252554 · doi:10.1080/21622965.2021.1875828

The clinical utility of the behavior rating inventory of executive function in preschool children with a history of perinatal stroke

2021· article· en· W3127252554 on OpenAlexaff
M Di Lorenzo, Mary Desrocher, Robyn Westmacott

Bibliographic record

VenueApplied Neuropsychology Child · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHospital for Sick ChildrenYork University
Fundersnot available
KeywordsPsychologyRating scaleExecutive functionsNormativeStroke (engine)Working memoryDevelopmental psychologyClinical psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

The current study examined the utility of the Behavior Rating Inventory of Executive Function-Preschool Version (BRIEF-P) in capturing emerging deficits in executive function in preschool children with a history of perinatal stroke. Parents and teachers of 55 clinically referred preschool children (3–5 years of age) provided ratings using the BRIEF-P. Both parent (M = 56.02, p = .001) and teacher ratings (M = 58.61, p = .002) indicated significant scale elevations for working memory compared to the normative sample, albeit below the clinically elevated range. Parent and teacher ratings were low-to-moderately correlated (r = .05–.55). Greater deficits in working memory (r = −.58), inhibition (r = −.45), and planning/organization (r = −.51), as rated by teachers, were associated with lower intellectual functioning. Parents’ ratings were not associated with intellectual functioning. Further, no neurological or personal characteristics were associated with ratings of executive function. The current study demonstrates children with a history of perinatal stroke are, on average, following a normal trajectory of executive function development according to BRIEF-P ratings. The needs for multi-informant ratings and performance-based measures to comprehensively assess executive functioning in preschoolers with a history of stroke are discussed.

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 score0.057
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.275
Teacher spread0.254 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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