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Does dual tasking ability change with age across childhood and adolescence? A systematic scoping review

2017· article· en· W2585960641 on OpenAlexaff
Shikha Saxena, Eda Çınar, Annette Majnemer, Isabelle Gagnon

Bibliographic record

VenueInternational Journal of Developmental Neuroscience · 2017
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsycINFOTask (project management)Human multitaskingPsychologyDevelopmental psychologyCognitionDual (grammatical number)Child developmentCognitive developmentCognitive psychologyMEDLINEPsychiatry

Abstract

fetched live from OpenAlex

The aim of this literature search was to identify nature and extent of the evidence supporting the development of dual tasking skills in typically developing children. We systematically searched PsycINFO, Ovid and Pubmed for studies evaluating dual task performances of children and adolescents <18 years of age. 31 studies published in English from 1990 to 2016 were included. A descriptive analysis was used for data extraction and charting. Study findings reported that age influenced dual task performances under difficult or complex task conditions but they were found to be inconclusive when the tasks were equated at everyone's difficulty level. Therefore, greater attention should be paid to meet the methodological and interpretive challenges to investigate if task coordination in children is affected by the dual tasking skills or just by development of motor and cognitive systems in isolation.

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)0.013
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.079
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0170.017
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.338
Teacher spread0.300 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations50
Published2017
Admission routes1
Has abstractyes

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