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Record W3100357965 · doi:10.1111/mbe.12269

Enhancing the Cognitive and Motor Abilities of very Young Children: A Pilot Study of the Efficacy of the <scp>PlayWisely</scp> Approach

2020· article· en· W3100357965 on OpenAlexaff
Craig Leth‐Steensen, Elena Gallitto, Mohsen Haghbin, Patricia Hannan

Bibliographic record

VenueMind Brain and Education · 2020
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsCognitionPsychologyMotor skillDevelopmental psychologyPhysical medicine and rehabilitationDifferential effectsRandomized controlled trialAudiologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

PlayWisely is a novel approach to early learning designed to target the positive development of a wide range of cognitive and physical/motor abilities by stimulating the rapidly developing brain of very young children (from 4 months to 3 years of age). The current pilot study represents a first step toward providing an evidence base for the efficacy of this approach by conducting a small‐sample (N = 17) randomized controlled comparison of the cognitive and motor abilities of a group of children who were administered 16 weeks of PlayWisely training with a wait‐list group of children who were administered this training 5 months later. Results showed a marginally significant 20% greater differential increase in the overall total cognitive scale scores over the 10‐month study period coupled with significant differential increases in both fine motor and visual motor subscale scores and a marginally significant differential increase in the speed of processing subscale scores (as measured by the Merrill‐Palmer‐Revised Scales of Development).

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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 designNon-randomized trial
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
Published2020
Admission routes1
Has abstractyes

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