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Record W2922203411 · doi:10.5539/gjhs.v11n4p76

Electronic Device Use and Fine Motor Dexterity & Handwriting: A Pilot Study of South African Grade 2 Children

2019· article· en· W2922203411 on OpenAlexvenueno aff
Monique M. Keller, Pragashnie Govender

Bibliographic record

VenueGlobal Journal of Health Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsnot available
Fundersnot available
KeywordsHandwritingTest (biology)PsychologyMedicineMotor skillAudiologyDevelopmental psychologyPhysical therapyPhysical medicine and rehabilitationComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Electronic media is at an all-time high in contemporary society with the developmental impact of electronic use still mostly unknown. This study aimed at determining the association between electronic device use and the impact on handwriting and dexterity in grade two children. Thirty four children aged between 7.2 to 8.1 years participated in a pilot study. A parental self-administered questionnaire was used to determine type and frequency of electronic usage, the Minnesota Handwriting Assessment measured six handwriting domains and the Nine-Hole-Peg-Test measured dexterity. Statistically significant correlations were computed for device use and handwriting score (r = 0.110) and device use and non-dominant hand dexterity (r = 0.137). Male children’s handwriting speed was superior (p < 0.015) and female children’s form of handwriting emerged as superior (p < 0.005). This study provides data on the potential impact of frequent device use on the overall fine motor 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 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)0.005
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.054
GPT teacher head0.363
Teacher spread0.309 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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