MétaCan
Menu
Back to cohort
Record W2290584183 · doi:10.1123/apaq.2015-0009

School-Based Fundamental-Motor-Skill Intervention for Children With Autism-Like Characteristics: An Exploratory Study

2016· article· en· W2290584183 on OpenAlexaff
Emily Bremer, Meghann Lloyd

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2016
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsOntario Tech UniversityMcMaster University
Fundersnot available
KeywordsAutismIntervention (counseling)PsychologyMotor skillGross motor skillMultiple baseline designExploratory researchSocial skillsDevelopmental psychology

Abstract

fetched live from OpenAlex

The purpose of this pilot study was to demonstrate the impact of a fundamental-motor-skill (FMS) intervention on the motor skills of 3- to 7-year-old children with autism-like characteristics in an early intervention classroom. A secondary purpose was to qualitatively assess the impact of the program as described by the classroom's special education teacher. All children in the classroom (N = 5) took part in an FMS intervention for two 6-wk blocks (fall 2013 and winter 2014). Motor-skill proficiency and social skills were assessed at 3 times: baseline, after Block 1 of the intervention, and after Block 2 of the intervention. In addition, an interview was conducted with the classroom teacher after Assessment 3 to draw further insights into the relative success and impact of the program. Results were analyzed through a visual analysis and presented individually. They indicated improvements in the participants' individual FMS and social-skill scores, possible improvements in declarative knowledge, and an increase in the special education teacher's readiness to teach FMS; further research with larger, controlled samples is warranted.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
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 science0.0010.001
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 head0.283
Teacher spread0.265 · 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 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

Citations97
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAdapted Physical Activity QuarterlySame topicChildren's Physical and Motor DevelopmentFrench-language works237,207