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Record W2105886449 · doi:10.3109/01942638.2013.791915

Psychosocial Determinants of Out of School Activity Participation for Children with and without Physical Disabilities

2013· article· en· W2105886449 on OpenAlexaffabout
Gillian King, Mary Law, Theresa Petrenchik, Patricia A. Hurley

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsMcMaster University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsPsychosocialPsychologyMultilevel modelDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Psychosocial determinants of children's out of school participation were examined, using secondary analyses of data from 427 children with physical disabilities (from 12 service locations in Ontario Canada) and 354 children without disabilities, ages 6 to 14. For both groups of children, hierarchical regression analyses indicated that psychosocial variables added significant incremental variance (6% to 14%) to the prediction of active physical intensity and social activity enjoyment, beyond that accounted for by family income, child age and sex, and physical functioning. As well, there were significant psychosocial determinants, with medium to large effect sizes. Athletic competence and hyperactivity had specific effects on active physical activities and social activities, respectively, for both groups of children. Disability-specific determinants included social acceptance, emotional functioning, and peer difficulties (only significant for children with disabilities). It was concluded that psychosocial variables play an important role in children's enjoyment and intensity of participation in leisure activities.

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 score0.019
Threshold uncertainty score0.307

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.061
GPT teacher head0.429
Teacher spread0.368 · 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

Citations29
Published2013
Admission routes2
Has abstractyes

Explore more

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