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Record W2768226985 · doi:10.1111/jir.12437

Exploring factors that impact activity participation of children and adolescents with severe developmental disabilities

2017· article· en· W2768226985 on OpenAlexafffund
Azin Taheri, Adrienne Perry, Patricia Minnes

Bibliographic record

VenueJournal of Intellectual Disability Research · 2017
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsQueen's UniversityYork University
FundersCanadian Institutes of Health Research
KeywordsPsychologyDevelopmental psychologyPerspective (graphical)Social engagementActivities of daily livingCommunity participationCommunity integrationGerontologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the benefits of social participation, children and adolescents with developmental disabilities (DD) are often excluded from taking part in social activities. There is a gap in the literature about the factors that contribute to adequate participation of children with severe DD in particular and the barriers to their participation. Taking an ecological perspective, the purpose of this study was to examine child, family and community variables that may impact the activity participation of children and adolescents with severe DD. METHODS: A total of 197 parents of children with severe DD (4-19 years) completed a survey, addressing a wide range of child, family and community related variables, as well as a measure of activity participation. RESULTS: Overall, the final model significantly accounted for 30% of the variance in activity participation. Higher adaptive behaviour, greater parental socialisation and placement in an integrated school programme were significant predictors of greater activity participation. CONCLUSION: Child, family and community factors were all important in understanding the activity participation of children with severe DD, thus supporting the value of an ecological approach. Suggestions for future research and clinical implications are discussed.

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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.393
GPT teacher head0.460
Teacher spread0.067 · 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.

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

Citations20
Published2017
Admission routes2
Has abstractyes

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