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Record W4402679798 · doi:10.1080/19315864.2024.2397368

Parent Perceptions of Occurrence, Predictors, and Treatment of Mental Health Concerns in Youth with Intellectual Disability with or without Autism Spectrum Disorder

2024· article· en· W4402679798 on OpenAlexaffabout
Christina Carrier, Carly Magnacca, Ethan Rinaldo, Jeffrey Esteves, Adrienne Perry

Bibliographic record

VenueJournal of Mental Health Research in Intellectual Disabilities · 2024
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyAutism spectrum disorderAutismMental healthPerceptionIntellectual disabilityClinical psychologyDevelopmental psychologyPsychiatryDevelopmental disorder

Abstract

fetched live from OpenAlex

Introduction Mental health concerns have been noted to be highly prevalent for youth with intellectual disability (ID), with or without autism spectrum disorder (ASD). The purpose of the current study was to examine a Canadian sample of youth with ID, with or without ASD, to explore caregiver-reported percentages, predictors, and treatment methods for mental health concerns.Method The sample included 358 caregivers who completed the GO4KIDDS survey on behalf of their child between the ages of 4 and 20 years (M = 11.36; SD = 3.82).Results In total, 56% of youth with ID (with or without ASD) were reported to experience mental health concerns. Adaptive functioning and diagnosis were significant predictors of mental health concerns. Of the youth who were reported to experience mental health concerns, 80% received some type of treatment, most commonly informal therapies (52%).Conclusion More than half of the samples were reported to experience mental health concerns and while the majority received some type of treatment, many of the treatments utilized are not evidence-based.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.214
GPT teacher head0.477
Teacher spread0.263 · 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 designQualitative
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
Published2024
Admission routes2
Has abstractyes

Explore more

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