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Record W3137573928 · doi:10.1080/07317107.2021.1895415

Mental Health Status of Youth Diagnosed With ASD Who Received Early Intensive Behavioral Intervention as Young Children

2021· article· en· W3137573928 on OpenAlexaff
Julie Koudys, Adrienne Perry, Hilda Ho, Meisha Charles

Bibliographic record

VenueChild & Family Behavior Therapy · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork UniversityBrock University
Fundersnot available
KeywordsMental healthPsychologyIntervention (counseling)AnxietyAutism spectrum disorderClinical psychologyPsychiatryAutismNormative

Abstract

fetched live from OpenAlex

Many youth diagnosed with autism spectrum disorder (ASD) experience comorbid mental health issues. However, treatment history is rarely reported in these samples making it impossible to determine whether there is any relation between treatment history and later mental health functioning. Further, studies that report on outcomes of early intensive behavioural intervention (EIBI) rarely report long-term outcomes or mental health outcomes. This means that very little is known about the mental health status of children who previously received EIBI. This brief report describes the mental health profiles of 12 youth diagnosed with ASD who previously received EIBI, including measures of internalizing and externalizing disorders, and specific anxiety symptoms. The majority of participants (approximately 70%) were not experiencing significant mental health difficulties (reported by youth, parents and teachers). However, group mean scores for internalizing difficulties were significantly worse than those of the normative sample (reported by parents and teachers).

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.046
GPT teacher head0.335
Teacher spread0.289 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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