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Record W4280621124 · doi:10.1177/17446295221093967

Family dynamics, trauma, and child-related characteristics: examining factors associated with co-occurring mental health problems in clinically-referred children with and without an intellectual (and developmental) disability

2022· article· en· W4280621124 on OpenAlexaff
Shannon L. Stewart, Hiten P. Dave, Natalia Lapshina

Bibliographic record

VenueJournal of Intellectual Disabilities · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsWestern University
Fundersnot available
KeywordsIntellectual disabilityMental healthPsychiatryMedical diagnosisPsychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Psychiatric disorders are common in youth with intellectual and developmental disabilities. This is a vulnerable group of children whose behavioural problems often have more complicated care needs than other children, which can place a great deal of stress on their families. However, the association of family mental health issues, level of intellectual ability, and diagnostic co-morbidity in children is relatively under-studied. In the present study, we investigated the relationship among child diagnoses, family mental health problems, risk for self-injury, and disruption in care among children with ( N = 517) and without ( N = 517) intellectual and developmental disabilities. A negative binomial regression showed that mental health problems in multiple family members, self-injurious behaviour, and self-reported abuse/trauma was related to greater likelihood of provisional diagnoses of co-occurring psychiatric disorders in both a clinically referred sample and a sample with IDD. Implications for care-planning 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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.076
GPT teacher head0.338
Teacher spread0.262 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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