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Record W3045874217 · doi:10.1186/s12888-020-02785-9

A psychometric evaluation of the interRAI Child and Youth Mental Health instruments (ChYMH) anxiety scale in children with and without developmental disabilities

2020· article· en· W3045874217 on OpenAlexafffundabout
Shannon L. Stewart, Sarah E. Babcock, Y. Li, Hiten P. Dave

Bibliographic record

VenueBMC Psychiatry · 2020
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsWestern University
FundersLondon Community Foundation
KeywordsAnxietyMental healthClinical psychologyPsychologyScale (ratio)Concurrent validityConvergent validityPsychiatryPsychometricsInternal consistency

Abstract

fetched live from OpenAlex

BACKGROUND: With 10 to 20% of Canadian children suffering with mental illness, the importance of early identification and accurate assessment systems is clear. Unfortunately, many do not receive the mental health treatment necessary and wait-times for assessment can span up to a year. In response, the interRAI suite of assessments were designed to comprehensively assess early signs of mental health impairments in children from birth to 18 years. METHODS: This study assesses the psychometric properties of the Anxiety Scale and addresses the identification of anxiety within children diagnosed with intellectual and developmental disabilities (IDD); a commonly underrepresented sample in mental health psychometric studies. Data was collected from children aged 4-18 years in three different samples. RESULTS: Results indicated reliable internal consistency and factor structure, as well as moderate-to-strong convergent validity. CONCLUSIONS: We conclude that the Anxiety Scale exhibits psychometric qualities which demonstrate its clinical utility for use within a child sample, as well as in children with IDD. The findings provide support to a larger body of research which show consistent psychometric rigour of the interRAI measures.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
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 score0.005
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.055
GPT teacher head0.322
Teacher spread0.267 · 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

Labeled directly by 2 models reading the full record.

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

Citations41
Published2020
Admission routes3
Has abstractyes

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