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Record W4410788855 · doi:10.1186/s12889-025-23051-1

Adaptation and validation of the Washington group/unicef child functioning module in a nationally representative sample of Canadian children and youth

2025· article· en· W4410788855 on OpenAlexafffundabout
Emma Nolan, Katherine Tombeau Cost, Ryan T. Miller, Li Wang, Chen Yun-Ju, Jordan Edwards, Eric Duku, Stelios Georgiades, Péter Szatmári, Harriet MacMillian, Charlotte Waddell, Katholiki Georgiades

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsSimon Fraser UniversityHospital for Sick ChildrenCentre for Addiction and Mental HealthUniversity of TorontoMcMaster UniversityOntario Centre of Excellence for Child and Youth Mental Health
FundersCanadian Institutes of Health Research
KeywordsConfirmatory factor analysisStructural equation modelingMeasurement invarianceBiostatisticsMental healthExploratory factor analysisPublic healthDevelopmental psychologyPsychologyTelephone interviewInterpersonal communicationClinical psychologyMedicineGerontologyPsychometricsPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The Washington Group/UNICEF Child Functioning Module (WG/UNICEF CFM) was developed to identify children and youth with disabilities by assessing functional difficulties. This study focuses on the cognitive, emotional, and behavioral components of the WG/UNICEF CFM, as these domains are particularly relevant to understanding child and youth mental health and developmental functioning. The objective of this study was to examine the latent structure of these domains using a graded response scale in a nationally representative sample of Canadian children and youth aged 5-17 years and to evaluate how this approach captures the dimensional nature of functional difficulties. METHODS: Data for analyses come from the 2019 Canadian Health Survey on Children and Youth (n = 33,420). Survey data were collected by Statistics Canada using an electronic questionnaire that was either self-completed online or interviewer-administered by telephone. To assess the latent structure of the WG/UNICEF CFM, analyses were conducted in four linked phases focusing on the following 9 domains: self-care, communication, learning, remembering, concentrating, accepting change, behavior, relationships, and emotions. An exploratory factor analysis (EFA) was conducted first, followed by, confirmatory factor analysis (CFA), then evaluations of measurement invariance across age and sex and external validity using structural equation modeling and instrumental variables. RESULTS: Results indicated that a two-factor model best described the data, χ2(26, N = 16,810) = 619.076, p < 0.002, CFI = 0.98, TLI = 0.97, RMSEA = 0.037). Factor one represented Cognitive, Behavioural and Interpersonal Functional Difficulties; while Factor two represented Emotional Functional Difficulties. The construct validity tests supported the distinction between the two factors by demonstrating stronger associations with instrumental variables measuring similar underlying constructs. CONCLUSIONS: This study extends existing research by demonstrating the utility of the WG/UNICEF CFM in assessing cognitive, behavioral, interpersonal, and emotional functional difficulties at the population level in a high-income country. The measure's strong psychometric properties, ease of use, and cost-free administration support its applicability in general population health surveys of children and youth. Findings highlight the value of a dimensional approach to functional difficulties, offering a more comprehensive understanding of population-level variations in functioning. Integrating this measure into large-scale surveys can facilitate trend monitoring, improve data-driven policy interventions, and support strategic planning for education, healthcare, and social services. These insights contribute to optimizing resource allocation and ensuring equitable access to services that address the diverse functional needs of children and youth.

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)0.012
metaresearch head score (Gemma)0.013
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 score0.028
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.083
GPT teacher head0.351
Teacher spread0.268 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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