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Validating the Child Behavior Checklist 1.5-5 as a screening tool for autism spectrum disorder.
Norton Kitanishi1, Daniela Bordini1, Marcos V V Ribeiro1
1Universidade Federal de São Paulo, Brazil.
The Child Behavior Checklist 1.5-5 Autism Spectrum Problems and Withdrawn scales effectively screen for autism spectrum disorder in Brazilian children. This cost-effective tool shows good reliability and validity for early identification in low-resource settings.
Area of Science:
- Child Psychology
- Developmental Pediatrics
- Psychometric Validation
Background:
- Early identification of autism spectrum disorder (ASD) is critical, particularly in low- and middle-income countries (LMICs) where resources are scarce.
- The Child Behavior Checklist (CBCL) 1.5-5, utilizing Autism Spectrum Problems (ASP) and Withdrawn Syndrome (WS) subscales, presents potential for ASD screening.
- However, its construct validity in LMIC contexts requires thorough investigation.
Purpose of the Study:
- To validate the CBCL 1.5-5 as an ASD screening tool in a representative Brazilian sample.
- To assess the reliability and construct validity of the ASP and WS subscales for ASD identification.
Main Methods:
- Confirmatory factor analysis (CFA) was employed to evaluate model fit and item-subscale correlations.
- Receiver operating characteristic (ROC) curves were used to determine optimal cutoff scores.
- The study included 1292 typically developing Brazilian children (3-5 years) and 70 children diagnosed with ASD (1-5 years).
Main Results:
- The ASP model showed good fit (CFI=0.96, RMSEA=0.037) and reliability (ω=0.869).
- The WS model also demonstrated good fit (CFI=0.974, RMSEA=0.034) and reliability (ω=0.776).
- Optimal cutoffs identified were 6 for ASP (82.5% sensitivity, 83.4% specificity) and 4 for WS (87.9% sensitivity, 82.2% specificity).
Conclusions:
- The CBCL 1.5-5 ASP and WS scales are reliable and valid level 1 ASD screeners for Brazilian children.
- The findings support the use of CBCL 1.5-5 for cost-effective early ASD identification in LMICs.
- Further validation in diverse populations is recommended to confirm its broad applicability.
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