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An abbreviated scoring algorithm for the baby and infant screen for children with autism traits
Paige E Cervantes1, Johnny L Matson1, W Jason Peters1
1a Department of Psychology , Louisiana State University , Baton Rouge , LA , USA.
Insights
A new 6-item Autism Spectrum Disorder (ASD) screening tool, the Baby and Infant Screen for Children with Autism Traits (BISCUIT) algorithm, efficiently identifies at-risk children. This tool offers high sensitivity and specificity for early ASD identification.
Area of Science:
- Developmental Pediatrics
- Child Psychology
- Clinical Assessment
Background:
- Early screening for Autism Spectrum Disorder (ASD) is recommended for children aged 18-24 months.
- Healthcare providers face time constraints when administering ASD screeners.
- Efficient and psychometrically sound screening tools are crucial for timely intervention.
Purpose of the Study:
- To update the abbreviated scoring algorithm of the Baby and Infant Screen for Children with Autism Traits (BISCUIT).
- To enhance the clinical utility of the BISCUIT screener.
- To develop a time-efficient ASD screening tool with strong psychometric properties.
Main Methods:
- An updated 6-item scoring algorithm for the BISCUIT was developed.
- The study included 6,003 children with ASD or atypical development in an early intervention program.
- Psychometric properties, including sensitivity and specificity, were evaluated.
Main Results:
- The 6-item algorithm achieved optimal performance with a cutoff score of 3.
- The algorithm demonstrated a sensitivity of 0.960 and a specificity of 0.864.
- These results are comparable to the full BISCUIT-Part 1.
Conclusions:
- The 6-item BISCUIT algorithm reliably identifies children at risk for ASD.
- This abbreviated tool supports early identification and further assessment needs.
- The updated algorithm is a promising, time-efficient tool for clinical practice.
Purpose:
Autism spectrum disorder (ASD) screening is recommended for all children aged 18-24 months. However, healthcare providers may be burdened with the responsibility of conducting these screens in addition to necessary services. Therefore, developing a time-efficient screener with sound psychometric properties is essential.
Methods:
This study sought to update the abbreviated scoring algorithm of the Baby and Infant Screen for Children with aUtIsm Traits (BISCUIT) and increase its clinical utility. Six thousand and three children with ASD or atypical development enrolled in an early intervention program participated.
Results:
A 6-item algorithm with a cutoff score of 3 was found to be optimal and yielded a sensitivity of 0.960 and a specificity of 0.864.
Conclusion:
Sensitivity and specificity estimates were similar to that of the complete BISCUIT-Part 1; thus, the 6-item algorithm can reliably differentiate children at-risk for ASD requiring further assessment. The algorithm appears to be a promising tool for early identification.
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