Predicting 18-month M-CHAT-R/F With PediaTrac^TMv3.0 Motor and Social/Communication/Cognition Domains.

Area of Science:

• Developmental Pediatrics
• Autism Spectrum Disorder Research
• Early Childhood Development

Background:

• Early identification of autism spectrum disorder (ASD) is crucial for timely intervention.
• Caregiver reports offer valuable insights into infant development.
• Understanding predictors of ASD at 18 months is essential for improving diagnostic accuracy.

Purpose of the Study:

• To determine if caregiver-reported motor (MOT) and social/communication/cognition (SCG) abilities in infancy predict ASD likelihood at 18 months.
• To compare the predictive power of cross-sectional infant abilities versus longitudinal developmental trajectories.
• To assess the role of socioeconomic factors in predicting ASD likelihood.

Main Methods:

• Longitudinal study of 415 caregiver-infant dyads from birth to 18 months.
• Analysis of cross-sectional MOT and SCG abilities at 9 and 12 months, and longitudinal trajectory parameters from birth to 12 months.
• Hierarchical multiple regression models predicting M-CHAT-R/F scores at 18 months, controlling for covariates.

Main Results:

• Longitudinal developmental trajectories explained more variance in M-CHAT-R/F scores than cross-sectional measures.
• Steeper developmental declines in MOT and SCG abilities predicted higher ASD likelihood.
• Higher neighborhood socioeconomic disadvantage was the strongest predictor of ASD likelihood.

Conclusions:

• Caregiver-reported developmental trajectories are valid indicators for identifying early patterns linked to later ASD likelihood.
• Integrating developmental trajectories with socioeconomic factors can enhance early ASD detection.
• This approach can inform the development of targeted interventions for children at risk for ASD.