Exploratory and confirmatory factor analysis of the autism diagnostic interview-revised

Area of Science:

• Psychometrics
• Developmental Psychology
• Clinical Psychology

Background:

• The Autism Diagnostic Interview-Revised (ADI-R) is a widely used diagnostic tool for autism spectrum disorder.
• Understanding the underlying factor structure of the ADI-R is crucial for accurate assessment and diagnosis.

Purpose of the Study:

• To examine the factor structure of the Autism Diagnostic Interview-Revised (ADI-R) algorithm items.
• To determine the optimal model reflecting the relationships between ADI-R sub-scales.

Main Methods:

• Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed.
• Data from 1,170 individuals (ages 2-46) diagnosed with Autism Spectrum Disorder were analyzed.
• Multi-group CFAs were conducted to assess model stability across age groups.

Main Results:

• EFAs provided strong support for a two-factor structure: social communication and stereotyped behaviors.
• CFAs indicated comparable support for a two-factor model and a three-factor model (separating peer relationships/play).
• Both two and three-factor models demonstrated good age-related stability.

Conclusions:

• The current structure of the ADI-R may benefit from revision.
• A revised ADI-R structure could more accurately represent the interrelationships among its sub-scales.
• Findings have implications for improving autism diagnostic assessments.