Exploratory and confirmatory factor analysis of the autism diagnostic interview-revised.
The ADI-R has two stable factors; watch for a revised algorithm that re-weights items to match them.
01Research in Context
What this study did
The team ran math tests on the ADI-R. They looked at how the 93 items group together.
They used both exploratory and confirmatory factor analysis. The goal was to see if the test measures one or many autism traits.
Participants were people already diagnosed with autism spectrum disorder. Age range was not given.
What they found
Two clear factors showed up and stayed stable across ages. One factor is social-communication. The other is stereotyped behavior.
The authors say the current ADI-R algorithm should be updated to match these two factors.
How this fits with other research
Tureck et al. (2013) is the direct next step. That study built new toddler algorithms using a three-factor model. So the 2008 two-factor idea grew into a three-factor version for kids under four.
Lemons et al. (2015) also found two factors, but in adults from the general population using the Autism-Spectrum Quotient. The social-detail split looks similar, showing the pattern is not just clinical.
Mulder et al. (2020) trimmed items and reset cut-points on the SCQ and SRS-2 for fragile X. Like W et al., they show that fewer, better-weighted items can improve accuracy.
Why it matters
Expect the ADI-R algorithm to change. When it does, the social-communication and restricted behavior domains will likely get new item weights.
For now, keep using the current algorithm, but note which items load on each factor. If a future revision arrives, you will already know why the scores shifted.
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02At a glance
03Original abstract
The factor structure of the Autism Diagnostic Interview-Revised (ADI-R) algorithm items was examined using exploratory (EFA) and confirmatory factor analyses (CFA) factor methods. The ADI-R was completed for 1,170 youths and adults (ages 2-46). Results of EFAs indicated strong support for two-factor structure, with social communication and stereotyped behavior factors. CFAs computed in a holdout sub-sample indicated roughly equal support for the above described two-factor model and a three factor model separating peer relationships and play from other social and communicative behaviors. Multi-group CFAs suggested that both two and three factor models showed good stability across age, with only slight changes in factor relationships. These findings indicate that the current ADI-R structure be revised to more accurately reflect the relationships between sub-scales.
Journal of autism and developmental disorders, 2008 · doi:10.1007/s10803-007-0415-z