Abstract
Background
A key question for any psychopathological diagnosis is whether the condition is continuous or discontinuous with typical variation. The primary objective of this study was to use a multi-method approach to examine the broad latent categorical versus dimensional structure of autism spectrum disorder (ASD).
Method
Data were aggregated across seven independent samples of participants with ASD, other neurodevelopmental disorders (NDD), and non-ASD/NDD controls (aggregate Ns = 512–16,755; ages 1.5–22). Scores from four distinct phenotype measures formed composite “indicators” of the latent ASD construct. The primary indicator set included eye gaze metrics from seven distinct social stimulus paradigms. Logistic regressions were used to combine gaze metrics within/across paradigms, and derived predicted probabilities served as indicator values. Secondary indicator sets were constructed from clinical observation and parent-report measures of ASD symptoms. Indicator sets were submitted to taxometric- and latent class analyses.
Results
Across all indicator sets and analytic methods, there was strong support for categorical structure corresponding closely to ASD diagnosis. Consistent with notions of substantial phenotypic heterogeneity, the ASD category had a wide range of symptom severity. Despite the examination of a large sample with a wide range of IQs in both genders, males and children with lower IQ were over-represented in the ASD category, similar to observations in diagnosed cases.
Conclusions
Our findings provide strong support for categorical structure corresponding closely to ASD diagnosis. The present results bolster the use of well-diagnosed and representative ASD groups within etiologic and clinical research, motivating the ongoing search for major drivers of the ASD phenotype. Despite the categorical structure of ASD, quantitative symptom measurements appear more useful for examining relationships with other factors.
A key question for any psychopathological diagnosis is whether the condition is continuous or discontinuous with typical variation. The primary objective of this study was to use a multi-method approach to examine the broad latent categorical versus dimensional structure of autism spectrum disorder (ASD).
Method
Data were aggregated across seven independent samples of participants with ASD, other neurodevelopmental disorders (NDD), and non-ASD/NDD controls (aggregate Ns = 512–16,755; ages 1.5–22). Scores from four distinct phenotype measures formed composite “indicators” of the latent ASD construct. The primary indicator set included eye gaze metrics from seven distinct social stimulus paradigms. Logistic regressions were used to combine gaze metrics within/across paradigms, and derived predicted probabilities served as indicator values. Secondary indicator sets were constructed from clinical observation and parent-report measures of ASD symptoms. Indicator sets were submitted to taxometric- and latent class analyses.
Results
Across all indicator sets and analytic methods, there was strong support for categorical structure corresponding closely to ASD diagnosis. Consistent with notions of substantial phenotypic heterogeneity, the ASD category had a wide range of symptom severity. Despite the examination of a large sample with a wide range of IQs in both genders, males and children with lower IQ were over-represented in the ASD category, similar to observations in diagnosed cases.
Conclusions
Our findings provide strong support for categorical structure corresponding closely to ASD diagnosis. The present results bolster the use of well-diagnosed and representative ASD groups within etiologic and clinical research, motivating the ongoing search for major drivers of the ASD phenotype. Despite the categorical structure of ASD, quantitative symptom measurements appear more useful for examining relationships with other factors.
| Original language | English |
|---|---|
| Article number | e12142 |
| Journal | JCPP Advances |
| Volume | 3 |
| Issue number | 2 |
| Publication status | Published - 21 Feb 2023 |
Keywords
- autism
- categorical
- dimensional
- latent
- taxometric