Abstract
Background: Autistic traits are often reported to be elevated in children diagnosed with attention-deficit/hyperactivity disorder (ADHD). However, the distribution of subclinical autistic traits in children with ADHD has not yet been established; knowing this may have important implications for diagnostic and intervention processes. The present study proposes a preliminary model of the distribution of parent-reported ADHD and subclinical autistic traits in two independent samples of Australian children with and without an ADHD diagnosis. Methods: Factor mixture modelling was applied to Autism Quotient and Conners' Parent Rating Scale – Revised responses from parents of Australian children aged 6–15 years who participated in one of two independent studies. Results: A 2-factor, 2-class factor mixture model with class varying factor variances and intercepts demonstrated the best fit to the data in both discovery and replication samples. The factors corresponded to the latent constructs of ‘autism’ and ‘ADHD’, respectively. Class 1 was characterised by low levels of both ADHD and autistic traits. Class 2 was characterised by high levels of ADHD traits and low-to-moderate levels of autistic traits. The classes were largely separated along diagnostic boundaries. The largest effect size for differences between classes on the Autism Quotient was on the Social Communication subscale. Conclusions: Our findings support the conceptualisation of ADHD as a continuum, whilst confirming the utility of current categorical diagnostic criteria. Results suggest that subclinical autistic traits, particularly in the social communication domain, are unevenly distributed across children with clinically significant levels of ADHD traits. These traits might be profitably screened for in assessments of children with high ADHD symptoms and may also represent useful targets for intervention.
| Original language | English |
|---|---|
| Article number | e12223 |
| Number of pages | 19 |
| Journal | JCPP Advances |
| Volume | 4 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jun 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- attention-deficit/hyperactivity disorder
- factor mixture modelling
- latent structure
- subclinical autism
Projects
- 1 Finished
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Data-driven diagnoses and treatments for neurodevelopmental disorders.
Bellgrove, M. (Primary Chief Investigator (PCI)), Johnson, B. (Chief Investigator (CI)), Cornish, K. (Chief Investigator (CI)), Kirk, H. (Chief Investigator (CI)), Williams, K. (Chief Investigator (CI)) & Hawi, Z. (Chief Investigator (CI))
Department of Health, Disability and Ageing (Australia)
20/01/20 → 30/06/25
Project: Research
Activities
- 1 Professional association or peak discipline body
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Australasian ADHD Professionals Association (AADPA) Curent Member
Tiego, J. (Member)
18 Sept 2024Activity: External Academic Engagement › Professional association or peak discipline body
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