Probing the overarching continuum theory: Data-driven phenotypic clustering of children with ASD or ADHD
Open accessAbstract
The clinical validity of the distinction between ADHD and ASD is a longstanding discussion. Recent advances in the realm of data-driven analytic techniques now enable us to formally investigate theories aiming to explain the frequent co-occurrence of these neurodevelopmental conditions. In this study, we probe different theoretical positions by means of a pre-registered integrative approach of novel classification, subgrouping, and taxometric techniques in a representative sample (N = 434), and replicate the results in an independent sample (N = 219) of children (ADHD, ASD, and typically developing) aged 7-14 years. First, Random Forest Classification could predict diagnostic groups based on questionnaire data with limited accuracy-suggesting some remaining overlap in behavioral symptoms between them. Second, community detection identified four distinct groups, but none of them showed a symptom profile clearly related to either ADHD or ASD in neither the original sample nor the replication sample. Third, taxometric analyses showed evidence for a categorical distinction between ASD and typically developing children, a dimensional characterization of the difference between ADHD and typically developing children, and mixed results for the distinction between the diagnostic groups. We present a novel framework of cutting-edge statistical techniques which represent recent advances in both the models and the data used for research in psychiatric nosology. Our results suggest that ASD and ADHD cannot be unambiguously characterized as either two separate clinical entities or opposite ends of a spectrum, and highlight the need to study ADHD and ASD traits in tandem.
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The current evidence base supports conceptualizing ADHD-ASD overlap as a distinct hybrid phenotype rather than a mere comorbidity.
“The current evidence base supports conceptualizing ADHD–ASD overlap as a distinct hybrid phenotype rather than a mere comorbidity”
From ADHD in Adulthood: Clinical Presentation, Comorbidities, and Treatment Perspectives (2025) · cites this paper as [48]
The Results (Community detection identifies subgroups that cross-diagnostic boundaries; page unavailable) report that children with both diagnoses appeared in multiple clusters, rather than a distinct hybrid group. The Conclusion (page unavailable) says the study cannot unambiguously characterize ADHD and ASD as separate entities or opposite ends of a spectrum. It therefore does not support presenting a distinct hybrid phenotype as the conclusion of the evidence. (LLM, conf=0.85)
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ADHD in Adulthood: Clinical Presentation, Comorbidities, and Treatment Perspectives
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“The current evidence base supports conceptualizing ADHD–ASD overlap as a distinct hybrid phenotype rather than a mere comorbidity [48–50].”
- Authors
- Deserno, M. K., Bathelt, J., Groenman, A. P., & Geurts, H. M.
- Affiliations
- Max Planck Institute for Human Development (DE)
- Royal Holloway University of London (GB)
- University of Amsterdam (NL)
- Parnassia Groep (NL)
- Corresponding author
- Deserno, M. K.
- Venue
- European Child & Adolescent Psychiatry
- Published
- 2022-06-10
- Volume
- 32
- Issue
- 10
- Pages
- 1909-1923
- ISSN
- 1018-8827 (ISSN-L)
- 1435-165X
- PMC
- PMC10533623
- OpenAlex
- W4281666639
- Cited by
- 22
- References
- 83
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 10 · 2023: 3 · 2022: 1
- FWCI
- 2.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- European Child & Adolescent Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- PsyArXiv (OSF Preprints) (submittedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (453-16-006, 019.191SG.005)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- autism spectrum disorder, attention deficit hyperactivity disorder, diagnostic classification, phenotypic clustering, taxometric analysis, community detection, random forest classification, psychiatric classification, children, symptom profiles, diagnostic validity
- MeSH terms
- Autism Spectrum Disorder, Attention Deficit Disorder with Hyperactivity, Child, Humans, Phenotype, Neurodevelopmental Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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