What happens when you measure function instead of counting diagnoses
The diagnostic boundary between autism and ADHD is treated as meaningful — clinically, administratively, and in how support is allocated. One diagnosis or the other determines which pathway you enter, which interventions you receive, which frameworks clinicians use to understand your difficulties. The assumption is that the distinction captures something real about how people function.
New research from the University of Padova directly challenges this assumption. When researchers measured actual functioning across six developmental domains and let the data cluster naturally, the clusters didn’t respect the diagnostic boundary. Half of the autistic children and half of the ADHD children ended up in the same functional profile. The diagnostic label predicted almost nothing about how they actually performed.
The study, published in Research in Developmental Disabilities in February 2026, examined 204 children and adolescents aged 8–16: 51 with autism diagnoses, 64 with ADHD diagnoses, and 89 non-diagnosed peers matched for age, sex, and IQ. Rather than simply comparing diagnostic groups on single measures, the researchers assessed all participants across six functional domains — theory of mind, pragmatic language, inattention, impulsivity, social skills, and behavioural problems — then used latent profile analysis to identify naturally occurring patterns in the data.
The first finding was striking enough on its own. When comparing the autism and ADHD groups directly, there were no statistically significant differences on any of the six measures. Both clinical groups performed worse than non-diagnosed peers across most domains, but the two diagnostic categories were functionally indistinguishable from each other. The researchers state it plainly: “the differences between the two clinical groups did not reach statistical significance, suggesting overlapping traits across the two conditions.”
This alone challenges the clinical assumption that autism and ADHD represent fundamentally different developmental trajectories requiring fundamentally different approaches. But the latent profile analysis went further — it asked what happens when you stop imposing diagnostic categories and let functional patterns emerge from the data itself.
Four profiles emerged, and they ignored the autism/ADHD boundary
The analysis identified four distinct functional profiles, each characterised by specific configurations of strengths and difficulties across the six domains. The profiles were labelled based on their defining features: “Inattentive with pragmatic difficulties,” “Social deficits with behavioural dysregulation,” “Highly impulsive,” and “Minimal impairments.”
The critical finding is how participants distributed across these profiles. If diagnostic categories captured something real about functional presentation, you would expect autistic children to cluster predominantly in autism-typical profiles and ADHD children to cluster predominantly in ADHD-typical profiles. That is not what happened.
Profile 1 (“Inattentive with pragmatic difficulties”) comprised 60% autistic participants and 40% ADHD participants.
Profile 2 (“Social deficits with behavioural dysregulation”) comprised 41% autistic participants, 51% ADHD participants, and 8% non-diagnosed participants.
Profile 3 (“Highly impulsive”) comprised 25% autistic participants, 62.5% ADHD participants, and 12.5% non-diagnosed participants.
Profile 4 (“Minimal impairments”) comprised 7% autistic participants, 9% ADHD participants, and 84% non-diagnosed participants.
The profiles cut across diagnostic categories rather than aligning with them. Children with different diagnoses clustered together based on how they actually functioned. Children with the same diagnosis scattered across multiple profiles with different functional presentations. The diagnostic label was a poor predictor of functional profile membership.
Why 50% of autistic and ADHD children clustered together
The most striking result is Profile 2 — the “Social deficits with behavioural dysregulation” profile characterised by the highest behavioural problems, lowest social skills, and difficulties in theory of mind and pragmatic language. Exactly 50% of the autistic participants and 50% of the ADHD participants were classified into this single profile.
Half of each diagnostic group ended up functionally indistinguishable from half of the other. The children in this profile shared a common functional presentation regardless of whether their clinical file said “autism” or “ADHD.” Whatever the diagnostic criteria are capturing, it is not what determines whether a child will present with this particular configuration of social and behavioural difficulties.
The researchers note that Profile 2 was “primarily characterised by difficulties reported by parents, alongside weaknesses performing tests.” This matters because it suggests the shared profile reflects real-world functional impairment — not just performance on narrow laboratory measures, but difficulties that parents observe across contexts and over time. The convergence between parent report and direct assessment strengthens the validity of the finding.
The flip side is equally important. Some autistic participants — 7 out of 51, approximately 14% — appeared in the “Minimal impairments” profile alongside 84% of the non-diagnosed group. Some ADHD participants — 9 out of 64, also approximately 14% — appeared there too. These are diagnostically confirmed cases who, when measured across functional domains, clustered with children who have no diagnosis at all.
This doesn’t mean their diagnoses are wrong. It means diagnosis captures something other than current functional presentation. A child can meet diagnostic criteria for autism or ADHD while presenting with minimal functional impairment across the measured domains. Diagnosis attempts to identify a neurological difference; it doesn’t determine how that difference actually manifests in daily functioning.
What this means for assessment, support, and the diagnostic system itself
The researchers frame their findings within the broader shift toward dimensional and transdiagnostic approaches in neurodevelopmental research. They cite the DSM-5’s 2013 decision to allow comorbid autism and ADHD diagnoses — previously prohibited under DSM-IV — as recognition that the categorical boundary was never as clean as the diagnostic system implied. But this study goes further than comorbidity. It suggests the categories themselves may be administrative conveniences rather than natural kinds.
The clinical implications are significant. If diagnostic category doesn’t predict functional profile, then support allocation based primarily on diagnostic label is misaligned with actual need. A child in Profile 2 needs support for social functioning and behavioural regulation regardless of whether their diagnosis is autism or ADHD. A child in Profile 4 may need minimal support regardless of carrying a diagnosis. The functional profile, if anything — not the diagnostic category — should drive “intervention” planning.
The researchers emphasise that “relying exclusively on psychometric test data may introduce bias, as incorporating parents’ perspectives is essential for accurately identifying a child’s areas of vulnerability.” This echoes a broader point about assessment: standardised testing in controlled conditions may not capture real-world functioning. Children can perform adequately in structured assessment contexts while struggling significantly in the uncontrolled complexity of daily life. Parent report captures what testing misses.
There is a tension here that the study acknowledges but doesn’t resolve. On one hand, their findings support dimensional approaches that cut across diagnostic boundaries. On the other hand, they caution that “when based primarily on psychometric data, [transdiagnostic approaches] risk overinterpreting test performance without considering the individual processes that explain why a child struggles in specific tasks.” The data-driven profiles are more informative than binary diagnostic labels, but clinical interpretation still matters.
The study has limitations — relatively small sample size, Italian sample limiting generalisability, use of aggregated scores that may mask within-domain variability. The researchers are appropriately cautious about overgeneralising. But the core finding is robust: when you measure function and let clusters emerge naturally, the autism/ADHD boundary largely disappears.
This matters for how we think about neurodevelopmental difference. The diagnostic system treats autism and ADHD as distinct categories with different aetiologies, different presentations, and different treatment and intervention needs. The administrative and clinical infrastructure is built around this distinction. But if half of each diagnostic group is functionally indistinguishable, the distinction is doing less work than we assume. The boundary is administrative — useful for billing codes and research recruitment and prevalence statistics — but not necessarily meaningful for understanding how any individual child actually functions or what support they actually need.
The question is whether the diagnostic system will evolve to reflect this, or whether we will continue sorting children into categories that predict less than we pretend they do.
Citations
Crisci, G., Lievore, R., & Mammarella, I. C. (2026) — Blurred lines: Investigating functional profiles in autism and ADHD across key developmental domains
