A Quick and Reliable Eye Movement Test to Help Diagnose ADHD in Children.

Attention Deficit Hyperactivity Disorder (ADHD) affects more than 5 % of children and adolescents, with a globally increasing prevalence. The condition imposes a significant burden on affected individuals, their families, and healthcare systems. Early and accurate diagnosis is crucial to ensure timely therapeutic and educational interventions. However, current diagnostic practices rely heavily on clinical interviews and behavioral observations, which are inherently subjective and resource-intensive.

There is a growing need for objective diagnostic tools that can complement or even partially replace current clinical assessments. One promising approach involves eye-tracking technology, as ADHD is associated with altered oculomotor control and attention-related neural circuits. These changes may be reflected in measurable eye movement parameters, including saccadic latency and fixation stability.

This clinical investigation uses a certified, CE-marked medical eye-tracking device (neos™) to assess whether specific eye movement parameters can serve as objective biomarkers for ADHD. Although the device was originally designed to assess visual pathway integrity, it also captures parameters related to attention and executive function through standardized protocols. The test is examiner-independent, non-invasive, and takes approximately 10 minutes.

The study is observational and non-interventional, involving two groups of participants aged 8 to 16: 50 children with a clinically confirmed diagnosis of ADHD and 50 age-matched non-ADHD controls. All participants will complete a single neos™ eye-tracking assessment.

The primary hypothesis is that children with ADHD will demonstrate greater variability in saccadic latency and a higher frequency of large saccades (\> 3°) during fixation compared to controls. These differences will be analyzed as potential diagnostic biomarkers. Diagnostic accuracy will be evaluated using receiver operating characteristic (ROC) analysis, with sensitivity, specificity and area under the curve (AUC) values reported.

Secondary hypotheses include:

Oculomotor parameters derived from the neos™ system can distinguish between ADHD subtypes (predominantly inattentive, hyperactive-impulsive and combined).

Combined oculomotor metrics correlate with ADHD symptom severity, potentially enabling a quantitative assessment of disease burden.

The results of this study could pave the way for the clinical adoption of objective, scalable and rapid diagnostic tools for ADHD. Beyond clinical use, such tools may also be adapted for population screening, telemedicine or integration into consumer-grade technologies such as virtual reality headsets. By validating a market-approved device for a new mental health indication, this study represents a critical step toward bridging research and clinical application in ADHD diagnostics.