Multimodal assessment of adult attention-deficit hyperactivity disorder using virtual reality

Attention-deficit hyperactivity disorder (ADHD) is a complex and heterogeneous disorder. As a result of this heterogeneity, it has been difficult to identify reliable objective tests and markers for ADHD. The neuropsychological continuous performance test (CPT) has often been explored as a candidate, but it is neither sensitive nor specific enough to be used for diagnosis on its own. Adding physiological measures has been shown to improve ist diagnostic ability, suggesting that combining different assessment levels may better reflect the complexity of the disorder. Another reason for the limited usefulness of the classic CPT in ADHD assessment may also be the abstract, computer-based nature of the test. Here, a possible solution may be the addition of virtual reality (VR), as it allows the creation of immersive and realistic, yet standardized test environments. For the assessment of ADHD in children, VR-based CPTs have already shown promising results, but there is still very little research in adults. <br> Therefore, in this dissertation, a VR-based CPT test environment for adult ADHD, the virtual seminar room (VSR) was developed and evaluated. In addition to CPT performance, head actigraphy, eye tracking, electroencephalography, functional nearinfrared spectroscopy, and subjective experience were assessed to better capture the heterogeneity of the disorder. This multimodal VSR was evaluated in three consecutive studies. In study I, we tested the general feasibility and tolerability of the setup in a sample of healthy adults. Next, in study II, we investigated whether group differences between unmedicated adults with ADHD, medicated adults with ADHD, and healthy controls (HC) could be found in the different modalities. Finally, in study III, we used machine learning to investigate the extent to which, on a single-subject basis, unmedicated individuals with ADHD and HC could be correctly classified using the VSR parameters. <br> The results showed that the VSR setup was feasible and tolerable for both healthy individuals (study I and II) and those with ADHD (study II). While there was no clear evidence for a sensitivity of the VSR to medication effects in study II, significant Group differences between unmedicated individuals with ADHD and HC were found in CPT performance, actigraphy, eye tracking, and subjective experience. Further, combining these modalities via machine learning resulted in high accuracy in distinguishing the two groups in study III, underlining the diagnostic potential of the VSR and especially the importance of a multimodal approach in the assessment of adult ADHD. This potential needs to be further explored in future, large sample studies, for example by investigating the ability of the VSR to differentiate ADHD from other disorders.