2026 ECNP Congress

PS04-4132

Fully automated computerised cognitive assessments suitable for deployment in psychiatric disorders

Bryony Goulding Mew — L. Rida, B. Gooddy, L. Schalk, A.R. Moura, T. Szentgyorgyi, B. Eiff, I. Rafiq, C. Davies, D. Martins, L.A. Porffy, C. Wooldridge, P.J. Hellyer, J.R. Nicholson, M. Waser, E. Tunbridge, M. von Heimendahl, S. Süssmuth, K.V. Allebrandt, S. Shergill, S.C.R. Williams, A. Hampshire · King's College London, Neuroimaging, London, United Kingdom

Cognitive dysfunction is a core feature of psychiatric disorders, with both shared and disorder-specific profiles across diagnostic categories [1,2]. It remains comparatively understudied relative to affective and behavioural symptoms. These impairments are strongly associated with functional outcomes, long-term prognosis, and socioeconomic burden, and are insufficiently addressed by existing pharmacological and psychological interventions [3-5]. Improved characterisation of cognitive dysfunction across disorders is therefore essential. To do so, cognitive assessments deployed in psychiatric research should cover sufficient breadth of cognitive domains in a feasible and scalable manner, while maintaining sensitivity to subtle individual differences across populations. The present study aimed to quantify cognitive performance in major depressive disorder (MDD) and schizophrenia (SZ) using a brief, scalable online cognitive battery designed for large-scale deployment. Participants with MDD (n = 75) and SZ (n = 50) were compared to healthy controls (HC; n = 50) on a set of standardised, computerised cognitive tasks assessing multiple domains of cognitive function, including attention, working memory, and executive control. To evaluate convergent validity and reliability, a subset of participants (n = 25 per group) completed a second in-person session involving the same computerised battery alongside established paper-based cognitive assessments. This design enabled direct comparison across modalities and assessment of test-retest stability across contexts. Task performance metrics included accuracy and reaction time measures, alongside derived contrast scores enabling detailed assessment of speed-accuracy trade-offs and cognitive control processes. Contrary to initial hypotheses, individuals with MDD did not exhibit significant deficits in objective cognitive performance relative to HCs. However, they reported significantly altered subjective cognitive states, indicating a divergence between perceived and measured cognitive function. In contrast, individuals with SZ demonstrated widespread and pronounced impairments across cognitive domains relative to both MDD and HC groups, consistent with extensive evidence of generalised cognitive disruption in SZ. Additional analyses confirmed that these findings were not attributable to limitations in measurement sensitivity or sample characteristics. Performance on the computerised tasks showed strong correspondence with gold-standard assessments, supporting convergent validity, and demonstrated good test-retest reliability across sessions and modalities. These findings provide evidence for a dissociation between subjective and objective cognition in MDD, alongside the robust and generalised cognitive impairment observed in SZ. The observed association between greater depressive symptom severity and improved cognitive performance further challenges assumptions derived from categorical diagnostic frameworks, highlighting the importance of considering dimensional variation in symptomatology when examining cognitive function. This study demonstrates the utility of brief, online cognitive assessments as valid, efficient, and scalable tools for characterising cognitive dysfunction across psychiatric populations. The capacity to deploy such measures remotely and at scale facilitates data collection in ecologically diverse settings and among underrepresented groups. These methodological advantages provide a foundation for future large-scale, transdiagnostic investigations aimed at elucidating the mechanisms linking cognitive control and psychopathology, and for informing the development of targeted, evidence-based interventions globally.

References

  1. Abramovitch A, Short T, Schweiger A. The C Factor: Cognitive dysfunction as a transdiagnostic dimension in psychopathology. Clin Psychol Rev. 2021;86:102007.
  2. Millan MJ, Agid Y, Brüne M, et al. Cognitive dysfunction in psychiatric disorders: Characteristics, causes and the quest for improved therapy. Nat Rev Drug Discov. 2012;11(2):141–168.
  3. Cambridge OR, Knight MJ, Mills N, Baune BT. The clinical relationship between cognitive impairment and psychosocial functioning in major depressive disorder: A systematic review. Psychiatry Res. 2018;269:157–171.
  4. Evans VC, Iverson GL, Yatham LN, Lam RW. The relationship between neurocognitive and psychosocial functioning in major depressive disorder: A systematic review. J Clin Psychiatry. 2014;75(12):1359–1370.
  5. McIntyre RS, Soczynska JZ, Woldeyohannes HO, et al. The impact of cognitive impairment on perceived workforce performance: Results from the International Mood Disorders Collaborative Project. Compr Psychiatry. 2015;56:279–282.