Personalized Cognitive Health in Psychiatry: Current State and the Promise of Computational Methods.

Abstract

Background: Decades of research have firmly established that cognitive health and cognitive treatment services are a key need for people living with psychosis. However, many current clinical programs do not address this need, despite the essential role that an individual's cognitive and social cognitive capacities play in determining their real-world functioning. Preliminary practice-based research in the Early Psychosis Intervention Network early psychosis intervention network shows that it is possible to develop and implement tools that delineate an individuals' cognitive health profile and that help engage the client and the clinician in shared decision-making and treatment planning that includes cognitive treatments. These findings signify a promising shift toward personalized cognitive health.

Study design: Extending upon this early progress, we review the concept of interindividual variability in cognitive domains/processes in psychosis as the basis for offering personalized treatment plans. We present evidence from studies that have used traditional neuropsychological measures as well as findings from emerging computational studies that leverage trial-by-trial behavior data to illuminate the different latent strategies that individuals employ.

Study result: We posit that these computational techniques, when combined with traditional cognitive assessments, can enrich our understanding of individual differences in treatment needs, which in turn can guide evermore personalized interventions.

Conclusion: As we find clinically relevant ways to decompose maladaptive behaviors into separate latent cognitive elements captured by model parameters, the ultimate goal is to develop and implement approaches that empower clients and their clinical providers to leverage individual's existing learning capacities to improve their cognitive health and well-being.