Accurate Prediction of Momentary Cognition From Intensive Longitudinal Data.

BACKGROUND: Deficits in cognitive performance are implicated in the development and maintenance of psychopathology. Emerging evidence further suggests that within-person fluctuations in cognitive performance may represent sensitive early markers of neuropsychiatric decline. Incorporating routine cognitive assessments into standard clinical care-to identify between-person differences and monitor within-person fluctuations-has the potential to improve diagnostic screening and treatment planning. In support of these goals, it is critical to understand to what extent cognitive performance varies under routine, remote assessment conditions (i.e., momentary cognition) in relation to a wide range of possible predictors. METHODS: Using data-driven, high-dimensional methods, we ranked strong predictors of momentary cognition and evaluated out-of-sample predictive accuracy. Our approach leveraged innovations in digital technology, including ambulatory assessment of cognition and behavior 1) at scale (n = 122 participants, n = 94 females), 2) in naturalistic environments, and 3) within an intensive longitudinal study design (mean = 25.5 assessments/participant). RESULTS: Reaction time (R2 > 0.70) and accuracy (0.56 >R2 > 0.35) were strongly predicted by age, between-person differences in mean performance, and time of day. Effects of self-reported, intraindividual fluctuations in environmental (e.g., noise) and internal (e.g., stress) states were also observed. CONCLUSIONS: Our results provide robust estimates of effect size to characterize sources of cognitive variability, to support the identification of optimal windows for psychosocial interventions, and to possibly inform clinical evaluation under remote neuropsychological assessment conditions.

The TestMyBrain Digital Neuropsychology Toolkit: Development and Psychometric Characteristics.

INTRODUCTION: To allow continued administration of neuropsychological evaluations remotely during the pandemic, tests from the not-for-profit platform, TestMyBrain.org (TMB), were used to develop the TMB Digital Neuropsychology Toolkit (DNT). This study details the psychometric characteristics of the DNT, as well as the infrastructure and development of the DNT. METHOD: The DNT was primarily distributed for clinical use, with (72.8%) of individuals requesting access for clinical purposes. To assess reliability and validity of the DNT, anonymous data from DNT test administrations were analyzed and compared to a large, non-clinical normative sample from TMB. RESULTS: DNT test scores showed acceptable to very good split-half reliability (.68-.99). Factor analysis revealed three latent factors, corresponding to processing speed, working memory, and a broader general cognitive ability factor that included perceptual reasoning and episodic memory. Average test scores were slightly poorer for the DNT sample than for the TMB comparison sample, as expected given the clinical use of the DNT. CONCLUSIONS: Initial estimates of reliability and validity of DNT tests support their use as digital measures of neuropsychological functioning. Tests within cognitive domains correlated highly with each other and demonstrated good reliability and validity. Future work will seek to validate DNT tests in specific clinical populations and determine best practices for using DNT outcome measures to assess engagement and psychological symptomatology.