AI Article Synopsis

  • Traditional cognitive assessments often measure performance at just one point in time, which can overlook how cognitive abilities change due to various factors like environment and health conditions, making these assessments less reliable for certain populations, like individuals with type 1 diabetes (T1D).
  • The study aimed to validate a new method called ecological momentary assessment (EMA) to track cognitive performance over time in both adults with T1D and a general community sample, measuring their performance multiple times daily across several days.
  • Results showed that cognitive EMA has high reliability and validity, effectively capturing both individual differences and fluctuations in cognitive performance within individuals, proving to be a useful tool for understanding cognitive variations in real-world settings.

Article Abstract

Background: The current methods of evaluating cognitive functioning typically rely on a single time point to assess and characterize an individual's performance. However, cognitive functioning fluctuates within individuals over time in relation to environmental, psychological, and physiological contexts. This limits the generalizability and diagnostic utility of single time point assessments, particularly among individuals who may exhibit large variations in cognition depending on physiological or psychological context (eg, those with type 1 diabetes [T1D], who may have fluctuating glucose concentrations throughout the day).

Objective: We aimed to report the reliability and validity of cognitive ecological momentary assessment (EMA) as a method for understanding between-person differences and capturing within-person variation in cognition over time in a community sample and sample of adults with T1D.

Methods: Cognitive performance was measured 3 times a day for 15 days in the sample of adults with T1D (n=198, recruited through endocrinology clinics) and for 10 days in the community sample (n=128, recruited from TestMyBrain, a web-based citizen science platform) using ultrabrief cognitive tests developed for cognitive EMA. Our cognitive EMA platform allowed for remote, automated assessment in participants' natural environments, enabling the measurement of within-person cognitive variation without the burden of repeated laboratory or clinic visits. This allowed us to evaluate reliability and validity in samples that differed in their expected degree of cognitive variability as well as the method of recruitment.

Results: The results demonstrate excellent between-person reliability (ranging from 0.95 to 0.99) and construct validity of cognitive EMA in both the sample of adults with T1D and community sample. Within-person reliability in both samples (ranging from 0.20 to 0.80) was comparable with that observed in previous studies in healthy older adults. As expected, the full-length baseline and EMA versions of TestMyBrain tests correlated highly with one another and loaded together on the expected cognitive domains when using exploratory factor analysis. Interruptions had higher negative impacts on accuracy-based outcomes (β=-.34 to -.26; all P values <.001) than on reaction time-based outcomes (β=-.07 to -.02; P<.001 to P=.40).

Conclusions: We demonstrated that ultrabrief mobile assessments are both reliable and valid across 2 very different clinic versus community samples, despite the conditions in which cognitive EMAs are administered, which are often associated with more noise and variability. The psychometric characteristics described here should be leveraged appropriately depending on the goals of the cognitive assessment (eg, diagnostic vs everyday functioning) and the population being studied.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10276323PMC
http://dx.doi.org/10.2196/45028DOI Listing

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