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Cognitive variability pathological aging8/12/2023 ![]() ![]() ![]() 10.1111/j. variability of reaction time (IIV RT), a proposed cognitive marker of neurobiological disturbance, increases in old age, and has been associated with dementia and mortality. Mild cognitive impairment–beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. ![]() Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Intraindividual variability, cognition, and aging. Hultsch DF, Strauss E, Hunter MA, MacDonald SWS. Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. 10.1002/alz.12328īondi MW, Edmonds EC, Jak AJ, Clark LR, Delano-Wood L, McDonald CR, et al. 2021 Alzheimer's disease facts and figures. The 16-day smartphone-based EMA measurement burst offers novel opportunity to leverage digital technology to measure performance variability across frequent assessments for studying cognitive health and identifying early clinical manifestations of cognitive impairment.Īlzheimer's disease and related dementias (ADRD) cognitive health cognitive performance variability ecological momentary assessment (EMA) intraindividual variability (IIV) mild cognitive impairment–MCI mobile cognitive assessment technology.Ĭopyright © 2021 Cerino, Katz, Wang, Qin, Gao, Hyun, Hakun, Roque, Derby, Lipton and Sliwinski.Īlzheimer's Association (2021). Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Conclusion: Our smartphone-based digital health approach facilitates the ambulatory assessment of cognitive performance in older adults and the capacity to differentiate individuals with MCI from those who were CU. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Results: Individuals with MCI exhibited greater within-day variability than those who were CU on ambulatory assessments that measure processing speed ( p < 0.001) and visual short-term memory binding ( p < 0.001) performance but not spatial working memory. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed. We employed heterogeneous variance multilevel models using log-linear prediction of residual variance to simultaneously assess cognitive status differences in mean performance, within-day variability, and day-to-day variability. All participants performed mobile cognitive tests of processing speed, visual short-term memory binding, and spatial working memory on a smartphone device up to six times daily for 16 days, yielding up to 96 assessments per person. One hundred individuals met Jak/Bondi criteria for MCI. Method: A sample of 311 systematically recruited, community-dwelling older adults from the Einstein Aging Study (Mean age = 77.46 years, SD = 4.86, Range = 70-90 67% Female 45% Non-Hispanic White, 40% Non-Hispanic Black) completed neuropsychological testing, neurological assessments, and self-reported questionnaires. We use a smartphone-based digital health approach with ecological momentary assessments (EMA) to examine differences in variability in performance among older adults with mild cognitive impairment (MCI) and those who were cognitively unimpaired (CU). Background and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. ![]()
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