No abstract

RTI reflects a novel dimension of performance that is a robust and theoretically informative predictor of BP and WP variation in cognitive function. Among the plenitude of RTI quantifications, not all are interchangeable, nor of comparable predictive utility.

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. 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).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. One hundred individuals met Jak/Bondi criteria for MCI. 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. 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. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed.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. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables.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. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. 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.

Objective: The aim of this study was to test the hypothesis that daily stress processes, including exposure and emotional reactivity to daily stressors, are associated with response time inconsistency (RTI), an indicator of processing efficiency and cognitive health. Furthermore, we considered daily stress-cognitive health associations at the level of individual differences and within-persons over time. Methods: Participants were 111 older adults (Mean=80 years, Range=66–95) enrolled in a measurement burst study where assessments of response-time based cognitive performance, stressful experiences, and affect were administered on each of 6 days over a two-week period. This protocol was repeated every six months for 2.5 years. Multilevel modeling was used to examine frequency of stressor exposure, non-stressor affect, and affect reactivity to daily stressors as individual difference and time-varying predictors of RTI. Results: Between-persons, higher levels of non-stressor negative affect (b=0.41, 95%CI: −0.01, 0.83, p=.055) and negative affect reactivity (b=0.80, 95%CI: 0.18, 1.42, p=.012) were associated with greater RTI. Within-persons over time, higher levels of negative affect (b=0.20, 95%CI: 0.06, 0.34, p=.006) and negative affect reactivity (b=0.13, 95%CI: 0.02, 0.24, p=.018) were associated with increased RTI among the oldest portion of the sample, while higher levels of positive affect (b=−0.11, 95% CI: −0.21, −0.02, p=.019) were associated with reduced RTI. Conclusions: Negative affect reactions to daily stressors are associated with compromised RTI both between- and within-persons. Findings suggest that emotional reactions to daily stressors contribute to compromise older adults’ cognitive health, while increased positive affect may be beneficial.

Objective : Increased intraindividual variability (IIV) in function has been linked to various age-related outcomes including cognitive decline and dementia. Most studies have operationalized IIV as fluctuations across trials (e.g., response latencies) for a single task, with comparatively few studies examining variability across multiple tasks for a given individual. In the present study, we derive a multivariable operationalization of dispersion across a broad profile of neuropsychological measures and use this index along with degree of engaged lifestyle to predict risk of cognitive impairment. Participants and Methods : Participants ( n = 60) were community-dwelling older adults aged 65+ years (M = 74.1, SD = 6.5) participating in a cross-sectional investigation of risk factors for amnestic mild cognitive impairment (a-MCI) and probable Alzheimer’s Disease (AD). Participants were classified into three subgroups based on test performance and clinical judgement. Healthy controls ( n = 30) scored better than −1 SD relative to existing norms on all classification measures, in the absence of memory complaints or functional impairments. The a-MCI group ( n = 23) had self- or informant-reported memory complaints and scored 1 SD or more below the mean for at least one memory task while scoring better than 1 SD below the mean for all other cognitive domains, in the absence of functional impairments. The AD group ( n = 7) scored at least 2 SD below the mean for two cognitive domains (including memory) with impairments in functioning. Measures spanned a range of cognitive domains (episodic memory, executive function, language), with the derived dispersion estimates reflecting variability across an individual’s neuropsychological profile relative to the group average. Further, an Activities Lifestyle Questionnaire, indexing social, cognitive, and physical behaviors, was administered to assess the protective benefits of engaged lifestyle. Results : Multinomial logistic regression models examined the risk of being classified as a-MCI or AD as a function of increased dispersion, (dis)engaged lifestyle, and their interaction. Greater dispersion was associated with an increased likelihood of being classified with AD, with protective engaged-lifestyle benefits apparent for a-MCI individuals only. Conclusion : As a measure of IIV, dispersion across neuropsychological profiles holds promise for the detection of cognitive impairment.