Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease.

OBJECTIVE: Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD. METHOD: Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials. RESULTS: Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites. CONCLUSIONS: Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

Predictors and outcomes of fluctuations in the clinical dementia rating scale.

INTRODUCTION: Reversion, or change in cognitive status from impaired to normal, is common in aging and dementia studies, but it remains unclear what factors predict reversion. METHODS: We investigated whether reverters, defined as those who revert from a Clinical Dementia Rating® (CDR®) scale score of 0.5 to CDR 0) differed on cognition and biomarkers from unimpaired participants (always CDR 0) and impaired participants (converted to CDR > 0 and had no reversion events). Models evaluated relationships between biomarker status, apolipoprotein E (APOE) ε4 status, and cognition. Additional models described predictors of reversion and predictors of eventual progression to CDR > 0. RESULTS: CDR reversion was associated with younger age, better cognition, and negative amyloid biomarker status. Reverters that eventually progressed to CDR > 0 had more visits, were older, and were more likely to have an APOE ε4 allele. DISCUSSION: CDR reversion occupies a transitional phase in disease progression between cognitive normality and overt dementia. Reverters may be ideal candidates for secondary prevention Alzheimer's disease (AD) trials. HIGHLIGHTS: Reverters had more longitudinal cognitive decline than those who remained cognitively normal. Predictors of reversion: younger age, better cognition, and negative amyloid biomarker status. Reverting from CDR 0.5 to 0 is a risk factor for future conversion to CDR > 0. CDR reversion may be a transitional phase in Alzheimer's Disease progression. CDR reverters may be ideal for Alzheimer's disease secondary prevention trials.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer's disease.

OBJECTIVE: Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer's disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants' personal devices in their everyday environments. METHODS: We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97 years) and 22 individuals with very mild dementia (ages 61-88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies. RESULTS: First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants. CONCLUSIONS: Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Bridging the Technological Divide: Stigmas and Challenges With Technology in Digital Brain Health Studies of Older Adults.

The COVID-19 pandemic has increased adoption of remote assessments in clinical research. However, longstanding stereotypes persist regarding older adults' technology familiarity and their willingness to participate in technology-enabled remote studies. We examined the validity of these stereotypes using a novel technology familiarity assessment (n = 342) and with a critical evaluation of participation factors from an intensive smartphone study of cognition in older adults (n = 445). The technology assessment revealed that older age was strongly associated with less technology familiarity, less frequent engagement with technology, and higher difficulty ratings. Despite this, the majority (86.5%) of older adults elected to participate in the smartphone study and showed exceptional adherence (85.7%). Furthermore, among those enrolled, neither technology familiarity, knowledge, perceived difficulty, nor gender, race, or education were associated with adherence. These results suggest that while older adults remain significantly less familiar with technology than younger generations, with thoughtful study planning that emphasizes participant support and user-centered design, they are willing and capable participants in technology-enabled studies. And once enrolled, they are remarkably adherent.

Sharper in the morning: Cognitive time of day effects revealed with high-frequency smartphone testing.

Decades of research has established a shift from an "eveningness" preference to a "morningness" preference with increasing age. Accordingly, older adults typically have better cognition in morning hours compared to evening hours. We present the first known attempt to capture circadian fluctuations in cognition in individuals at risk for Alzheimer disease (AD) using a remotely administered smartphone assessment that samples cognition rapidly and repeatedly over several days. Older adults (N = 169, aged 61-94 years; 93% cognitively normal) completed four brief smartphone-based testing sessions per day for 7 consecutive days at quasi-random time intervals, assessing associate memory, processing speed, and visual working memory. Scores completed during early hours were averaged for comparison with averaged scores completed during later hours. Mixed effects models evaluated time of day effects on cognition. Additional models included clinical status and cerebrospinal fluid (CSF) biomarkers for beta amyloid (Aß42) and phosphorylated tau181 (pTau). Models with terms for age, gender, education, APOE ε4 status, and clinical status revealed significantly worse performance on associate memory in evening hours compared to morning hours. Contemporaneously reported mood and fatigue levels did not moderate relationships. Using CSF data to classify individuals with and without significant AD pathology, there were no group differences in performance in morning hours, but subtle impairment emerged in associate memory in evening hours in those with CSF-confirmed AD pathology. These findings indicate that memory is worse in evening hours in older adults, that this pattern is consistent across several days, and is independent of measures of mood and fatigue. Further, they provide preliminary evidence of a "cognitive sundowning" in the very earliest stages of AD. Time of day may be an important consideration for assessments in observational studies and clinical trials in AD populations.