The Survey for Memory, Attention, and Reaction Time (SMART): Preliminary normative online panel data and user attitudes for a brief web-based cognitive performance measure.

ObjectiveThe Survey for Memory, Attention, and Reaction Time (SMART) was recently introduced as a brief (<5 min), self-administered, web-based measure of cognitive performance in older adults. The purpose of this study was threefold: (1) to develop preliminary norms on the SMART; (2) to examine the relationship between demographic variables (i.e. age, sex, education), device type used, and SMART performance; and (3) to assess user attitudes of the SMART. Method A sample of 1,050 community-dwelling adults (M age =59.5 (15.2), M education = 16.5 (2.1), 67.1% female, 96% white) was recruited from an ongoing web-based research cohort. Participants completed the SMART, which consists of four face-valid cognitive tasks assessing visual memory, attention/processing speed, and executive functioning. SMART performance outcome metrics were subtest completion time (CT), click count, and total CT. Participants provided demographic information and completed a survey of user attitudes toward the SMART (i.e. usability, acceptability). Results Older age was the only demographic variable associated with slower SMART total CT (r = .60, p <.001). Education was not associated with SMART CT or click counts overall (p > .05). Male sex was generally associated with longer SMART CT (p < .001, partial eta squared = .14) on all sub-tests. Regarding acceptability, 97.3% indicated willingness to take the SMART again, with more than half willing to complete it on a weekly basis. Conclusion The preliminary normative data on the SMART indicates that it is a feasible and well-accepted web-based cognitive assessment tool that can be administered on multiple device platforms.

Cognitive and psychological improvements following CogSMART in veterans with mental health diagnoses.

INTRODUCTION: The present study examined the efficacy of a CogSMART-based program in improving cognitive and emotional functioning in a clinic-based sample of Veterans presenting with cognitive concerns and history of mental health diagnoses. METHOD: Forty Veterans (Mage = 61.2 years, 85% male) completed a weekly CogSMART-based group program as well as a battery of neuropsychological and psychological measures at both pre- and post-group evaluations. Participants met DSM-5 criteria for at least one mental health diagnosis. RESULTS: Significant improvements on global cognition as well as measures of learning/memory and attention were observed from pre- to post-group (p < .05, cohen's d range = .48-1.01). As many as 33.3% of participants showed significant improvement, depending on the cognitive domain. Significant overall improvements were observed in depression symptoms and life satisfaction (p < .01, cohen's d = .67 and .59, respectively). Over one-third of the sample demonstrated a reliable improvement in depressive symptoms, 25% in anxiety symptoms, and 18% in life satisfaction. CONCLUSIONS: Among individuals with mental health diagnosis but without major neurocognitive disorders, CogSMART-based interventions may be an effective treatment for improving aspects of cognition, depression, and life satisfaction.

Age Predicts Older Adults' Driving Self-Regulation but Not Dangerous Driving Behaviors after Controlling for Executive Function.

OBJECTIVES: The aim of the study was to examine the unique contributions of age to objectively measure driving frequency and dangerous driving behaviors in healthy older adults after adjusting for executive function (EF). METHOD: A total of 28 community-dwelling older adults (mean age = 82.0 years, standard deviation [SD] = 7.5) without dementia who were in good physical health and enrolled in a longitudinal aging study completed several EF and clinical self-report measures at baseline. Participants subsequently had a sensor installed in their vehicle for a mean of 208 (SD = 38, range = 127-257) days. RESULTS: Participants drove for an average of 54 min per day. Mixed-effects models indicated that after controlling for EF, older age was associated with less time driving per day, decreased number of trips, and less nighttime driving. Age was not associated with hard brakes or hard accelerations. DISCUSSION: After accounting for EF, greater age is associated with higher driving self-regulation but not dangerous driving behaviors in healthy older adults. Future studies should recruit larger samples and collect sensor-measured driving data over a more extended time frame to better determine how and why these self-regulation changes take place.

Older Adults' Daily Activity and Mood Changes Detected During the COVID-19 Pandemic Using Remote Unobtrusive Monitoring Technologies.

BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has limited older adults' access to in-person medical care, including screenings for cognitive and functional decline. Remote, technology-based tools have shown recent promise in assessing changes in older adults' daily activities and mood, which may serve as indicators of underlying health-related changes (e.g., cognitive decline). This study examined changes in older adults' driving, computer use, mood, and travel events prior to and following the COVID-19 emergency declaration using unobtrusive monitoring technologies and remote online surveys. As an exploratory aim, the impact of mild cognitive impairment (MCI) on these changes was assessed. RESEARCH DESIGN AND METHODS: Participants were 59 older adults (41 cognitively intact and 18 MCI) enrolled in a longitudinal aging study. Participants had their driving and computer use behaviors recorded over a 5-month period (75 days pre- and 76 days post-COVID emergency declaration) using unobtrusive technologies. Measures of mood, overnight guests, and frequency of overnight travel were also collected weekly via remote online survey. RESULTS: After adjusting for age, gender, and education, participants showed a significant decrease in daily driving distance, number of driving trips, highway driving, and nighttime driving, post-COVID-19 as compared to pre-COVID-19 (p < .001) based on generalized estimating equation models. Further, participants spent more time on the computer per day post-COVID-19 (p = .03). Participants endorsed increases in blue mood (p < .01) and loneliness (p < .001) and decreases in travel away from home and overnight visitors (p < .001) from pre- to post-COVID-19. Cognitive status did not impact these relationships. DISCUSSION AND IMPLICATIONS: From pre- to post-COVID-19 emergency declaration, participants drove and traveled less, used their computer more, had fewer overnight visitors, and reported greater psychological distress. These results highlight the behavioral and psychological effects of stay-at-home orders on older adults who are cognitively intact and those with MCI.

The Survey for Memory, Attention, and Reaction Time (SMART): Development and Validation of a Brief Web-Based Measure of Cognition for Older Adults.

INTRODUCTION: Brief, Web-based, and self-administered cognitive assessments hold promise for early detection of cognitive decline in individuals at risk for dementia. The current study describes the design, implementation, and convergent validity of a fWeb-based cognitive assessment tool, the Survey for Memory, Attention, and Reaction Time (SMART), for older adults. METHODS: A community-dwelling sample of older adults (n = 69) was included, classified as cognitively intact (n = 44) or diagnosed with mild cognitive impairment (MCI, n = 25). Participants completed the SMART at home using their computer, tablet, or other Internet-connected device. The SMART consists of 4 face-valid cognitive tasks available in the public domain assessing visual memory, attention/processing speed, and executive functioning. Participants also completed a battery of standardized neuropsychological tests, a cognitive screener, and a daily function questionnaire. Primary SMART outcome measures consisted of subtest completion time (CT); secondary meta-metrics included outcomes indirectly assessed or calculated within the SMART (e.g., click count, total CT, time to complete practice items, and time of day the test was completed). RESULTS: Regarding validity, total SMART CT, which includes time to complete test items, practice items, and directions, had the strongest relationship with global cognition (ß = -0.47, p < 0.01). Test item CT was significantly greater for the MCI group (F = 5.20, p = 0.026). Of the SMART tasks, the executive functioning subtests had the strongest relationship with cognitive status as compared to the attention/processing speed and visual memory subtests. The primary outcome measures demonstrated fair to excellent test-retest reliability (intraclass correlation coefficient = 0.50-0.76). CONCLUSIONS: This study provides preliminary evidence for the use of the SMART protocol as a feasible, reliable, and valid assessment method to monitor cognitive performance in cognitively intact and MCI older adults.

Subtle Changes in Medication-taking Are Associated With Incident Mild Cognitive Impairment.

INTRODUCTION: Medication-taking is a routine instrumental activity of daily living affected by mild cognitive impairment (MCI) but difficult to measure with clinical tools. This prospective longitudinal study examined in-home medication-taking and transition from normative aging to MCI. METHODS: Daily, weekly, and monthly medication-taking metrics derived from an instrumented pillbox were examined in 64 healthy cognitively intact older adults (Mage=85.5 y) followed for a mean of 2.3 years; 9 transitioned to MCI during study follow-up. RESULTS: In the time up to and after MCI diagnosis, incident MCI participants opened their pillbox later in the day (by 19 min/mo; ß=0.46, P<0.001) and had increased day-to-day variability in the first pillbox opening over time (by 4 min/mo) as compared with stable cognitively intact participants (ß=4.0, P=0.003). DISCUSSION: Individuals who transitioned to MCI opened their pillboxes later in the day and were more variable in their medication-taking habits. These differences increased in the time up to and after diagnosis of MCI. Unobtrusive medication-taking monitoring is an ecologically valid approach for identifying early activity of daily living changes that signal transition to MCI.