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.

Background: Computer use is a cognitively complex instrumental activity of daily living (IADL) that has been linked to cognitive functioning in older adulthood, yet little work has explored its capacity to detect incident mild cognitive impairment (MCI). Objective: To examine whether routine home computer use (general computer use as well as use of specific applications) could effectively discriminate between older adults with and without MCI, as well as explore associations between use of common computer applications and cognitive domains known to be important for IADL performance. Methods: A total of 60 community-dwelling older adults (39 cognitively healthy, 21 with MCI) completed a neuropsychological evaluation at study baseline and subsequently had their routine home computer use behaviors passively recorded for three months. Results: Compared to those with MCI, cognitively healthy participants spent more time using the computer, had a greater number of computer sessions, and had an earlier mean time of first daily computer session. They also spent more time using email and word processing applications, and used email, search, and word processing applications on a greater number of days. Better performance in several cognitive domains, but in particular memory and language, was associated with greater frequency of browser, word processing, search, and game application use. Conclusion: Computer and application use are useful in identifying older adults with MCI. Longitudinal studies are needed to determine whether decreases in overall computer use and specific computer application use are predictors of incident cognitive decline.

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; β=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 (β=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.

Background Aging military veterans are an important and growing population who are at an elevated risk for developing mild cognitive impairment (MCI) and Alzheimer dementia, which emerge insidiously and progress gradually. Traditional clinic-based assessments are administered infrequently, making these visits less ideal to capture the earliest signals of cognitive and daily functioning decline in older adults. Objective This study aimed to evaluate the feasibility of a novel ecologically valid assessment approach that integrates passive in-home and mobile technologies to assess instrumental activities of daily living (IADLs) that are not well captured by clinic-based assessment methods in an aging military veteran sample. Methods Participants included 30 community-dwelling military veterans, classified as healthy controls (mean age 72.8, SD 4.9 years; n=15) or MCI (mean age 74.3, SD 6.0 years; n=15) using the Clinical Dementia Rating Scale. Participants were in relatively good health (mean modified Cumulative Illness Rating Scale score 23.1, SD 2.9) without evidence of depression (mean Geriatrics Depression Scale score 1.3, SD 1.6) or anxiety (mean generalized anxiety disorder questionnaire 1.3, SD 1.3) on self-report measures. Participants were clinically assessed at baseline and 12 months later with health and daily function questionnaires and neuropsychological testing. Daily computer use, medication taking, and physical activity and sleep data were collected via passive computer monitoring software, an instrumented pillbox, and a fitness tracker watch in participants’ environments for 12 months between clinical study visits. Results Enrollment began in October 2018 and continued until the study groups were filled in January 2019. A total of 201 people called to participate following public posting and focused mailings. Most common exclusionary criteria included nonveteran status 11.4% (23/201), living too far from the study site 9.4% (19/201), and having exclusionary health concerns 17.9% (36/201). Five people have withdrawn from the study: 2 with unanticipated health conditions, 2 living in a vacation home for more than half of the year, and 1 who saw no direct benefit from the research study. At baseline, MCI participants had lower Montreal Cognitive Assessment (P<.001) and higher Functional Activities Questionnaire (P=.04) scores than healthy controls. Over seven months, research personnel visited participants’ homes a total of 73 times for technology maintenance. Technology maintenance visits were more prevalent for MCI participants (P=.04) than healthy controls. Conclusions Installation and longitudinal deployment of a passive in-home IADL monitoring platform with an older adult military veteran sample was feasible. Knowledge gained from this pilot study will be used to help develop acceptable and effective home-based assessment tools that can be used to passively monitor cognition and daily functioning in older adult samples.

<b><i>Introduction:</i></b> 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. <b><i>Methods:</i></b> A community-dwelling sample of older adults (<i>n</i> = 69) was included, classified as cognitively intact (<i>n</i> = 44) or diagnosed with mild cognitive impairment (MCI, <i>n</i> = 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). <b><i>Results:</i></b> Regarding validity, total SMART CT, which includes time to complete test items, practice items, and directions, had the strongest relationship with global cognition (β = −0.47, <i>p</i> &#x3c; 0.01). Test item CT was significantly greater for the MCI group (<i>F =</i> 5.20, <i>p</i> = 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). <b><i>Conclusions:</i></b> 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.