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Background: Traditional paper and pencil approaches measure cognitive performance at one time point. Early indications of cognitive impairment often appear irregularly, suggesting diagnoses derived from a single session can fail to characterize normal fluctuations and lead to inaccurate conclusions. Mobile applications enable brief cognitive assessments to be completed frequently and remotely. However, the feasibility of older adults adhering to a schedule of repeated self‐administered cognitive assessments is unclear. We tested the repeated use of a mobile assessment among older adults as a potential method for collecting cognitive performance data to detect early signs of cognitive impairment. Method: The current study included 33 participants (n = 23 cognitively unimpaired, n = 10 cognitively impaired) recruited from the Boston University Alzheimer's Disease Center. A remote practice session using the Digital Automated Neurobehavioral Assessment (DANA) mobile application was completed prior to beginning an assessment schedule consisting of three assessments within the first week (segment 1) and one assessment per week during the following three weeks (segment 2). Feasibility was measured via schedule adherence across segments, stratified by age and cognitive status. Cognitive efficiency, a derived measure of speed and accuracy, was compared for the Procedural Reaction Time (PRT) task at the first assessment and longitudinally across segments 1 and 2. Demographics including age, sex, race, education, and mobile device type were also collected (Table 1). Result: Across all segments, 90.9% of participants adhered to the assessment schedule with a ±1 day grace period applied. Adherence was similar between each segment, and by cognitive status and age group (Table 2). No significant differences in cognitive efficiency were observed on the PRT task between cognitive groups (Figures 1‐2, Table 3). Conclusion: Our findings suggest that older adults, including those with cognitive impairment, are capable of completing self‐administered remote smartphone assessments at a high‐frequency. Traditional analytic methods failed to differentiate cognitive groups based on mean cognitive performance; however, between‐group comparisons could mask within‐person fluctuations characteristic of cognitive impairment. Therefore, further study with a longer longitudinal assessment period and larger sample size will be required to determine whether more advanced analyses can distinguish impairment status based on cognitive performance patterns. [ABSTRACT FROM AUTHOR]

Background: Longitudinal studies that embrace digital data collection offer a low cost, time‐efficient solution compared to traditional methods. As such, ongoing advances in data science combined with the wealth of data produced by digital technologies can enable a pragmatic shift from investigator‐ to participant‐driven protocols. A participant‐driven study design might bring major efficiencies across the life course of longitudinal studies. Method: We recruited participants from the Boston University Alzheimer's Disease Research Center to a longitudinal study on brain health utilizing a multimodal, technology‐based protocol. Remote assessment technologies included active and passive engagement mobile and computer‐based applications and wearable devices to capture digital measures of cognition, voice, gait, motor activity, and activities of daily living. A full list of study technologies is shown in Table 1. Participants specify which technologies they would like to continue to use, providing a sense of ownership that promotes study participation. Result: Through January 2022, a total of 22 participants (average age = 74.3+ 8.8 years; 68.2% women) have been recruited. The majority of participants (n = 21, 95.5%) have expressed a willingness to engage with multiple technologies. Among those enrolled for >3 months, 14 participants (87.5%) have opted to use 3 or more technologies (mean number of technologies = 4.38). Several technologies only worked on specific operating systems (NeuraMetrix, Longevity). Compatibility (n = 16, 72.7%) was the most frequent factor in leading a participant to not use a study technology, followed by concern over the burden of using an additional device or application (n = 14, 63.6%). The most common factor leading participants to select a given technology was the availability of participant‐facing data (n = 15, 68.2%), such as step counts or scores on gamified cognitive tests. Conclusion: Through the use of a participant‐driven study design, we have been able to conduct longitudinal brain health digital phenotyping with high uptake of digital technologies. Participant's selections offer insights to investigators assessing which technologies to use in clinical research. Digital data collection opens opportunities for participant‐driven approaches that can enable longitudinal follow‐up with broader more inclusive reach with appropriate retention of data quality. [ABSTRACT FROM AUTHOR]

Background: Prior to a diagnosis of Alzheimer's disease, many individuals experience cognitive and behavioral fluctuations that are not detected during a single session of traditional neuropsychological assessment. Mobile applications now enable high-frequency cognitive data to be collected remotely, introducing new opportunities and challenges. Emerging evidence suggests cognitively impaired older adults are capable of completing mobile assessments frequently, but no study has observed whether completion rates vary by assessment frequency or adherence type., Methods: Thirty-three older adults were recruited from the Boston University Alzheimer's Disease Research Center (mean age = 73.5 years; 27.3% cognitively impaired; 57.6% female; 81.8% White, 18.2% Black). Participants remotely downloaded and completed the DANA Brain Vital application on their own mobile devices throughout the study. The study schedule included seventeen assessments to be completed over the course of a year. Specific periods during which assessments were expected to be completed were defined as subsegments, while segments consisted of multiple subsegments. The first segment included three subsegments to be completed within one week, the second segment included weekly subsegments and spanned three weeks, and the third and fourth segments included monthly subsegments spanning five and six months, respectively. Three distinct adherence types - subsegment adherence , segment adherence , and cumulative adherence - were examined to determine how completion rates varied depending on assessment frequency and adherence type., Results: Adherence type significantly impacted whether the completion rates declined. When utilizing subsegment adherence , the completion rate significantly declined (p = 0.05) during the fourth segment. However, when considering completion rates from the perspective of segment adherence , a decline in completion rate was not observed. Overall adherence rates increased as adherence parameters were broadened from subsegment adherence (60.6%) to segment adherence (78.8%), to cumulative adherence (90.9%)., Conclusions: Older adults, including those with cognitive impairment, are able to complete remote cognitive assessments at a high-frequency, but may not necessarily adhere to prescribed schedules.