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

The effects of shared, depression-specific, and anxiety-specific internalizing symptoms on negative and neutral episodic memories following post-learning sleep

Emotional memory bias is a common characteristic of internalizing symptomatology and is enhanced during sleep. The current study employs bifactor S-1 modeling to disentangle depression-specific anhedonia, anxiety-specific anxious arousal, and the common internalizing factor, general distress, and test whether these internalizing symptoms interact with sleep to influence memory for emotional and neutral information. Healthy adults (N = 281) encoded scenes featuring either negative objects (e.g., a vicious looking snake) or neutral objects (e.g., a chipmunk) placed on neutral backgrounds (e.g., an outdoor scene). After a 12-hour period of daytime wakefulness (n = 140) or nocturnal sleep (n = 141), participants judged whether objects and backgrounds were the same, similar, or new compared with what they viewed during encoding. Participants also completed the mini version of the Mood and Anxiety Symptom Questionnaire. Higher anxious arousal predicted worse memory across all stimuli features, but only after a day spent being awake-not following a night of sleep. No significant effects were found for general distress and anhedonia in either the sleep or wake condition. In this study, internalizing symptoms were not associated with enhanced emotional memory. Instead, memory performance specifically in individuals with higher anxious arousal was impaired overall, regardless of emotional valence, but this was only the case when the retention interval spanned wakefulness (i.e., not when it spanned sleep). This suggests that sleep may confer a protective effect on general memory impairments associated with anxiety.

Integration of sex/gender and utilization of ecological Momentary assessment of cognition in clinical populations: A scoping review

Objectives: We aimed to describe the methods of smartphone-based cognitive ecological momentary assessment designs in clinical populations, with an intention to evaluate how the role of sex and/or gender has been considered in the design and analyses, particularly including female-specific physiology. Methods: This scoping review was conducted based on JBI scoping review methodology. On March 2nd, 2023, we searched for literature across four databases. Screening of the results and data extraction were conducted in duplicate according to the a priori methods in the pre-registered protocol. Results: 31 articles were included in this review. Participants ranged in age from 15-85 years old with various clinical disorders. Prompts were given between 1-7 times per day for 7-84 days. Executive function was the most frequently assessed cognitive domain. Over half the studies (n = 17, 55%) did not investigate the effects of sex and/or gender, and only one study considered the impact of hormonal therapy. Many studies (n = 14, 45%) used sex and gender interchangeably or incorrectly. Conclusions: Studies varied in design, with heterogeneity in the reporting of methodological information. The lack of attention to sex/gender on neuropsychological outcomes can lead to confusion and contradiction regarding its potential impact on cognition in clinical populations. This may hinder the identification of effective interventions for those assigned female at birth who have been overlooked or considered indistinguishable from their male counterparts. Given the well-documented impact of sex/gender on cognition, it is essential that future neuropsychological research, especially EMA-based studies, prioritize investigating sex/gender to ensure better outcomes for all.

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.

Chronotype, Time of Day, and Children's Cognitive Performance in Remote Neuropsychological Assessment

Research on the influence of chronotype and time of day (TOD) on cognitive performance, especially in children, is limited. We explored potential interactive effects, hypothesizing that performance differs when comparing preferred vs. non-preferred TOD. In total, 76 morning-type (MT = 37) or evening-type (ET = 39) children from the third and fourth grades (48.7% girls; M age = 8.05; SD age = 0.51), identified through the Children Chronotype Questionnaire, completed two 30-min neuropsychological assessment sessions via videoconference on the first (9:00) or last hour (16:00) of the school day. The protocol included neuropsychological tests targeting memory, language, and attention/executive domains. The results revealed an interactive effect of medium size between chronotype and TOD on a Rapid Alternating Stimulus (Naming) Task. MT and ET performed faster in asynchrony conditions (morning for ET; afternoon for MT). Additionally, ET outperformed MT in a Backward Digit Span Task, irrespective of TOD. TOD also influenced performance on an Alternating Verbal Fluency Task, with both MT and ET children performing better in the morning. These results underscore the importance of chronotype and TOD in children's cognitive performance, particularly in working memory and verbal fluency. Children assessed during non-preferred TOD exhibited better performance on some cognitive tasks, challenging the assumption that optimal times always yield superior results.

Capturing learning curves with the multiday Boston Remote Assessment of Neurocognitive Health (BRANCH): Feasibility, reliability, and validity

OBJECTIVE

Unsupervised remote digital cognitive assessment makes frequent testing feasible and allows for measurement of learning over repeated evaluations on participants' own devices. This provides the opportunity to derive individual multiday learning curve scores over short intervals. Here, we report feasibility, reliability, and validity, of a 7-day cognitive battery from the Boston Remote Assessment for Neurocognitive Health (Multiday BRANCH), an unsupervised web-based assessment.

METHOD

Multiday BRANCH was administered remotely to 181 cognitively unimpaired older adults using their own electronic devices. For 7 consecutive days, participants completed three tests with associative memory components (Face-Name, Groceries-Prices, Digit Signs), using the same stimuli, to capture multiday learning curves for each test. We assessed the feasibility of capturing learning curves across the 7 days. Additionally, we examined the reliability and associations of learning curves with demographics, and traditional cognitive and subjective report measures.

RESULTS

Multiday BRANCH was feasible with 96% of participants completing all study assessments; there were no differences dependent on type of device used (t = 0.71, p = .48) or time of day completed (t = -0.08, p = .94). Psychometric properties of the learning curves were sound including good test-retest reliability of individuals' curves (intraclass correlation = 0.94). Learning curves were positively correlated with in-person cognitive tests and subjective report of cognitive complaints.

CONCLUSIONS

Multiday BRANCH is a feasible, reliable, and valid cognitive measure that may be useful for identifying subtle changes in learning and memory processes in older adults. In the future, we will determine whether Multiday BRANCH is predictive of the presence of preclinical Alzheimer's disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Relationships between hourly cognitive variability and risk of Alzheimer's disease revealed with mixed-effects location scale models

OBJECTIVE

Observational studies on aging and Alzheimer's disease (AD) typically focus on mean-level changes in cognitive performance over relatively long periods of time (years or decades). Additionally, some studies have examined how trial-level fluctuations in speeded reaction time are related to both age and AD. The aim of the current project was to describe patterns of variability across repeated days of testing as a function of AD risk in cognitively normal older adults.

METHOD

The current project examined the performance of the Ambulatory Research in Cognition (ARC) smartphone application, a high-frequency remote cognitive assessment paradigm, that administers brief tests of episodic memory, spatial working memory, and processing speed. Bayesian mixed-effects location scale models were used to explore differences in mean cognitive performance and intraindividual variability across 28 repeated sessions over a 1-week assessment interval as function of age and genetic risk of AD, specifically the presence of at least one apolipoprotein E (APOE) ε4 allele.

RESULTS

Mean performance on processing speed and working memory was negatively related to age and APOE status. More importantly, e4 carriers exhibited increased session-level variability on a test of processing speed compared to noncarriers. Age and education did not consistently relate to cognitive variability, contrary to expectations.

CONCLUSION

Preclinical AD risk, defined as possessing at least one APOE ε4 allele, is not only associated with mean-level performance differences, but also with increases in variability across repeated testing occasions particularly on a test of processing speed. Thus, cognitive variability may serve as an additional and important indicator of AD risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Time of Day Effects in the Relationships Between Daytime Sleepiness, Current Arousal, and Cognitive Performance

OBJECTIVE

Daytime sleepiness is commonly reported among older adults. Additionally, aging is associated with a shift toward greater alertness in the morning that wanes throughout the day. The impact of time of day of testing on the relationships between daytime sleepiness and cognition is unknown.

METHODS

We explored the effects of time of testing in relation to self-reported daytime sleepiness/current arousal and cognition among 133 older adults.

RESULTS

Time of testing moderated the relationship between daytime sleepiness and immediate learning/memory, with greater sleepiness being associated with poorer performance in the afternoon, but not morning. Time of testing also moderated the relationship between current arousal and processing speed, with lower arousal being associated with worse performance in the afternoon.

CONCLUSIONS

These findings suggest that time of testing is important to account for when assessing sleepiness and cognition in older adults and that consideration should be given to how sleepiness is measured.

Remote and in-clinic digital cognitive screening tools outperform the MoCA to distinguish cerebral amyloid status among cognitively healthy older adults

INTRODUCTION

We evaluated the accuracy of remote and in-person digital tests to distinguish between older adults with and without AD pathological change and used the Montreal Cognitive Assessment (MoCA) as a comparison test.

METHODS

Participants were 69 cognitively normal older adults with known beta-amyloid (Aβ) PET status. Participants completed smartphone-based assessments 3×/day for 8 days, followed by TabCAT tasks, DCTclock™, and MoCA at an in-person study visit. We calculated the area under the curve (AUC) to compare task accuracies to distinguish Aβ status.

RESULTS

Average performance on the episodic memory (Prices) smartphone task showed the highest accuracy (AUC = 0.77) to distinguish Aβ status. On in-person measures, accuracy to distinguish Aβ status was greatest for the TabCAT Favorites task (AUC = 0.76), relative to the DCTclockTM (AUC = 0.73) and MoCA (AUC = 0.74).

DISCUSSION

Although further validation is needed, our results suggest that several digital assessments may be suitable for more widespread cognitive screening application.

Web-based cognitive assessment in older adults: Where do we stand?

PURPOSE OF REVIEW

The use of digital tools for remote cognitive measurement of older adults is generating increasing interest due to the numerous advantages offered for accessibility and scalability. However, these tools also pose distinctive challenges, necessitating a thorough analysis of their psychometric properties, feasibility and acceptability.

RECENT FINDINGS

In this narrative review, we present the recent literature on the use of web-based cognitive assessment to characterize cognition in older adults and to contribute to the diagnosis of age-related neurodegenerative diseases. We present and discuss three types of web-based cognitive assessments: conventional cognitive tests administered through videoconferencing; unsupervised web-based assessments conducted on a computer; and unsupervised web-based assessments performed on smartphones.

SUMMARY

There have been considerable progress documenting the properties, strengths and limitations of web-based cognitive assessments. For the three types of assessments reported here, the findings support their promising potential for older adults. However, certain aspects, such as the construct validity of these tools and the development of robust norms, remain less well documented. Nonetheless, the beneficial potential of these tools, and their current validation and feasibility data, justify their application [see Supplementary Digital Content (SDC), http://links.lww.com/CONR/A69 ].

Adherence type impacts completion rates of frequent mobile cognitive assessments among older adults with and without cognitive impairment

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.

Feasibility of Remote Unsupervised Cognitive Screening With SATURN in Older Adults

Widespread cognitive test screening as part of tele-public health initiatives necessitates a test that is self-administered online and automatically scored, with no clinician effort. The feasibility of unsupervised cognitive screening is unclear. We adapted the Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN) to make it suitable for self-administration and automatic scoring. A sample of 364 healthy older adults completed SATURN via a web browser, in a fully independent manner. SATURN's overall score was not modulated by gender, education, reading speed, the time of day at which the test was taken, or an individual's familiarity with technology. SATURN proved extremely portable across operating systems. Importantly, comments from participants reported satisfaction with the experience and the clarity of the instructions. SATURN represents a fast and easy screening tool that can be used for a first assessment, during a routine test or clinical evaluation, or during periodic health monitoring, in person or remotely.

Ecological Momentary Assessment of Cognition in Clinical and Community Samples: Reliability and Validity Study

BACKGROUND

The current methods of evaluating cognitive functioning typically rely on a single time point to assess and characterize an individual's performance. However, cognitive functioning fluctuates within individuals over time in relation to environmental, psychological, and physiological contexts. This limits the generalizability and diagnostic utility of single time point assessments, particularly among individuals who may exhibit large variations in cognition depending on physiological or psychological context (eg, those with type 1 diabetes [T1D], who may have fluctuating glucose concentrations throughout the day).

OBJECTIVE

We aimed to report the reliability and validity of cognitive ecological momentary assessment (EMA) as a method for understanding between-person differences and capturing within-person variation in cognition over time in a community sample and sample of adults with T1D.

METHODS

Cognitive performance was measured 3 times a day for 15 days in the sample of adults with T1D (n=198, recruited through endocrinology clinics) and for 10 days in the community sample (n=128, recruited from TestMyBrain, a web-based citizen science platform) using ultrabrief cognitive tests developed for cognitive EMA. Our cognitive EMA platform allowed for remote, automated assessment in participants' natural environments, enabling the measurement of within-person cognitive variation without the burden of repeated laboratory or clinic visits. This allowed us to evaluate reliability and validity in samples that differed in their expected degree of cognitive variability as well as the method of recruitment.

RESULTS

The results demonstrate excellent between-person reliability (ranging from 0.95 to 0.99) and construct validity of cognitive EMA in both the sample of adults with T1D and community sample. Within-person reliability in both samples (ranging from 0.20 to 0.80) was comparable with that observed in previous studies in healthy older adults. As expected, the full-length baseline and EMA versions of TestMyBrain tests correlated highly with one another and loaded together on the expected cognitive domains when using exploratory factor analysis. Interruptions had higher negative impacts on accuracy-based outcomes (β=-.34 to -.26; all P values <.001) than on reaction time-based outcomes (β=-.07 to -.02; P<.001 to P=.40).

CONCLUSIONS

We demonstrated that ultrabrief mobile assessments are both reliable and valid across 2 very different clinic versus community samples, despite the conditions in which cognitive EMAs are administered, which are often associated with more noise and variability. The psychometric characteristics described here should be leveraged appropriately depending on the goals of the cognitive assessment (eg, diagnostic vs everyday functioning) and the population being studied.

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.

Feasibility and acceptability of remote smartphone cognitive testing in frontotemporal dementia research

Introduction

Remote smartphone assessments of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) could enable decentralized clinical trials and improve access to research. We studied the feasibility and acceptability of remote smartphone data collection in FTD research using the ALLFTD Mobile App (ALLFTD-mApp).

Methods

A diagnostically mixed sample of 214 participants with FTD or from familial FTD kindreds (asymptomatic: CDR®+NACC-FTLD = 0 [N = 101]; prodromal: 0.5 [N = 49]; symptomatic ≥1 [N = 51]; not measured [N = 13]) were asked to complete ALLFTD-mApp tests on their smartphone three times within 12 days. They completed smartphone familiarity and participation experience surveys.

Results

It was feasible for participants to complete the ALLFTD-mApp on their own smartphones. Participants reported high smartphone familiarity, completed ∼ 70% of tasks, and considered the time commitment acceptable (98% of respondents). Greater disease severity was associated with poorer performance across several tests.

Discussion

These findings suggest that the ALLFTD-mApp study protocol is feasible and acceptable for remote FTD research.

HIGHLIGHTS

The ALLFTD Mobile App is a smartphone-based platform for remote, self-administered data collection.The ALLFTD Mobile App consists of a comprehensive battery of surveys and tests of executive functioning, memory, speech and language, and motor abilities.Remote digital data collection using the ALLFTD Mobile App was feasible in a multicenter research consortium that studies FTD. Data was collected in healthy controls and participants with a range of diagnoses, particularly FTD spectrum disorders.Remote digital data collection was well accepted by participants with a variety of diagnoses.

A scoping review of neurodegenerative manifestations in explainable digital phenotyping

Neurologists nowadays no longer view neurodegenerative diseases, like Parkinson's and Alzheimer's disease, as single entities, but rather as a spectrum of multifaceted symptoms with heterogeneous progression courses and treatment responses. The definition of the naturalistic behavioral repertoire of early neurodegenerative manifestations is still elusive, impeding early diagnosis and intervention. Central to this view is the role of artificial intelligence (AI) in reinforcing the depth of phenotypic information, thereby supporting the paradigm shift to precision medicine and personalized healthcare. This suggestion advocates the definition of disease subtypes in a new biomarker-supported nosology framework, yet without empirical consensus on standardization, reliability and interpretability. Although the well-defined neurodegenerative processes, linked to a triad of motor and non-motor preclinical symptoms, are detected by clinical intuition, we undertake an unbiased data-driven approach to identify different patterns of neuropathology distribution based on the naturalistic behavior data inherent to populations in-the-wild. We appraise the role of remote technologies in the definition of digital phenotyping specific to brain-, body- and social-level neurodegenerative subtle symptoms, emphasizing inter- and intra-patient variability powered by deep learning. As such, the present review endeavors to exploit digital technologies and AI to create disease-specific phenotypic explanations, facilitating the understanding of neurodegenerative diseases as "bio-psycho-social" conditions. Not only does this translational effort within explainable digital phenotyping foster the understanding of disease-induced traits, but it also enhances diagnostic and, eventually, treatment personalization.

How Does Chronobiology Contribute to the Development of Diseases in Later Life

An increasingly older population is one of the major social and medical challenges we currently face. Between 2010 and 2050, it is estimated that the proportion of adults over 65 years of age will double from 8% to 16% of the global population. A major concern associated with aging is the changes in health that can lead to various diseases such as cancer and neurogenerative diseases, which are major burdens on individuals and societies. Thus, it is imperative to better understand changes in sleep and circadian rhythms that accompany aging to improve the health of an older population and target diseases associated with aging. Circadian rhythms play a role in most physiological processes and can contribute to age-related diseases. Interestingly, there is a relationship between circadian rhythms and aging. For example, many older adults have a shift in chronotype, which is an individual's natural inclination to sleep certain times of the day. As adults age, most people tend to go to sleep earlier while also waking up earlier. Numerous studies also suggest that disrupted circadian rhythms may be indicative of developing age-related diseases, like neurodegenerative disorders and cancer. Better understanding the relationship between circadian rhythms and aging may allow us to improve current treatments or develop novel ones that target diseases commonly associated with aging.

Developments in scalable strategies for detecting early markers of cognitive decline

Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using 'gamified' versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

Mindfulness Training for Depressed Older Adults Using Smartphone Technology: Protocol for a Fully Remote Precision Clinical Trial

BACKGROUND

Precision medicine, optimized interventions, and access to care are catchphrases for the future of behavioral treatments. Progress has been slow due to the dearth of clinical trials that optimize interventions' benefits, individually tailor interventions to meet individual needs and preferences, and lead to rapid implementation after effectiveness is demonstrated. Two innovations have emerged to meet these challenges: fully remote trials and precision clinical trials.

OBJECTIVE

This paper provides a detailed description of Mindful MyWay, a study designed to test online mindfulness training in older adults with depression. Consistent with the concept of fully remote trials using a smartphone app, the study requires no in-person contact and can be conducted with participants anywhere in the United States. Based upon the precision medicine framework, the study assesses participants using high-frequency assessments of symptoms, cognitive performance, and patient preferences to both understand the individualized nature of treatment response and help individually tailor the intervention.

METHODS

Mindful MyWay is an open-label early-phase clinical trial for individuals 65 years and older with current depression. A smartphone app was developed to help coordinate the study, deliver the intervention, and evaluate the acceptability of the intervention, as well as predictors and outcomes of it. The curriculum for the fully remote intervention parallels the mindfulness-based stress reduction curriculum, a protocolized group-based mindfulness training that is typically provided in person. After consent and screening, participants download The Healthy Mind Lab mobile health smartphone app from the Apple App Store, allowing them to complete brief smartphone-based assessments of depressive symptoms and cognitive performance 4 times each day for 4 weeks prior to and after completing the intervention. The intervention consists of an introduction video and 10 weekly mindfulness training sessions, with the expectation to practice mindfulness at home daily. The app collects participant preference data throughout the 10-week intervention period; these high-frequency assessments identify participants' individually dynamic preferences toward the goal of optimizing the intervention in future iterations.

RESULTS

Participant recruitment and data collection began in March 2019. Final end point assessments will be collected in May 2022. The paper describes lessons learned regarding the critical role of early-phase testing prior to moving to a randomized trial.

CONCLUSIONS

The Mindful MyWay study is an exemplar of innovative clinical trial designs that use smartphone technology in behavioral and neuropsychiatric conditions. These include fully remote studies that can recruit throughout the United States, including hard-to-access areas, and collect high-frequency data, which is ideal for idiographic assessment and individualized intervention optimization. Our findings will be used to modify our methods and inform future randomized controlled trials within a precision medicine framework.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03922217; https://clinicaltrials.gov/ct2/show/NCT03922217.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39233.

Time of Day Effects on Inhibitory Functioning: Cognitive and Neural Evidence of Sundowning in Amnestic Mild Cognitive Impairment

Background: Amnestic mild cognitive impairment (aMCI), a prodromal phase of Alzheimer’s disease (AD), is characterized by episodic memory dysfunction, but inhibitory deficits have also been commonly reported. Time of day (TOD) effects have been confirmed in 1) healthy aging on cognitive processes such as inhibitory control, and 2) on behavior in AD (termed the sundowning effect), but no such research has addressed aMCI. Objective: The present study examined the impact of TOD on the behavioral and electrophysiological correlates of inhibition in 54 individuals with aMCI and 52 healthy controls (HCs), all of morning chronotype. Methods: Participants were randomly assigned to complete two inhibition tasks (Go-NoGo and Flanker) during their optimal (morning) or non-optimal (evening) TOD, while electroencephalography was recorded. Results: Both tasks elicited changes in N2 and P3 event-related potential (ERP) components, which commonly index inhibitory functioning. Analyses showed that the Go-NoGo difference in P3 amplitude was reduced in individuals with aMCI relative to HCs. Compared to HCs, the Flanker difference in P3 amplitude was also reduced and coincided with more errors in the aMCI group. Notably, these behavioral and ERP differences were exaggerated in the non-optimal TOD relative to the optimal TOD. Conclusion: Findings confirm the presence of inhibition deficits in aMCI and provide novel evidence of sundowning effects on inhibitory control in aMCI. Results reinforce the need to consider the influences of TOD in clinical assessments involving individuals with aMCI.

Feasibility and validity of ecological momentary cognitive testing among older adults with mild cognitive impairment

It is critical to intervene early in the mild cognitive impairment (MCI) stage of the Alzheimer's disease trajectory, but traditional cognitive testing methods are costly, burdensome, and difficult to access. We examined adherence and validity data to a 30-day self-administered ecological momentary cognitive testing protocol among a sample of older adults with MCI and cognitively normal controls to evaluate feasibility, tolerability, and initial validity in comparison to standard neuropsychological tests. Participants included 48 participants with MCI (Mean age = 72 years, SD = 7 years) and 46 demographically-matched cognitively normal (NC) control participants (Mean age = 70 years, SD = 7 years). Participants completed traditional neuropsychological testing to determine MCI status, followed by 30 days of remote ecological momentary cognitive testing. Ecological momentary assessment (EMA) surveys were administered 3 times per day for 30 days (possible total = 90), and mobile cognitive tests were administered every other day (for a total of 15 administrations). Mobile cognitive tests included the Variable Difficulty List Memory Test (VLMT; measure of learning and memory), Memory Matrix (measure of visual working memory), and the Color Trick Test (measure of executive function). EMA and mobile cognitive test adherence, fatigue effects, mobile cognitive test performance and group differences, and psychometrics (reliability, convergent validity, ceiling effects, and practice effects) were examined. Overall mean-level adherence to the mobile cognitive tests was 85% and did not differ by MCI status. The reliability of stable between-person individual differences for the VLMT and Memory Matrix were very high. Moreover, although the reliability of within-person change for Memory Matrix was adequate, the corresponding reliability for VLMT was somewhat low. Averaged performance on the mobile cognitive tests was correlated with lab-based tests measuring the same construct. Participants with MCI performed worse than NCs on the VLMT and Color Trick Test, and there was no evidence of fatigue effects for these two tests. These findings support the feasibility and potential for ecological momentary cognitive testing to support clinical trials and for measuring cognitive changes over time in persons with increased risk for Alzheimer's disease such as those with MCI.

Neuroscience from the comfort of your home: Repeated, self-administered wireless dry EEG measures brain function with high fidelity

Recent advances have enabled the creation of wireless, “dry” electroencephalography (EEG) recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by naïve users, unsupervised in the home. Here, we evaluated the validity of dry-EEG, cognitive task gamification, and unsupervised home-based recordings used in combination. Two separate cohorts of participants—older and younger adults—collected data at home over several weeks using a wireless dry EEG system interfaced with a tablet for task presentation. Older adults (n = 50; 25 females; mean age = 67.8 years) collected data over a 6-week period. Younger male adults (n = 30; mean age = 25.6 years) collected data over a 4-week period. All participants were asked to complete gamified versions of a visual Oddball task and Flanker task 5–7 days per week. Usability of the EEG system was evaluated via participant adherence, percentage of sessions successfully completed, and quantitative feedback using the System Usability Scale. In total, 1,449 EEG sessions from older adults (mean = 28.9; SD = 6.64) and 684 sessions from younger adults (mean = 22.87; SD = 1.92) were collected. Older adults successfully completed 93% of sessions requested and reported a mean usability score of 84.5. Younger adults successfully completed 96% of sessions and reported a mean usability score of 88.3. Characteristic event-related potential (ERP) components—the P300 and error-related negativity—were observed in the Oddball and Flanker tasks, respectively. Using a conservative threshold for inclusion of artifact-free data, 50% of trials were rejected per at-home session. Aggregation of ERPs across sessions (2–4, depending on task) resulted in grand average signal quality with similar Standard Measurement Error values to those of single-session wet EEG data collected by experts in a laboratory setting from a young adult sample. Our results indicate that easy-to-use task-driven EEG can enable large-scale investigations in cognitive neuroscience. In future, this approach may be useful in clinical applications such as screening and tracking of treatment response.

Feasibility of Digital Memory Assessments in an Unsupervised and Remote Study Setting

Sensitive and frequent digital remote memory assessments via mobile devices hold the promise to facilitate the detection of cognitive impairment and decline. However, in order to be successful at scale, cognitive tests need to be applicable in unsupervised settings and confounding factors need to be understood. This study explored the feasibility of completely unsupervised digital cognitive assessments using three novel memory tasks in a Citizen Science project across Germany. To that end, the study aimed to identify factors associated with stronger participant retention, to examine test-retest reliability and the extent of practice effects, as well as to investigate the influence of uncontrolled settings such as time of day, delay between sessions or screen size on memory performance. A total of 1,407 adults (aged 18–89) participated in the study for up to 12 weeks, completing weekly memory tasks in addition to short questionnaires regarding sleep duration, subjective cognitive complaints as well as cold symptoms. Participation across memory tasks was pseudorandomized such that individuals were assigned to one of three memory paradigms resulting in three otherwise identical sub-studies. One hundred thirty-eight participants contributed to two of the three paradigms. Critically, for each memory task 12 independent parallel test sets were used to minimize effects of repeated testing. First, we observed a mean participant retention time of 44 days, or 4 active test sessions, and 77.5% compliance to the study protocol in an unsupervised setting with no contact between participants and study personnel, payment or feedback. We identified subject-level factors that contributed to higher retention times. Second, we found minor practice effects associated with repeated cognitive testing, and reveal evidence for acceptable-to-good retest reliability of mobile testing. Third, we show that memory performance assessed through repeated digital assessments was strongly associated with age in all paradigms, and individuals with subjectively reported cognitive decline presented lower mnemonic discrimination accuracy compared to non-complaining participants. Finally, we identified design-related factors that need to be incorporated in future studies such as the time delay between test sessions. Our results demonstrate the feasibility of fully unsupervised digital remote memory assessments and identify critical factors to account for in future studies.