Efficacy of Digital and Non-Digital Compensatory Strategies in Supporting Prospective Memory Task Completion among Community-Dwelling Mid-Life and Older Adults.

OBJECTIVE: Compensatory strategies can be used to help mid-life and older adults successfully manage instrumental activities of daily living that rely upon prospective memory. This study compared the quality of digital and non-digital compensatory strategies in supporting accurate completion of naturalistic, real-world prospective memory tasks. METHOD: Participants included 70 community-dwelling mid-life and older adults. In this cross-sectional study, participants were tested remotely via Zoom in their homes. They were tasked with completing four real-world prospective memory tasks and encouraged to use their typical compensatory strategies. Utilized strategies were categorized, counted, and assigned quality scores (rating of thoroughness and utility), and prospective memory performance was coded. RESULTS: Participants who used any digital strategies utilized significantly more (ηp2 = .17) and better quality (ηp2 = .12) strategies than participants who did not use any digital strategies. However, the groups demonstrated equivalent prospective memory performance (ηp2 = .006). Within the digital group, participants' digital and non-digital strategies were of similar quality (d = .14) and resulted in similar prospective memory task accuracy (d = .01). CONCLUSIONS: Digital and non-digital strategies led to similar performance on naturalistic prospective memory tasks. Findings suggest that many different types of strategies can provide adequate prospective memory support to healthy mid-life and older adults. To inform development of compensatory strategy interventions, future studies should explore other factors that lead to successful prospective memory, such as the specific strategy type and task type match, across the continuum of cognitive impairment.

Health literacy in older adults: The newest vital sign and its relation to cognition and healthy lifestyle behaviors.

Health literacy tends to decrease with age, and lower health literacy has been associated with lower levels of physical function, mental health, and medication adherence. The present study examined health literacy in relation to cognition in a sample of community-dwelling older adults. The study also examined the impact of health literacy on engagement in healthy aging lifestyle behaviors. Participants included 128 older adults (age: M = 72.07, SD = 6.71; education: M = 16.34, SD = 2.56; 74% female) who completed a health literacy measure (Newest Vital Sign; NVS), a lifestyle behavior questionnaire (Healthy Aging Activity Engagement scale; HAAE), and several neuropsychological tests. The cognitive domains assessed included memory, executive function, and attention/working memory. Two variables were computed from the NVS to represent the health literacy factors of document and numeracy literacy; these factors demonstrated a small correlation (r = .18). Results revealed that attention/working memory, executive function, and memory were all significantly related to numeracy literacy and overall health literacy. Only memory was significantly related to document literacy. After accounting for age, education, and cognition, a hierarchical regression revealed that health literacy significantly predicted engagement in healthy aging lifestyle behaviors. Multiple cognitive abilities are necessary for searching, finding, and processing information to make health-related decisions. Health literacy accounted for a significant amount of variance in older adults' engagement in everyday lifestyle behaviors. Health literacy skills may be an area of focus for intervention efforts to improve brain health in older adults.

Predicting daily cognition and lifestyle behaviors for older adults using smart home data and ecological momentary assessment.

OBJECTIVE: Extraction of digital markers from passive sensors placed in homes is a promising method for understanding real-world behaviors. In this study, machine learning (ML) and multilevel modeling (MLM) are used to examine types of digital markers and whether smart home sensors can predict cognitive functioning, lifestyle behaviors, and contextual factors measured through ecological momentary assessment (EMA). METHOD: Smart home sensors were installed in the homes of 44 community-dwelling midlife and older adults for 3-4 months. Sensor data were categorized into eight digital markers. Participants responded to iPad-delivered EMA prompts 4×/day for 2 wk. Prompts included an n-back task and survey on recent (past 2 h) lifestyle and contextual factors. RESULTS: ML marker rankings revealed that sensor counts (indicating increased activity) and time outside the home were among the most influential markers for all survey questions. Additionally, MLM revealed for every 1000 sensor counts, mental sharpness, social, physical, and cognitive EMA responses increased by 0.134-0.155 points on a 5-point scale. For every additional 30-minutes spent outside home, social, physical, and cognitive EMA responses increased by 0.596, 0.472, and 0.157 points. Advanced ML joint classification/regression significantly predicted EMA responses from smart home digital markers with error of 0.370 on a 5-point scale, and n-back performance with a normalized error of 0.040. CONCLUSION: Results from ML and MLM were complimentary and comparable, suggesting that machine learning may be used to develop generalized models to predict everyday cognition and track lifestyle behaviors and contextual factors that impact health outcomes using smart home sensor data.

Naturalistic assessment of everyday multitasking in Parkinson's disease with and without mild cognitive impairment.

Objective: Multitasking is an essential part of everyday functioning often not formally assessed by traditional neuropsychological tests. Although individuals with Parkinson's disease (PD) experience both motor and cognitive difficulties, previous research has demonstrated more pronounced functional difficulties with the presence of mild cognitive impairment (PD-MCI). The current study compared individuals with PD-MCI, PD with normal cognition (PD-NC), and healthy controls on a naturalistic task of multitasking, the Day Out Task (DOT). Method: Participants were 38 healthy older adults (HOA), 23 individuals with PD-NC, and 15 individuals with PD-MCI. Participants completed a battery of neuropsychological tasks and the DOT. Informants also completed a self-reported questionnaire of participants' everyday executive functioning. Results: Compared to PD-NC and HOA, participants with PD-MCI were less accurate and efficient and took longer to complete the DOT. After controlling for motor performance, only DOT accuracy remained worse, with poorer accuracy resulted from more subtasks being left incomplete or being completed inaccurately by the PD-MCI group. DOT sequencing was a significant predictor of informant reported everyday dysexecutive symptoms. Conclusions: The findings highlight that individuals with PD-MCI are likely to experience difficulties completing complex everyday tasks due to both motor and cognitive impairments. Clinicians may therefore recommend strategies to support efficiency and accuracy in complex tasks of everyday functioning in treatment considerations.

Real-world compensatory strategy use in community-dwelling mid-life and older adults: An evaluation of quality.

Objective: Older adults often spontaneously engage in compensatory strategies (CS) to support everyday task completion, but factors that influence success of chosen CS remain unclear. This study examines whether real-world prospective memory (PM) task completion is better predicted by CS count or a CS quality rating. Method: Seventy mid-life and older adult participants were presented four novel, real-world PM tasks via remote assessment and encouraged to use their typical CS. The examiner captured detailed information about planned CS at task presentation (T1) and utilized CS at follow-up testing (T2). From this information, count (CS Count; quantity of CS) and quality (CS Quality; rating of CS thoroughness and utility) scores were coded separately for the planned and utilized CS. PM task performance accuracy was also coded (PM Accuracy). Results: Hierarchical regressions revealed planned CS Count and Quality did not predict PM Accuracy. In contrast, the utilized CS Quality predicted a significant amount of PM Accuracy variance over and above CS Count, global cognition, and age (R2 = .47, ΔR2 = .24, ΔF = 29.36, p < .001, f2 = .45). Furthermore, utilized CS Quality accounted for a similar amount of variance in PM Accuracy when utilized CS Count was removed from the model. Conclusions: This study's CS coding system can capture and quantify the quality of strategies, which uniquely predicts real-world PM performance. This coding system may provide researchers with a nuanced CS measure and lead to improved CS interventions designed to support everyday PM performance, such as targeted CS trainings.

A Clinic-Based Measure of Everyday Planning Ability: The Overnight Trip Task.

OBJECTIVE: Traditional measures of cognitive abilities most used by neuropsychologists are generally low in ecological validity and only capture a small proportion of the variance of a person's true functional capacity. This study evaluates the association between clinic-based performance and parallel real-world completion of an everyday planning test, the Overnight Trip Task (OTT). METHOD: A cross-sectional cohort of 65 community-dwelling older adults completed a battery of cognitive assessments and two formats of the OTT: the paper-and-pencil clinic OTT, which was completed remotely through video conferencing (Zoom), and the parallel real-world OTT (RW-OTT), which was completed at home between sessions. Both formats required participants to plan for what they would pack and prepare for a hypothetical overnight trip based on a provided story that included rules and embedded contingencies. RESULTS: The clinic OTT demonstrated a small-to-moderate relationship with the RW-OTT (r = 0.35) and no relationship with measures of learning, long delay recall, an executive function composite, and a measure of everyday planning. Hierarchical regressions indicated that the clinic OTT demonstrated incremental validity above an executive function composite measure and global cognition when predicting self-reported everyday functioning and RW-OTT performance. CONCLUSIONS: The clinic OTT showed only modest association with the RW-OTT and discriminate but not convergent validity was demonstrated. The clinic OTT showed incremental validity when predicting self-reported everyday functioning and RW-OTT performance above more traditional measures. Before the clinic OTT could be considered a reliable and valid clinic-based measure for predicting real-world behavior, additional research would be needed.

Instrumental activities of daily living and mild cognitive impairment.

BACKGROUND: Functional impairments are a necessary requirement for the diagnosis of a dementia along with observed cognitive impairment. Comparatively, functional abilities are often relatively intact in those with mild cognitive impairment (MCI). OBJECTIVE: The current research examined the associations between memory clinic participants classified as cognitively intact, amnestic MCI, and mixed/dysexecutive MCI, using Jak-Bondi criteria, and Instrumental Activities of Daily Living - Compensation Scale (IADL-C) abilities, an informant-based questionnaire that quantifies functional abilities. The associations between functional abilities as assessed with the IADL-C and performance on neuropsychological tests were also investigated. METHODS: IADLC scores were obtained along with a comprehensive neuropsychological protocol on memory clinic participants (n = 100) classified as cognitively normal (CN), amnestic MCI (aMCI), or a combined mixed/dysexecutive (mixed/dys) MCI. Regression analyses were employed to determine how the IADLC related to neuropsychological test performance. RESULTS: On the IADLC, greater functional impairment was commonly observed in the mixed/dys MCI group compared to CN participants. Furthermore, the mixed/dys MCI group had lower scores on activities such as Money and Self-Management, Travel and Event Memory subscales compared to the CN group. Linear regression analyses found greater functional impairment in relation to lower scores on executive and episodic memory tests. CONCLUSIONS: Greater functional impairment as assessed with the IADL-C appears to be disproportionately associated with dysexecutive difficulty, and to a lesser degree, episodic memory.

But will they use it? Predictors of adoption of an electronic memory aid in individuals with amnestic mild cognitive impairment.

OBJECTIVE: Electronic memory aids are being researched and developed widely to assist the everyday functioning of individuals experiencing cognitive decline. Although development studies show promise in the initial use of electronic memory aids, little is known about the factors that influence adoption of these aids after training ends. METHOD: We analyzed the baseline characteristics (e.g., demographics, cognitive performance) and training usage (e.g., frequency and pattern of use) of 32 older adults experiencing amnestic mild cognitive impairment who participated in a pilot clinical trial with an electronic memory and management aid (EMMA) tablet application. Sixteen participants who were still using EMMA at 3-months posttraining were defined as "adopters," whereas the 16 participants who were not using EMMA at 3-months posttraining were defined as "nonadopters." RESULTS: Adopters scored higher on baseline delayed memory (Cohen's d = .87) and language (Cohen's d = .82) index scores than nonadopters. Adopters also interacted with EMMA more frequently (Cohen's d = 1.34) and in greater quantities (Cohen's d > .87) than nonadopters by Week 2 of training. Stepwise logistic regression revealed that higher baseline language score and increased frequency of use during training significantly predicted classification of adopters at 3-months posttraining. CONCLUSIONS: Adoption of this electronic memory aid was enhanced by teaching the aid to individuals who demonstrated average-level language abilities and who used the aid on average eight times per day during training. Encouraging individuals to use the aid early and often during training can increase adoption of electronic memory aids. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Error monitoring in amnestic mild cognitive impairment: Cognitive correlates and relationship to measures of everyday function.

OBJECTIVE: Accurate error monitoring is important for successful completion of everyday tasks and compensatory strategy use. This study examined how error awareness is impacted in amnestic mild cognitive impairment (aMCI) compared to cognitively healthy older adults (HOA). Cognitive correlates of error monitoring and relation to objective and self-reported measurement of everyday function were also evaluated. METHOD: Twenty-four individuals with aMCI and 24 cognitively HOAs completed standardized cognitive measures (domains: attention, working memory, executive functioning, memory, language, visuospatial abilities); a computerized go-no-go paradigm task that evaluated error monitoring; a naturalistic, performance-based measure of everyday functioning (day-out-task; DOT); and self- and informant-report measures of everyday dysexecutive difficulties (DEX). RESULTS: Participants with aMCI demonstrated significantly poorer error monitoring as compared to the HOA group (Cohen's d = 1.02). Working memory and executive functioning were significantly related to error monitoring for both groups. After accounting for age and global cognitive status, hierarchical regressions revealed error monitoring significantly predicted DOT total time (but not accuracy) as well as both self- and informant-report DEX scores. CONCLUSIONS: Compared to HOAs, individuals with aMCI exhibited poorer conscious error awareness. Better error monitoring was associated with higher working memory and executive functioning abilities and predicted better everyday functioning. If individuals with aMCI experience difficulties recognizing performance inaccuracies, they will be unable to correct their errors, leading to mistakes in everyday task completion and difficulty implementing appropriate compensatory strategies. Findings suggest that error monitoring may be a potential target for intervention with individuals with aMCI. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Intraindividual Cognitive Variability and Magnetic Resonance Imaging in Aging American Indians: Data from the Strong Heart Study.

BACKGROUND: American Indians have high prevalence of risk factors for Alzheimer's disease and related dementias (ADRD) compared to the general population, yet dementia onset and frequency in this population are understudied. Intraindividual cognitive variability (IICV), a measure of variability in neuropsychological test performance within a person at a single timepoint, may be a novel, noninvasive biomarker of neurodegeneration and early dementia. OBJECTIVE: To characterize the cross-sectional associations between IICV and hippocampal, total brain volume, and white matter disease measured by magnetic resonance imaging (MRI) among older American Indians. METHODS: IICV measures for memory, executive function, and processing speed, and multidomain cognition were calculated for 746 American Indians (aged 64-95) who underwent MRI. Regression models were used to examine the associations of IICV score with hippocampal volume, total brain volume, and graded white matter disease, adjusting for age, sex, education, body mass index, intracranial volume, diabetes, stroke, hypertension, hypercholesterolemia, alcohol use, and smoking. RESULTS: Higher memory IICV measure was associated with lower hippocampal volume (Beta = -0.076; 95% CI -0.499, -0.023; p = 0.031). After adjustment for Bonferroni or IICV mean scores in the same tests, the associations were no longer significant. No IICV measures were associated with white matter disease or total brain volume. CONCLUSION: These findings suggest that the IICV measures used in this research cannot be robustly associated with cross-sectional neuroimaging features; nonetheless, the results encourage future studies investigating the associations between IICV and other brain regions, as well as its utility in the prediction of neurodegeneration and dementia in American Indians.

Assessing functional ability of healthy adults with the Night Out Task.

Objective: Given the negative health outcomes associated with functional loss, there is need to better understand the trajectory of functional change and compensation use with age. Many older adults successfully age in place, and there is not a one-to-one relationship between cognitive changes and ability to live independently. This study compared healthy age cohorts' performance and approach on a functional measure, particularly examining compensatory strategy use to support task performance. Methods: 57 young adults (YAs; ages 18-39), 42 young-old adults (YOAs; ages 60-69) and 47 old-old (OOAs; ages 70+) completed the Night Out Task (NOT); an open-ended functional assessment in which participants complete eight subtasks in preparation for a night out with a friend (e.g. prepare tea and gather items for a recipe). The NOT measures both primary outcome variables (e.g. time and accuracy), error types and 'compensation variables', which are process-approach variables intended to map on to the types of compensatory strategies individuals use in their everyday lives (e.g. planning and checking). Results: Results revealed that YAs performed better than the oldest group on the NOT in accuracy, execution time and number of both inefficient and inaccurate/incomplete errors. YAs additionally used fewer compensatory strategies than both older groups. Only one compensation variable had a positive relationship to outcome; double-checking was related to improved accuracy and fewer inaccurate/incomplete errors within the oldest cohort. Conclusion: Together these findings support a spectrum of functional change with age. While compensation use increased with age, the relationship between compensation use and outcome was unclear. Future work is needed to understand under what conditions older adults' self-initiate compensation use and to understand the relationship between compensation use and outcome.

Ecological validity reconsidered: the Night Out Task versus the D-KEFS.

INTRODUCTION: Although executive functioning (EF) correlates with execution of instrumental activities of daily living (IADLs), tests of EF have been criticized for having poor ecological validity. Attempts have been made to develop new tests that approximate naturalistic daily tasks. However, the incremental utility of such tests has not been convincingly demonstrated. The Night Out Task (NOT) is a novel measure designed to increase ecological validity. This study examined whether the NOT correlates with traditional lab- and home-based measures of EF and IADLs, and whether it outperforms traditional measures of EF in predicting IADLs. METHOD: Participants (50 adults aged 60 to 95) completed (1) the Delis Kaplan Executive Function System (D-KEFS) and IADLs in the laboratory, and (2) ecological momentary assessment of EF and daily IADL tasks at home across three weeks (using the Daily Assessment of Independent Living and Executive Skills protocol; DAILIES). RESULTS: The NOT correlated with a lab-based measure of EF beyond covariates, and lab-based IADLs beyond covariates and beyond the D-KEFS. However, it was unrelated to at-home variables beyond covariates. In contrast, the D-KEFS was a significant predictor of at-home IADLs, and this association was mediated by at-home EF performance. CONCLUSION: This study provides a preliminary validation of the NOT as a correlate of office-based performances in a primarily college educated white sample. Despite its high face validity, the NOT does not appear to sufficiently tap EF processes needed for home-based IADLs as measured by the DAILIES, although small sample size limits the interpretability of this negative finding.

Multimodal Fusion of Smart Home and Text-based Behavior Markers for Clinical Assessment Prediction.

New modes of technology are offering unprecedented opportunities to unobtrusively collect data about people's behavior. While there are many use cases for such information, we explore its utility for predicting multiple clinical assessment scores. Because clinical assessments are typically used as screening tools for impairment and disease, such as mild cognitive impairment (MCI), automatically mapping behavioral data to assessment scores can help detect changes in health and behavior across time. In this paper, we aim to extract behavior markers from two modalities, a smart home environment and a custom digital memory notebook app, for mapping to ten clinical assessments that are relevant for monitoring MCI onset and changes in cognitive health. Smart home-based behavior markers reflect hourly, daily, and weekly activity patterns, while app-based behavior markers reflect app usage and writing content/style derived from free-form journal entries. We describe machine learning techniques for fusing these multimodal behavior markers and utilizing joint prediction. We evaluate our approach using three regression algorithms and data from 14 participants with MCI living in a smart home environment. We observed moderate to large correlations between predicted and ground-truth assessment scores, ranging from r = 0.601 to r = 0.871 for each clinical assessment.

Detecting Smartwatch-based Behavior Change in Response to a Multi-domain Brain Health Intervention.

In this study, we introduce and validate a computational method to detect lifestyle change that occurs in response to a multi-domain healthy brain aging intervention. To detect behavior change, digital behavior markers (DM) are extracted from smartwatch sensor data and a Permutation-based Change Detection (PCD) algorithm quantifies the change in marker-based behavior from a pre-intervention, one-week baseline. To validate the method, we verify that changes are successfully detected from synthetic data with known pattern differences. Next, we employ this method to detect overall behavior change for n=28 BHI subjects and n=17 age-matched control subjects. For these individuals, we observe a monotonic increase in behavior change from the baseline week with a slope of 0.7460 for the intervention group and a slope of 0.0230 for the control group. Finally, we utilize a random forest algorithm to perform leave-one-subject-out prediction of intervention versus control subjects based on digital marker delta values. The random forest predicts whether the subject is in the intervention or control group with an accuracy of 0.87. This work has implications for capturing objective, continuous data to inform our understanding of intervention adoption and impact.

A Comparison of Functional Abilities in Individuals with Mild Cognitive Impairment and Parkinson's Disease with Mild Cognitive Impairment Using Multiple Assessment Methods.

OBJECTIVE: This study used multiple assessment methods to examine instrumental activities of daily living (IADLs) performance in individuals with Parkinson's disease with mild cognitive impairment (PD-MCI) compared to individuals with mild cognitive impairment (MCI) and cognitively healthy older adults (HOA). Associations between functional performance and cognition were also examined. METHODS: Eighteen individuals with PD-MCI, 48 individuals with MCI, and 66 HOAs were assessed with multiple IADL measures, including direct observation, a performance-based measure, and self- and informant-report questionnaires. Performance on the direct-observation measure was further characterized by coding for four error types: omissions, substitutions, and inefficient and irrelevant/off-task actions. RESULTS: Both the PD-MCI and MCI groups performed more poorly on the overall score for all IADL measures relative to HOAs. Although the PD-MCI and MCI groups did not differ in overall performance, on the direct-observation measure, the PD-MCI group took longer and made more inefficient and irrelevant/off-task errors relative to the HOA and MCI groups, whereas the MCI group made more omission and substitution errors relative to HOAs. Further, the pattern of cognitive correlates that associated most strongly with the functional measures varied across groups and functional assessment methods. CONCLUSION: Compared to HOAs, PD-MCI and MCI groups demonstrated increased difficulties performing everyday activities, and cognitive and motor abilities differentially contributed to the everyday task difficulties of these two groups.

Cost Effectiveness of a Cultural Physical Activity Intervention to Reduce Blood Pressure Among Native Hawaiians with Hypertension.

OBJECTIVE: The aim of this study was to calculate the costs and assess whether a culturally grounded physical activity intervention offered through community-based organizations is cost effective in reducing blood pressure among Native Hawaiian adults with hypertension. METHODS: Six community-based organizations in Hawai'i completed a randomized controlled trial between 2015 and 2019. Overall, 263 Native Hawaiian adults with uncontrolled hypertension (≥ 140 mmHg systolic, ≥ 90 mmHg diastolic) were randomized to either a 12-month intervention group of hula (traditional Hawaiian dance) lessons and self-regulation classes, or to an education-only waitlist control group. The primary outcome was change in systolic blood pressure collected at baseline and 3, 6, and 12 months for the intervention compared with the control group. Incremental cost-effectiveness ratios (ICERs) were calculated for primary and secondary outcomes. Non-parametric bootstrapping and sensitivity analyses evaluated uncertainty in parameters and outcomes. RESULTS: The mean intervention cost was US$361/person, and the 6-month ICER was US$103/mmHg reduction in systolic blood pressure and US$95/mmHg in diastolic blood pressure. At 12 months, the intervention group maintained reductions in blood pressure, which exceeded reductions for usual care based on blood pressure outcomes. The change in blood pressure at 12 months resulted in ICERs of US$100/mmHg reduction in systolic blood pressure and US$93/mmHg in diastolic blood pressure. Sensitivity analyses suggested that at the estimated intervention cost, the probability that the program would lower systolic blood pressure by 5 mmHg was 67 and 2.5% at 6 and 12 months, respectively. CONCLUSION: The 6-month Ola Hou program may be cost effective for low-resource community-based organizations. Maintenance of blood pressure reductions at 6 and 12 months in the intervention group contributed to potential cost effectiveness. Future studies should further evaluate the cost effectiveness of indigenous physical activity programs in similar settings and by modeling lifetime costs and quality-adjusted life-years. TRIAL REGISTRATION NUMBER: NCT02620709.

Self-Reported Behavior Change and Predictors of Engagement With a Multidomain Brain Health Intervention for Midlife and Older Adults: A Pilot Clinical Trial.

OBJECTIVES: This study evaluated the efficacy of a multidomain brain health intervention on health behavior change and sought to understand whether health literacy or brain health knowledge predicted engagement with the intervention. METHODS: One-hundred thirty midlife and older adults were assigned to one of three intervention conditions: brain fitness (B-Fit) utilizing education and goal setting, education-only, or waitlist. Questionnaires were completed at baseline and post-intervention. RESULTS: Both B-Fit and education-only conditions reported improvements in health behaviors over time. Although effect size for the education-only condition was moderate, only the B-Fit condition differed significantly in health behaviors from the waitlist post-intervention. Lower baseline brain health knowledge predicted improvements in health behaviors for education-only condition. DISCUSSION: The multidomain brain health intervention was successful in helping participants change their behaviors, but it was not more effective than the education-only condition. For those with lower brain health knowledge, an education-only intervention may be sufficient to encourage behavior change.

Partnering a Compensatory Application with Activity-Aware Prompting to Improve Use in Individuals with Amnestic Mild Cognitive Impairment: A Randomized Controlled Pilot Clinical Trial.

BACKGROUND: Compensatory aids can help mitigate the impact of progressive cognitive impairment on daily living. OBJECTIVE: We evaluate whether the learning and sustained use of an Electronic Memory and Management Aid (EMMA) application can be augmented through a partnership with real-time, activity-aware transition-based prompting delivered by a smart home. METHODS: Thirty-two adults who met criteria for amnestic mild cognitive impairment (aMCI) were randomized to learn to use the EMMA app on its own (N = 17) or when partnered with smart home prompting (N = 15). The four-week, five-session manualized EMMA training was conducted individually in participant homes by trained clinicians. Monthly questionnaires were completed by phone with trained personnel blind to study hypotheses. EMMA data metrics were collected continuously for four months. For the partnered condition, activity-aware prompting was on during training and post-training months 1 and 3, and off during post-training month 2. RESULTS: The analyzed aMCI sample included 15 EMMA-only and 14 partnered. Compared to the EMMA-only condition, by week four of training, participants in the partnered condition were engaging with EMMA more times daily and using more basic and advanced features. These advantages were maintained throughout the post-training phase with less loss of EMMA app use over time. There was little differential impact of the intervention on self-report primary (everyday functioning, quality of life) and secondary (coping, satisfaction with life) outcomes. CONCLUSION: Activity-aware prompting technology enhanced acquisition, habit formation and long-term use of a digital device by individuals with aMCI. (ClinicalTrials.gov NCT03453554).

Fusing Ambient and Mobile Sensor Features Into a Behaviorome for Predicting Clinical Health Scores.

Advances in machine learning and low-cost, ubiquitous sensors offer a practical method for understanding the predictive relationship between behavior and health. In this study, we analyze this relationship by building a behaviorome, or set of digital behavior markers, from a fusion of data collected from ambient and wearable sensors. We then use the behaviorome to predict clinical scores for a sample of n = 21 participants based on continuous data collected from smart homes and smartwatches and automatically labeled with corresponding activity and location types. To further investigate the relationship between domains, including participant demographics, self-report and external observation-based health scores, and behavior markers, we propose a joint inference technique that improves predictive performance for these types of high-dimensional spaces. For our participant sample, we observe correlations ranging from small to large for the clinical scores. We also observe an improvement in predictive performance when multiple sensor modalities are used and when joint inference is employed.

Medication Management Performance in Parkinson's Disease: Examination of Process Errors.

OBJECTIVE: Individuals with Parkinson's disease (PD) are at risk for increased medication mismanagement, which can lead to worse clinical outcomes. However, the nature of the errors (i.e., undertaking or overtaking medications) contributing to mismanagement and their relationship to cognition in PD is unknown. Therefore, this study sought to examine errors committed on the Medication Management Ability Assessment (MMAA) between PD participants with normal cognition (PD-NC) or mild cognitive impairment (PD-MCI) relative to healthy adults (HA). METHOD: HA (n = 74), PD-NC (n = 102), and PD-MCI (n = 45) participants were administered the MMAA to assess undertaking, overtaking, and overall errors as well as overall performance (total score). Additionally, participants were administered a comprehensive neuropsychological battery from which cognitive composites of Attention, Learning, Memory, Language, Visuospatial, and Executive Functioning were derived. RESULTS: Separate negative binomial regression analyses indicated the PD-MCI group performed significantly worse overall on the MMAA (total score) and committed more undertaking and overall errors relative to HA and PD-NC. In the PD-MCI group, poorer MMAA performance was associated with worse delayed memory performance, whereas cognitive performance was not related to MMAA in HA or PC-NC. CONCLUSION: Compared to PD and healthy adults with normal cognition, PD-MCI patients exhibited greater difficulty with medication management, particularly with undertaking medications. Poorer medication management in PD-MCI was associated with worse delayed recall. Thus, PD-MCI patients experiencing memory problems may require additional assistance with their medications. Findings have clinical relevance suggesting that objective measures of medication errors may assist clinicians in identifying PD patients needing adherence strategies.