scholarly journals An Ecologically Valid, Longitudinal, and Unbiased Assessment of Treatment Efficacy in Alzheimer Disease (the EVALUATE-AD Trial): Proof-of-Concept Study

10.2196/17603 ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. e17603
Author(s):  
Neil William Douglas Thomas ◽  
Zachary Beattie ◽  
Jennifer Marcoe ◽  
Kirsten Wright ◽  
Nicole Sharma ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Cognitive Impairment ◽  
Medication Adherence ◽  
Alzheimer Disease ◽  
Outcome Measures ◽  
Treatment Efficacy ◽  
Computing System ◽  
Home Based ◽  
Care Partners ◽  
Current Clinical Trial

Background The current clinical trial assessment methodology relies on a combination of self-report measures, cognitive and physical function tests, and biomarkers. This methodology is limited by recall bias and recency effects in self-reporting and by assessments that are brief, episodic, and clinic based. Continuous monitoring of ecologically valid measures of cognition and daily functioning in the community may provide a more sensitive method to detect subtle, progressive changes in patients with cognitive impairment and dementia. Objective This study aimed to present an alternative trial approach using a home-based sensing and computing system to detect changes related to common treatments employed in Alzheimer disease (AD). This paper introduces an ongoing study that aims to determine the feasibility of capturing sensor-based data at home and to compare the sensor-based outcomes with conventional outcomes. We describe the methodology used in the assessment protocol and present preliminary results of feasibility measures and examples of data related to medication-taking behavior, activity levels, and sleep. Methods The EVALUATE-AD (Ecologically Valid, Ambient, Longitudinal and Unbiased Assessment of Treatment Efficacy in Alzheimer’s Disease) trial is a longitudinal naturalistic observational cohort study recruiting 30 patients and 30 spouse coresident care partners. Participants are monitored continuously using a home-based sensing and computing system for up to 24 months. Outcome measures of the automated system are compared with conventional clinical outcome measures in AD. Acceptance of the home system and protocol are assessed by rates of dropout and protocol adherence. After completion of the study monitoring period, a composite model using multiple functional outcome measures will be created that represents a behavioral-activity signature of initiating or discontinuing AD-related medications, such as cholinesterase inhibitors, memantine, or antidepressants. Results The home-based sensing and computing system has been well accepted by individuals with cognitive impairment and their care partners. Participants showed good adherence to the completion of a weekly web-based health survey. Daily activity, medication adherence, and total time in bed could be derived from algorithms using data from the sensing and computing system. The mean monitoring time for current participants was 14.6 months. Medication adherence, as measured with an electronic pillbox, was 77% for participants taking AD-related medications. Conclusions Continuous, home-based assessment provides a novel approach to test the impact of new or existing dementia treatments generating objective, clinically meaningful measures related to cognition and everyday functioning. Combining this approach with the current clinical trial methodology may ultimately reduce trial durations, sample size needs, and reliance on a clinic-based assessment. International Registered Report Identifier (IRRID) DERR1-10.2196/17603

scholarly journals An Ecologically Valid, Longitudinal, and Unbiased Assessment of Treatment Efficacy in Alzheimer Disease (the EVALUATE-AD Trial): Proof-of-Concept Study (Preprint)

2019 ◽  
Author(s):  
Neil William Douglas Thomas ◽  
Zachary Beattie ◽  
Jennifer Marcoe ◽  
Kirsten Wright ◽  
Nicole Sharma ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Cognitive Impairment ◽  
Medication Adherence ◽  
Alzheimer Disease ◽  
Outcome Measures ◽  
Treatment Efficacy ◽  
Computing System ◽  
Home Based ◽  
Care Partners ◽  
Current Clinical Trial

BACKGROUND The current clinical trial assessment methodology relies on a combination of self-report measures, cognitive and physical function tests, and biomarkers. This methodology is limited by recall bias and recency effects in self-reporting and by assessments that are brief, episodic, and clinic based. Continuous monitoring of ecologically valid measures of cognition and daily functioning in the community may provide a more sensitive method to detect subtle, progressive changes in patients with cognitive impairment and dementia. OBJECTIVE This study aimed to present an alternative trial approach using a home-based sensing and computing system to detect changes related to common treatments employed in Alzheimer disease (AD). This paper introduces an ongoing study that aims to determine the feasibility of capturing sensor-based data at home and to compare the sensor-based outcomes with conventional outcomes. We describe the methodology used in the assessment protocol and present preliminary results of feasibility measures and examples of data related to medication-taking behavior, activity levels, and sleep. METHODS The EVALUATE-AD (Ecologically Valid, Ambient, Longitudinal and Unbiased Assessment of Treatment Efficacy in Alzheimer’s Disease) trial is a longitudinal naturalistic observational cohort study recruiting 30 patients and 30 spouse coresident care partners. Participants are monitored continuously using a home-based sensing and computing system for up to 24 months. Outcome measures of the automated system are compared with conventional clinical outcome measures in AD. Acceptance of the home system and protocol are assessed by rates of dropout and protocol adherence. After completion of the study monitoring period, a composite model using multiple functional outcome measures will be created that represents a behavioral-activity signature of initiating or discontinuing AD-related medications, such as cholinesterase inhibitors, memantine, or antidepressants. RESULTS The home-based sensing and computing system has been well accepted by individuals with cognitive impairment and their care partners. Participants showed good adherence to the completion of a weekly web-based health survey. Daily activity, medication adherence, and total time in bed could be derived from algorithms using data from the sensing and computing system. The mean monitoring time for current participants was 14.6 months. Medication adherence, as measured with an electronic pillbox, was 77% for participants taking AD-related medications. CONCLUSIONS Continuous, home-based assessment provides a novel approach to test the impact of new or existing dementia treatments generating objective, clinically meaningful measures related to cognition and everyday functioning. Combining this approach with the current clinical trial methodology may ultimately reduce trial durations, sample size needs, and reliance on a clinic-based assessment. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/17603

scholarly journals IDENTIFYING CARE ACTIVITIES THAT WERE SUPPORTED BY AMAZON ECHO FOR CARE PARTNERS AFTER ONSET OF COGNITIVE IMPAIRMENT

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S328-S328
Author(s):  
Galina Madjaroff
Keyword(s):  
Quality Of Life ◽  
Cognitive Impairment ◽  
Lived Experience ◽  
Intelligent Agent ◽  
Well Being ◽  
Multiple Sources ◽  
Home Based ◽  
Care Partners ◽  
Voice User

Abstract There are several important challenges when addressing the needs of older adults with cognitive impairment and their care partners including the potential for diminishing emotional well-being and loss of autonomy, which could potentially lead to a lower overall quality of life for both care partners (CPs). The motivation of this study was to identify the care activities that were supported by home based technology for care partners after the onset of cognitive impairment. This work was done through gathering multiple sources of qualitative and quantitative data, including mobile application dialogue history logs, pre and post interviews, user feedback groups and home visits. The technology deployed in the home of the care partners was a Voice User Interface Intelligent Agent, specifically the Amazon Echo with its intelligent agent “Alexa.” This technology was selected because it was not built from a traditional care model, yet embodies functions that could be used for all potential forms of care, including those that achieve a higher level of quality of life goals for care partners. From this study, we can further our understanding of how to deploy and design technology that shifts the perspective from “cure to care” with a focus on the older person and their lived experience, monitoring wellness, and not just addressing illness. Results and findings indicated that daily care activities of dyads that are seemingly fundamental are actually complex care activities that emerge from using the technology that support the care partners on multiple levels in satisfying multiple needs.

scholarly journals Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review (Preprint)

2018 ◽  
Author(s):  
Antoine Piau ◽  
Katherine Wild ◽  
Nora Mattek ◽  
Jeffrey Kaye
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Alzheimer Disease ◽  
Alternative Assessment ◽  
Real Life ◽  
Community Dwelling ◽  
Home Based ◽  
Passive Sensors ◽  
Digital Biomarkers

BACKGROUND Among areas that have challenged the progress of dementia care has been the assessment of change in symptoms over time. Digital biomarkers are defined as objective, quantifiable, physiological, and behavioral data that are collected and measured by means of digital devices, such as embedded environmental sensors or wearables. Digital biomarkers provide an alternative assessment approach, as they allow objective, ecologically valid, and long-term follow-up with continuous assessment. Despite the promise of a multitude of sensors and devices that can be applied, there are no agreed-upon standards for digital biomarkers, nor are there comprehensive evidence-based results for which digital biomarkers may be demonstrated to be most effective. OBJECTIVE In this review, we seek to answer the following questions: (1) What is the evidence for real-life, home-based use of technologies for early detection and follow-up of mild cognitive impairment (MCI) or dementia? And (2) What transformation might clinicians expect in their everyday practices? METHODS A systematic search was conducted in PubMed, Cochrane, and Scopus databases for papers published from inception to July 2018. We searched for studies examining the implementation of digital biomarker technologies for mild cognitive impairment or mild Alzheimer disease follow-up and detection in nonclinic, home-based settings. All studies that included the following were examined: community-dwelling older adults (aged 65 years or older); cognitively healthy participants or those presenting with cognitive decline, from subjective cognitive complaints to early Alzheimer disease; a focus on home-based evaluation for noninterventional follow-up; and remote diagnosis of cognitive deterioration. RESULTS An initial sample of 4811 English-language papers were retrieved. After screening and review, 26 studies were eligible for inclusion in the review. These studies ranged from 12 to 279 participants and lasted between 3 days to 3.6 years. Most common reasons for exclusion were as follows: inappropriate setting (eg, hospital setting), intervention (eg, drugs and rehabilitation), or population (eg, psychiatry and Parkinson disease). We summarized these studies into four groups, accounting for overlap and based on the proposed technological solutions, to extract relevant data: (1) data from dedicated embedded or passive sensors, (2) data from dedicated wearable sensors, (3) data from dedicated or purposive technological solutions (eg, games or surveys), and (4) data derived from use of nondedicated technological solutions (eg, computer mouse movements). CONCLUSIONS Few publications dealt with home-based, real-life evaluations. Most technologies were far removed from everyday life experiences and were not mature enough for use under nonoptimal or uncontrolled conditions. Evidence available from embedded passive sensors represents the most relatively mature research area, suggesting that some of these solutions could be proposed to larger populations in the coming decade. The clinical and research communities would benefit from increasing attention to these technologies going forward.

scholarly journals Developing feedback methods for caregivers of persons with cognitive impairment using a home‐based sensing and computing system

2020 ◽  
Vol 16 (S7) ◽  
Author(s):  
Neil W Thomas ◽  
Laura Ault ◽  
Rafik Goubran ◽  
Bruce Wallace ◽  
Frank Knoefel ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Computing System ◽  
Home Based

TD-P-011: ASSESSING EVERYDAY COGNITION IN OLDER ADULTS WITH MCI OR ALZHEIMER DISEASE USING A HOME-BASED SENSING AND COMPUTING SYSTEM

2006 ◽  
Vol 14 (7S_Part_3) ◽  
pp. P190-P190
Author(s):  
Neil W. Thomas ◽  
Nora Mattek ◽  
Thomas Riley ◽  
Phelps Witter ◽  
Christina L. Reynolds ◽  
...  
Keyword(s):  
Older Adults ◽  
Alzheimer Disease ◽  
Computing System ◽  
Everyday Cognition ◽  
Home Based

scholarly journals A pilot protocol to assess the feasibility of a virtual multiple crossover, randomized controlled trial design using methylphenidate in mild cognitive impairment

Trials ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Libby A. DesRuisseaux ◽  
Victoria J. Williams ◽  
Alison J. McManus ◽  
Anoopum S. Gupta ◽  
Becky C. Carlyle ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Randomized Controlled Trial ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Outcome Measures ◽  
Trial Design ◽  
Controlled Trial ◽  
Symptomatic Treatment ◽  
Randomized Controlled ◽  
Parallel Group

Abstract Background The conventional clinical trial design in Alzheimer’s disease (AD) and AD-related disorders (ADRDs) is the parallel-group randomized controlled trial. However, in heterogeneous disorders like AD/ADRDs, this design requires large sample sizes to detect meaningful effects in an “average” patient. They are very costly and, despite many attempts, have not yielded new treatments for many years. An alternative, the multi-crossover, randomized control trial (MCRCT) is a design in which each patient serves as their own control across successive, randomized blocks of active treatment and placebo. This design overcomes many limitations of parallel-group trials, yielding an unbiased assessment of treatment effect at the individual level (“N-of-1”) regardless of unique patient characteristics. The goal of the present study is to pilot a MCRCT of a potential symptomatic treatment, methylphenidate, for mild-stage AD/ADRDs, testing feasibility and compliance of participants in this design and efficacy of the drug using both standard and novel outcome measures suited for this design. Methods Ten participants with mild cognitive impairment or mild-stage dementia due to AD/ADRDs will undergo a 4-week lead-in period followed by three, month-long treatment blocks (2 weeks of treatment with methylphenidate, 2 weeks placebo in random order). This trial will be conducted entirely virtually with an optional in-person screening visit. The primary outcome of interest is feasibility as measured by compliance and retention, with secondary and exploratory outcomes including cognition as measured by neuropsychological assessment at the end of each treatment period and daily brain games played throughout the study, actigraphy, and neuropsychiatric and functional assessments. Discussion This pilot study will gauge the feasibility of conducting a virtual MCRCT for symptomatic treatment in early AD/ADRD. It will also compare home-based daily brain games with standard neuropsychological measures within a clinical trial for AD/ADRD. Particular attention will be paid to compliance, tolerability of drug and participation, learning effects, trends and stability of daily measures across blocks, medication carryover effects, and correlations between standard and brief daily assessments. These data will provide guidance for more efficient trial design and the use of potentially more robust, ecological outcome measures in AD/ADRD research. Trial registration ClinicalTrials.gov, NCT03811847. Registered on 21 January 2019.

scholarly journals Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review

10.2196/12785 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e12785 ◽  
Author(s):  
Antoine Piau ◽  
Katherine Wild ◽  
Nora Mattek ◽  
Jeffrey Kaye
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Alzheimer Disease ◽  
Alternative Assessment ◽  
Real Life ◽  
Community Dwelling ◽  
Home Based ◽  
Passive Sensors ◽  
Digital Biomarkers

Background Among areas that have challenged the progress of dementia care has been the assessment of change in symptoms over time. Digital biomarkers are defined as objective, quantifiable, physiological, and behavioral data that are collected and measured by means of digital devices, such as embedded environmental sensors or wearables. Digital biomarkers provide an alternative assessment approach, as they allow objective, ecologically valid, and long-term follow-up with continuous assessment. Despite the promise of a multitude of sensors and devices that can be applied, there are no agreed-upon standards for digital biomarkers, nor are there comprehensive evidence-based results for which digital biomarkers may be demonstrated to be most effective. Objective In this review, we seek to answer the following questions: (1) What is the evidence for real-life, home-based use of technologies for early detection and follow-up of mild cognitive impairment (MCI) or dementia? And (2) What transformation might clinicians expect in their everyday practices? Methods A systematic search was conducted in PubMed, Cochrane, and Scopus databases for papers published from inception to July 2018. We searched for studies examining the implementation of digital biomarker technologies for mild cognitive impairment or mild Alzheimer disease follow-up and detection in nonclinic, home-based settings. All studies that included the following were examined: community-dwelling older adults (aged 65 years or older); cognitively healthy participants or those presenting with cognitive decline, from subjective cognitive complaints to early Alzheimer disease; a focus on home-based evaluation for noninterventional follow-up; and remote diagnosis of cognitive deterioration. Results An initial sample of 4811 English-language papers were retrieved. After screening and review, 26 studies were eligible for inclusion in the review. These studies ranged from 12 to 279 participants and lasted between 3 days to 3.6 years. Most common reasons for exclusion were as follows: inappropriate setting (eg, hospital setting), intervention (eg, drugs and rehabilitation), or population (eg, psychiatry and Parkinson disease). We summarized these studies into four groups, accounting for overlap and based on the proposed technological solutions, to extract relevant data: (1) data from dedicated embedded or passive sensors, (2) data from dedicated wearable sensors, (3) data from dedicated or purposive technological solutions (eg, games or surveys), and (4) data derived from use of nondedicated technological solutions (eg, computer mouse movements). Conclusions Few publications dealt with home-based, real-life evaluations. Most technologies were far removed from everyday life experiences and were not mature enough for use under nonoptimal or uncontrolled conditions. Evidence available from embedded passive sensors represents the most relatively mature research area, suggesting that some of these solutions could be proposed to larger populations in the coming decade. The clinical and research communities would benefit from increasing attention to these technologies going forward.

Sign in / Sign up

Export Citation Format

Share Document