ToolboxDetect Cognitive Screening for Cognitive Impairment
Recruiting in Palo Alto (17 mi)
Age: 65+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Northwestern University
Disqualifiers: Severe vision, hearing impairment
No Placebo Group
Trial Summary
What is the purpose of this trial?
Our study objective is to widely implement and evaluate a user-centered, scalable, electronic health record (EHR)-linked strategy for the routine detection of cognitive decline among diverse primary care settings. This strategy, called ToolboxDetect, will provide an efficient and sensitive cognitive screen that can be easily implemented in everyday clinical settings, and is responsive to patient, family, and caregiver concerns for potential symptoms of cognitive decline (CD) and cognitive impairment (CI).
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications.
Is ToolboxDetect Cognitive Screening safe for humans?
How is the ToolboxDetect treatment different from other treatments for cognitive impairment?
ToolboxDetect is unique because it is a portable device that allows for rapid cognitive testing in various settings, unlike traditional methods that are often paper-based, time-consuming, and require a healthcare professional. This makes it more practical for widespread screening and early detection of cognitive impairment.46789
Eligibility Criteria
This trial is for adults aged 65 and older who may or may not have signs of cognitive decline, such as memory loss or confusion. They must be able to see and hear well enough to participate in the tests. Participants will come from practices linked with Northwestern Medicine and Access Community Health Network.Inclusion Criteria
I may or may not have issues with my memory or thinking.
Practices affiliated with Northwestern Medicine and Access Community Health Network
I am 65 years old or older.
See 3 more
Exclusion Criteria
I have severe vision or hearing loss that cannot be corrected.
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Implementation
Implementation of ToolboxDetect as a standard of care for cognitive assessment during Medicare Annual Wellness Visits
Up to 3 years
Routine visits as part of Annual Wellness Visits
Follow-up
Participants are monitored for cognitive decline detection and management effectiveness
Up to 3 years
Follow-up visits post AWV
Treatment Details
Interventions
- ToolboxDetect (Behavioural Intervention)
Trial OverviewToolboxDetect is being tested; it's a new strategy using electronic health records to spot early signs of cognitive decline in diverse primary care settings. It aims to be user-friendly, efficient, and sensitive to concerns about memory problems.
Participant Groups
2Treatment groups
Experimental Treatment
Active Control
Group I: ToolboxDetect StrategyExperimental Treatment1 Intervention
All practices randomized to the intervention arm will implement the ToolboxDetect battery as the standard of care routine cognitive assessment to fulfill the Medicare Annual Wellness Visit (AWV) requirement. The 7-8 minute ToolboxDetect battery contains self-administered versions of the NIH ToolBox Picture Sequence Memory Test (PSM) and the NIH ToolBox Dimensional Change Card Sorting (DCCS). PSM measures episodic memory and DCCS tests executive functioning.
The validated ToolboxDetect application will be imparted either as an application on an iPad or on a PC desktop/laptop computer commonly found in a clinical exam room for EHR access.
Group II: Enhanced Usual CareActive Control1 Intervention
At Northwestern Medicine, cognitive assessments included in Annual Wellness Visits or other routine or sick/problem-based visits vary by practice and also by clinician. However, the choice of test was limited to either a Mini-Cog©, Montreal Cognitive Assessment (MoCA), or Mini Mental Status Exam (MMSE).
While we will not make any explicit recommendations to these practices with regard to their use of a cognitive assessment, we will ensure that 1) any chosen test is linked to an Epic SmartData element, which will allow the clinician to record the results of the test as discrete data (which can then be queried), and that 2) providers receive a compiled list of local medical and non-medical referrals for any detected cases of CI. The Alzheimer's Association recommendations for early detection efforts among primary care practices will also be provided to each clinic's medical leadership.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Northwestern UniversityChicago, IL
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Who Is Running the Clinical Trial?
Northwestern UniversityLead Sponsor
ACCESS Community Health NetworkCollaborator
References
Primary care detection of cognitive impairment leveraging health and consumer technologies in underserved US communities: protocol for a pragmatic randomised controlled trial of the MyCog paradigm. [2023]Early identification of cognitive impairment (CI), including Alzheimer's disease and related dementias (ADRD), is a top public health priority. Yet, CI/ADRD is often undetected and underdiagnosed within primary care settings, and in health disparate populations. The MyCog paradigm is an iPad-based, self-administered, validated cognitive assessment based on the National Institutes of Health (NIH) Toolbox Cognition Battery and coupled with clinician decision-support tools that is specifically tailored for CI/ADRD detection within diverse, primary care settings.
The value of assessing cognitive function in drug development. [2023]This paper reviews the value and utility of measuring cognitive function in the development of new medicines by reference to the most widely used automated system in clinical research. Evidence is presented from phase 1 to 3 of the nature and quality of the information that can be obtained by applying the Cognitive Drug Research computerized assessment system to ongoing clinical trials. Valuable evidence can be obtained even in the first trial in which a novel compound is administered to man. One application of such testing is to ensure that novel compounds are relatively free from cognition-impairing properties, particularly in relation to competitor products. Another is to ensure that unwanted interactions with alcohol and other medications do not occur, or, if they do, to put them in context. In many patient populations, cognitive dysfunction occurs as a result of the disease process, and newer medicines which can treat the symptoms of the disease without further impairing function can often reveal benefits as the disease-induced cognitive dysfunction is reduced. Another major application is to identify benefits for compounds designed to enhance cognitive function. Such effects can be sought in typical phase 1 trials, or a scopolamine model of the core deficits of Alzheimer's disease can be used to screen potential antidernentia drugs. Ultimately, of course, such effects can be demonstrated using properly validated and highly sensitive automated procedures in the target populations. The data presented demonstrate that the concept of independently assessing a variety of cognitive functions is crucial in helping differentiate drugs, types of dementia, and different illnesses. Such information offers a unique insight into how the alterations to various cognitive functions will manifest themselves in everyday behavior. This reveals a major limitation of scales that yield a single score, because such limited information does not permit anything but a quantitative interpretation; and the concept of "more" cognitive function or "less" is manifestly inappropriate for something as complex and diverse as the interplay between cognitive function and human behavior. Finally, the next generations of cognitive testing are described. Testing via the telephone has just been introduced and will have dramatic effects on the logistics of conducting cognitive testing in large patient trials. Testing via the Internet is not far off either, and will come fully into play as the proportion of homes connected to the Internet increases in Europe and North America. There are no sound reasons for not wishing to include cognitive function testing in the development protocol of any novel medicine.
Developments in scalable strategies for detecting early markers of cognitive decline. [2022]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.
Current advances in digital cognitive assessment for preclinical Alzheimer's disease. [2021]There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost-effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech-adoption increases, and external events (i.e., COVID-19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in-clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study-provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.
Unsupervised assessment of cognition in the Healthy Brain Project: Implications for web-based registries of individuals at risk for Alzheimer's disease. [2022]Web-based platforms are used increasingly to assess cognitive function in unsupervised settings. The utility of cognitive data arising from unsupervised assessments remains unclear. We examined the acceptability, usability, and validity of unsupervised cognitive testing in middle-aged adults enrolled in the Healthy Brain Project.
The trail-making-test: Comparison between paper-and-pencil and computerized versions in young and healthy older adults. [2022]One of the key challenges in assessing cognitive performance is to detect not only apparent impairment but to also pick up on subtle differences. Computerized tests benefit especially from the acquisition of fine-grained outcome measures. However, the equivalency of paper-based and computerized tests cannot be assumed. The Trail-Making-Test is a paper-pencil cognitive assessment tool (ppTMT) that has been used in many research studies to evaluate visuomotor abilities and mental flexibility. A digital version of the extended TMT (including a condition measuring fine motor speed) called the dTMT has been developed. This study aims to test (1) reliability, (2) equivalence, and (3) agreement of the ppTMT and dTMT. A total of 53 healthy individuals aged 19 to 82 years of age (22 men, 31 women; mean age 42.2, SD = 22.8) completed three trials per ppTMT and dTMT condition. Part M involves following a predefined path, Part A links numbers randomly distributed in space, in ascending order, and Part B alternates between linking numbers and letters. dTMT scores were highly reproducible, correlated strongly with paper-pencil administered durations, and discriminated young from older adults. Measures of reliability, sensitivity, and clinical meaning for dTMT scores were favorable compared with ppTMT-based testing. Our findings support the comparability of TMT-indices in computerized assessments. While many digital biomarker efforts are in progress (e.g., neurodegenerative disorders), the dTMT sets itself apart through its high sensitivity, the alternate forms, and the additional component measures. In this light, it could serve as a starting point for an early diagnostic tool.
A novel technology to screen for cognitive impairment in the elderly. [2011]Traditional evaluation of mild cognitive impairment (MCI) can be costly, time consuming, and impractical for widespread screening. DETECT is a portable device developed to rapidly perform cognitive testing in diverse settings. This study compares DETECT with formal clinical assessment.
Integrated Cognitive Assessment: Speed and Accuracy of Visual Processing as a Reliable Proxy to Cognitive Performance. [2023]Various mental disorders are accompanied by some degree of cognitive impairment. Particularly in neurodegenerative disorders, cognitive impairment is the phenotypical hallmark of the disease. Effective, accurate and timely cognitive assessment is key to early diagnosis of this family of mental disorders. Current standard-of-care techniques for cognitive assessment are primarily paper-based, and need to be administered by a healthcare professional; they are additionally language and education-dependent and typically suffer from a learning bias. These tests are thus not ideal for large-scale pro-active cognitive screening and disease progression monitoring. We developed the Integrated Cognitive Assessment (referred to as CGN_ICA), a 5-minute computerized cognitive assessment tool based on a rapid visual categorization task, in which a series of carefully selected natural images of varied difficulty are presented to participants. Overall 448 participants, across a wide age-range with different levels of education took the CGN_ICA test. We compared participants' CGN_ICA test results with a variety of standard pen-and-paper tests, such as Symbol Digit Modalities Test (SDMT) and Montreal Cognitive Assessment (MoCA), that are routinely used to assess cognitive performance. CGN_ICA had excellent test-retest reliability, showed convergent validity with the standard-of-care cognitive tests used here, and demonstrated to be suitable for micro-monitoring of cognitive performance.
Development and validity of computerized neuropsychological assessment devices for screening mild cognitive impairment: Ensemble of models with feature space heterogeneity and retrieval practice effect. [2022]This study aimed to develop and validate computerized neuropsychological assessment devices for screening patients with mild cognitive impairment (MCI).