Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry.

Backgrounds: Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in the Brain Health Registry (BHR), an online registry for neuroscience research.

Methods: This study included BHR participants aged 55 + who completed both the baseline ECog and repeated administrations of the CANTAB Paired Associates Learning (PAL) visual learning and memory test.

Performance of a Short Version of the Everyday Cognition Scale (ECog-12) to Detect Cognitive Impairment.

Background: The Everyday Cognition (ECog) 12-item scale, a functional decline measurement, can distinguish dementia from cognitively unimpaired (CU). Limited data compare ECog-12 performance by raters (self vs. informant) and scoring systems (average numeric vs.

The ADNI Administrative Core: Ensuring ADNI's success and informing future AD clinical trials.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Administrative Core oversees and coordinates all ADNI activities, to ensure the success and maximize the impact of ADNI in advancing Alzheimer's disease (AD) research and clinical trials. It manages finances and develops policies for data sharing, publications using ADNI data, and access to ADNI biospecimens. The Core develops and executes pilot projects to guide future ADNI activities and identifies key innovative methods for inclusion in ADNI.

Remote olfactory assessment using the NIH Toolbox Odor Identification test and the brain health registry.

Background: Early identification of deficits in our ability to perceive odors is important as many normal (i.e., aging) and pathological (i.

Unsupervised Online Paired Associates Learning Task from the Cambridge Neuropsychological Test Automated Battery (CANTAB®) in the Brain Health Registry.

Background: Unsupervised online cognitive assessments have demonstrated promise as an efficient and scalable approach for evaluating cognition in aging, and Alzheimer's disease and related dementias.

Objectives: The aim of this study was to evaluate the feasibility, usability, and construct validity of the Paired Associates Learning task from the Cambridge Neuropsychological Test Automated Battery® in adults enrolled in the Brain Health Registry.

Design, Setting, Participants, Measurements: The Paired Associates Learning task was administered to Brain Health Registry participants in a remote, unsupervised, online setting.

An Approach for Generating Realistic Australian Synthetic Healthcare Data.

Healthcare data is a scarce resource and access is often cumbersome. While medical software development would benefit from real datasets, the privacy of the patients is held at a higher priority. Realistic synthetic healthcare data can fill this gap by providing a dataset for quality control while at the same time preserving the patient's anonymity and privacy.

Participant completion of longitudinal assessments in an online cognitive aging registry: The role of medical conditions.

Introduction: This study aimed to understand whether older adults' longitudinal completion of assessments in an online Alzheimer's disease and related dementias (ADRD)-related registry is influenced by self-reported medical conditions.

Methods: Brain Health Registry (BHR) is an online cognitive aging and ADRD-related research registry that includes longitudinal health and cognitive assessments. Using logistic regressions, we examined associations between longitudinal registry completion outcomes and self-reported (1) number of medical conditions and (2) eight defined medical condition groups (cardiovascular, metabolic, immune system, ADRD, current psychiatric, substance use/abuse, acquired, other specified conditions) in adults aged 55+ ( 23,888).

The Community Engaged Digital Alzheimer's Research (CEDAR) Study: A Digital Intervention to Increase Research Participation of Black American Participants in the Brain Health Registry.

Background: Although Black/African American older adults bear significant inequities in prevalence, incidence, and outcomes of Alzheimer's disease and related dementias, they are profoundly under-included in Alzheimer's Disease research. Community-Engaged Research (e.g.

Brain Health Registry Study Partner Portal: Novel infrastructure for digital, dyadic data collection.

Background: In Alzheimer's disease (AD) research, subjective reports of cognitive and functional decline from participant-study partner dyads is an efficient method of assessing cognitive impairment and clinical progression.

Methods: Demographics and subjective cognitive/functional decline (Everyday Cognition Scale [ECog]) scores from dyads enrolled in the Brain Health Registry (BHR) Study Partner Portal were analyzed. Associations between dyad characteristics and both ECog scores and study engagement were investigated.

Evaluation of the Electronic Clinical Dementia Rating for Dementia Screening.

Importance: The Clinical Dementia Rating (CDR) is a well-validated instrument widely used to detect and stage dementia due to Alzheimer disease. The digital Electronic Clinical Dementia Rating (eCDR) can be remotely self-administered and automatically scored, with potential to facilitate efficient dementia screening and staging.

Objective: To evaluate the association of the eCDR with the CDR and other in-clinic assessments for screening older adults for cognitive impairment.

Associations between Participant Characteristics and Participant Feedback about an Unsupervised Online Cognitive Assessment in a Research Registry.

Background: This study aims to understand whether and how participant characteristics (age, gender, education, ethnocultural identity) are related to their feedback about taking a remote, unsupervised, online cognitive assessment.

Methods: The Brain Health Registry is a public online registry which includes cognitive assessments. Multivariable ordinal regressions assessed associations between participant characteristics and feedback responses of older (55+) participants (N=11,553) regarding their Cogstate Brief Battery assessment experience.

Understanding Online Registry Facilitators and Barriers Experienced by Black Brain Health Registry Participants: The Community Engaged Digital Alzheimer's Research (CEDAR) Study.

Background: Failure of Alzheimer's disease and related diseases (ADRD) research studies to include and engage Black participants is a major issue, which limits the impact and generalizability of research findings. Little is known about participation of Black adults in online ADRD-related research registries.

Objectives: As part of the Community Engaged Digital Alzheimer's Research (CEDAR) Study, this study aims to increase our understanding of facilitators and barriers of Black adults to participating in ADRD-related online registries, as well as to understand their preferences for communication channels.

Association of Major Depressive Disorder with remotely administered measures of cognition and subjective report of cognitive difficulties across the adult age spectrum.

Background: Major depressive disorder (MDD) has increasing prevalence with age. Both objective measures of cognitive dysfunction and subjective report of cognitive difficulties related to MDD are often thought to worsen with increasing age. However, few studies have directly evaluated these characteristics across the adult lifespan.

Digital culturally tailored marketing for enrolling Latino participants in a web-based registry: Baseline metrics from the Brain Health Registry.

Introduction: This culturally tailored enrollment effort aims to determine the feasibility of enrolling 5000 older Latino adults from California into the Brain Health Registries (BHR) over 2.25 years.

Methods: This paper describes (1) the development and deployment of culturally tailored BHR websites and digital ads, in collaboration with a Latino community science partnership board and a marketing company; (2) an interim feasibility analysis of the enrollment efforts and numbers, and participant characteristics (primary aim); as well as (3) an exploration of module completion and a preliminary efficacy evaluation of the culturally tailored digital efforts compared to BHR's standard non-culturally tailored efforts (secondary aim).

Semantic Search for Large Scale Clinical Ontologies.

Finding concepts in large clinical ontologies can be challenging when queries use different vocabularies. A search algorithm that overcomes this problem is useful in applications such as concept normalisation and ontology matching, where concepts can be referred to in different ways, using different synonyms. In this paper, we present a deep learning based approach to build a semantic search system for large clinical ontologies.

Remote blood collection from older adults in the Brain Health Registry for plasma biomarker and genetic analysis.

Introduction: Use of online registries to efficiently identify older adults with cognitive decline and Alzheimer's disease (AD) is an approach with growing evidence for feasibility and validity. Linked biomarker and registry data can facilitate AD clinical research.

Methods: We collected blood for plasma biomarker and genetic analysis from older adult Brain Health Registry (BHR) participants, evaluated feasibility, and estimated associations between demographic variables and study participation.

What matters for people with brain cancer? Selecting clinical quality indicators for an Australian Brain Cancer Registry.

Background: The goal of a clinical quality registry is to deliver immediate gains in survival and quality of life by delivering timely feedback to practitioners, thereby ensuring every patient receives the best existing treatment. We are developing an Australian Brain Cancer Registry (ABCR) to identify, describe, and measure the impact of the variation and gaps in brain cancer care from the time of diagnosis to the end of life.

Methods: To determine a set of clinical quality indicators (CQIs) for the ABCR, a database and internet search were used to identify relevant guidelines, which were then assessed for quality using the AGREE II Global Rating Scale.

Reliability and Validity of a Home-Based Self-Administered Computerized Test of Learning and Memory Using Speech Recognition.

Introduction: The objective of this study is to evaluate the reliability and validity of the ReVeRe word list recall test (RWLRT), which uses speech recognition, when administered remotely and unsupervised.

Methods: Prospective cohort study. Participants included 249 cognitively intact community dwelling older adults.

Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry.

Introduction: This study investigated the extent to which subjective and objective data from an online registry can be analyzed using machine learning methodologies to predict the current brain amyloid beta (Aβ) status of registry participants.

Methods: We developed and optimized machine learning models using data from up to 664 registry participants. Models were assessed on their ability to predict Aβ positivity using the results of positron emission tomography as ground truth.

Brain health registry GenePool study: A novel approach to online genetics research.

Introduction: Remote data collection, including the establishment of online registries, is a novel approach to efficiently identify risk for cognitive decline and Alzheimer's disease (AD) in older adults, with growing evidence for feasibility and validity. Addition of genetic data to online registries has the potential to facilitate identification of older adults at risk and to advance the understanding of genetic contributions to AD.

Methods: 573 older adult participants with longitudinal online Brain Health Registry (BHR) data underwent apolipoprotein E (APOE) genotyping using remotely collected saliva samples and a novel, automated Biofluid Collection Management Portal.

Predicting amyloid status using self-report information from an online research and recruitment registry: The Brain Health Registry.

Introduction: This study aimed to predict brain amyloid beta (Aβ) status in older adults using collected information from an online registry focused on cognitive aging.

Methods: Aβ positron emission tomography (PET) was obtained from multiple in-clinic studies. Using logistic regression, we predicted Aβ using self-report variables collected in the Brain Health Registry in 634 participants, as well as a subsample (N = 533) identified as either cognitively unimpaired (CU) or mild cognitive impairment (MCI).

Validation of online functional measures in cognitively impaired older adults.

Introduction: Assessment of functional status is associated with risk of cognitive decline and diagnosis of dementia, and can be assessed by participants and study partners (SPs).

Methods: In 770 older adults enrolled in the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study and the online Brain Health Registry (BHR), we estimated associations between online assessments and clinical variables related to Alzheimer's disease (AD) risk.

Results: Worse online learning scores and SP-reported functional decline were associated with higher probability of AD dementia diagnosis and poor in-clinic cognitive assessment, and with higher odds of amyloid beta (Aβ) positivity when combined with participants' report of less decline.

Effects of sex, race, ethnicity, and education on online aging research participation.

Introduction: This study aimed to identify the relationship of sociodemographic variables with older adults participation in an online registry for recruitment and longitudinal assessment in cognitive aging.

Methods: Using Brain Health Registry (BHR) data, associations between sociodemographic variables (sex, race, ethnicity, education) and registry participation outcomes (task completion, willingness to participate in future studies, referral/enrollment in other studies) were examined in adults aged 55+ (N = 35,919) using logistic regression. All models included sex, race, ethnicity, education, age, and subjective memory concern.

Associations among amyloid status, age, and longitudinal regional brain atrophy in cognitively unimpaired older adults.

The goal of this study was to compare regional brain atrophy patterns in cognitively unimpaired (CU) older adults with and without brain accumulation of amyloid-β (Aβ) to elucidate contributions of Aβ, age, and other variables to atrophy rates. In 80 CU participants from the Alzheimer's Disease Neuroimaging Initiative, we determined effects of Aβ and age on longitudinal, regional atrophy rates, while accounting for confounding variables including sex, APOE ε4 genotype, white matter lesions, and cerebrospinal fluid total and phosphorylated tau levels. We not only found overlapping patterns of atrophy in Aβ+ versus Aβ- participants but also identified regions where atrophy pattern differed between the 2 groups.

Can Wikipedia Be Used to Derive an Open Clinical Terminology?

Clinical terminologies play an essential role in enabling semantic interoperability between medical records. However, existing terminologies have several issues that impact data quality, such as content gaps and slow updates. In this study we explore the suitability of existing, community-driven resources, specifically Wikipedia, as a potential source to bootstrap an open clinical terminology, in terms of content coverage.