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IntroductionThis 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.MethodsBrain 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+ (N = 23,888). Longitudinal registry completion outcomes were assessed by the completion of the BHR initial questionnaire (first questionnaire participants see at each visit) at least twice and completion of a cognitive assessment (Cogstate Brief Battery) at least twice. Models included ethnocultural identity, education, age, and subjective memory concern as covariates.ResultsWe found that the likelihood of longitudinally completing the initial questionnaire was negatively associated with reporting a diagnosis of ADRD and current psychiatric conditions but was positively associated with reporting substance use/abuse and acquired medical conditions. The likelihood of longitudinally completing the cognitive assessment task was negatively associated with number of reported medical conditions, as well as with reporting cardiovascular conditions, ADRD, and current psychiatric conditions. Previously identified associations between ethnocultural identity and longitudinal assessment completion in BHR remained after accounting for the presence of medical conditions.DiscussionThis post hoc analysis provides novel, initial evidence that older adults' completion of longitudinal assessments in an online registry is associated with the number and types of participant-reported medical conditions. Our findings can inform future efforts to make online studies with longitudinal health and cognitive assessments more usable for older adults with medical conditions. The results need to be interpreted with caution due to selection biases, and the under-inclusion of minoritized communities.

IntroductionThis 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.MethodsThis 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).ResultsIn 12.5 months, 3603 older Latino adults were enrolled (71% of the total California Latino BHR initiative enrollment goal). Completion of all BHR modules was low (6%).DiscussionTargeted ad placement, culturally tailored enrollment messaging, and culturally tailored BHR websites increased enrollment of Latino participants in BHR, but did not translate to increased module completion.HighlightsCulturally tailored social marketing and website improvements were implemented. The efforts enrolled 5662 Latino individuals in 12.5 months. The number of Latino Brain Health Registry (BHR) participants increased by 122.7%. We failed to adequately enroll female Latinos and Latinos with lower education. Future work will evaluate effects of a newly released Spanish-language BHR website.

IntroductionThe objective of this study is to evaluate the reliability and validity of the ReVeReTM word list recall test (RWLRT), which uses speech recognition, when administered remotely and unsupervised.MethodsProspective cohort study. Participants included 249 cognitively intact community dwelling older adults. Measures included clinician administered neuropsychological assessments at baseline and unsupervised remotely administered tests of cognition from six time-points over six months.ResultsThe RWLRT showed acceptable validity. Reliability coefficients varied across time points, with poor reliability between times 1 and 2 and fair-to-good reliability across the remaining five testing sessions. Practice effects were observed with repeated administration as expected.DiscussionUnsupervised computerized tests of cognition, particularly word list learning and memory tests that use speech recognition, have significant potential for large scale early detection and long-term tracking of cognitive decline due to AD.

Hoarding behaviors are positively associated with medical morbidity, however, current prevalence estimates and types of medical conditions associated with hoarding vary. This analysis aims to quantify the medical morbidity of hoarding disorder (HD). Cross-sectional data were collected online using the Brain Health Registry (BHR). Among 20,745 participants who completed the Hoarding and Clutter and Medical History thematic modules, 1348 had HD (6.5%), 1268 had subclinical HD (6.1%), and 18,829 did not meet hoarding criteria (87.4%). Individuals with HD were more likely to report a lifetime history of cardiovascular/metabolic conditions: diabetes (HD adjusted odds ratio (AOR):1.51, 95% confidence interval (CI):[1.20, 1.91]; subclinical HD AOR:1.24, 95% CI:[0.95, 1.61]), and hypercholesterolemia (HD AOR:1.24, 95% CI:[1.06, 1.46]; subclinical HD AOR:1.11, 95% CI:[0.94, 1.31]). Those with HD and subclinical HD were also more to report chronic pain (HD AOR: 1.69, 95% CI:[1.44, 1.98]; subclinical HD AOR: 1.44, 95% CI:[1.22, 1.69]), and sleep apnea (HD AOR: 1.58, 95% CI:[1.31, 1.89]; subclinical HD AOR:1.30, 95% CI:[1.07, 1.58]) than non-HD participants. For most conditions, likelihood of diagnosis did not differ between HD and subclinical HD. Structural equation modeling revealed that more severe hoarding symptomatology was independently associated with increased cardiovascular/metabolic vulnerability. The assessment and management of medical complications in individuals with HD is a fundamental component in improving quality of life, longevity, and overall physical health outcomes.

The Hoarding Rating Scale, Self Report (HRS-SR) is a 5-item assessment developed to ascertain the presence and severity of hoarding symptoms. This study aimed to evaluate the validity of an online adaptation of the HRS-SR in a remote, unsupervised internet sample of 23,214 members of the Brain Health Registry (BHR), an online research registry that evaluates and longitudinally monitors cognition, medical and psychiatric health status. Convergent validity was assessed among a sub-sample of 1,183 participants who completed additional, remote measures of self-reported hoarding behaviors. Structured clinical interviews conducted in-clinic and via video conferencing tools were conducted among 230 BHR participants; ROC curves were plotted to assess the diagnostic performance of the internet-based HRS-SR using best estimate hoarding disorder (HD) diagnoses as the gold standard. The area under the curve indicated near-perfect model accuracy, and was confirmed with 10-fold cross validation. Sensitivity and specificity for distinguishing clinically relevant hoarding were optimized using an HRS-SR total score cut-off of 5. Longitudinal analyses indicated stability of HRS-SR scores over time. Findings indicate that the internet-based HRS-SR is a useful and valid assessment of hoarding symptoms, though additional research using samples with more diverse hoarding behavior is needed to validate optimal cut-off values.

IntroductionAssessment of functional status is associated with risk of cognitive decline and diagnosis of dementia, and can be assessed by participants and study partners (SPs).MethodsIn 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.ResultsWorse 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. SP report of functional decline conferred predictive value independent of online cognitive assessments. Participants underreported decline compared to SPs.DiscussionThe results support the validity of online assessments and their greater utilization in healthcare and research settings. Online SP-reported functional decline is an indicator of dementia and AD risk.

IntroductionThis 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.MethodsUsing 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.ResultsNon-white race, being Latino, and lower educational attainment were associated with decreased task completion and enrollment in additional studies. Results for sex were mixed.DiscussionThe findings provide novel information about engagement in online aging-related registries, and highlight a need to develop improved engagement strategies targeting underrepresented sociodemographic groups. Increasing registry diversity will allow researchers to refer more representative populations to Alzheimer's and related dementias prevention and treatment trials.

IntroductionThis study aimed to predict brain amyloid beta (Aβ) status in older adults using collected information from an online registry focused on cognitive aging.MethodsAβ 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). Cross-validated area under the curve (cAUC) evaluated the predictive performance.ResultsThe best prediction model included age, sex, education, subjective memory concern, family history of Alzheimer's disease, Geriatric Depression Scale Short-Form, self-reported Everyday Cognition, and self-reported cognitive impairment. The cross-validated AUCs ranged from 0.62 to 0.66. This online model could help reduce between 15.2% and 23.7% of unnecessary Aβ PET scans in CU and MCI populations.DisucssionThe findings suggest that a novel, online approach could aid in Aβ prediction.

Objective: The ability to assess cognitive skills remotely is increasing with the widespread use and availability of smartphones. The Mobile Toolbox (MTB) is a measurement system that includes Sequences, a new measure of working memory designed specifically for smartphones. This study describes the development of Sequences and presents the studies conducted to evaluate its psychometric properties. Methods: We developed a new measure of working memory that can be self-administered remotely using an iOS or Android smartphone. In Sequences, a series of numbers and letters are shown on the screen one at a time, and the participant must first tap the letters they see in alphabetical order, followed by tapping the numbers in ascending numerical order. The Sequences measure was evaluated for usability and feasibility across two pilot studies and then assessed in this validation study (which included a total sample size of N = 1,246). Psychometric properties of the new measure were evaluated in three studies involving participants aged 18–90 years. In Study 1 (N = 92), participants completed MTB measures in a laboratory setting. They were also administered both an equivalent NIH Toolbox (NIHTB) measure along with external measures of similar constructs. In Study 2 (N = 1,007), participants were administered NIHTB measures in the laboratory and then completed MTB measures remotely on their own devices. In Study 3 (N = 147), participants completed MTB measures twice, remotely on their own devices, with a 2–week interval between sessions. Results: Sequences exhibited moderately high correlations with a comparable NIHTB test and external measures of a similar construct, while exhibiting a lower correlation with an unrelated test, as hypothesized. Internal consistency was high, but test-retest reliability was moderate. When controlling for age, phone operating system (iOS vs. Android) and sex assigned at birth did not significantly impact performance; however, there was a significant difference between individuals who completed college and those with a high school education or lower. Conclusion: The results support the validity of Sequences as a measure of working memory for remote self-administered use. The internal consistency was strong, with moderate test-retest reliability that is likely a function of the test's unproctored self-administration method. The findings suggest that Sequences is appropriate for use with adults aged 18–90 years in remote self-administered designs that focus on group results. [ABSTRACT FROM AUTHOR]

IntroductionMethods for efficiently identifying cognitive decline and Alzheimer's disease (AD) are a critical unmet need. The goal of this work was to validate novel online study partner (SP)-reported outcomes to identify cognitive decline in older adults.MethodsIn older adults enrolled in the Brain Health Registry, we analyzed associations between SP-reported cognitive decline, measured by the Everyday Cognition Scale, and either (1) participant cognition, assessed by Cogstate Brief Battery or (2) participant-reported diagnosis of mild cognitive impairment or AD.ResultsWe found strong associations between SP-reported Everyday Cognition Scale and both Cogstate scores and participant diagnosis. The associations were cognitive domain specific, dependant on participant diagnosis, and were stronger in spouse dyads and those who knew each other longer.DiscussionCollecting SP-reported data online from a large cohort is feasible. Results support the construct validity of our approach, which has the potential to facilitate clinical AD and aging research.

Background: In Alzheimer's disease research, subjective report of cognitive and functional decline from participant‐study partner (SP) dyads is an efficient method of assessing cognitive impairment and risk of clinical progression. The extent to which discordance (disagreement) between self‐ and SP–report is associated with diagnosis of cognitive impairment is not known. Method: We tested the hypothesis that discordance between baseline self‐ and SP‐report Everyday Cognition Scale (ECog) scores was associated with greater probability of mild cognitive impairment (MCI) diagnosis. Dyads enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the University of California, San Francisco Brain Health Registry (BHR), an online longitudinal aging‐related research registry, completed an online adaptation of the 39‐item ECog to assess subjective change across six cognitive domains. We derived four metrics of discordance between participant and SP ECog scores (dyadic discordance): Raw Score Difference, Absolute Score Difference, Overreport Score, and Underreport Score (Table 1). In the ADNI cohort, we fit a logistic regression model for each of the discordance metrics to independently evaluate their association with MCI diagnosis, after adjusting for dyad relationship and sociodemographic factors. Then, to further evaluate the predictive utility of these measures, we carried out a model selection procedure using cross‐sectional data collected from ADNI dyads (N = 921; Table 1). Finally, we externally validated the model in a BHR cohort with clinically confirmed diagnoses (N = 279; Table 1). Result: Higher Raw and Absolute Score Difference, greater Underreport scores, and lower Overreport scores were associated with greater probability of MCI in the ADNI cohort (Table 2). The model selection procedure identified a number of highly predictive variables, which were then included in a model that was externally validated in the BHR cohort. This model distinguished diagnostic groups in the BHR cohort with AUC = 0.892, Sensitivity = 0.61, Specificity = 0.95 (Figure 1) based on a restricted cubic spline regression model. Conclusion: Results indicate that ECog score discordance is associated with MCI diagnosis. The selected model showcased good predictive performance in the validation cohort, and highlights the potential utility of subjective dyadic discordance metrics to help identify older adults with MCI in diverse settings. [ABSTRACT FROM AUTHOR]

Objective: The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties. Method: MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart. Results: All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability. Conclusions: Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs. [ABSTRACT FROM AUTHOR]

Arranging Pictures is a new episodic memory test based on the NIH Toolbox (NIHTB) Picture Sequence Memory measure and optimized for self-administration on a personal smartphone within the Mobile Toolbox (MTB). We describe evidence from three distinct validation studies. In Study 1, 92 participants self-administered Arranging Pictures on study-provided smartphones in the lab and were administered external measures of similar and dissimilar constructs by trained examiners to assess validity under controlled circumstances. In Study 2, 1,021 participants completed the external measures in the lab and self-administered Arranging Pictures remotely on their personal smartphones to assess validity in real-world contexts. In Study 3, 141 participants self-administered Arranging Pictures remotely twice with a two-week delay on personal iOS smartphones to assess test-retest reliability and practice effects. Internal consistency was good across samples (ρxx =.80 to.85, p <.001). Test-retest reliability was marginal (ICC =.49, p <.001) and there were significant practice effects after a two-week delay (ΔM = 3.21 (95% CI [2.56, 3.88]). As expected, correlations with convergent measures were significant and moderate to large in magnitude (ρ =.44 to.76, p <.001), while correlations with discriminant measures were small (ρ =.23 to.27, p <.05) or nonsignificant. Scores demonstrated significant negative correlations with age (ρ = -.32 to −.21, p <.001). Mean performance was slightly higher in the iOS compared to the Android group (MiOS = 18.80, NiOS = 635; MAndroid = 17.11, NAndroid = 386; t(757.73) = 4.17, p <.001), but device type did not significantly influence the psychometric properties of the measure. Indicators of potential cheating were mixed; average scores were significantly higher in the remote samples (F(2, 850) = 11.415, p <.001), but there were not significantly more perfect scores. The MTB Arranging Pictures measure demonstrated evidence of reliability and validity when self-administered on personal device. Future research should examine the potential for cheating in remote settings and the properties of the measure in clinical samples. [ABSTRACT FROM AUTHOR]

Background: Early identification of deficits in our ability to perceive odors is important as many normal (i.e., aging) and pathological (i.e., sinusitis, viral, neurodegeneration) processes can result in diminished olfactory function. To realistically enable population-level measurements of olfaction, validated olfaction tests must be capable of being administered outside the research laboratory and clinical setting. Aim: The purpose of this study was to determine the feasibility of remotely testing olfactory performance using a test that was developed with funding from the National Institutes of Health as part of a ready-to-use, non-proprietary set of measurements useful for epidemiologic studies (NIH Toolbox Odor ID Test). Materials and methods: Eligible participants older than 39 years and active (within 6 months) in the Brain Health Registry (BHR), an online cognitive assessment platform which connects participants with researchers, were recruited for this study. Interested participants were mailed the NIH Toolbox Odor ID Test along with instructions on accessing a website to record their responses. Data obtained from subjects who performed the test at home was compared to the normative data collected when the NIH Toolbox Odor ID Test was administered by a tester in a research setting and validated against the Smell Identification Test. The age-range and composition of the population ensured we had the ability to observe both age-related decline and gender-related deficits in olfactory ability, as shown in the experimental setting. Results: We observed that age-associated olfactory decline and gender-associated performance was comparable to performance on the administered test. Self-administration of this test showed the age-related loss in olfactory acuity, F(4, 1156)=14.564, p<.0001 as well as higher accuracy for women compared to men after controlling for participants' age, F(1, 1160) = 22.953, p <.0001. The effect size calculated as Hedge's g, was 0.41. Conclusion: These results indicate that the NIH Toolbox Odor ID Test is an appropriate instrument for self-administered assessment of olfactory performance. The ability to self-administer an inexpensive olfactory test increases its utility for inclusion in longitudinal epidemiological studies and when in-person testing is not feasible. [ABSTRACT FROM AUTHOR]

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. RESULTS: A total of 10,494 BHR participants (mean age = 66.9 ± 12.16 standard deviations, 67.4% female) have enrolled study partners (mean age = 64.3 ± 14.3 standard deviations, 49.3% female), including 8987 dyads with a participant 55 years of age or older. Older and more educated study partners were more likely to complete tasks and return for follow‐up. Twenty‐five percent to 27% of older adult participants had self and study partner‐report ECog scores indicating a possible cognitive impairment. DISCUSSION: The BHR Study Partner Portal is a unique digital tool for capturing dyadic data, with high impact applications in the clinical neuroscience and AD fields. Highlights: The Brain Health Registry (BHR) Study Partner Portal is a novel, digital platform of >10,000 dyads.Collection of dyadic online subjective cognitive and functional data is feasible.The portal has good usability as evidenced by positive study partner feedback.The portal is a potential scalable strategy for cognitive impairment screening in older adults. [ABSTRACT FROM AUTHOR]

Background: The Imaging Dementia‐Evidence for Amyloid Scanning (IDEAS) Study collected over 15,000 community‐acquired amyloid‐PET scans, without structural MRI and with different acquisition times, tracers and scanners. Here we describe and validate rPOP (robust PET‐Only Processing), a pipeline for 18F‐Florbetapir (FBP), 18F‐Florbetaben (FBB) and 18F‐Flutemetamol (FLUTE) scans collected in IDEAS. Method: Each image undergoes automatic origin reset to center of mass, spatial normalization based on weighted PET templates (with SPM12) and data‐driven differential smoothing (with AFNI). We received n=740 (514 FBP, 182 FBB, 44 FLUTE) amyloid‐PET scans from the IDEAS–Brain Health Registry substudy (IDEAS‐BHR), with amyloid‐PET local visual reads available for N=663 scans. We performed semi‐quantification via rPOP and estimated neocortical Centiloids after tracer‐specific calibrations using the GAAIN VOIs with whole cerebellum reference. Centiloids were calculated for clinical groups (MCI or dementia), to compare rPOP‐based amyloid‐status (centiloids≥24.4) with visual reads. The pipeline was validated with n=1518 ADNI scans (n=1249 FBP, n=269 FBB), using MRI‐based amyloid‐status as a reference and testing the associations between rPOP‐ and MRI‐based centiloids. Result: rPOP successfully processed N=2233/2258 (98.9%) scans in the first pass, with N=24/25 warping‐related failures rescued with a manual reorientation and origin reset prior to warping. In IDEAS‐BHR, we observed the expected centiloids distribution (Figure 1A‐B) both according to visual reads and also stratifying by clinical stage amyloid‐negative, i.e. mean±sd Centiloids MCI/Dementia: 2±23/‐5±27; amyloid‐positive: MCI/Dementia: 65±42/80±37. There was high concordance (Table 1) between rPOP‐based amyloid status and both local visual reads (IDEAS‐BHR, Cohen's k=0.72 [0.7‐0.74], ∼86% concordance). Very high concordance was also observed in the ADNI dataset (k=0.88 [0.87‐0.89], ∼94% concordance), with rPOP‐ and MRI‐based Centiloids being strongly linearly associated (R2:0.95, p<0.001), with a tighter relationship in images with better resolution (β= ‐0.016, p<0.001). Conclusion: With rPOP, we successfully derived Centiloids quantification from heterogeneous IDEAS amyloid‐PET scans and validated the pipeline with ADNI scans acquired in a research setting. These data show that community‐acquired amyloid‐PET scans can be successfully analyzed, enabling joint efforts by clinical sites and research centers. [ABSTRACT FROM AUTHOR]