Online platforms are an 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 Brain Health Registry (BHR), an online registry for neuroscience research. From the BHR database, we included participants aged 55+ who completed both the baseline ECog and repeated administrations of the CANTAB® Paired Associates Learning (PAL) test. Both self-reported ECog (Self-ECog) and study partner ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We used multiple ECog scoring outputs, based on previously established cut-offs for likely impairment (Self-ECog positive [total score ≥1.31], SP-ECog positive [total score ≥1.36], and ECog consistent [any item≥3]). A linear mixed effects model was employed to assess the effect of baseline ECog on longitudinal change in PAL. Additionally, logistic regression models were used to assess the ability of ECog to identify ‘decliners’, who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below. The study included a total of 16,683 participants, who were followed for 11.49±11.53 months. Both Self-ECog positive (estimate = -0.01, p <0.0019) and Self-ECog consistent (estimate = -0.008, p <0.0085) were significant predictors for longitudinal change in PAL FAMS after adjusting for age, gender, education, race, depression, family history of Alzheimer’s disease (AD), taking AD medication, and self-reported impairment. Those who were SP-ECog positive (Odds ratio [95% confidence interval] = 1.760 [1.143–2.667]) and SP-ECog consistent (2.021 [1.344–3.021]) had higher probability of being decliners based on PAL FAMS. Regarding the prediction of PAL TEA decliner, both Self-ECog consistent (1.248 [1.043–1.494]) and Self-ECog total (1.287 [1.054–1.557]) were associated with higher odds of being decliners. In the BHR’s unsupervised online setting, ECog demonstrated utility in predicting longitudinal progression in PAL scores, both in terms of continuous changes and when dichotomized as a decliner. Online, self-administered measures of subjective cognitive change, together with objective neuropsychological test results have great potential to identify individuals with cognitive impairments.

Abstract 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. Both self-reported ECog (Self-ECog) and study partner-reported ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We estimated associations between multiple ECog scoring outputs (ECog positive [same or above cut-off score], ECog consistent [report of consistent decline in any item], and total score) and longitudinal change in PAL. Additionally we assessed the ability of ECog to identify ‘decliners’, who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below. Results Participants (n = 16,683) had an average age of 69.07 ± 7.34, 72.04% were female, and had an average of 16.66 ± 2.26 years of education. They were followed for an average of 2.52 ± 1.63 visits over a period of 11.49 ± 11.53 months. Both Self-ECog positive (estimate = -0.01, p < 0.001, R²m = 0.56) and Self-ECog consistent (estimate=-0.01, p = 0.002, R²m = 0.56) were associated with longitudinal change in PAL FAMS after adjusting demographics and clinical confounders. Those who were Self-ECog total (Odds ratio [95% confidence interval] = 1.390 [1.121–1.708]) and SP-ECog consistent (2.417 [1.591–3.655]) had higher probability of being decliners based on PAL FAMS. Conclusion In the BHR’s unsupervised online setting, baseline subjective change was feasible in predicting longitudinal decline in neuropsychological tests. Online, self-administered measures of subjective cognitive change might have a potential to predict objective subjective change and identify individuals with cognitive impairments.

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. 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). 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. 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.

Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.

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+ (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. RESULTS:We 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. DISCUSSION:This 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.

Scalable tools to efficiently identify individuals likely to have cognitive impairment (CI) are critical in the Alzheimer’s disease and related dementias field. The Everyday Cognition scale (ECog) and its short form (ECog12) assess subjective cognitive and functional changes and are useful in predicting CI. This study aimed to compare the ability of the online ECog and the in-clinic ECog in distinguishing between CI and cognitively unimpaired (CU) individuals, and to evaluate the effectiveness of the ECog12 compared to the full ECog in an online setting. Participants were recruited from the Brain Health Registry (BHR; online) and Alzheimer’s Disease Neuroimaging Initiative (ADNI; in-clinic) with available clinical diagnoses. Ability of ECog and ECog12 (Self- and study partner [SP]-ECog) to discriminate CI from CU were calculated using Receiver Operating Characteristic (ROC) curves. Area under the ROC curves (AUCs) between BHR and ADNI were compared using the DeLong test, as were AUCs between ECog12 and ECog in BHR. Both online and in-clinic ECog effectively discriminated CI from CU, with no significant differences in AUCs (BHR Self-ECog AUC = 0.722 vs. ADNI Self-ECog AUC = 0.769, DeLong P = .06; BHR SP-ECog AUC = 0.818 vs. ADNI SP-ECog AUC = 0.840, DeLong P = .50). Comparison between online ECog and ECog12 showed no significant differences in AUCs (Self-ECog AUC = 0.722 vs. Self-ECog12 AUC = 0.709, DeLong P = .18). Online ECog, including the short-form ECog12, is as valid as in-clinic ECog for identifying clinically diagnosed CI, offering a cost-effective and accessible screening tool for large-scale online studies for identifying potential candidates for disease-modifying therapy.

INTRODUCTION:Remote, internet-based methods for recruitment, screening, and longitudinally assessing older adults have the potential to facilitate Alzheimer's disease (AD) clinical trials and observational studies. METHODS:The Brain Health Registry (BHR) is an online registry that includes longitudinal assessments including self- and study partner-report questionnaires and neuropsychological tests. New initiatives aim to increase inclusion and engagement of commonly underincluded communities using digital, community-engaged research strategies. New features include multilingual support and biofluid collection capabilities. RESULTS:BHR includes > 100,000 participants. BHR has made over 259,000 referrals resulting in 25,997 participants enrolled in 30 aging and AD studies. In addition, 28,278 participants are coenrolled in BHR and other studies with data linkage among studies. Data have been shared with 28 investigators. Recent efforts have facilitated the enrollment and engagement of underincluded ethnocultural communities. DISCUSSION:The major advantages of the BHR approach are scalability and accessibility. Challenges include compliance, retention, cohort diversity, and generalizability. HIGHLIGHTS:Brain Health Registry (BHR) is an online, longitudinal platform of > 100,000 members. BHR made > 259,000 referrals, which enrolled 25,997 participants in 32 studies. New efforts increased enrollment and engagement of underincluded communities in BHR. The major advantages of the BHR approach are scalability and accessibility. BHR provides a unique adjunct for clinical neuroscience research.

The aim of this study was to evaluate the feasibility and usability of collecting data from an unsupervised online version of the Paired Associates Learning (PAL) task from the Cambridge Neuropsychological Test Automated Battery (CANTAB™) in adults enrolled in the Brain Health Registry (BHR). BHR is an online cognitive aging registry for referral and longitudinal unsupervised assessment. The PAL assesses visual associative learning and memory and was administered in BHR between 03/2021-07/2022. PAL variables included in this analysis were ‘Memory Score’ (patterns correctly identified at first attempt for each difficulty level) and ‘Total Errors’, adjusted for level reached. We analyzed PAL task completion rate and characteristics of PAL completers and used linear regressions to assess whether cross-sectional PAL Memory Score and PAL Total Errors were associated with participant data (age, gender, education, self- and study partner-reported cognitive complaints (Everyday Cognition scale (ECog)), self-reported memory concern, and self-reported depressive symptom severity (PHQ-9), self-report of Mild Cognitive Impairment (MCI)). As of July 2022, 14,520 participants aged 18+ years have completed PAL at least once. Participants were on average 66.3 years old (SD = 11.3), 72.4% female gender, 92.8% self-identified as White, and had a mean of 16.6 years of education (SD = 2.27). BHR received 374 requests for study support regarding PAL, of which 36% (135) were related to device compatibility. Mean PAL scores were similar to those of previous, supervised studies (Figure 1). Worse PAL performance was significantly associated with being older, female gender, having less education, more self- and study partner-reported ECog, self-reported memory concern, more depressive symptoms, and self-report of MCI (Table 1). Our findings provide evidence for the feasibility of collecting PAL data in an unsupervised online setting and construct validity of cross-sectional BHR PAL. In terms of usability, there was a minimal need for support. Future studies will investigate the predictive value of BHR PAL in identifying adults with self-reported MCI, longitudinal BHR PAL performance and associations with in-clinic assessments and Alzheimer’s disease biomarkers. Our sample lacked diversity. Therefore, a future direction is to increase accessibility of PAL to ethnoculturally and socioeconomically diverse communities.

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.Methods: Participants included 23,594 adults completing objective and subjective measures of cognition on an online research registry. Linear regression including interactions of age group with depression was used to evaluate the association of self-reported MDD with measures of cognition in three age groups: 21-40 years; 41-60 years; 61+ years.Results: MDD (n = 2127) demonstrated poorer objective cognitive performance and greater subjective ratings of cognitive difficulties across all domains assessed compared to non-depressed individuals (ND; n = 21,467). Significant interactions of age group and MDD status with objective and subjective measures of cognition were observed for both middle age and older adults when compared to young adults but few significant differences between middle-aged and older adults were evident.Limitations: This study relied on self-report of MDD diagnosis, utilized remotely administered and unsupervised measures of cognition, and the sample was not diverse.Conclusions: The magnitude of association between MDD and cognitive correlates appears to plateau in middle age. Our results suggest that increased rates of dementia are not due to greater cognitive consequence of MDD in older adults and that age effects, and not greater effects of depression, may lead to increased diagnosis of MDD based on subjective report of cognitive symptoms.

BACKGROUND: Hoarding disorder is a chronic psychiatric condition of increasing public health concern. Recent investigation suggests a positive association between hoarding severity and insomnia symptoms. However, these findings have yet to be replicated, and the prevalence and type of sleep impairment experienced by individuals with clinically relevant hoarding symptoms (CHSs) are not known.METHODS: This analysis of 20,473 members of the internet-based Brain Health Registry uses multivariate logistic regression modeling and structural equation modeling to evaluate the relationship between hoarding symptoms, sleep impairment, adverse health, and cognitive functioning.RESULTS: More than 12% of study participants endorsed CHSs or subclinical hoarding symptoms. After adjustment for demographic characteristics and psychiatric comorbidity, individuals with CHSs reported increased odds of sleep impairment in nearly all domains. The odds of poor sleep quality (adjusted odds ratio, 2.07; 95% CI, 1.83-2.34), sleep disturbances (adjusted odds ratio, 2.15; 95% CI, 1.91-2.43), and daytime dysfunction (adjusted odds ratio, 5.84; 95% CI, 5.12-6.65) were two- to fivefold higher for individuals with CHSs compared with those without. For all measures, the proportion of individuals reporting sleep impairment increased with hoarding severity. In our structural equation model, sleep impairment acted as a partial mediator on the indirect pathways from hoarding to subjective cognitive complaints and poorer quality of life. CONCLUSIONS: Identification of sleep problems among those with hoarding symptoms is a critical component of hoarding assessment. Additional research is needed to better understand the mechanisms underlying the observed relationships, including neurobiological underpinnings, and to examine the role of sleep management in treatment for hoarding behaviors.

Remote, internet-based methods for recruitment, screening, and longitudinally assessing older adults have the potential to greatly facilitate Alzheimer’s disease and related research, including clinical trials and observational studies. The Brain Health Registry (BHR) is an online website and registry that includes a comprehensive battery of self- and study partner-report questionnaires and online neuropsychological tests. Participants are asked to return at 6-month intervals for longitudinal follow-up. Recently, new online infrastructure for managing remote biomarker (saliva, blood) collection and for linking in-clinic and online data were added. Multiple current initiatives aim to increase recruitment and engagement of underrepresented populations using digital, community engaged research strategies to improve generalizability of results. These include the recent launch of a Spanish-language website, and projects focused on increasing enrollment and task completion of Black/African American and Hispanic/Latinx individuals. BHR includes >95,000 participants, >9000 of whom have enrolled study partners, 40% return for longitudinal follow up, 64% are age 55+, 80% are female, 80% identify as Non-Latinx White, and 10% identify as Hispanic/Latinx. Participants have an average of 16.2 years of education. BHR has made >86,000 referrals to other studies, resulting in >5000 BHR participants enrolled in 25 different aging and AD observational studies and treatment trials. Over 2400 participants are co-enrolled in BHR and collaborator studies, with online data linked to in-clinic data. 573 participants have undergone APOE genotyping using remote saliva collection, and 629 have had blood collected using local phlebotomy for AD plasma biomarker analysis. Accumulating evidence supports the feasibility and validity of the approach, including associations with in-clinic assessments, the ability to accurately detect MCI and enrichment for amyloid positivity. Major advantages of the BHR approach are scalability and accessibility. Challenges include compliance, retention, and cohort diversity. Lessons learned from BHR, and components of the existing infrastructure, can be used to inform future remote clinical trial design. One such future effort is ADNI4. To facilitate enrollment of new participants, ADNI4 will establish an online recruitment and screening portal, with a remote phlebotomy component, to efficiently identify those from underrepresented populations, and those likely to have preclinical and prodromal AD.

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. Results Of 7150 participants invited to the study, 864 (12%) enrolled and 629 (73%) completed remote blood draws. Participants reported high study acceptability. Those from underrepresented ethnocultural and educational groups were less likely to participate. Discussion This study demonstrates the challenges of remote blood collection from a large representative sample of older adults. Remote blood collection from > 600 participants within a short timeframe demonstrates the feasibility of our approach, which can be expanded for efficient collection of plasma AD biomarker and genetic data.

Research registries focused on brain diseases, such as Alzheimer’s disease and related dementias (ADRD), have been developed to accelerate clinical study recruitment. Completion of registry components can affect the representativeness of registry populations and data, especially where retention is critical. This study aims to provide insights for online research and retention by studying participants’ perceptions of the Brain Health Registry (BHR), with a focus on those from different ethnocultural and socioeconomic backgrounds. BHR is a public online registry for recruitment and longitudinal assessment focused on cognitive aging and ADRD research. Participants can provide feedback to the study team about their overall experience at any time using a questionnaire and are asked to complete feedback questionnaires after completing the Cogstate Brief Battery (CBB) (Table 1). Multivariable ordinal logistic regression estimated associations between sociodemographic characteristics (ethnocultural identity and education attainment) and feedback responses. All analyses covaried for age and gender. Of all participants (N = 89,673), 5,469 (6.1%) provided feedback about their overall BHR experience and 14,676 (16.4%) provided feedback about CBB (Table 2). See Table 3 for associations between sociodemographic characteristics and feedback responses. Identifying as Latino was associated with a poorer experience with the cognitive assessment. Identifying as Latino or non-White was associated with perceiving the cognitive assessment instructions as less clear and rating that additional help for cognitive assessment instructions would be useful. Higher educational attainment was associated with perceiving BHR site as easier to use and the instructions as clearer, as well as rating additional help for cognitive assessment instructions as less useful. Our findings highlight the need to improve and/or tailor online cognitive assessment design and instructions to better suit the needs of diverse ethnocultural and educational populations. More research is needed to deepen insight into improvements in cognitive assessment design to facilitate engagement and retention of diverse populations.

Background Hoarding symptoms are associated with functional impairment, though investigation of disability among individuals with hoarding disorder has largely focused on clutter-related impairment to home management activities and difficulties using space because of clutter. This analysis assesses disability among individuals with hoarding symptoms in multiple domains of everyday functioning, including cognition, mobility, self-care, interpersonal and community-level interactions, and home management. The magnitude of the association between hoarding and disability was compared to that of medical and psychiatric disorders with documented high disability burden, including major depressive disorder (MDD), diabetes, and chronic pain. Methods Data were cross-sectionally collected from 16,312 adult participants enrolled in an internet-based research registry, the Brain Health Registry. Pearson's chi-square tests and multivariable logistic regression models were used to quantify the relationship between hoarding and functional ability relative to MDD, diabetes, and chronic pain. Results More than one in ten participants endorsed clinical (5.7%) or subclinical (5.7%) hoarding symptoms (CHS and SCHS, respectively). After adjusting for participant demographic characteristics and psychiatric and medical comorbidity, CHS and SCHS were associated with increased odds of impairment in all domains of functioning. Moderate to extreme impairment was endorsed more frequently by those with CHS or SCHS compared to those with self-reported MDD, diabetes, and/or chronic pain in nearly all domains (e.g., difficulty with day-to-day work or school: CHS: 18.7% vs. MDD: 11.8%, p < 0.0001) except mobility and self-care. While those with current depressive symptoms endorsed higher rates of impairment than those with hoarding symptoms, disability was most prevalent among those endorsing both hoarding and comorbid depressive symptoms. Conclusions Hoarding symptoms are associated with profound disability in all domains of functioning. The burden of hoarding is comparable to that of other medical and psychiatric illnesses with known high rates of functional impairment. Future studies should examine the directionality and underlying causality of the observed associations, and possibly identify target interventions to minimize impairment associated with hoarding symptomatology.

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).RESULTS:In 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%).DISCUSSION:Targeted 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.HIGHLIGHTS:Culturally 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.

Hoarding disorder often results in debilitating functional impairment and may also compromise health-related quality of life (QoL). This study investigated the association between hoarding behavior and QoL relative to six highly impairing medical and psychiatric disorders in a sample of 20,722 participants enrolled in the internetbased Brain Health Registry. Nearly 1 in 8 participants (12.2%) endorsed clinically relevant hoarding symptoms (CHS). In separate multivariable linear regression models, hoarding was more strongly associated with mental QoL than diabetes (Standardized beta =-0.21, 95% CI: [-0.22,-0.20] vs.-0.01 [-0.02, 0.0]), heart disease (-0.22 [-0.23,-0.20] vs. 0.00 [-0.02, 0.01]), chronic pain (-0.18 [-0.19,-0.16] vs.-0.12 [-0.13,-0.10]), post traumatic stress disorder (PTSD;-0.20 [-0.22,-0.19] vs.-0.07 [-0.09,-0.06]), and substance use disorder (SUD;-0.21 [-0.23,-0.20] vs.-0.04 [-0.05,-0.03]). Similarly, CHS was more strongly negatively associated with physical QoL than diabetes (-0.11 [-0.10,-0.12] vs.-0.08 [-0.06,-0.09]), major depressive disorder mental (Standardized beta =-0.28, Delta R2 = 0.08, p < 0.0001) and physical (beta =-0.12, Delta R2 = 0.02, p < 0.0001) QoL, though the strength of the relationship between hoarding symptoms and QoL varied with depression severity. Efforts to improve the overall QoL and well-being of those with CHS are needed.

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.

Abstract 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. Results Non‐white race, being Latino, and lower educational attainment were associated with decreased task completion and enrollment in additional studies. Results for sex were mixed. Discussion The 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.