bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Social Isolation and Perception of Loneliness in a Group of Chilean Older People post‐pandemic
Authors: Gierke Christine , Navarro Carlos F. , Martinez Melissa , Delgado Carolina , Delano Paul H , Medel Vicente , Leiva Alexis , De Gatica Cristina , Vidal Victor , Martin Simon San , Garcia Ximena , Cerda Mauricio , Vergara Rodrigo C. , Farías Gonzalo 
Published: January 2025

AbstractBackgroundDuring the pandemic, Social Isolation (SI) and the perception of loneliness emerged as critical factors associated with significant psychological and physical impacts (Tyrrell, C. & Williams, N., 2020; González, D., 2021).This study examines gender differences and explores the impact of social isolation and the perception of loneliness on self‐sufficient older people in Santiago, Chile, in the post‐pandemic period (March to November 2022). The focus is on understanding the relationship between these factors and psychiatric symptoms, utilizing specific scales to evaluate these variables.The pandemic introduced three main variables that affected older individuals: the severity of the disease and the fear of contagion; the effects of social isolation, and the perception of vulnerability, which was amplified by the media (NCHS, 2020; CEVE‐UC, 2022; Smith, B. & Lim, M., 2020; Ayalon et al., 2020; Monahan et al., 2020; Vervaeke & Meisner, 2020).MethodA descriptive cross‐sectional study included 150 participants (ages 60‐87). Surveys administered were the Steptoe Social Isolation Index, Three‐Item UCLA Loneliness Scale, Yesavage Geriatric Depression Scale (GDS‐15), current concern about the pandemic (Likert Scale, 1‐10), and gender differences in these variables. JAMOVI software version 2.36 was utilized for data processing and statistical analysis.ResultFrom March to December 2022, 150 older adults were surveyed (Mean = 69.5, Median = 69, SD = 5.93, Variance = 35.11). The sample comprised 68% women and 32% men (Women = 102, Men = 48). Of the variables analyzed, 42% of the sample experienced Social Isolation (Chi‐square = 3.2, p = 0.696 / U = 2395.0, p = 0.825). 26% perceived Loneliness (Chi‐square = 6.10, p = 0.412 / U = 2210.0, p = 0.290), 30% indicated depression (Chi‐square = 7.94, p = 0.848 / U = 2270.0, p = 0.470), and 91% expressed concern about the pandemic (Chi‐square = 0.10, p = 1 / U = 2442, p = 0.980).ConclusionThe results suggest that, although there are no significant gender differences in individual variables, there are significant correlations between all combinations of the variables (Social Isolation, Loneliness, GDS‐15, and Pandemic Concern). Among men, significant correlations were found between Social Isolation and Loneliness (rho = 0.432, p = 0.002), Loneliness and GDS‐15 (rho = 0.299, p = 0.03), and Loneliness and Age (rho = 0.381, p = 0.008). In women, all correlations were significant, except with age, between Social Isolation and Loneliness (rho = 0.419, p≤0.001), Social Isolation and GDS‐15 (rho = 0.279, p = 0.005), and Loneliness and GDS‐15 (rho = 0.474, p≤0.001).
Association between everyday perceived discrimination and cognitive function as mediated by depression in diverse populations: A HABS‐HD Study
Authors: Mendoza Edna Patricia , Nolan Emma , Phillips Nicole , Barber Robert , O'Bryant Sid E. , Zhou Zhengyang 
Published: January 2025

AbstractBackgroundPrevious research suggests that perceived discrimination is associated with cognitive function impairment, and such association is mediated by depression. With minority populations continuously growing, it is crucial to investigate such relationships in diverse populations. This study aims to examine and compare the above relationships among non‐Hispanic white (NHW), Mexican American (MA), and African American (AA) participants.MethodA sample size of 1,129 participants (640 AAs, 248 NHWs, 241 MAs) aged 50+ came from the Health and Aging Brain Study – Health Disparities (HABS‐HD). Multiple linear regression was conducted to explore the direct association between perceived discrimination, measured by the Everyday Discrimination Scale mean score, and cognitive function, measured by the Mini Mental State Examination (MMSE) Score. The mediation effect of depression, measured by the Geriatric Depression Scale total score, was evaluated by the indirect effect estimate and confidence interval through Monte Carlo simulations.ResultEveryday perceived discrimination negatively influenced cognitive function, and the effect was fully mediated by depression across the three populations (estimate for indirect effect = ‐0.16, 95% CI = [‐0.24, ‐0.09]). When stratified, the mediation effect of depression on the association between discrimination and cognitive function remained significant for NHW (estimate for indirect effect = ‐0.37, 95% CI = [‐0.63, ‐0.16]) and MA (estimate for indirect effect = ‐0.42, 95% CI = [‐0.74, ‐0.16]). However, such mediation effect was not observed for the AA population.ConclusionDepression mediates the link between everyday discrimination and cognitive decline, but differences between racial/ethnic groups underscore the need for further research into underlying mechanisms among minority groups, including Mexican American and African American populations. Depression interventions may mitigate negative cognitive effects from discrimination. Tailoring such interventions by race/ethnicity and targeting at‐risk groups could optimally promote cognitive health.
Caregiving experience and service utilization of informal caregivers for community‐living older adults with neurocognitive disorders: preliminary findings in Hong Kong
Authors: Huo Zhaohua , Lee Allen TC , Yip Benjamin HK , Lin Cuichan , Ma Suk Ling , Wong Samuel YS , Lam Linda CW 
Published: January 2025

AbstractBackgroundCaring for people with dementia in communities inevitably brings heavy burden for their family caregivers. Senses of positive aspects from caring and proper service support may help shape a healthy care journey for carers. This study aims to evaluate the caregiving burden, positive aspects, and service utilization of informal caregivers for community‐living older adults with neurocognitive disorders (NCDs).Method448 informal caregivers of older adults aged ≥60 (major NCD/ dementia: 68, mild NCD: 254, normal cognition: 126) were recruited from in a community‐based prevalence survey in Hong Kong. Caregivers’ subjective burden was measured by Zarit Burden Interview (ZBI), while their gain was measured by positive aspect of caregiving scale (PACS). Caregivers’ use of medical and social service was also recorded. Differences in measures across three disease groups were examined by analysis of variance and t‐test. Correlations between measures were estimated by Pearson coefficient.ResultNearly 60% of interviewed carers were female, spouses of care recipients, and not in employment. Over 75% of them cohabited with care recipients and take the major responsibility for caring. Compared to normal controls, carers of major and mild NCD had higher scores in caring burden, and over one in ten dementia carers were suffering moderate to severe degree of burden. Regarding positive aspects, carers of major and mild NCDs also have higher scores, mainly in items of “feel needed”, “feel appreciated”, and “feel important”. As for service utilization, dementia carers used more psychological and home help services. Finally, caring burden was positively correlated to positive gain (r = 0.233, P<0.001), psychological (r = 0.186, P<0.001) and social services (r = 0.146, P<0.001). The sense of positive aspects was uncorrelated to psychological services (r = ‐0.064, P = 0.174) but positively correlated to social services (r = 0.149, P = 0.002).ConclusionInformal caregivers of major and mild NCD are experiencing heavier caring burden. They also have higher sense of positive aspects from caring and more utilization of psychological and social care. Relationships between positive and negative experience of caregivers and their service utilization need further investigations.
Impact of AI‐based segmentation on PET analyses
Authors: Bracoud Luc , Cajgfinger Thomas , Rousset Olivier , Ingalhalikar Madhura , Conklin Chris , Lehmann Manja , Schaerer Joel , Scott David , Suhy Joyce ,   the Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundBrain MRI segmentation is required for quantitative PET analysis, in order to derive regional uptake and calculate uptake ratio relative to reference regions. FreeSurfer has been a popular method but is being supplanted by faster and more robust AI‐driven methods. The objective of this work is to confirm that the use of Clario’s novel AI segmentation method, whose impact was assessed towards various MRI endpoints, is also valid in the context of PET quantification.Method507 subjects from ADNI were selected, including normal controls, subjective memory complainers, early/late MCI and AD subjects. Besides, 210 were selected with available test/re‐test data. For each, a pair of good quality 3DT1 MRI and Amyloid PET scans were available.3DT1 data were segmented with both FreeSurfer v6 (FS) and Clario’s AI method (AI), and registered to PET space for calculation of Standard Uptake Value (SUV) in a set of cortical regions (frontal, posterior cingulate, lateral parietal and lateral temporal) and reference regions (cerebellar grey and whole cerebellum). SUVR (ratio to reference region) was calculated for both. Results were also converted to Centiloid (CL) units.SUV and SUVR values were compared across segmentation methods via Bland‐Altmann plots and correlated with Pearson’s coefficient. The ability to distinguish between disease severity stages was assessed by ROC analysis using global AUC. Finally, classification as amyloid (Aβ) positive or negative was assessed by setting a cut‐off of 20.1 CL and looking at Cohen’s Kappa.ResultsSUV and SUVR values were highly and significantly correlated between FS and AI methods (r>0.99, p<0.001) and for test/re‐test, for all regions investigated, with a difference that did not exceed 0.41% on average (SD<1.38%). Global AUC was comparable for both methods and for test/retest (average gAUC=0.62). Aβ classification was near‐perfect across methods (κ=0.98) and between test/retest data (κFS=0.97, κAI=0.99).ConclusionComparing FreeSurfer and Clario’s AI‐based MRI segmentation method, no impact was found on subsequent PET analyses and test/retest performance was equivalent. These results support the use of either method for PET quantification. For future trials, the AI method could either be used as the primary method, or as a back‐up when traditional FS segmentation fails.
Exploring Neighborhood Level Socioeconomic Status and Volumetric MRI Results in Patients with Memory Impairment
Authors: Stamos Hannah M , Achitoov Mia , Zia Nadia , Sadatsafavi Hessam , Niknejad Bahar , Okhravi Hamid 
Published: January 2025

AbstractBackgroundThis study addresses the impact of neighborhood‐level socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), on individuals with mild cognitive impairment and dementia. Our primary outcome aimed to explore associations between ADI and hippocampal volume in cognitively impaired individuals from a comprehensive memory center.MethodsWe conducted a retrospective, cross‐sectional analysis of patients over 50 from Virginia and North Carolina, with visits between January 1st, 2014, and July 1st, 2022. Normative percentile of hippocampal volume, total hippocampal occupancy scores (HOC), superior lateral ventricular volume, and inferior lateral ventricular volume of patients living in census block groups at the top and bottom 20th ADI percentiles were compared. We fitted a linear regression model on propensity‐matched data in the two ADI groups, with multiple covariates. We performed g‐computation in the matched sample and included the interaction of ADI category with covariates and the matching weights in the estimation.ResultsA total of 310 patients were included in the analysis, with 8% of the subjects in the high‐ADI category. The actual sample size slightly varied for each outcome after excluding missing records, thus full matching was utilized. The estimated average treatment effect for high versus low ADI groups only reached statistical significance for hippocampal volume with the difference of 13.9% (SE = 5.83, p = 0.01). The difference of 0.7% (SE = 2.11, p = 0.75) for HOC, 0.5% (SE = 4.13, p = 0.90) for superior lateral ventricular volume, and ‐0.2% (SE = 7.18, p = 0.90) for inferior lateral ventricular volume were not statistically significant.ConclusionsContrary to expectations, high versus low ADI groups only showed a difference in hippocampal volume, but in the reverse direction. This finding may suggest global effects of the ADI on the brain health, rather than focal effects on hippocampus. Due to the limited size of our sample in the top 20th percentile, further validation of this discovery is necessary through studies employing larger sample sizes.
Changes to Medicare Advantage Risk Adjustment and Dementia Diagnosis in Older Adults
Authors: Haye Sidra , Jacobson Mireille , Joyce Geoffrey , Zissimopoulos Julie M 
Published: January 2025

AbstractBackgroundDiagnosing dementia supports patients’ access to treatment options and social services. The addition of dementia to the risk adjustment model for Medicare Advantage (MA) plan payments, affecting claims beginning in 2019, provided an incentive for MA plans to improve the detection and diagnosis of dementia among their enrollees. The objective of this project is to examine the changes in annual incident dementia diagnoses rates associated with the inclusion of dementia diagnoses in risk adjustment models for Medicare Advantage.MethodsWe conducted a retrospective study using 2017‐2020 data for community‐dwelling beneficiaries enrolled in TM and MA. We estimated difference‐in‐differences (DiD) models to examine changes in incident dementia diagnosis rates in MA relative to TM before and after 2019. The rate of incident dementia diagnosis in each year among beneficiaries without any dementia diagnosis in the year prior to the year of interest.ResultsThere were 84,997,374 beneficiaries. In regression models that adjusted for beneficiary characteristics and time trends, we find that in response to the payment change, the annual incident dementia diagnosis rates in MA increased by about 0.282 percentage points or 11.5% relative to TM. We further find that the increase in incident dementia diagnosis was concentrated among beneficiaries who were more likely to have undiagnosed dementia, specifically, beneficiaries who were Hispanic or Black, who were ages 85 and over, and who were dual‐eligible/low‐income subsidy. Sensitivity analyses excluding 2020 data and allowing beneficiaries to switch between TM and MA during our sample years finds similar results.ConclusionFinancial incentives to detect dementia resulted in more dementia diagnoses, particularly among persons at high risk of dementia and of undetected dementia but also raises concerns about diagnostic upcoding and the potential for over‐diagnosis.
Predicting future Biomarker changes in Alzheimer's Disease, Brain Aging and Comorbidities
Authors: Tassopoulou Vasiliki 
Published: January 2025

AbstractBackgroundThe Spatial Pattern of Abnormality for REcognition of Alzheimer's Disease (SPARE‐AD) index ∖citep{davatzikos2009longitudinal} is one such marker that robustly discriminates between early brain changes observed in cognitively normal aging (CN), mild cognitive impairment (MCI), and Alzheimer's Disease (AD) phenotypes. The adoption of such markers to the clinical setting combined with the ability to forecast their future trajectories would be of great value during clinical assessment, and could improve clinical trial design through targeted risk stratification.MethodSubjects scanned using the same scanner with more than four longitudinal MRI acquisitions from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Baltimore Longitudinal Study of Aging (BLSA) study cohorts were used for method development. T1 structural MRIs were preprocessed and segmented into 145 gray (GM) and white matter (WM) regions of interest (ROIs) using previously described methods. The output of the model is the temporal function of the biomarker score, which in this work is the SPARE‐AD and the SPARE‐BA, seperately. The core of our methodological advancement revolves around the concept that the progression of each biomarker can be represented by a temporal function, f, which is approximated with a Gaussian Process (GP). The learned temporal function is a function of the baseline acquisition of the subject, which means that on inference time, we need only the first scan of the subject so as to get the temporal function of the biomarkerResultThe Temporal Deep Kernel GP (TempDKGP) model achieves higher predictive performance on both SPARE‐AD and SPARE‐BA model. Our model had lower MAE averaged across all participants per K‐fold when compared to ithe LMM. MAEs were also lower when the cohort was subgrouped by their longitudinal cognitive status (i.e., stable vs progression), and by short‐term (less than 5 years ahead of baseline) or long‐term predictions (more than 5 years ahead of baseline). Longitudinal trajectories predicted using baseline features by TempDKGP more closely followed the ground truth trajectories than the LMM as illustrated.ConclusionThe TempDKGP model is a predictive model that extrapolates biomarker trajectories along with uncertainty intervals.
Uptake of Medicare’s Annual Wellness Visit and Cognitive Screening: Evidence of Urban‐Rural Disparity from a National Survey
Authors: Liu Ying , Mattke Soeren 
Published: January 2025

AbstractBackgroundEarly‐stage cognitive impairment remains severely under‐detected. In the U.S., Medicare covers an Annual Wellness Visit (AWV) that includes assessment of cognitive state, but it remains under‐utilized: only 55% of beneficiaries reported having had AWV, of whom only 26% were given a structured cognitive test in 2019. We obtained updated estimates and analyzed association with beneficiary characteristics.MethodWe used a nationally representative survey, the Understanding America Study, to collect data on uptake of AWV and whether the visit included a formal cognitive test or simple questions about memory complaints in December 2023. The survey also collects data on demographics (age, sex, race/ethnicity, education, and yearly household income) and urbanicity of the participant’s residence. Logistic regression was used to predict a beneficiary having an AWV or been probed for cognitive state during the AWV using the beneficiary’s characteristics.ResultTable 1 shows the logistic regression results. Among 1,885 respondents, 81% reported having had an AWV, higher likelihood among older, female, and higher education beneficiaries. During AWV, 51% were probed for their cognitive condition: 31% with formal screening and 35% being asked about subjective memory complaint.Despite no urban‐rural difference in AWV’s uptake (compared to urban residents, Odds Ratio [OR] = 1.29 for rural and OR = 1.04 for mixed, p>0.05), conditional on the uptake, residents of rural (OR = 1.83, p<0.001) and mixed (OR = 1.68, p<0.001) areas were more likely to undergo formal screening than their urban counterparts, with adjusted probabilities of 36% for rural, 34% for mixed, and 24% for urban (Figure 1). Results are similar on being probed about memory complaints.ConclusionAWV uptake is increasing, despite a lesser increase in cognitive screening. Female, older, and higher educated beneficiaries are more likely to use the AWV. The unexpected finding of urban residents being less likely to be probed for cognitive impairment deserves further investigation. Potential explanations include clinicians’ awareness of higher disease burden in rural populations, and greater familiarity with their patients. Also, limited access to specialists could cause clinicians to offer a greater range of diagnostic services themselves and become more experienced in cognitive testing.
The Synergistic Effect of Sleep and Physical Activity on Memory in Cognitively Normal Older Adults
Authors: Callies Lana S. , Chen Coty , Lee Shannon Y. , Diaz Valentina E. , Tucker Miwa , Hallgarth Savannah R. , Lo Carina , VandeBunte Anna M. , Pandher Natalie , Li Esther , Song Felicia , Coppola Quentin , Saloner Rowan , Watson Caitlin Wei‐Ming , Dutt Shubir , Neylan Thomas C. , Kramer Joel H. , Walsh Christine M , Casaletto Kaitlin B. , Paolillo Emily W. 
Published: January 2025

AbstractBackgroundModifiable risk factors are important for prevention of age‐related cognitive decline. Prior research has linked both physical activity (PA) and sleep with better memory outcomes. To better understand their potential synergistic effects, we examined independent and interactive effects of actigraphy‐based PA and total sleep time on cognitive functioning in cognitively unimpaired older adults.MethodParticipants included 40 cognitively unimpaired older adults (age = 71.1 ± 10.8yrs; 52% female; 75% White; mean education = 18.2yrs) enrolled in studies at the UCSF Memory and Aging Center. All participants completed in‐person neuropsychological assessments and 30 days of FitbitTM Inspire 2 monitoring, which tracked average nightly total sleep time and average daily step count. Average sleep time was dichotomized into optimal sleep (6‐8hrs) and sub‐optimal sleep (<6hrs, >8hr) based on previous literature, and average daily step count was dichotomized by median split (high PA ³ 8490 steps). Composite cognitive z‐scores were calculated for memory and executive functioning. Multiple linear regression models examined the interaction between sleep and PA on cognitive domain z‐scores, controlling for age, sex, and education.ResultNeither sleep nor average daily steps were independently related to memory (sleep:b = ‐0.58, 95%CI [‐1.36, 0.20], p = 0.141; steps: b = ‐0.27, 95%CI [‐0.86, 0.32], p = 0.357) or executive functioning (sleep:b = ‐0.68, 95%CI [‐1.46, 0.10], p = 0.087; steps: b = ‐0.21, 95%CI [‐0.82, 0.40], p = 0.487). In combination, however, sleep significantly moderated the effect of PA on memory (b = 1.47, 95%CI [0.03, 2.92], p = 0.046) such that higher PA related to better memory performance only among participants with optimal sleep times. The interaction between PA and sleep on executive functioning was not significant (b = 0.49, 95%CI [‐1.06, 2.03], p = 0.528).ConclusionUsing unobtrusive objective monitoring of modifiable lifestyle factors via wearable actigraphy, we found a beneficial synergistic relationship between sleep and PA on memory. Results highlight the clinical relevance of supporting multi‐domain improvements in modifiable lifestyle factors, including optimal sleep time and higher PA in older adults.