Journals of Gerontology Series B-Psychological Sciences and Social Sciences最新文献

{"title":"Loneliness and Biomarkers of Alzheimer's Disease, Axonal Damage, and Astrogliosis: A Coordinated Analysis of Two Longitudinal Cohorts.","authors":"Antonio Terracciano, Keenan A Walker, Yang An, Murat Bilgel, Angelina R Sutin, Martina Luchetti, Selin Karakose, Yannick Stephan, Kaj Blennow, Henrik Zetterberg, Nicholas J Ashton, Thomas K Karikari, Przemysław R Kac, Abhay R Moghekar, Madhav Thambisetty, Luigi Ferrucci, Susan M Resnick","doi":"10.1093/geronb/gbaf006","DOIUrl":"10.1093/geronb/gbaf006","url":null,"abstract":"<p><strong>Objectives: </strong>Loneliness is associated with an elevated risk of dementia. There is mixed evidence from imaging studies on whether loneliness is associated with neuropathology in dementia-free adults. This study tests whether loneliness is associated with plasma neurobiomarkers of amyloid (Aβ42/Aβ40), phosphorylated tau 181 (pTau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) and imaging measures of amyloid and tau.</p><p><strong>Methods: </strong>Participants were cognitively unimpaired older adults from the Baltimore Longitudinal Study on Aging (BLSA; N = 1,028 individuals and up to 2,277 neurobiomarker measurements; Baseline mean age = 66, SD = 15 years) and the UK Biobank (N = 1,263 individuals and up to 2,526 neurobiomarker measurements; Baseline mean age = 60, SD = 7 years). Single-item measures of loneliness and the Quanterix Single Molecule Array assays were used in both samples. In a subset of BLSA participants, positron emission tomography (PET) was used to assess cerebral amyloid burden (n = 220) and tau in the entorhinal cortex (n = 102).</p><p><strong>Results: </strong>In both samples and meta-analyses, loneliness was unrelated to plasma measures of Aβ42/Aβ40, pTau181, NfL, and GFAP. Changes in loneliness were also unrelated to changes in the plasma neurobiomarkers, and no consistent evidence of moderation by age, sex, or APOE ε4 allele was found. Loneliness was also unrelated to PET-based measures of amyloid and tau.</p><p><strong>Discussion: </strong>This study found no associations between loneliness and measures of Alzheimer's disease pathology, axonal damage, or astrogliosis.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mindfulness Interventions in Older Adults for Mental Health and Well-Being: A Meta-Analysis.","authors":"Paul Verhaeghen, Shelley N Aikman, Grazia Mirabito","doi":"10.1093/geronb/gbae205","DOIUrl":"10.1093/geronb/gbae205","url":null,"abstract":"<p><strong>Objectives: </strong>Mindfulness interventions are consistently associated with beneficial effects in younger adults. In this meta-analysis, we seek to quantify the effectiveness of mindfulness interventions for the mental health and well-being of older adults.</p><p><strong>Methods: </strong>We include 46 studies that implemented a mindfulness intervention (MBSR = 20; MBCT = 9; ad hoc protocol = 17) with older adults (samples with an average age of 60 or older; healthy adults = 20; adults with underlying symptoms = 26), examining a wide range of outcome measures (e.g., stress, quality of life, sleep).</p><p><strong>Results: </strong>Mindfulness interventions in older adults yielded an estimated Hedges' g of 0.25. Moderator analyses revealed three significant effects. Type of intervention mattered, with the effect size for MBSR not significantly different from zero (Hedges' g = 0.12) while the effect sizes for MBCT (Hedges' g = 0.33) and \"other\" interventions (Hedges' g = 0.36) were. Outcome measure mattered, with significant beneficial effect sizes for mental functioning (Hedges' g = 0.59), depression (Hedges' g = 0.35), sleep (Hedges' g = 0.39), anxiety (Hedges' g = 0.32), \"other\" (Hedges' g = 0.24), stress (Hedges' g = 0.22) and mindfulness (Hedges' g = 0.23). Finally, whether the outcome was targeted (e.g., measures of depression in a population suffering from major depressive disorder) mattered: variables that measured targeted outcomes yielded stronger effects (Hedges' g = 0.30).</p><p><strong>Discussion: </strong>Mindfulness interventions with older adults are effective, but modestly so. The extant literature is limited by reliance on modified interventions that have not been evaluated for effectiveness.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Childhood Adversities, Midlife Health, and Elder Abuse Victimization: A Longitudinal Analysis Based on Cumulative Disadvantage Theory.","authors":"","doi":"10.1093/geronb/gbaf047","DOIUrl":"https://doi.org/10.1093/geronb/gbaf047","url":null,"abstract":"","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":"80 4","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Childhood Adversity on Late-Life Cognition in Older Puerto Rican Adults.","authors":"James Lian, Michael Crowe, Kaarin J Anstey, Kim M Kiely, Ana Luisa Dávila, Ross Andel","doi":"10.1093/geronb/gbae199","DOIUrl":"10.1093/geronb/gbae199","url":null,"abstract":"<p><strong>Objectives: </strong>This study examined the association between childhood adversity and late-life cognitive outcomes among older Puerto Rican adults.</p><p><strong>Methods: </strong>Data were from the Puerto Rican Elder: Health Conditions study, a population-based cohort of 3,713 older Puerto Rican adults (mean age 72.5 years; 60% female). Adverse childhood experiences were categorized into four factors: economic hardship, parental illiteracy, childhood illness, and neighborhood disadvantage. Cognition was assessed with the Mini-Mental Cabán (MMC). For our analyses, cognitive impairment was defined as scoring 1.5 standard deviations below the expected score, adjusted for age, sex, education, and reading ability. Ordinal logistic regression (baseline) and generalized linear mixed models (all 3 waves) analyzed MMC scores; generalized estimating equations assessed incident cognitive impairment (Waves 2 and 3).</p><p><strong>Results: </strong>All four adversity factors were associated with poorer MMC scores at baseline. Parental illiteracy (β = -0.35, p < .001) and neighborhood disadvantage (β = -0.27, p < .001) showed stronger associations than economic hardship (β = -0.10, p = .003) and childhood illness (β = -0.21, p < .001). No factors were significantly related to changes in cognitive scores over time. Depressive symptoms and self-rated health partially mediated cross-sectional relationships, with depressive symptoms showing a stronger effect. All adversity factors except economic hardship were linked to baseline cognitive impairment (OR = 1.42 parent illiteracy, OR = 1.24 childhood illness, OR = 1.82 neighborhood disadvantage, p < .05). Only neighborhood disadvantage was associated with incident cognitive impairment (OR = 1.19, p = .003).</p><p><strong>Discussion: </strong>This study highlights the lasting effect of childhood adversity on late-life cognitive health among older Puerto Ricans, suggesting that addressing early adversity may promote cognitive health later in life.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Connectedness in Older Adults: The Potential of Social Internet Use to Maintain a Strong and Stable Personal Network.","authors":"Jeroen H M Janssen, Theo G van Tilburg, Erik J van Ingen, Rense Corten, G M E E Geeske Peeters","doi":"10.1093/geronb/gbaf014","DOIUrl":"10.1093/geronb/gbaf014","url":null,"abstract":"<p><strong>Objectives: </strong>Maintaining a strong social network in later life can be challenging due to limited resources, life events, and changes in health. Social internet use provides an accessible way for communication that is less susceptible to age-related challenges. Although social internet use is increasingly used by older adults, we do not know how social internet use shapes older adults' offline networks. The purpose of this study is to examine whether social internet use can help maintain strong social relationships.</p><p><strong>Methods: </strong>We used data from 3 waves (2012-2013, 2015-2016, and 2018-2019) of the Longitudinal Aging Study Amsterdam. Our sample included 2,266 older adults aged 55-99 (mean = 68.2 years, 54% female). We included the frequency of social internet use and computed personal network size, contact frequency, and the number of continued, gained, and lost ties over time. Hybrid models were applied to disentangle between within- and between-person associations.</p><p><strong>Results: </strong>More frequent social internet users had significantly larger personal networks and, relative to the previous wave, more continued and gained network ties, compared to less frequent social internet users. A within-person increase in social internet use over time was associated with more continued and gained ties.</p><p><strong>Discussion: </strong>Social internet use may help maintain a strong and stable network, which is important for social connectedness in later life. It allows for additional interaction opportunities, as well as network maintenance and growth. Social internet use thus proves to be a valuable addition to the social interaction resources of older adults.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143043519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards AI-Driven Precision Measurement of Cognition, Behavior, and Psychological Function in Aging and AD/ADRD.","authors":"Luke E Stoeckel, Dinesh John, Matthew Sutterer","doi":"10.1093/geronb/gbaf045","DOIUrl":"https://doi.org/10.1093/geronb/gbaf045","url":null,"abstract":"<p><p>The National Institute on Aging (NIA) is at the forefront of leveraging advances in artificial intelligence (AI) to better understanding of aging and the diagnosis and treatment of Alzheimer's Disease (AD) and Alzheimer's Disease-Related Dementias (ADRD). Recent NIA-supported projects have highlighted the transformative potential of AI, digital health, and computational approaches in improving the modeling, detection, and monitoring of changes in healthy aging and AD/ADRD. This perspective is forward looking, emphasizing key areas and efforts in AI-driven precision measurement in cognition, behavior, and psychological function.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering key features of social resilience versus social vulnerability in later life: A biopsychosocial model of social asymmetry.","authors":"Hai-Xin Jiang, Jing Yu","doi":"10.1093/geronb/gbaf046","DOIUrl":"https://doi.org/10.1093/geronb/gbaf046","url":null,"abstract":"<p><strong>Objectives: </strong>Confronted with shrinking social networks, older adults exhibit individual differences in social adaptability, reflected as socially resilient versus socially vulnerable. The purpose of this study was to examine key features that reflect this social asymmetry in later life.</p><p><strong>Methods: </strong>Three datasets were analyzed, with the training set (N = 424) included older adults from China, while two test sets (N1 = 2877, N2 = 2343) were from the United States. Social asymmetry was assessed using residuals from a regression of social network on loneliness, with individuals with positive residuals categorized as socially vulnerable and those with negative residuals as socially resilient. Feature selection was performed with the Boruta algorithm, model building with the gradient boosting machine (GBM) algorithm, and model interpretation with the local interpretable model-agnostic explanations (LIME) algorithm.</p><p><strong>Results: </strong>Socially resilient older adults were more prevalent than socially vulnerable ones across datasets from various cultural backgrounds. Five key features-depression, anxiety, stress, sleep disturbance, and personality-were found to predict social asymmetry, with area under the curve (AUC) values ranging from 0.76-0.86 across datasets. Older adults with lower levels of depression, anxiety, stress, and sleep disturbance, and typical A or B (versus intermediate) personality, were more likely to be socially resilient.</p><p><strong>Discussion: </strong>The prevalence of socially resilient older adults indicates a relatively positive trend, and most of the key features are plastic and amenable, such as negative emotions and sleep behavior. Developing emotional regulation strategies and providing sleep hygiene education could improve the social adaptability of older adults.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Machine Learning and Environmental and Genetic Risk Factors for the Early Detection of Preclinical Alzheimer's Disease.","authors":"Noor Al-Hammadi, Mahmoud Abouelyazid, David C Brown, Pooja Lalwani, Hannes Devos, David B Carr, Ganesh M Babulal","doi":"10.1093/geronb/gbaf023","DOIUrl":"https://doi.org/10.1093/geronb/gbaf023","url":null,"abstract":"<p><strong>Objective: </strong>This study classified preclinical Alzheimer's disease (AD) using cognitive screening, neighborhood deprivation via the Area Deprivation Index (ADI), and sociodemographic and genetic risk factors. Additionally, it compared the predictive accuracy of multiple machine learning algorithms and examined model performance with two bootstrapping procedures.</p><p><strong>Methods: </strong>Data were drawn from a longitudinal cohort that required participants to be age 65 or older, cognitively normal at baseline, and active drivers, defined as taking at least one trip a week. Naturalistic driving data were collected using a commercial datalogger. Biomarker positivity was determined via amyloid pathology using cerebrospinal fluid and positron emission tomography imaging. ADI was captured based on geocoding latitude and longitude to derive a national ranking for the specific location (home or unique destination). Machine learning algorithms classified preclinical AD. Each individual model's predictive ability was confirmed in a 20% testing dataset with 100 rounds of resampling with and without replacement.</p><p><strong>Results: </strong>Among 292 participants (n = 2,792 observations), including ADI of trip destinations, participants' home ADI, and frequency of trips to the same ADI led to a slight but notable improvement in predicting preclinical AD. The ensemble model demonstrated superior predictive performance, highlighting the potential of integrating multiple models for early AD detection.</p><p><strong>Discussion: </strong>Our findings underscore the importance of incorporating socioeconomic and environmental variables, such as neighborhood deprivation, in predicting preclinical AD. Addressing socioeconomic disparities through public health strategies is crucial for mitigating AD risk and enhancing the quality of life for older adults.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational phenotyping of cognitive decline with retest learning.","authors":"Zita Oravecz, Joachim Vandekerckhove, Jonathan G Hakun, Sharon H Kim, Mindy J Katz, Cuiling Wang, Richard B Lipton, Carol A Derby, Nelson A Roque, Martin J Sliwinski","doi":"10.1093/geronb/gbaf030","DOIUrl":"10.1093/geronb/gbaf030","url":null,"abstract":"<p><strong>Objectives: </strong>Cognitive change is a complex phenomenon encompassing both retest-related performance gains and potential cognitive decline. Disentangling these dynamics is necessary for effective tracking of subtle cognitive change and risk factors for Alzheimer's Disease and Related Dementias (ADRD).</p><p><strong>Method: </strong>We applied a computational cognitive model of learning and forgetting to data from Einstein Aging Study (EAS; n = 316). EAS participants completed multiple bursts of ultra-brief, high-frequency cognitive assessments on smartphones. Analyzing response time data from a measure of visual short-term working memory, the Color Shapes task, and from a measure of processing speed, the Symbol Search task, we extracted several key cognitive markers: short-term intraindividual variability in performance, within-burst retest learning and asymptotic (peak) performance, across-burst change in asymptote and forgetting of retest gains.</p><p><strong>Results: </strong>Asymptotic performance was related to both mild cognitive impairment (MCI) and age, and there was evidence of asymptotic slowing over time. Long-term forgetting, learning rate, and within-person variability uniquely signified MCI, irrespective of age.</p><p><strong>Discussion: </strong>Computational cognitive markers hold promise as sensitive and specific indicators of preclinical cognitive change, aiding risk identification and targeted interventions.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights into the Heterogeneity of Cognitive Aging: A Comparative Analysis of Two Data-Driven Clustering Algorithms.","authors":"Truc Nguyen, Yu-Ling Chang","doi":"10.1093/geronb/gbaf022","DOIUrl":"https://doi.org/10.1093/geronb/gbaf022","url":null,"abstract":"<p><strong>Objectives: </strong>Cognitive aging entails diverse patterns of cognitive profiles, brain imaging, and biomarkers. Yet, few studies have explored the performance of multiple clustering algorithms on a single dataset. Here, we employ data-driven methods to analyze neuropsychological performance in older individuals with normal cognition (NC) and mild cognitive impairment (MCI).</p><p><strong>Methods: </strong>A total of 311 older adults without dementia completed a comprehensive assessment, consisting of 17 cognitive tests and a memory complaint questionnaire. We utilized two clustering algorithms: nonnegative matrix factorization (NMF) and model-based clustering (MBC). Cluster characteristics were examined in demographic, clinical, and brain morphometric data.</p><p><strong>Results: </strong>Both NMF and MBC uncovered two- and three-cluster solutions, with satisfactory data fit. The two-cluster profiles encompassed a cognitively intact (CI) group and a cognitively suboptimal (CS) group, distinguished by cognitive performance. The three-cluster solutions included CI-memory proficient, CI-nonmemory proficient, and CS groups. Remarkably, patterns of cognitive heterogeneity and their association with demographic and neuroimaging variables were highly comparable across NMF and MBC. Phenotypic homogeneity improved after identifying participants with consistent and mismatched memberships from the two algorithms.</p><p><strong>Discussion: </strong>The results indicate that two distinct data-driven algorithms, with different heuristics, generated comparable patterns regarding cognitive heterogeneity within NC and MCI. These findings may inform future subtyping studies in cognitive aging, where replication of stratifications found across different methods is strongly recommended.</p>","PeriodicalId":56111,"journal":{"name":"Journals of Gerontology Series B-Psychological Sciences and Social Sciences","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}