Innovation in Aging最新文献

People living with physical disability (PD) receiving long-term services & supports (LTSS) experience greater unmet service needs. It is unclear if having a case manager for service coordination modifies PD-associated LTSS outcomes. To fill this knowledge gap, we evaluated associations of PD with emergency department (ED) visits and community integration among older LTSS consumers with and without a case manager. Among 6,756 respondents (age, ≥65 years) from the National Core Indicators- Aging & Disability Survey (2018-2019), we evaluated three dichotomized outcomes (yes vs no): ED visits (over 12 months); and self-reported community integration indicated by both- activity (i.e. being as active in community as preferred) and enjoyment (i.e. enjoying things outside home). We used logistic regression, adjusting for consumers' sociodemographic and health-related characteristics, with random intercept for state. PD was documented in 60% of survey respondents. People living with PD were 27% more likely to report not having a case manager (p < 0.001). Among those without a case manager, PD was associated with significantly greater odds of ED visits (odds ratio [OR], 1.80, 95% CI, 1.48-2.19) and lower odds of community integration [activity: OR, 0.75, 95% CI, 0.62-0.90; enjoyment: OR, 0.69, 95% CI, 0.58-0.83]. These associations were attenuated among consumers with a case manager [ED visits: OR, 1.09, 95% CI, 0.94-1.25; activity: OR, 0.86, 95%CI, 0.75-1.00; enjoyment: OR, 0.85, 95% CI, 0.73-1.00]. Older LTSS consumers living with documented PD are more likely to report not having a case manager; and having a case manager might mitigate PD-associated adverse LTSS outcomes.

Background and objectives: While traditional topic modeling methods have been applied to analyze social media content from dementia caregivers, they often struggle with semantic understanding and coherent topic generation. This study explores the direct application of large language models (LLMs) for topic modeling of caregiver tweets, aiming to leverage their advanced semantic comprehension capabilities.

Research design and methods: We analyzed 231 870 tweets from dementia caregivers after preprocessing using ChatGPT as the primary topic modeling tool. To address context length limitations, we developed a 2-stage approach: first splitting the dataset into 226 batches of 1000 tweets each for initial topic extraction, then combining these results through a second-stage prompt for final topic synthesis. We compared our approach against 11 baseline methods, including Latent Dirichlet Allocation (LDA), Gibbs Sampling Dirichlet Multinomial Mixture Model (GSDMM), their term-weighted variants, and state-of-the-art BERTopic models. Topic quality was evaluated using Sentence-BERT-based coherence scores, and topic comprehensiveness was assessed through both ChatGPT and human expert evaluation.

Results: Our LLM-based approach achieved a coherence score of 0.358, significantly outperforming all baseline methods. Traditional approaches like GSDMM (0.317) and LDA (0.320), their term-weighted variants (ranging from 0.264 to 0.302), and BERTopic variants (approximately 0.30) showed lower coherence scores. The 2-stage batching strategy effectively handled the large dataset while maintaining topic quality and representativeness. Expert evaluation confirmed the topics' relevance to caregiver experiences and their comprehensive coverage of key themes.

Discussion and implications: This study introduces a novel methodology for applying LLMs to large-scale topic modeling tasks, demonstrating superior performance over traditional and state-of-the-art approaches. The significant improvement in coherence scores suggests that LLMs can better capture the semantic relationships within topics. Our approach addresses key challenges in context length limitations and prompt engineering, while providing more coherent and interpretable insights into caregiver experiences that can inform targeted support strategies.

Background and objectives: Homesharing provides a strategy for addressing housing insecurity by pairing home providers, often older adults, with an extra room in their house with home seekers needing housing. Despite 5 decades of use, research on this intervention remains limited. This study aims to build on this sparse scholarship to provide insight into the motivations for participating as either home seekers or home providers.

Research design and methods: This community-engaged qualitative project includes data from 24 in-depth interviews and short demographic surveys with a diverse group of home providers (n = 13) and home seekers (n = 11) recruited from 2 nonprofit homesharing organizations. Interviews were recorded and professionally transcribed. The researchers used constant comparison techniques to identify patterns and unique perspectives in the transcripts.

Results: Home providers and home seekers had a mean age of 67.92 (SD = 9.39) and 52.09 (SD = 19.03), respectively and were racially/ethnically diverse. The overall sample was primarily female (71%), though more home providers were female (85%) than home seekers (55%). Participants described a range of motivations for participating in homesharing, including financial motivations, the desire for companionship, the result of a disaster or life change, the desire for a task exchange arrangement, the need for administrative/third-party support for housing (including a need for safety and security), and altruistic reasons.

Discussion and implications: This article provides important new data in a vastly understudied area that can inform policy and practice to support affordable housing options for older adults-particularly through nonprofit homesharing programs.

Background and objectives: Middle age is a pivotal developmental life stage marked by health transitions, including the onset of major chronic diseases and functional limitations. Social determinants of health, particularly race/ethnicity, can play a significant role in accentuating the effects of comorbidity and functional limitations. This study examines how comorbidity, functional limitations, and race/ethnicity influence patterns of health services use and spending among middle-aged adults.

Research design and methods: We used pooled yearly cross-sectional data (Medical Expenditure Panel Survey, 2008-2022; excluding 2020) from middle-aged adults (ages 50-64). We derived comorbidity phenotypes using latent class analyses (LCA) and generalized linear regression to examine their associations with health services outcomes, considering the vulnerabilities introduced by functional limitations and race/ethnicity.

Results: LCA supported a 3-class solution: low prevalence of chronic conditions (63.4%), hypertensive/arthritis/joint pain (29.3%), and complex cardiovascular (C-CVD, 7.3%). Individuals with C-CVD had elevated levels of healthcare spending and use, including problematically high levels of emergency department and inpatient hospitalizations, despite higher use of office-based visits (OBVs). We found that Non-Hispanic Black adults (NHBs) and Hispanic adults had lower health spending compared to Non-Hispanic White adults (NHWs) and were less likely to use OBVs. NHBs had a higher propensity for ED use, whereas Hispanic adults were less likely to be hospitalized. Physical and instrumental/activities of daily living (I/ADL) limitations increased OBVs for both NHBs and NHWs, while I/ADLs increased hospitalizations among Hispanic adults.

Discussion and implications: These findings underscore the importance of targeted healthcare for high-risk patient populations for mitigating excess health burdens.

Background and objectives: Noise during cognitive assessments may impact cognitive performance and lead to biases in estimates of dementia prevalence, especially in developing regions where optimal test conditions may be harder to ensure. However, evidence on noise during testing and older adults' cognitive performance remains limited. To fill this gap, this study aimed to analyze the role of noise during cognitive assessments in older adults' cognitive scores, using data from a population-based study in India.

Research design and methods: Using data from the second wave of the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (n = 3,509), we examined the associations between noise during testing and cognitive scores, and whether these associations varied by respondents' hearing ability.

Results: Noise during testing was significantly associated with lower scores of general cognitive performance and individual cognitive domains. The association between loud noise exposure and cognitive performance was stronger for respondents with normal hearing range and severe hearing loss.

Discussion and implications: Noise during assessments may contribute to biases in cognitive performance in population-based surveys. Further research is needed to better understand the implications of noise during cognitive tests.

Background and objectives: This study estimates life expectancy with basic activities of daily living (ADL) and instrumental ADL (IADL) limitations by living arrangements at age 60 for Mexican adults, using the Mexican Health and Aging Study (MHAS) data from 2012 to 2021. We extend previous research by examining assistance with ADL and IADL as a measure of disability severity and exploring the association of disability assistance and mortality.

Research design and methods: Generalized estimating equations were used to examine the relationship between receiving help and living arrangements (living alone, with spouse only, or in extended households). Cox proportional hazards regression assessed the effect of receiving help on mortality. Multistate life table models were used to estimate life expectancy with and without help for ADL and IADL limitations, by gender and living arrangements.

Results: At age 60, those living alone spent a larger share of post-disability life without receiving assistance (ADL: 68.1%; IADL: 19.9%) than those living with others (ADL: 61.6%; IADL: 15.8%). Compared with co-residers, older adults living alone had higher odds of not receiving help with ADL and IADL. Individuals receiving help had higher mortality (ADL hazard ratio [HR] = 1.57; IADL HR = 1.62), consistent with help being a marker of greater severity, not a causal effect.

Discussion and implications: Extended households enable individuals with disabilities to receive assistance for a longer period. Disability assistance was associated with increased mortality risk, highlighting its role as an indirect measure of disability severity.

Background and objectives: Enhancing empathy and attitudes among formal caregivers is essential for improving dementia care quality. However, traditional educational approaches often lack the emotional depth needed to foster person-centered care. The primary objective was to evaluate whether an immersive virtual reality (VR) intervention produced greater improvements than a traditional lecture-based education program in empathy and dementia attitudes; secondary outcomes were caregiver burden and psychological distress.

Research design and methods: This parallel-group randomized controlled trial involved 160 formal caregivers randomly assigned to an immersive VR intervention or a time-matched lecture-based comparator. The intervention was delivered as a single 3-hr session comprising three consecutive VR segments, each followed by guided small-group reflection, with brief breaks between segments. Outcomes were measured at baseline, post-intervention, and at 1 month. Analyses followed the intention-to-treat principle using generalized estimating equations.

Results: The VR intervention group exhibited greater improvements in empathy (2.21, 95% CI: 0.42-4.01, p = .016) and attitudes toward dementia (1.18, 95% CI: 0.18-2.17, p = .021) immediately post-intervention compared to the control group. However, these effects were not sustained at the 1-month follow-up.

Discussion and implications: A single-session, multi-segment VR program can produce immediate improvements in empathy and attitudes toward dementia compared with lecture-based education. As effects were not maintained at 1 month, implementation may pair modular VR with low-burden refreshers to support durability while maintaining feasibility. Future research should compare delivery schedules and assess longer-term and behavioral outcomes.

Clinical trial registration: NCT06072274.

Background and objectives: Despite the growing importance of digital technology for awareness of and access to government services, and the persistent digital divide by education, few studies have investigated the associations among education, digital technology use, and awareness of government services among older adults. This study examined whether and how digital technology use mediates and moderates the relationship between education and service awareness.

Research design and methods: Data were obtained from the 2023 National Survey of Older Koreans, a nationally representative survey. Multiple regression analyses were conducted to examine the associations among education, digital technology use, and awareness of government services, and to assess the moderating effect of digital technology use. Bootstrapping was used to examine the mediating effect of digital technology use.

Results: Digital technology use partially mediated the relationship between education and service awareness. Lower educational levels were associated with reduced technology use, which was linked to lower awareness. Digital technology use also had a significant moderating effect. Older adults with lower education and limited digital technology use were the most disadvantaged in terms of service awareness. However, their awareness increased substantially with greater digital technology use, showing a steeper improvement than that of higher-educated counterparts.

Discussion and implications: A lack of digital technology use may amplify the negative impact of lower education on service awareness. However, less-educated older adults may achieve greater awareness if their digital technology use is high. Promoting digital skills among those with lower education may be crucial for addressing inequalities in service awareness.

Background and objectives: While intrinsic capacity (IC) impairment and adverse neighborhood environments are established independent risk factors for dementia, their interaction effects and potential mediating pathways remain poorly understood. This study aimed to examine the independent, interactive, and mediating associations of IC, neighborhood environment, and dementia risk among middle-aged and older adults.

Research design and methods: We analyzed data from 8,107 adults aged 50+ in the China Health and Retirement Longitudinal Study (2011-2020). IC was quantified using a composite impairment score encompassing locomotor, cognitive, sensory, psychological, and vitality domains. Neighborhood environment was classified by resource availability and social provisions (low risk; moderate risk; high risk). Cox proportional hazards models evaluated associations between IC, neighborhood environment, and dementia risk. The four-way decomposition model was used to examine the potential interaction and mediation effects of IC.

Results: Over a median follow-up of 9 years, 909 incident dementia cases occurred. Adjusted analyses revealed dose-dependent relationships: each 1-point increase in IC impairment score elevated dementia risk by 26% (hazard ratio [HR] = 1.29, 95% confidence interval [CI]: 1.22-1.36). Compared with low-risk neighborhoods, moderate-risk (HR = 1.26, 95% CI: 1.08-1.47), and high-risk neighborhoods (HR = 1.41, 95% CI: 1.13-1.77) independently increased dementia risk. Four-way decomposition revealed the association between adverse neighborhood environments and increased dementia risk was partially explained by the pure mediation effect of IC, with no significant interaction-only/mediated interaction effects observed.

Discussion and implications: IC impairments and adverse neighborhood environments independently escalate dementia risk, with IC partially mediating the environmental effects. Integrating interventions targeting both individual capacity and community-level infrastructure may optimize dementia prevention strategies.