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: While early detection of Alzheimer's disease and related dementias (ADRD) can help delay progression and improve outcomes, limited research is available on dementia-related health behavior, such as screening intention among American Indian/Alaska Native communities. Guided by the Theory of Reasoned Action, the Theory of Planned Behavior, and the Health Belief Model, this study examines whether self-efficacy mediates the association between dementia knowledge and intention to seek ADRD screening among American Indian adults.

Research design and methods: Using a community-based participatory research approach, a cross-sectional survey was conducted with 248 American Indian adults (18 years and over) from a partner tribal community in the Northern Plains region in 2024. Measures included dementia knowledge, self-efficacy, screening intention, perceived susceptibility, stigma, and demographic factors. Mediation was tested using the Baron and Kenny framework and Sobel-Goodman tests.

Results: Dementia knowledge significantly predicted both ADRD screening intention and self-efficacy. Self-efficacy also significantly predicted screening intention and partially mediated the relationship between knowledge and intention. Approximately 32% of the effect of dementia knowledge on screening intention was mediated by self-efficacy.

Discussion and implications: Findings underscore self-efficacy as a critical mechanism through which dementia knowledge translates into ADRD screening intention in American Indian communities. Interventions to promote early ADRD detection could enhance both knowledge and individual confidence. Future research should include more diverse groups within American Indian communities to identify common and unique dynamics among knowledge, self-efficacy, and screening intention, informing effective intervention strategies to reduce stigma and confidence in seeking timely ADRD screening.

Background and objectives: Being homebound with cognitive impairment (CI) presents major public health challenges, increasing home healthcare costs and contributing to caregiver burden, social isolation, and reduced quality of life. As loneliness and social isolation rise among this population, socially focused intelligent assistive technologies (SFIATs) have emerged as increasingly viable solutions. This scoping review examined the current body of literature on SFIATs and the barriers and facilitators to their support of homebound older adults with CI and their caregivers.

Research design and methods: Using Arksey and O'Malley's framework, we searched 12 databases with MeSH terms related to older adults, CI, SFIATs, and homebound status. Data were analyzed descriptively using themes, with findings mapped across the socioecological framework.

Results: Nineteen studies conducted in 12 high-income countries were included. Robots, tablets, telephones, computers, virtual avenues, and other smart devices were among the SFIATs utilized in caregiving for older individuals who were homebound or had CI. SFIATs facilitated social interaction, engagement, and connectedness among older adults and caregivers. Challenges and benefits associated with their use were evident at individual, interpersonal, community, organizational, and policy levels.

Discussion and implications: Research suggests significant potential in SFIATs, but their implementation faces multi-level challenges, often due to limited direct input from end-users, leading to concerns that impact their utilization. SFIAT development must adopt co-creation approaches to ensure its contextual appropriateness. Further research is needed, particularly in low- and middle-income countries, to understand the landscape, benefits, and challenges of SFIATs in diverse global settings.

Background and objectives: Subjective cognitive decline (SCD) is a preclinical stage of mild cognitive impairment (MCI). Although dance training has been shown to be beneficial for mental health, cognitive function, and neural activity in older adults with MCI, its effect on SCD remains unclear. This study aimed to examine the effects of dance training on the aforementioned factors and on oxytocin secretion in older adults with SCD.

Research design and methods: Participants (aged 65-84 years) were assigned to either the intervention group (n = 22) with a 12-week dance training program or the control group without any alternative training (n = 22). Apathy, depression, Montreal Cognitive Assessment scores, urinary oxytocin levels, and resting-state functional magnetic resonance imaging indices, including amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC), were evaluated pre- and post-intervention.

Results: Compared to the control group, the intervention group exhibited significantly higher urinary oxytocin levels and significantly higher ALFF in the left medial orbitofrontal cortex post-intervention. Moreover, the intervention group showed more enhanced FC between the left medial orbitofrontal cortex and the left precuneus post-intervention than the control group. However, mental health or cognitive performance was not significantly different between the groups.

Discussion and implications: Our results are particularly important in light of previous findings that older adults with SCD show a reduced FC between the medial orbitofrontal cortex and the precuneus, and that oxytocin levels are positively associated with the prefrontal-amygdala oxytocinergic circuit in socioemotional processing. Thus, dance training may contribute to socioemotional resilience-related neural and molecular adaptations in SCD.

Background and objectives: Transportation is crucial to maintaining social engagement in later life. Lack of transportation is significantly associated with depressive/anxiety symptoms in older adults. In this study, we examined the extent to which loneliness mediates the relationship between transportation barriers and depressive/anxiety symptoms.

Research design and methods: Using the 2023 National Health and Aging Trends Study (N = 7,547; age 65+), we defined transportation barriers as transportation problems that kept older adults from visiting family/friends, attending religious services, attending club meetings, or going out for enjoyment. We fitted a path model, and to test the mediation effect, we used bootstrapped analysis to obtain estimates of the indirect effects and their 95% confidence intervals (CIs).

Results: Of the study population, 4.4%, or 2 million people, reported transportation barriers. We found significant direct effects of transportation barriers on loneliness and depressive/anxiety symptoms and indirect effects of loneliness (0.40, 95% CIs = [0.23, 0.57], z = 4.57, p < .001) on depressive/anxiety symptoms. The ratio of the indirect effect to the total effect of transportation barriers on depressive/anxiety symptoms (indirect effect [0.40] + direct effect [0.50] = 0.90) was 0.44. The ratio of the indirect effect of loneliness to the direct effect of transportation barriers on depressive/anxiety symptoms was 0.80.

Discussion and implications: Loneliness significantly mediates the association between transportation barriers and depression/anxiety in older adults. Transportation should be recognized as both a mobility and a mental health issue. Policies to enable older adults to continue social engagement, decrease loneliness, and alleviate depression/anxiety are needed.

Background and objectives: Climate change has a substantial impact on the environment, biodiversity, and human health and well-being. Individuals in the global South are particularly vulnerable to the negative effects of the changing climate, which often trigger relocation in search of better living conditions. This study relied on a phenomenological approach to understand the decision of older Nepalese to stay in place despite increasing climate threats.

Research design and methods: Five focus group discussions with 54 Nepalese over the age of 60 (mean age 69.33 years) were analyzed using thematic analysis. All participants self-identified as non-migrants and reported experiencing severe climate change impacts.

Results: Findings reveal a predominant sense of helplessness rooted in four themes: financial incapacity, perceived age-related limitations, dependency on government support, and a bleak outlook on environmental improvements. Participants expressed that poverty restricts mobility, while advanced age and place attachment reinforce their decision to remain in place. A shared belief that government intervention is inadequate further diminishes agency. Pervasive hopelessness emerged as a core barrier to migration, with many accepting their fate as unchangeable.

Discussion and implications: The study underscores how socio-economic vulnerabilities and institutional failings contribute to older persons' inability to adapt or relocate amidst climate change. However, the findings also highlight the important role of subjective perceptions in determining one's decision to remain in place. Addressing these barriers requires integrated policy interventions that enhance livelihood resources, strengthen institutional support, and recognize the agency of vulnerable populations to foster resilience in climate-affected communities.