Gerontologist最新文献

Background and objectives: Ageism often emerges in childhood, yet rigorously evaluated school-based interventions-especially in multicultural settings-are scarce. The study evaluated the efficacy of a 90-min educational intervention to reduce ageism among Israeli Jewish and Arab middle school students.

Research design and methods: Using a randomized controlled trial (RCT) design, 606 Israeli Jew and Arab middle school students (aged 12-16, 53.3% girls) were assigned to either an intervention (N = 314) or a control group (N = 292), with measures of stereotypes, prejudice, and discrimination collected at three time points.

Results: In contrast to successful pilot findings, the intervention yielded no significant improvements over time on the measured outcomes. An exploratory analysis revealed that the pattern of change over time did not significantly differ across Israeli Jews and Arabs.

Discussion and implications: Results highlight challenges associated with reducing ageism in early adolescence. Our null findings contribute valuable knowledge that can guide future intervention design and advance cross-cultural ageism research.

Background and objectives: Centenarians represent a growing demographic that remains under-theorized in gerontology. Subsumed within the broader category of the oldest old, they are often examined through a biomedical lens, which tends to frame extreme old age as the final stage of decline. While a number of qualitative, interview-based studies have explored centenarians' views and experiences, these accounts have not yet been systematically reviewed or conceptually integrated, leaving a gap in our understanding of this phase of life. This study aimed to synthesize and reinterpret existing qualitative research on centenarians.

Research design and methods: Through six English-language databases, this meta-ethnography identified and included qualitative studies that captured the first-order constructs of centenarians and the second-order constructs of primary researchers, which informed our third-order interpretations. Study quality was appraised against the CASP Qualitative Checklist, and we followed the 19 steps of the eMERGe reporting guidelines.

Results: From 28 included studies, involving a total count of 359 centenarians with potential sample overlap, five lines of argument were constructed: (a) reaching 100 as a continuation of everyday life, (b) resilience shaped by loss, (c) staying connected through people and space, (d) autonomy in physical and mental health, and (e) reconsidering the meaning of life and death after losing loved ones.

Discussion and implications: Our findings invite a reconsideration of late life as a space of continuous meaning-making, marked by intergenerational connection, resonant loss, and autonomy in care and end-of-life choices. Further research should incorporate centenarians who were not represented in the reviewed studies.

Background and objectives: Older African American women have excess rates of stress-associated chronic diseases. Yet, limited research exists that explores within-group differences in their stress exposures and coping responses. Specifically, limited research has investigated stress and coping among college-educated African American women in later life, and this study sought to fill this gap in the literature.

Research design and methods: Constructivist grounded theory methods informed this study. Sixteen semistructured interviews were conducted with older (aged 65+ years) African American women holding a bachelor's degree or higher. Purposive and snowball sampling was used to reach the population of interest, including posting flyers in areas that might serve older African American women (local libraries, parks). Interviews focused on questions that elicited the women's perceived stressors and identified coping strategies used to buffer stress and protect well-being. Data analysis procedures involved open and focused coding, analytical memo writing, and the constant comparative approach. Several strategies, including member-check interviews, were used to achieve rigor and minimize threats to trustworthiness.

Results: A spirit of survival emerged as the core category that underpins how women experience and respond to stress. Four primary stressors were reported, which included gendered racism, losing independence, romantic relationships, and financial strain. Women described diverse coping strategies, including friendships, religion and spirituality, community care, self-care, and self-numbing strategies.

Discussion and implications: Findings provide evidence that can support the development of holistic stress-reduction interventions that integrate and center the unique stressors impacting well-educated older African American women and the coping strategies they use.

Artificial intelligence (AI) models and applications are proliferating rapidly throughout gerontological research and education. Machine learning has catapulted gerontological research in diagnosing and treating age-related health conditions. Students and educators have new tools for customized learning and innovation. Yet many of these developments come with persistent challenges, including bias, inaccuracy, and data security. As in other fields, engagement with AI models in gerontology is often siloed within disciplines. Exploring common opportunities and challenges in this space requires collaboration and conversations across disciplines. To fill this gap, the Gerontological Society of America (GSA)'s Public Policy Advisory Panel convened a multidisciplinary panel discussion of experts from the six GSA member groups and three advisory panels in November 2024 to discuss how AI is shaping various disciplines, and what ethical issues exist within or across disciplines. Several common themes emerged across disciplines: (1) human interaction remains critical to offset AI limitations in human experience, abstract reasoning, creativity, and bias; (2) AI provides opportunities for customized support across disciplines for older adults, care partners, practitioners, researchers, and students; (3) ongoing training is essential to navigate this rapidly evolving landscape; and (4) cross-disciplinary collaboration is needed to address overlapping challenges, limitations, and risks concerning AI.

Background and objectives: Frail older adults with coronary heart disease (CHD) face significantly elevated risks of adverse clinical outcomes, including mortality, prolonged hospitalizations, and frequent readmissions. Conventional risk stratification tools, inadequately account for frailty and multi-morbidity, limiting their effectiveness in geriatric care. To address this gap, we developed and validated the first machine learning (ML) model that integrates frailty into a multi-outcome risk assessment framework, thereby enhancing clinical decision-making in geriatric cardiology.

Research design and methods: Utilizing electronic health records from hospitalized frail CHD patients, we developed a multinomial prediction model employing advanced ML techniques, including principal component analysis, gradient boosting, and random forest. The model incorporates explainable AI features to enhance interpretability and a clinical applicability, prioritizing key predictors such as biomarkers and comorbidities.

Results: The ML model demonstrated superior predictive performance with Receiver Operating Characteristic (ROC) curve analysis (Area Under the Curve [AUC] 0.94, 95% CI 0.88-1.00) for mortality, 0.72 (95% CI: 0.55-0.87) readmission and 0.68 (95% CI: 0.57-0.77) prolonged hospital stay, enabling earlier risk identification and personalized intervention strategies.

Discussion and implications: This AI-driven approach represents a significant advancement in geriatric cardiology designed for integration into hospital dashboards, providing real-time patient-centred decision support, optimization of clinical workflow and resource allocation. By advancing digital health solutions and AI driven precision medicine this model sets a new standard for digital health innovations in aging care.

Background and objectives: Alzheimer's disease and related dementias (ADRD) significantly affects older adults and their caregivers, necessitating innovative caregiving solutions. This systematic review and meta-analysis evaluate the efficacy of the application of AI-based socially assistive robots (AI-SARs) in ADRD care.

Research design and methods: A comprehensive literature search of randomized controlled trials was conducted across 11 databases (e.g., PubMed, Web of Science) following PRISMA guidelines. Eligible trial studies must be interventions that adopted AI-SARs in supporting older adults with ADRD or family caregivers. Outcomes analyzed included care recipient cognitive function, depression, anxiety, and agitation.

Results: Fourteen studies were included in the systematic review and ten in the meta-analysis. AI-SAR interventions showed a statistically significant reduction in depression (SMD = -0.30; 95% CI: -0.56 to -0.03; p = .027) and agitation (SMD = -0.26; 95% CI: -0.49 to -0.03; p = .027). No significant effects were found on cognitive function (SMD = -0.07; 95% CI: -0.30 to 0.16; p = .555), or anxiety (SMD = 1.12; 95% CI: -1.73 to 3.98; p = .440).

Discussion and implications: AI-SARs may reduce depressive symptoms and agitation among older adults with ADRD. However, evidence for other outcomes remains inconclusive. Future research should focus on large-scale trials with standardized outcomes and explore the role of AI-SARs in supporting caregivers.

Background and objectives: Well-being is essential for older adults in an aging society. Although numerous studies have examined the relationship between attachment styles and well-being in older adults, the primary aim of this meta-analysis was to clarify the distinct associations of secure and insecure attachment with both well-being and ill-being in this population.

Research design and methods: Following the guidelines of the PRISMA statement, a three-level meta-analytic model was applied to quantitatively synthesize relevant findings and conduct moderator analyses. A systematic literature search retrieved a total of 54 studies with 261 effect sizes (N = 19,162) for this meta-analysis.

Results: The results revealed a positive correlation (r = 0.247) between secure attachment and well-being in older adults. Insecure attachment was negatively correlated with well-being (r = -0.181) and positively correlated with ill-being in older adults (r = 0.246). Moreover, publication year, publication status, culture, marital status, attachment measurement, types of insecure attachment, and types of well-being were found to have significant moderating effects.

Discussion and implications: The present meta-analysis highlights the significance of attachment style and may have important implications for future research and interventions aimed at enhancing well-being in older adults.

Background and objectives: The population living with dementia has been growing globally. Supportive neighbourhood environments are essential for maintaining their autonomy, independence and social participation. This paper explores the cognitive aspects (e.g., attention, task execution, recognition, spatial navigation) of the walking experiences of people living with dementia in neighbourhoods, identifying attributes that support and hinder their ability to walk outside the home.

Research design and methods: This qualitative study presents findings based on 26 participants living with mild to moderate dementia in Metro Vancouver, Canada. Each participant (or dyad with care partner) took part in four sessions, encompassing a structured questionnaire, semi-structured sit-down and walk-along interviews with concurrent photo and video documentation. Reflexive thematic analysis was performed.

Results: Five themes were generated: 1) Comfort of Knowing supported decision making and reduced anxiety, 2) Planning and Coping Strategies mitigated stress, 3) Routines in walking routes and frequency, 4) Paying Attention to prevent injuries and 5) Use of Technology for independence, motivation and stimulation reduction.

Discussion and implications: The findings underscore the significant role of familiarity and daily routines in supporting independence, the active role people living with dementia play in planning walking routes and coping with challenges, the potential environmental hazards requiring attention and the emerging role of technology. These insights offer practical implications for policymakers, urban planners, and researchers to design dementia-inclusive neighbourhoods, promote volunteer-accompanied walking programs, expand supportive housing options, and develop accessible technologies to enhance safety and autonomy for people living with dementia.