Gerontologist最新文献

Background and objectives: This review focuses on tools used in dementia diagnostic disclosure, particularly from family caregivers' perspectives. With dementia affecting millions globally, caregivers face challenges needing clear information and assistance. The review aims to: (a) identify tools used, (b) assess caregivers' preferences and challenges, and (c) highlight gaps to enhance communication strategies in dementia care.

Research design and methods: This systematic review, adhering to the PRISMA guidelines and registered with PROSPERO (CRD42024557806), synthesized evidence from nine studies on tools for dementia disclosure, with a focus on family caregiver perspectives. A comprehensive search of eight databases up to September 16, 2025, combined LLM-assisted screening and human review to identify qualitative, quantitative, and mixed-methods studies. Thematic synthesis analyzed caregiver preferences, tool effectiveness, and practice gaps.

Results: Across five countries (UK, Australia, USA, Denmark, Netherlands), written materials were universally valued (e.g., 80-95% satisfaction), with visual aids and brain images less common but effective when used. Caregivers preferred direct, comprehensive information (e.g., 98% sought details about behavior and psychological symptoms of dementia) delivered face-to-face, with written backups, although retention challenges (e.g., 61% recall) and inconsistent tool provision persisted. Gaps included limited visual aid adoption and poor post-diagnostic support, highlighting unmet needs.

Discussion and implications: This review highlights the importance of tools in supporting caregivers during dementia disclosure and calls for the development of a standardized Dementia Disclosure Evaluation Tool. Despite limitations (e.g., small sample sizes, urban bias), the findings lay the groundwork for improving caregiver support and guiding future research in diverse contexts.

Background and objectives: We explored the use of machine learning models for predicting safety accident subtypes among individuals with dementia using in-home sensors and to identify key predictors.

Research design and methods: An observational study was conducted using 966 days of in-home sensor data, sleep data from wearable Actiwatch devices, caregiver-completed structured safety accident diary data, and individual data collected in South Korea. Five machine learning classification models were developed to predict physical injury, nighttime behaviors/wandering, and risky behaviors. Model performance was compared, and the most important predictive features were extracted.

Results: The Gradient Boosting Model showed the best performance in predicting physical injury and nighttime behaviors, while CatBoost performed best for risky behaviors. Activity patterns recorded using in-home sensors emerged as essential features for predicting different safety accident subgroups, particularly for nighttime behaviors and wandering.

Discussion and implications: These findings highlight the potential of these technologies to identify high-risk individuals with dementia. Further research is recommended to integrate these methods for daily safety monitoring of this population.

Background and objectives: Sleep quality is a critical component of health and recovery for hospitalized older adults, yet current monitoring practices often lack the precision and detail required for effective intervention. This qualitative study aimed to evaluate the feasibility and acceptance of implementing the artificial intelligence-powered Sleepsense bed sensor for sleep monitoring in a geriatric inpatient hospital setting.

Research design and methods: This qualitative study involved interviews with 22 patients and focus groups with 33 interdisciplinary staff members. Data were analyzed using an interpretive description approach, guided by the technology acceptance model and unified theory of acceptance and use of technology, to explore the feasibility and acceptance of Sleepsense bed sensors in a geriatric inpatient setting.

Results: Key findings from thematic analysis emerged in three main themes representing the feasibility and acceptance of Sleepsense bed sensors among hospitalized older adults: user acceptance, integration with somnolog into clinical practice, and implementation barriers and practical challenges. Staff reported high acceptance of Sleepsense technology due to its nonintrusiveness and ability to reduce disruptive nighttime checks. However, challenges such as the need for consent, data interpretation, and occasional inaccuracies were also identified. Integrating Sleepsense with existing care practices was recommended to enhance patient care while maintaining staff confidence.

Discussion and implications: This study underscores the potential of advanced sleep monitoring technologies in subacute care settings and highlights the importance of addressing implementation barriers for effective adoption.

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: 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 semi-structured 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 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.

Background and objectives: Circumstances more common with aging may challenge the ability for older adults to maintain appropriate housing. The objective of this scoping review was to identify the risk factors and conditions associated with homelessness in older adults.

Research design and methods: We searched OVID, CINAHL, Embase, PsycINFO, CENTRAL, and Social Works Abstracts from inception to February 2023. We included studies of older adults (defined as 50 years of age or older) or completed subgroup analyses accounting for older adults. We mapped the risk factors and conditions using an ecological framework (individual, relational, and structural/societal components).

Results: Sixty-five studies were included. Individual factors included identifying membership in a racialized group, and experiencing psychiatric illnesses or substance use disorders. Relational factors included being unmarried, relationship breakdown, and adverse childhood events. Structural factors included the lack of affordable housing or income supports, and systemic discrimination. Those experiencing first-onset late life homelessness were more likely to be female, had relative lifelong socioeconomic stability, but experienced sudden relational or economic changes. Those experiencing chronic homelessness were more likely to be male, often facing persistent structural vulnerabilities with comorbid substance use or psychiatric disorders. Important research gaps include measures of social support, and age and sex disaggregated analyses.

Discussion and implications: Key individual, relational, and structural factors are associated with homelessness in older adults. Adverse experiences and structural factors such as social losses and isolation have important implications towards the risk of homelessness at different stages in life. sFurther research evaluating age-appropriate interventions is paramount.

Background and objectives: Compared with people in any other age group, older adults worldwide have more suicidal ideation; however, their suicidal ideation is easily overlooked. Social support is currently one of the most widely researched social resources for preventing suicide. Currently, the impact of social support on suicidal ideation in this population is still uncertain. This study aimed to explore the impact of social support on suicidal ideation in older adults.

Research design and methods: A comprehensive literature search was conducted across multiple databases, including the Web of Science, PubMed, EMBASE, CINAHL, Cochrane Library and Scopus databases. Two independent researchers selected the studies, extracted the data and evaluated their quality. Statistical analysis was performed using STATA version 18.0.

Results: This review identified 23 studies, and 14 eligible studies were included in the meta-analyses. High social support was significantly associated with a low risk of suicidal ideation (OR, 0.75; 95% CI, 0.67 to 0.84; I  2 = 93.1%; P < 0.001). Social support is more effective in reducing the risk of SI in women than in men. Social support from families is most effective at reducing suicidal ideation in older adults, and social support can also influence suicidal ideation through mediating factors.

Discussion and implications: Social support is significantly correlated with suicidal ideation in older adults. Medical staff or researchers can prioritise social support from families and develop targeted interventions to more effectively reduce the risk of suicidal ideation in older adults.

Background and objectives: Population aging underscores the need for a comprehensive understanding of the multi-level factors that support aging in place. Physical environments are closely linked to social environments, and caregivers often observe how these environmental features shape the everyday experience of people with memory problems. This study examines how caregivers' perceptions of neighborhood built environments are associated with their perceptions of the social inclusion of people with memory problems in communities.

Research design and methods: A statewide survey was conducted in Texas, involving 95 caregivers of individuals with memory problems (defined as having significant memory impairment that impacts daily functioning). Descriptive statistics summarized neighborhood characteristics and caregivers' perception of the community's social inclusion. Logistic regression predicted two target outcomes of social inclusion for people with memory problems: (1) respect and support and (2) intergenerational exchange (e.g., age-integrated social interactions).

Results: For neighborhood characteristics, legibility-related environmental features were more commonly present than those related to accessibility or safety. For social inclusion, caregivers perceived positive community respect and support for people with memory problems but limited intergenerational interaction. Legibility of neighborhood environments was positively associated with caregivers' perceptions of respect and support for people with memory problems, while accessibility was associated with intergenerational exchange.

Discussion and implications: The findings underscore the role and potential of neighborhood environments for improving social inclusion for people living with memory problems. They suggest that improving legibility and accessibility of neighborhood environments can foster respect and social support and intergenerational exchanges central to aging in place.

Background and objectives: Employee background checks can help protect older adults in long-term care facilities. The National Background Check Program (NBCP) offers federal support to strengthen employee background check systems. Yet, regulations on provider requirements, disqualifying offenses, and administrative processes differ across states. We examine differences between NBCP (N = 27) and non-NBCP (N = 23) states across three domains: (1) types of LTC providers required to conduct background checks (2) disqualifying offenses considered by each state, and (3) processes used to administer background checks. We also assess regulatory changes across these domains from 2005 to 2024 across all 50 states.

Research design and methods: We conducted policy surveillance of state regulations on employee background check programs applicable to individuals seeking work at long-term care facilities. Our sample includes all 50 states, with 27 receiving an NBCP grant. We assess current regulations across three policy domains and review how these regulations have evolved since 2005, when the NBCP pilot program was initiated.

Results: NBCP states have expanded background check regulations to include a broader range of long-term care providers and disqualifying offenses following the grant. However, minimal differences were observed between the two groups in background check processes such as fingerprinting and registry reviews.

Discussion and implications: While many NBCP states have adopted measures like disqualifying offenses and RAP back systems, their overall impact on hiring practices, F-tags and quality of care remains uncertain.

Background and objectives: Sexual and gender minority (SGM) older adults are more likely to use long-term care (LTC) than their cisgender, heterosexual counterparts. However, LTC settings may lack SGM-affirming policies necessary for inclusive care. This study analyzed the prevalence of SGM-affirming policies in nursing homes (NH) and assisted living facilities (ALF) in Minnesota and examined differences across facility characteristics.

Research design and methods: A survey was conducted across 165 NH and 266 ALF in Minnesota. Facilities were assessed by their explicit inclusion of 28 SGM-affirmative policies, like nondiscrimination and training policies, with a mean index score calculated to determine the overall prevalence of affirming policies. Differences by facility type (NH vs ALF), location (rural vs. urban), ownership (non-profit vs. for-profit), and religious affiliation (religious vs. secular) were assessed in multinomial logistic regression. Latent class analysis compared lower (n = 244) and higher (n = 153) performers across facility characteristics.

Results: Across LTC facilities, there was an average of 11.30 SGM-affirming policies out of 28 policies assessed. Lower performing facilities reported fewer SGM-affirming policies (mean = 7.34) than higher performing facilities (mean = 17.24). No significant differences in policy prevalence were found between NH and ALF; between rural and urban facilities or by ownership status. However, striving facilities were more likely to be secular than religious.

Discussion and implications: The prevalence of SGM-affirming policies was distributed binomially, suggesting facilities fall within two categories (lower performers and high performers). Efforts should focus on adopting SGM-affirmative policies across all LTC facilities to ensure equitable and inclusive care for SGM older adults.