Gerontologist最新文献

Recent advancements in artificial intelligence, particularly in speech technologies, hold significant potential for improving the health and well-being of older adults by offering noninvasive, accessible, and scalable solutions to increase social engagement, assist with daily activities, and diagnose disease. However, the development of AI models has been almost exclusively based on English-language data sets, marginalizing the over 1 billion older adults worldwide who speak non-English, low resource languages. This lack of linguistic inclusivity restricts their access to innovations, contributes to delayed diagnoses and reduced quality of care, and exacerbates existing health care inequities. Here we highlight the urgent need to curate speech data sets in low resource languages by prioritizing community agency, ensuring equitable distribution of benefits, and establishing sustainable pathways for long-term participation and empowerment, with the aim of advancing inclusive and equitable speech-based health care tools for older adults.

Background and objectives: This scoping review explored caregiving experiences and relationships among migrant home care workers, older adult care recipients and employer families, with the aim of analyzing the nature and extent of these relationships and understanding the factors that influence caregiving dynamics.

Research design and methods: The review was conducted in accordance with Arksey and O'Malley's scoping review framework. The researchers searched WoS Core Collection, Scopus, Pubmed, EBSCOhost: Psychology and Behavioral Sciences, EBSCOhost: PsycArticles, EBSCOhost: PsycInfo databases, and Google Scholar. Inclusion criteria were (a) articles reporting a research study; (b) articles focusing on triadic or dyadic caregiving relationships and experiences involving the migrant home care worker and/or the older care recipient and/or the employer family; (c) articles focusing on transnational migrant care workers; (d) articles published since 2013; and (e) articles written in English or Spanish. The researchers screened a total of 637 records, and 38 articles met the inclusion criteria.

Results: These studies represented a number of countries and used various quantitative, qualitative and mixed-method study designs. The findings revealed that caregiving dynamics among the three parties are strongly influenced by cultural, structural, and interpersonal factors. Positive relationships improve the well-being of all parties involved; however, challenges such as abuse, exploitation, and poor working conditions persist, especially for live-in care workers.

Discussion and implications: Strengthening triadic caregiving relationships through cultural training, improved legal and institutional protections and psychosocial and language support are critical for enhancing quality of care and the well-being of all those involved in the caregiving process.

Background and objectives: The Resident VIEW (Voicing Importance, Experience, and  Well-being) is a 63-item measure of person-centered care (PCC) developed for use in residential long-term care settings. We set out to test the psychometric properties of the original Resident VIEW and to develop a short-form version for use in research and quality improvement projects.

Research design and methods: Data were collected from 258, 195, and 227 residents living in 32 nursing homes, 119 adult foster homes, and 31 assisted living and residential care residents in Oregon, respectively, using structured interviews and questionnaires. Descriptive statistics and confirmatory factor analyses were used to examine the factor structure and correlations were used to test concurrent validity. A decision-making algorithm was used to develop the short form (SF) of the final Resident VIEW.

Results: Confirmatory factor analysis models showed poor fit for the original eight-factor structure. Based on fit indicators, a revised six-factor structure showed excellent fit to the data across three settings. Based on the factor loadings and other decision-making criteria, the Resident VIEW-SF consists of 10 items representing the six factors, consistent with the multiple dimensional aspects of PCC. The SF is highly correlated with the original Resident VIEW, and both are highly correlated with other indicators of resident well-being.

Discussion and implications: The Resident VIEW is a valid and reliable tool for assessing resident care preferences within a framework of PCC. The SF can be used in research and quality improvement projects where the long form is burdensome to residents or part of a larger research protocol.

Background and objectives: This study examined whether transitions in living arrangements, that is, changes in cohabitation status or household composition are associated with life satisfaction in later life and whether these relationships differ by race/ethnicity.

Research design and methods: Data from the 2014 to 2020 waves of the Health and Retirement Study (HRS; N = 8,389) were analyzed. The 2014 baseline was chosen to ensure harmonization of the study variables across waves, specifically accounting for changes in psychosocial indicators. Linear regression models assessed associations between living arrangement types, living arrangement transitions and changes in life satisfaction, using a two-wave before/after design.

Results: Older adults who lived alone at baseline experienced lower life satisfaction during the observation period. Additionally, older adults who lived alone at both time points, transitioned to living alone, or transitioned to living with others, experienced declines in life satisfaction. Non-Hispanic Black older adults experienced greater declines to life satisfaction than non-Hispanic White older adults experiencing the same transitions, including living with others at both time points, transitioning to living with others, or transitioning to living alone.

Discussion and implications: Findings from this study demonstrated a negative association between living alone and life satisfaction, irrespective of whether we focused on baseline living arrangement status or transition to living alone. The moderating role of race/ethnicity reflects both cultural norms, such as stronger family support among non-Hispanic Black older adults, and structural inequalities affecting living arrangement choices. These findings underscore the importance of generating policies and programs that promote social connection, financial stability, and culturally responsive support for older adults living alone.

Background and objectives: As the prevalence of Alzheimer's disease and related dementias (ADRD) continues to rise worldwide, so does the demand for home care workers who provide essential personal care that enables individuals living with ADRD to age in place. However, there is limited knowledge about dementia-specific training programs for home care workers. This scoping review aims to examine existing dementia training programs available for home care workers and evaluate their outcomes.

Research design and methods: We searched five databases, including PubMed, Web of Science, CINAHL, Sociological Abstracts, and Scopus. We used the PRISMA Extension for Scoping Reviews (PRISMA-ScR) and Arksey and O'Malley's five-step scoping review framework. Eligibility criteria included relevant study population (paid home care workers), dementia education or training programs, and original evaluations and published in English.

Results: Of the 903 articles identified through the five databases, 17 articles met eligibility criteria and 12 were included in the final analytic sample. The results are presented in three sections: (1) training details, (2) methods and measures, and (3) training outcomes.

Discussion and implications: This scoping review has implications for three groups of stakeholders, including researchers, governments and policymakers, and home care workers. This work underscores the importance of further implementation and evaluation of dementia training programs for home care workers.

Background and objectives: Sexual health is essential to older adults' quality of life, yet it remains understudied due to ageism. This review aims to explore how different forms of ageism influence the sexual health of older adults.

Research design and methods: Whittemore and Knafl's five-step integrative review method served as guideline of this review. A systematic search was performed across multiple databases, including PubMed, Scopus, Web of Science, and EBSCOhost published before January 2025. The search combined keywords related to ageism, sexual health, and older adult. A reference list search of all included publications was conducted to identify additional studies. Quality appraisal of the included studies was evaluated using Mixed Methods Appraisal Tool while Gough's weight of evidence framework was used to assess the level of evidence. Data extraction was organized in spreadsheets, and research themes were synthesized using the constant comparison method.

Results: Out of 634 records identified, 29 studies were included in the review. Evidence suggests that both societal and internalized ageism negatively impacts sexual health in older adults, including: (1) stigmatizing sexuality in aging population, (2) neglecting intimate and private environments for older adults, (3) decreased experience of sexual pleasure among older adults, (4) overlooked sexual health concerns in later life, and (5) underestimation of sexual violence against older adults.

Discussion and implications: This review indicates that ageism negatively impacts various aspects of sexual health in older adults. Sexual health awareness of older adults should be enhanced by mitigating ageism toward older adults.

Background and objectives: Generative artificial intelligence, particularly large language models (LLMs), is increasingly used to navigate information, potentially shaping users' perceptions of different social groups. This study examines age-related stereotypes in LLM-generated text using natural language processing (NLP) techniques.

Research design and methods: To ensure neutrality, extensive pilot testing was conducted to craft a prompt that did not elicit bias yet generated coherent responses. The final prompt, "Describe the personality of a [AGE]-year-old person," was used with OpenAI's GPT-4o API in February 2025, varying AGE from 10 to 90 in 10-year increments. The analysis was guided by the Stereotype Content Model, which assesses social cognition along two key dimensions: warmth (sociability, morality) and competence (ability, assertiveness). Scores were quantified using sentence embeddings.

Results: Text similarity and stereotype content analyses revealed three age clusters, with older adults showing the most internal consistency. Descriptions of individuals aged 60 years and above featured relatively higher warmth but lower competence compared to younger groups. Notably, positive assertiveness terms were rarely used to describe older adults.

Discussion and implications: Findings suggest that GPT-4o may embed subtle age-related stereotypes, even when using largely positive language. These patterns potentially influence user perceptions through repeated exposure. Future research should investigate the mechanisms behind these biases and explore mitigation strategies to promote more age-inclusive artificial intelligence-generated content.

Background and objectives: Artificial intelligence (AI) combined with smart sensors or conversational agents are becoming part of our lives, and have the potential to improve aging in place by supporting independent living. Trust and willingness to use AI seem essential for actual embedding. Explainable AI (XAI), originating from the recognition that AI infrastructures often operate in an opaque, "black boxed" way, might assist in understanding the underlying logic of AI-made decisions. However, it is unknown what older adults think about XAI and what they consider as needed explainability.

Research design and methods: I conducted 28 semi-structured interviews to explore XAI in the worlds of older adults. Inductive analysis was applied to analyze what do older adults know about AI and how do they imagine our society with AI? What is XAI to them and how do they value explainability?

Findings: The analysis resulted in nine themes: four regarding the knowledge on AI of older adults, including definitions, knowledge acquisition, attitudes, and expectations, and five themes were leading for the views on XAI in which XAI is not desirable, XAI is necessary, or collaboration is preferred.

Discussion and implications: The visions of XAI are different from current technological discourses. For older adults, XAI is not only technological, but a constellation between humans and machines. Most argue that a form of joint decision-making is important. As a follow-up, it seems recommended to explore the enactment of XAI in real life, and investigate the form or degree of XAI needed and for whom.

Background and objectives: The global ageing population calls for innovative strategies to support healthy ageing. Community organized/sponsored activities (COAs) are community-led nonclinical activities, typically facilitated by community centers, volunteers or peers, designed to promote social participation, interpersonal connections and enhanced well-being. COAs are increasingly promoted to enhance older adults' health. As research on their health impact is fragmented, this systematic review aims to synthesize evidence on the relationship between distinct COAs and health outcomes among older adults, focusing on physical, mental, behavioral health, and overall well-being.

Research design and methods: A search of PsycINFO, CINAHL, PubMed, Scopus, and Web of Science identified peer-reviewed empirical studies published between 2004 and 2024. Eligible studies examined COAs and health outcomes in older adults. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool, and thematic analysis classified activities into six types across four health dimensions.

Results: Twenty-one studies met the inclusion criteria. Physical, social, and volunteer activities consistently correlated with improved physical health outcomes, including enhanced mobility and reduced disability risk. Social activities also correlated with better mental health, reducing depressive symptoms. However, associations between educational/cultural and health promotion activities with behavioral health were less clear. Studies lacking specified activity types produced mixed findings, highlighting a need for standardized classifications.

Discussion and implications: COAs significantly contribute to healthy ageing, particularly enhancing physical and mental health. Future research should adopt standardized classifications and longitudinal designs to clarify causal relationships and subgroup differences, guiding targeted activities and fostering age-friendly communities.

Background and objectives: Effective education on Alzheimer's disease (AD) requires methods fostering empathy, confidence, and knowledge. Artificial intelligence (AI)-enhanced virtual reality (VR) provides immersive experiences potentially superior to traditional modalities. No previous studies have compared VR immersive learning experiences to analogous computer-based or in-person embodiment exercises. This quasi-experimental study compared the efficacy of an AI-enhanced VR scenario, "Beatriz," with computer-based and face-to-face methods in improving students' confidence, empathy, and knowledge of AD.

Research design and methods: A quasi-experimental design included 173 undergraduate health science students assigned to AI-enhanced VR, computer-based, or face-to-face modalities depicting early, middle, and late AD stages. Confidence, empathy, and knowledge were measured via pre-post surveys. Repeated measures analysis of variance values determined significant differences.

Results: All groups significantly improved confidence across AD stages post-intervention. The VR group showed greater improvement specifically in early-stage confidence. VR also significantly increased empathy compared to other modalities. No modality significantly improved factual knowledge of AD symptoms.

Discussion and implications: AI-enhanced VR effectively improved empathy and early-stage confidence, suggesting strong benefits for dementia education. However, it did not surpass traditional methods in improving factual knowledge. AI-driven VR has promising implications for enhancing therapeutic and caregiving practices for aging populations. Further research should explore long-term impacts and direct older adult care applications.