"Live Gerontology": Understanding and Representing Aging, Loneliness, and Long-Term Care Through Science and Art.

This article proposes an expansive conceptualization of gerontological research by engaging with a "live gerontology" that combines sciences and arts to better understand and represent aging and its diverse meanings and contexts. Borrowing the sociological concept of "live methods," we argue that gerontology can benefit from a "live" approach-not only methodologically, but also conceptually. To guide pathways between artistic and gerontological fields and frame its practices and outcomes, we suggest four propositions for a live gerontology: (1) using multiple genres to artfully connect the whole-interweaving micro-, meso-, and macrolevels to contextualize aging within various sociocultural milieus; (2) fostering the use of the senses to capture more than just what people say-what they do, display, and feel; (3) enabling a critical inventiveness by relying on arts' playfulness to design/refine instruments; and (4) ensuring a constant reflection on ethics of representation and public responsibility. To apply and experiment with a live gerontological approach, we describe collaborations with an award-winning writer and an illustrator. The collaborations drew on qualitative data from a study on lived experiences of loneliness in long-term care through ethnography and interviews with residents of 2 Australian facilities. The writer explored participants' accounts as creative stories, which were then illustrated. Motivated by an ethics of representation, we aimed to represent findings without othering or further marginalizing participants. The creative materials offered more than appealing representations, shining new light on the intricate nature of aging, loneliness, institutionalization, and gerontology research and practice.

The relationship between social isolation, social support, and loneliness with cardiovascular disease and shared risk factors: A narrative review.

BACKGROUND: Cardiovascular disease (CVD) is the greatest contributor to global morbidity and mortality. Poor social health plays a critical role in CVD incidence. Additionally, the relationship between social health and CVD may be mediated through CVD risk factors. However, the underlying mechanisms between social health and CVD are poorly understood. Certain social health constructs (social isolation, low social support and loneliness) have complicated the characterisation of a causal relationship between social health and CVD. AIM: To provide an overview of the relationship between social health and CVD (and its shared risk factors). METHOD: In this narrative review, we examined published literature on the relationship between three social health constructs (social isolation, social support, and loneliness) and CVD. Evidence was synthesised in a narrative format, focusing on the potential ways in which social health affects CVD, including shared risk factors. RESULTS: The current literature highlights an established relationship between social health and CVD with a likelihood for bi-directionality. However, there is speculation and varied evidence regarding how these relationships may be mediated through CVD risk factors. CONCLUSIONS: Social health can be considered an established risk factor for CVD. However, the potential bi-directional pathways of social health with CVD risk factors are less established. Further research is needed to understand whether targeting certain constructs of social health may directly improve the management of CVD risk factors. Given the health and economic burdens of poor social health and CVD, improvements to addressing or preventing these interrelated health conditions would have societal benefits.

Artificial Intelligence in Long-Term Care: Technological Promise, Aging Anxieties, and Sociotechnical Ageism.

This article explores views about older people and aging underpinning practices and perceptions of development and implementation of Artificial Intelligence (AI) in long-term care homes (LTC). Drawing on semi-structured interviews with seven AI developers, seven LTC staff, and four LTC advocates, we analyzed how AI technologies for later life are imagined, designed, deployed, and resisted. Using the concepts of "promissory discourse" and "aging anxieties", we investigated manifestations of ageism in accounts of AI applications in LTC. Despite positive intentions, both AI developers and LTC staff/advocates engaged in simplistic scripts about aging, care, and the technological capacity of older people. We further uncovered what we termed sociotechnical ageism-a form that is not merely digital but rests on interacting pre-conceptions about the inability or lack of interest of older people to use emerging technologies coupled with social assumptions about aging, LTC, and technological innovation.

Pandemic Diaries: Lived Experiences of Loneliness, Loss, and Hope Among Older Adults During COVID-19.

BACKGROUND AND OBJECTIVES: While research on loneliness in later life has increased during the coronavirus disease 2019 (COVID-19) pandemic, we still lack diverse qualitative approaches capturing lived experiences of lonely older adults. Approaches to research with older adults instead of on them are also scant in gerontological literature on loneliness. Through solicited diaries, this study aimed to explore how older Australians who were already lonely before the pandemic managed lockdowns (stay-at-home orders) in Victoria, Australia, which lived through one of the longest lockdowns in the world. RESEARCH DESIGN AND METHODS: This article is based on qualitative diaries completed by 32 older adults (aged 65 and older). Diaries provide a 'live' document where participants become active research partners, recording and sharing their perceptions and experiences. This method is useful to capture sensitive issues, but to the best of our knowledge has not been employed in loneliness studies. Data were thematically analyzed through the identification of themes within and across diaries. RESULTS: Loneliness was defined by participants as a detrimental absence of companionship and meaningful social interactions. For most, lockdowns exacerbated loneliness, presented new triggers, and upended coping strategies. The disruption of the 'emotion work' involved with managing loneliness led to a reconfiguration of response strategies, including through digital technology, which brought both challenges (e.g., digital ageism) and opportunities (e.g., novel communication forms). DISCUSSION AND IMPLICATIONS: Understanding how older people living alone define and respond to loneliness in diverse contexts-for example, before and during a pandemic that restricts social interaction-provides critical insights to inform interventions to tackle loneliness.

Dignity, Autonomy, and Style of Company: Dimensions Older Adults Consider for Robot Companions.

Research into companion robots for older adults, including those who are socially isolated and lonely, continues to grow. Although some insight into older adults' preferences for various robotic types and functionality is emerging, we lack research examining how these robots fulfil or challenge a range of values and aspirations individuals have in later life. This study examines the attitudes and perspectives of 16 older adults (aged 65+) living independently but alone in their own homes, who were interviewed and shown videos depicting three distinctive companion robots: a talking assistant; a roving toylike vehicle; and a robotic dog. This approach illuminated values, preferences, and needs amongst older people that are vital for understanding the potential of companion robots. In comparing the robots, participants expressed concerns about the impact of different companion robots on their abilities and skills, their sense of autonomy and control over their lives, and the maintenance of several kinds of dignity. These results inform user-centered design and use of companion robots for older people living alone and independently.

Latent Class Models in action: bridging social capital & Internet usage.

This paper explores how Latent Class Models (LCM) can be applied in social research, when the basic assumptions of regression models cannot be validated. We examine the usefulness of this method with data collected from a study on the relationship between bridging social capital and the Internet. Social capital is defined here as the resources that are potentially available in one's social ties. Bridging is a dimension of social capital, usually related to weak ties (acquaintances), and a source of instrumental resources such as information. The study surveyed a stratified random sample of 417 inhabitants of Lisbon, Portugal. We used LCM to create the variable bridging social capital, but also to estimate the relationship between bridging social capital and Internet usage when we encountered convergence problems with the logistic regression analysis. We conclude by showing a positive relationship between bridging and Internet usage, and by discussing the potential of LCM for social science research.