Lisa D’aMbrosio

As a result of a rapidly aging population and the increasing prevalence of dementia among older adults, technological solutions are increasingly being considered to facilitate caregiving. This research investigates the perspectives of 20 caregiving dyads on VGo, a telepresence social robot with features designed to support caregiving. Care recipients (CRs), aged 65 and older, diagnosed with Alzheimer’s disease and related dementias, along with their primary caregivers (CGs), evaluated the robot through an online interview study. The interviews integrated informative videos showcasing VGo’s features and functions. Insights from the interviews revealed diverse expectations, interests, and reservations. The majority of CGs and their CRs perceived the robot’s features as beneficial. In particular, the voice command capability was appreciated as an alternative to using smartphones and as a way to manage home appliances. The community feature, however, did not align well with many participants’ lifestyles, and participants had a number of suggestions to enhance the robot’s notification function. Based on the interview results, the study offers a set of design recommendations for telepresence social robots in home caregiving contexts. This investigation highlights the promise of social robots in caregiving contexts and underscores the need for further improvements to ensure they fit users’ needs.

The increasing integration of Artificial Intelligence (AI) into areas like financial planning has spurred interest in how various demographic groups, notably older adults, perceive and adopt this technology. This paper aims to identify personas and explore how factors like age, gender, and knowledge impact AI acceptance. The data shows varying levels of willingness to adopt AI in finance across demographics. Younger, more educated individuals demonstrate greater trust and usage of AI-enabled financial tools, raising concerns about inclusivity and potential barriers for older or less educated individuals. The paper will delve into these disparities, exploring the underlying reasons for resistance, such as perceived risks or lack of education about AI. To ensure equitable distribution of AI’s benefits, we recommend enhancing AI literacy and designing more inclusive AI, as this approach paves the way for a society in which AI empowers all ages with its potential.

Autonomous vehicles (AVs) may significantly impact people’s choice of residential locations and spatial structures. The impact may vary across different countries, but few studies have focused on it. This study drew on China and the United States (US) as two cases to study car drivers’ knowledge of AVs and willingness to move farther if AVs were available by estimating ordered logistic regression models. The results showed that 42.3% of Chinese and 29.8% of US respondents were likely to consider moving farther away from the nearest city or the destination for the most frequent trip if they had an AV. The Chinese sample had less knowledge of AVs than the US sample, but they were more likely to consider a move. AVs may lead to a new round of urban sprawl, but the challenge may be greater for China. We captured the socio-economic and transport factors that affected this result.

Gerontological scholarship has long seen the environment to be a silent partner in aging. Environmental Gerontology, an established approach in Social Gerontology, has shown how the everyday lives of older adults are deeply entangled in socio-spatial environments. Adopting an Environmental Gerontology approach, we explore social and cultural dimensions of the association between out-of-home mobility and wellbeing among older adults in a north western city of India. This was established by combining high resolution time-space data collected using GPS receivers, questionnaire data and time diaries. Following a multi-staged analytical strategy, we first examine the correlation between out-of-home mobility and wellbeing using bivariate correlation. Second, we introduce gender and family structure into regression models as moderating variables to improve the models’ explanatory power. Finally, we use our results to reinterpret the Ecological Press Model of Aging to include familial structure as a factor that moderates environmental stress. Findings emphasize the central role that social constructs play in the long-established relationship between the environment and the wellbeing of older adults.