Technology has recently begun to be explored as a way to cope with the challenges related to the aging of the population. However, while many technological systems for older adults have entered the ...market, the rate of adoption is low despite the potential benefits they intend to provide. The market response suggests that older adults' adoption of technology is not simply a matter of performance and price, but a complex issue that is affected by multiple factors. To address the issue in a more comprehensive way, this review study identifies factors that influence older adults' perceptions and decisions around adoption and use of technology‐enabled products and services with an integration of related findings from various fields. Based on a survey of related studies, 10 factors—value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence—are identified as the facilitators or determinants of older adults' adoption of technology. While previous studies have focused on detailed design and physical ease‐of‐use, the 10 factors provide a holistic framework that covers social contexts of use and delivery and communication channels as well as individual characteristics and technical features. This paper describes the factors with empirical evidence and design implications. The goal of this paper is to provide a base for a more comprehensive understanding of older adults as users and consumers of technology; to inform designers, developers, and managers about practical implications; and to set a research agenda for future studies in related fields.
Self‐driving vehicles will affect the future of transportation, but factors that underlie perception and acceptance of self‐driving cars are yet unclear. Research on feelings as information and the ...affect heuristic has suggested that feelings are an important source of information, especially in situations of complexity and uncertainty. In this study (N = 1,484), we investigated how feelings related to traditional driving affect risk perception, benefit perception, and trust related to self‐driving cars as well as people's acceptance of the technology. Due to limited experiences with and knowledge of self‐driving cars, we expected that feelings related to a similar experience, namely, driving regular cars, would influence judgments of self‐driving cars. Our results support this assumption. While positive feelings of enjoyment predicted higher benefit perception and trust, negative affect predicted higher risk and higher benefit perception of self‐driving cars. Feelings of control were inversely related to risk and benefit perception, which is in line with research on the affect heuristic. Furthermore, negative affect was an important source of information for judgments of use and acceptance. Interest in using a self‐driving car was also predicted by lower risk perception, higher benefit perception, and higher levels of trust in the technology. Although people's individual experiences with advanced vehicle technologies and knowledge were associated with perceptions and acceptance, many simply have never been exposed to the technology and know little about it. In the absence of this experience or knowledge, all that is left is the knowledge, experience, and feelings they have related to regular driving.
This article explores innovative applications of sharing economy services that have the potential to support a population aging in place, especially the "oldest old," aged 85 and older, and their ...caregivers. A mixed-methods study conducted by the MIT AgeLab examined perceptions of and experiences with sharing economy services, ultimately finding opportunities and barriers to use. Thus, although sharing economy services have potential to support aging in place, to do so successfully will require reconstructing how older adults, family caregivers, aging service professionals, gerontology educators, and gerontology students conceptualize and deliver care to an aging population. We suggest examples for gerontology educators to integrate into their classrooms to further cultivate an appreciation among students of multiple approaches to intervention, including those that leverage sharing economy and technology-enabled platforms to support older adults and their caregivers.
Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, ...presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms.
This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation. To implement this framework, an m-health tool named Monipar was developed that uses off-the-shelf smart devices.
An experimental protocol was conducted with the participation of 21 early-stage PD patients and 7 healthy controls who used Monipar installed in off-the-shelf smartwatches and smartphones. Movement data collected using the built-in acceleration sensors were used to extract relevant digital indicators (features). These indicators were then compared with clinical evaluations performed using the MDS-UPDRS scale.
The results showed moderate to strong (significant) correlations between the clinical evaluations (MDS-UPDRS scale) and features extracted from the movement data used to assess resting tremor (i.e., the standard deviation of the time series:
= 0.772,
< 0.001) and data from the pronation and supination movements (i.e., power in the band of 1-4 Hz:
= -0.662,
< 0.001).
These results suggest that the proposed framework could be used as a complementary tool for the evaluation of motor symptoms in early-stage PD patients, providing a feasible and cost-effective solution for remote and ambulatory monitoring of specific motor symptoms such as resting tremor or bradykinesia.
The oldest olds (aged 85 and over) are the fastest-growing age segment. However, our understanding of their mobility is limited. To address this gap, we invited 19 U.S. and 30 Chinese "oldest old" to ...take part in focus groups and complete a mobility questionnaire. We focus on travel mode choice, which includes changes in travel modes, frequency of usage, and perceptions of comfort.
Older adults' familiarity and acceptance of new mobility technologies (e.g., ridesharing, carsharing, and autonomous vehicles) were measured by questionnaire and focus group. Word clouds were also used to illustrate people's reasons for choosing their primary mode of transportation.
The results show that both panels of older adults similarly feel some extent of travel limitations. But the responses among the two groups differ: 18 American participants chose "drive myself" as their primary option a decade ago, while 11 chose it now; no Chinese participants selected it either a decade ago or now. Both currently and 10 years ago, there was a significant difference in mode choice between participants in China and the United States. However, this gap has narrowed over the past decade. Participants in China have significantly changed their transportation preferences compared to 10 years ago, while participants in the US have remained nearly unchanged. American respondents consider "ease" as an important factor, while Chinese respondents pay more attention to "safety" and "no other option to get around" when making travel mode choices. Compared to Chinese participants, American participants were more comfortable with driving an autonomous vehicle. These differences may result from the various developmental stages and transportation policies of the two countries. This study supports the development of new mobility technologies for the oldest old to improve their quality of life.
Abstract
Technologies developed to make life easier for the general population – including smart home products, internet-enabled services, communication platforms, and health management systems – ...also have the potential to assist individuals who provide care to loved ones. While caregivers may be eager users of technology to support their responsibilities, some technologies remain untapped resources. An in-depth survey conducted with the MIT AgeLab Caregiver Panel around attitudes toward and use of technology for themselves and for caregiving showed that while caregivers use a wide range of technologies for themselves, their use for caregiving is limited. However, while caregivers did not universally use technologies or services to support the care they provided, those who did so generally reported positive feelings about their use. This presentation will report on technology experiences – including perceived usefulness, ease of use and integration, impacts, and overall satisfaction – among caregivers of various characteristics and conditions.
Robo‐advisors have recently been gaining interest as a technology‐enabled means to make financial management easier. The aim of this study is to examine how people's self‐assessed financial ...experience, affective reactions, and the interplay with individual values influence their willingness to use a robo‐advisor. We argue that one's self‐assessed financial experience influences the willingness to use robo‐advisors as a result of different affective reactions (i.e., anxiety and joy) associated with its usage. We further posit that the mediating effect of anxiety varies with individual levels of a motivational factor—self‐enhancement—which has been found to regulate anxiety‐related feelings. Based on a large‐scale nationwide survey with an online sample of American adults, it was found that affective responses (i.e., anxiety and joy) explain (i.e., mediate) the effect of self‐assessed financial experience on the willingness to use robo‐advisor. Moreover, the mediating effect of anxiety was found to vary with levels of self‐enhancement motives. The findings suggest that willingness to use robo‐advisors may be increased with positive emotions (e.g., joy) expected from use, while decreased by anticipated negative emotions (e.g., anxiety), and that the relationship may be altered by inducing individuals' self‐enhancement motives (e.g., possibility of accumulating wealth).
Abstract Recent advancements in digital technologies, including artificial intelligence (AI), Internet of Things (IoT), and information and communication technologies (ICT), are transforming homes ...into interconnected ecosystem of services. Yet, discourse on home technologies remains fragmented due to inconsistent terminologies. This paper addresses the lack of a framework, studying distinctions between smart and non-smart homes and forecasting connectivity and automation growth. Experts (21) participated in online surveys and interviews in 2021, exploring language, structure, and technical/social aspects of basic and smarter homes. Quantitative survey data and qualitative interview analyses yield insights on defining smarter homes, barriers to adoption, and framework improvements to establish universal definitions. This study underscores the urgency of harmonizing language and concepts in the domain of smart homes, revealing user understanding gaps and usability issues as barriers. This bridges gaps for consumer engagement and tech adoption.
Despite concerns over distracted driving, many Americans still engage in risky activities while driving, leading to crashes and fatal outcomes. This study aims to investigate the impact of individual ...risk attitudes and in-vehicle technologies on various types of distracted driving behaviors (DDB), providing insights into the factors that contribute to an increased likelihood of DDB and enhancing an understanding of the effects of advanced vehicle technologies (AVT) on driver behavior. The analysis leverages self-reported survey questionnaire data from a nationally representative sample of participants. To assess the relationships between the variables, exploratory factor analysis and multiple linear regression analysis were used. The findings revealed that the presence of AVT and individual risk attitudes each predicted DDB. The presence of driver-assist and safety features did, however, lead to some degree of decreased distracted driving. Convenience features, such as Wi-Fi and Bluetooth, were most likely to increase DDB, highlighting the need for the design of AVT systems to minimize distracted driving while leveraging the benefits of technology. The data also indicate that other factors affect DDB. Notably, younger individuals engaged in more DDB compared with older individuals, and individuals who drive more frequently and for longer distances also exhibited a higher frequency of DDB. Factors such as driving experience and exposure also affected DDB, with driving exposure having a more substantial influence.
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