Examining the Roles of Technology in Aging and Quality of Life

Technology surrounds us, from the mobile phones that most of us carry to the televisions that we watch to the ways that we find information about a restaurant or vacation destination. Older adults are no exception; they are increasingly incorporating diverse types of technologies into their lives. According to the latest Pew statistics, 67 percent of individuals aged 65 and older in the United States use the Internet, while 43 percent own smartphones (Anderson and Perrin, 2017). Although these figures have increased substantially over the past decade, they are still lower than the estimated 90 percent of the U.S. adult population aged 18 and older that uses the Internet and 77 percent who use smartphones. Although the increases in usage over the past decade represent more digital inclusion for older adults in general, the Pew statistics actually overestimate the percentages of older adults who use the Internet and smartphones. The Pew estimates include only community-dwelling older adults and exclude older adults in different types of care facilities (e.g., nursing homes, dementia units, etc.), the majority of whom do not use the Internet or other information and communication technologies (ICTs). Although it is useful to know the percentages of older adults who use ICTs, we know little about the effects of this technology integration and pervasive use on individuals and society at large. The articles in this special section help us better understand how technologies can be used as a methodological tool as well as how technology use among older adults may impact their quality of life. These articles contribute methodologically and substantively. With the pervasiveness of technology use in society, researchers are in a unique position to methodologically harness the power of the data being generated from this technology use, as well as using new technologies to aid in data collection. Oscar and colleagues (2017) and Cornwell and Cagney (2017) expand on the pervasiveness of technology use to advance methodology to address substantive problems related to problems facing older adults. Although substantial research has focused on stigma surrounding health problems, much of this research has been ethnographic or based on individuals’ self-reports. Oscar and colleagues go beyond this work to examine how public discourse, in this case on twitter, can perpetuate stigma. Their research on the use of twitter as a forum for understanding stigma related to Alzheimer’s disease is an example of emerging research that harnesses “big data” to examine health outcomes and health-related characteristics. Machine learning, used in this study, utilizes artificial intelligence to have a computer system learn from itself without having to be continually programmed. The potential to use machine learning to mine large amounts of data may yield critical insights into aging processes and health in the coming years. Smartphone use has increased dramatically in the past decade, yielding the potential to obtain objective use data as well as tracking people’s movements. Cornwell and Cagney (2017) combine global positioning system (GPS) tracking data from smartphones with ecological momentary assessment (EMA) data to describe older adults’ activity spaces. Although a small-scale study (n = 60), it suggests that older adults operate in larger geographic spaces than in the areas where they reside. GPS data yield more precise measures of activity space than self-report data, as long as people carry their smartphones with them as they move. Larger studies across geographically diverse areas that last for longer than 1 week are needed to determine whether GPS tracking data from smartphones will be a useful data gathering tool for the future. Although mobile phone use among older adults is increasing, more than half of older adults have not crossed the “smartphone” divide (Anderson and Perrin, 2017). Determining the generalizability of studies utilizing these technologies will be important as research in this area evolves. Although not intended per se as a methodological article, Peterson, Meng, Dobbs, and Hyer (2016) encourage researchers to think more broadly about our conceptualization of technology and “devices.” Using National Health and Aging Trends Study (NHATS) data, they found gender differences in mobility device use—with women less likely to report using canes, even when in poor health or with poor balance. This study suggests that we should broaden our focus on technology use among older adults. They focus on the use of canes as a “device.” Though most of the research focusing on older adults and technology use focuses on ICTs, technology is much broader than just the types used for information and communication. A broader conceptualization of technology may help illustrate use/nonuse patterns and motivations that could suggest fruitful interventions to enhance health and well-being among older adults. Substantively, the articles in this series add to emerging research focusing on how technology use affects social connection/engagement and health, as well as the impacts of health on technology usage. Within each of these areas, motivations for use, as well as, types of use matter. However, before technology use can yield impacts on the lives of older adults, they must first begin to use the technologies. Much of my own and others’ research focuses on how to get older adults to cross the digital divide and to gain benefits from technology use (Cotten et al. 2016; Czaja and Sharit 2013; Watkins and Xie 2014). Myhre, Mehl, and Glisky (2016) add to this body of work. They conducted a small-scale intervention designed to assess whether teaching older adults to use Facebook, a specific type of technology application, could have cognitive benefits. They found modest change in complex working memory, yet no change in other measures of cognitive function or social support. Determining the correct social media “dose” to yield improvements in cognition will be important as researchers expand on this work. Using data from the National Cancer Institute’s (NCI) Health Information National Trends Survey (HINTS), Hong and Cho (2016) highlight the need to continue efforts to decrease the digital divide among older adults. Older adults aged 75 and older, those without high school education, and with incomes less than $25,000/year were less likely to report health-related Internet use. As they and others have shown, tailored interventions are needed to help disadvantaged older adults cross the digital divide (Berkowsky, Rikard, and Cotten 2015; Cotten et al. 2016; Robinson et al. 2015; Watkins and Xie 2014). Motivations for deciding to use ICTs initially and over time are important for understanding the potential effects that ICT use may have on people’s lives. Sims, Reed, and Carr’s (2016) study of ICT users aged 80 and older, an underexplored group in terms of ICT use, expands on prior research focusing on ICT use and well-being among older adults by examining the motivations for ICT use as well as psychological and physical health outcomes. They find that motivations for use are important for understanding how ICT use may enhance well-being, and these motivations may mediate some or all of the relationship between ICT use and well-being, depending on the type of outcome being examined. Two studies focus on technology use and social engagement. Using NHATS data from 2011, Kim, Lee, Christensen, and Merighi (2016) focus on differential access and uses of ICTs and whether these disparities affect social engagement among older adults, with a focus on gender differences in these relationships. Although studies with younger samples have found few gender differences in access, Kim and colleagues find that older men were more likely to access and use ICTs than older women. Historically, men have had more experience with technology in the workforce than women. ICT access was associated with formal and informal social engagement for women, but only informal social participation for men. Jun and Kim (2016) use a nationally representative cross-sectional sample of Korean older adults, aged 50 and older, and reveal the importance of Internet use in relation to satisfaction with social relationships, depression, and suicidal ideation among older adults. Both studies illustrate the importance of using ICTs for social engagement and support; given high rates of loneliness and social isolation among older adults, getting them online may be one way to enhance their social integration. Levine and colleagues (2017), using NHATs data, examine whether health decline from 2011 to 2014 is related to technology use and digital health technology use, which comprises activities like finding information about health conditions, handling insurance issues, contacting health care professionals, and filling prescriptions. They find low rates of technology use, in general, and digital health technology use, more specifically—which challenges some of the usage statistics noted by Pew in prior reports. Similar to Berkowsky and colleagues (2016) and Rikard and colleagues (2017), they find that changes in health status matter, particularly in terms of general technology usage; Levine and colleagues, however, focus on more extensive changes in health status than have prior studies. Usability issues may also affect whether people can continue to use technologies as they experience particular types of health declines. Older adults with health issues may need personalized care for which technology is not a substitute. As older adults increasingly use a range of technologies, researchers have ample opportunities to gather data in increasingly sophisticated ways to track behavioral, monitoring, and health outcomes. Combining self-report with objective device usage log and behavioral data can help us understand how and when patterns of behavior change and identify trends that could signal significant declines or health event precursors for older adults. Machine learning can also help identify these trends. Identifying ways to help older adults successfully use and maintain use of technologies over time is critical if they are to be able to reap the benefits of technology in our digitally based society. Passwords, changing interfaces, safety and privacy concerns, plus declines in health status, are key factors that impede older adults’ continued use of technologies (Cotten et al. 2016; Tsai et al. 2016; Berkowsky et al. 2016). Designing and evaluating tailored interventions to determine whether specific types of resources and training programs can help older adults to stay safe online and successfully maintain use over time is one way to advance work in this area. Many of the studies in this section are cross-sectional or of short duration, reflecting the relatively nascent state of the field. Of the few existing longitudinal studies that include technology use measures, most include minimal technology use measures as this is not the main study focus. Or, the studies for which this topic is a main focus have only been in existence for a few years. We need well-designed, longitudinal studies that follow people over long periods of time, as they move through the life course. This is challenging when studying the use and impacts of technology, as technologies are constantly evolving. It is also challenging from a funding standpoint. Large-scale longitudinal studies are expensive to conduct. Without federal funding and investigators who have the expertise in aging and technology use and impacts, it is likely that research will still significantly lag behind in this area. Finally, gerontologists and aging experts should collaborate with technology developers to help design technologies that will be useful and user friendly for older adults. Although many older adults do not want technologies that are designed just for them, having accessible and useable technologies will benefit everyone, not just older adults. As experts in aging and gerontology, it behooves us to utilize our training and knowledge to not just study older adults but to also do research and outreach that improves their lives.