A growing number of technology options that can support older adults in the aging process are being introduced. However, these technologies can be of little benefit to older adults if they are not accepted and implemented. A recent review of research sheds light on the factors that influence the adoption of technology for aging in place by community-dwelling adults 60 and better.
The technology covered in this review was intended to support the independence of community-dwelling adults by alleviating or preventing functional or cognitive impairment, limiting the impact of chronic diseases, or enabling social or physical activity. The authors looked at the adoption of such technology in both the pre-implementation stage, when the technology had not yet been used, and the post-implementation stage, when users had used and experienced a technology.
The review found that most of the research available on technology acceptance focused on technologies that enhance safety, followed by technology assisting social interaction. Less prevalent was research on technology designed to support older adults in activities of daily living or instrumental activities of daily living.
In the pre-implementation stage, six themes were identified that were affecting technology adoption. The themes that negatively impacted individuals’ acceptance of technology were concerns about the technology itself, including cost, privacy implications, stigma concerns, and usability factors; and having alternatives to technology, such as receiving assistance from a family member or caregiver. Themes with a positive impact on individuals’ acceptance of technology were the expected benefit from the technology, such as increased safety or perceived usefulness; and the need for technology.
The other two themes fell into both camps; they could either encourage or discourage technology acceptance. They include the social influence on technology adoption, such as encouragement or discouragement from family, friends, or professional caregivers; and last was the characteristics of the older adults considering adoption. For example, how much did the older adult desire to age in place or how familiar was the older adult with modern electronic technology?
Looking at post-implementation acceptance of technology, some of the same factors seen in the pre-implementation stage were still observed, but different factors also emerged in this stage. Privacy and stigmatization concerns still remained even after using a technology, and perceived need for a technology also remained an important factor in the acceptance of technology. In this stage, studies showed that an expected increase in safety positively impacted technology acceptance.
Once the technology had been used, additional factors also emerged that affect technology acceptance. These included the occurrence of false alarms when using the technology, concerns for losing or forgetting portable technology devices, and concerns about the technology not working in certain locations. The issue of the availability of home care as an alternative to aging in place technology also emerged at this stage. Lastly, the level of overall satisfaction and the emotions associated with the technology use affected technology acceptance.
Throughout the aging services industry, there is considerable enthusiasm about the promise for technology to assist older adults, in order to both provide them with a higher quality of life and to contain caregiving costs and burdens. But without acceptance of technology by older adults, the promise it holds will go unrealized. This review provides valuable guidance about factors that should be taken into account when considering the adoption of any particular technology for older adults, as well as highlights important concerns and social factors that should be taken into account and addressed when encouraging greater technology use by older adults.
Source: Peek STM, Wouters EJM, van Hoof J, et al. Factors influencing acceptance of technology for aging in place: A systematic review. International Journal of Medical Informatics (2014); Vol. 83(4): 235–248.