Caregivers' Willingness to Pay for Technologies to Support Caregiving

Richard Schulz, PhD; Scott R. Beach, PhD; Judith T. Matthews, PhD; Karen Courtney, PhD; Annette De Vito Dabbs, PhD; Laurel Person Mecca, MA


Gerontologist. 2016;56(5):817-829. 

In This Article

Abstract and Introduction


Purpose of the Study: We report the results of a study designed to assess whether and how much informal caregivers are willing to pay for technologies designed to help monitor and support care recipients (CRs) in performing kitchen and personal care tasks.

Design and Methods: We carried out a web survey of a national sample of adult caregivers (age 18–64) caring for an older adult (N = 512). Respondents completed a 25min online survey that included questions about their caregiving situation, current use of everyday technology, use of specific caregiving technologies, general attitudes toward technology, and questions about technologies designed to help them monitor and provide assistance for CRs' kitchen and self-care activities.

Results: About 20% of caregivers were not willing to pay anything for kitchen and self-care technologies. Among those willing to pay something, the mean amount was approximately $50 per month for monitoring technologies and $70 per month for technologies that both monitored and provided some assistance. Younger caregivers, those caring for a person with Alzheimer's disease, and caregivers with more positive attitudes toward and experience with technology were willing to pay more. Most caregivers feel that the government or private insurance should help pay for these technologies.

Implications: Caregivers are receptive and willing to pay for technologies that help them care for their CR, although the amount they are willing to pay is capped at around $70 per month. The combination of private pay and government subsidy may facilitate development and dissemination of caregiver technologies.


Advances in digital technology in the last three decades have fundamentally changed the lives of individuals of all ages. The shift from analog electronic and mechanical devices to digital technology has fostered the development of computers, smartphones, the internet, robots, and a myriad of sensing and actuating devices that have revolutionized communication, health care, mobility, and the everyday lives of most humans throughout the world. Digital technologies have become increasingly important for older individuals and their family caregivers because of their potential to maintain and improve the health, functioning, safety, and psychological well-being of older individuals (Schulz et al., in press; Schulz, Lustig, Handler, & Martire, 2002).

Over the last several decades, scholars, designers, and practitioners have sought to identify factors that influence technology acceptance and adoption in general (Czaja et al., 2006; Davis, 1989), and the acceptability and uptake of consumer health technologies in particular (Center for Technology and Aging, 2010; Rogers & Mead, 2004). To varying degrees, existing models of technology acceptance have focused on: (a) abilities, needs, and preferences of end users; (b) features of the technology; and (c) societal factors, including social and health policy, and the regulatory environment (Schulz et al., 2014). For example, the original technology acceptance model (Davis, 1989) broadly argued that perceived usefulness and ease of use were key to predicting intent and actual technology use. Technology acceptance models have evolved to include additional predictors, including individual differences such as age, gender, prior experience with technology, and price/value, as presented in the unified theory of acceptance and use of technology (Venkatesh, Thong, & Xu, 2012). Our own work on technology uptake draws attention to implicit cost-benefit calculations carried out by end-users, including costs such as loss of privacy, expense, reduced efficiency, reduced social interaction, stigma, and training and maintenance requirements and benefits such as enhanced functioning, increased autonomy/independence, reduced burden on others, better health, and enhanced safety (Schulz, 2013).

A central feature of all uptake models is the monetary cost of the technology. Research by Mahoney, Mutschler, Tarlow, and Liss (2008), Bradford, Kleit, Krousel-Wood, and Re (2005), Venkatesh, Thong, and Xu (2012), and Schulz et al. (2014) suggests that a key limiting factor for technology adoption may be cost. In a recent study of a nationally representative sample of U.S. baby boomers and older adults, Schulz and colleagues (2014) found low levels of willingness to pay for technologies that might improve their own functioning and independence. Nearly one third of respondents were not willing to pay anything for technology that would help them with kitchen tasks or personal care when asked to assume that they needed help in these areas. Those willing to pay something were on average willing to pay about $28.00 per month for technology-based assistance with kitchen tasks and $31.00 per month for personal care assistance. The median amount they were willing to pay for both types of technologies was $25 per month.

Our goal in this study was to collect similar data from a national sample of caregivers who were asked about their willingness to pay for such technologies in order to better monitor the everyday activities of their care recipients (CRs). We focused on caregivers because they are a potentially large market for monitoring and assistive technologies. Several large corporations including Intel, General Electric, and Philips have developed home monitoring systems which have the potential of keeping the caregiver informed of the daily activities of the CR (Adler & Mehta, 2014). Based on existing models of technology uptake, we focused on three classes of variables thought to be important predictors of willingness to pay: (a) demographic characteristics of caregivers; (b) caregiving context variables; and (c) attitudes toward and prior experience with technology. We hypothesized that caregivers would be more willing to pay for such technologies than baby boomers or older adults because they had existing as opposed to hypothetical needs which the technology could address, and that that younger caregivers and those with prior technology use and experience would be willing to pay more. In addition, we predicted that caregivers in more demanding caregiving situations (e.g., providing more hours of care per week; caring for someone with Alzheimer's disease [AD]) would be willing to pay more for caregiving technology. Finally, in exploratory analyses we sought to gauge whether or not caregivers felt that these technologies should be an entitlement and, therefore, paid for by the government. Since state and Federal agencies are increasingly involved in providing support to caregivers, we felt it important to assess caregiver expectations with regard to technology for caregivers.