Older Adults' and Family Caregivers' Technological Arrangements on Risk of Institutionalization

• We examined whether different family-level arrangements of internet use may affect the risk of institutionalization among older Medicare beneficiaries using multinominal logistic regression and inverse-probability weighted Cox proportional hazard models.

• A total of 15% of care recipients moved from the community to a residential facility (i.e., assisted living, nursing home) between 2015 and 2020.

• The most prevalent technological arrangement in 2015 was the one where neither the care recipient nor their caregiver reported using the internet (44%).

• Relatively disadvantaged older care recipients (e.g., people of color, fewer years of education, less income, worse cognitive functioning) and caregivers (e.g., older, fewer years of education) were more likely to be in a non-internet use arrangement. 

• Older adults who were internet users and had a family caregiver who also used the internet in their caregiving tasks had a much lower risk of relocation.

The internet can be an important resource for older adults to age in place, potentially helping them to seek health information, boost self-management of chronic conditions, facilitate social connections, and buy goods and services. Dynamics in internet use between older adults and their family caregivers may affect both parties involved, but existing studies typically treat them as separate entities. We analyzed the National Health and Aging Trends Study (2015-2020) and National Study on Caregiving (2015) to show that sociodemographic characteristics of older adults and their family caregivers, as well as older adults’ level of cognitive functioning, mostly contributed to the differences in how families used the internet. Findings from the Cox regression model, weighted by the inverse probability of selection into technological arrangements show that having both the care recipient and the caregiver use the internet leads to the best outcome in terms of aging in place. By accounting for caregivers’ technology use in their caregiving tasks, this study foremost contributes to the efforts to describe the heterogeneity of the digital divide in later life. 

Community-dwelling older adults can face considerable challenges while trying to live independently, including staying safe, socially connected, and performing certain activities of daily living on a regular basis1. The internet can be an important resource for older adults to age in place, but health-related difficulties, lack of access and knowledge in the use of technologies preclude many older adults from using the internet2-4. Support from family members may play an important role in older adults’ internet use by setting up and configuring technology, maintaining online security, and solving technical difficulties1,5. Family caregivers’ internet use is also relevant for community-dwelling older adults. Care recipients benefit when their family caregivers use computers, smartphones, and other electronic means to seek health information and make appointments with a health care provider, and coordinate care activities6-7. Approximately half of unpaid caregivers in 2020 used software or went online to help their care recipients, ranging from tracking the care recipient’s finances to searching for services, aids, facilities, or other help9. 

1. To identify groups especially vulnerable to being digitally excluded, this project considers a set of sociodemographic and health characteristics that may be associated with the older care recipients’ own internet use and whether their family caregivers utilize the internet in their caregiving tasks (e.g., to shop, order medicines, or do banking on behalf of the care recipient. 

2. We also examined four categories of technological arrangements between older care recipient and their family caregivers (i.e., no internet use, only caregiver use, only care recipient use, both internet use) and asks how these arrangements may affect older care recipients’ risk of relocation to a residential facility (e.g., assisted living, nursing home). 

The National Health and Aging Trends Study (NHATS) is a nationally representative longitudinal cohort study of Medicare beneficiaries 65 years and older, designed to assess late-life disability and functioning trends through annual in-home interviews. The National Study on Caregiving (NSOC) – conducted in 2011, 2015, and 2017 – is a telephone survey of up to five family and other unpaid caregivers, who assist the NHATS participants with mobility, self-care, household activities, transportation, or medically oriented tasks. We leverage dyadic information on both older adults and their caregivers by linking six rounds of NHATS (2015-2020) to caregiver information in NSOC II (2015). Of 1,458 NHATS care recipients in 2015, we excluded those who resided in assisted living or skilled nursing facilities (n=228), did not have family caregivers (n=42), or missing information on key variables (n=36). The final analytic sample was 1,152 care recipients with information on their 1,667 family caregivers. 

Using a multinomial logistic regression model, we first estimated the associations between individuals’ sociodemographic and health characteristics and technological arrangements in 2015 (i.e., no internet use, caregiver internet use, care recipient internet use, both caregiver and care recipient internet use; “technological arrangements”). Findings from the multinomial logistic regression model were used to construct the inverse probability of selection into each type of technological arrangement. We then applied the inverse probability as weights to a Cox proportional hazard model that assesses the association between the technological arrangement (2015) and care recipients’ risk of institutionalization (2015-2020). This two-step approach allowed us to balance baseline characteristics that confound the association between technological arrangements and institutionalization risks. 

Sample Characteristics

Care recipients were about 82 years old, and the majority were non-Hispanic white, female, had completed high school or more, were living with someone, and rated their health as being fair to average. Approximately 29% reported having gone on the internet to email, shop, do banking, contact medical providers, or visit social network sites in the past month. Caregivers on average were 60 years old, and the majority were female, in good health, had received some college education or more, and were living with the care recipient. About 30% of caregivers reported having used the internet to either shop, order medicines, or do banking on behalf of the care recipient in 2015. 

Caregivers’ and Care-recipients’ Characteristics and Technological Arrangements

Those in a group where neither care recipient nor caregiver used the internet (44%), care recipients were likely to be older, people of color, live in rural areas, have less education, less income, more cognitive impairment, a smaller family care network, and have caregivers who were older and have less education. For those in a group where care recipients did not use the internet but caregivers did (27%), care recipients were likely to be people of color, without a college degree, have cognitive impairment, a larger family care network, and have caregivers who were younger and more educated. For those in a group where care recipients used the internet but caregivers did not (17%), care recipient were likely to be younger, non-Hispanic white, college-educated, and without dementia are more likely to be in an arrangement. For those in a group where both care recipients and caregivers used the internet (12%), care recipients were likely to be younger, non-Hispanic white, college-educated, without dementia, have a larger family care network, and have caregivers who were more educated. 

To better understand how internet-enabled resources may help older adults, this project considered internet use between older care recipients and their caregivers and examined whether different categories of technological arrangements relate to the risk of institutionalization over time. In conclusion, we find that sociodemographic characteristics of older adults and their family caregivers, as well as older adults’ level of cognitive functioning, mostly contributed to the differences in how families used the internet. Conversations around the digital divide have moved beyond the binary notions (i.e., internet use versus non-use) to include a spectrum of skills and outcomes. Research around older adults’ digital inclusion should consider their social surroundings. We also find that older adults who were internet users and whose family caregivers also used the internet in their caregiving tasks showed the lowest risk of moving to a residential facility during the 6-year study period. Social partners play a key role in facilitating older adults’ interaction with internet-enabled resources. Older adults’ social network members recommend or advise against certain technologies, offer support to facilitate and maintain the use of technology, and share their experiences as co-users. Likewise, being embedded in a tech-savvy care network may allow older adults to adopt different types of technology in ways that support their desire to age in place.  

We acknowledge several limitations. The number of web-based service providers has grown exponentially in recent years; for example, on-demand ride-hailing services such as Uber/Lyft have grown dramatically since 2015 as a complementary form of transportation for older adults. This phenomenon is likely not captured by the 2015 data. Moreover, because the NSOC was not conducted annually, our study lacks insights into the mechanisms by which the changes or consistencies in technological arrangements affect older adults’ relocation risks over time. We also acknowledge that we were unable to account for other possible confounders such as individuals’ preferences for living arrangements or geographical characteristics due to data limitations. Future research should confirm the present findings with more detailed information and establish a more specified conceptual framework for capturing the role of social connections in enabling older adults’ access to online resources.

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2. Ang, S., Lim, E., & Malhotra, R. (2020). Health-related difficulty in internet use among older adults: correlates and mediation of its association with quality of life through social support networks. The Gerontologist. https://doi.org/10.1093/geront/gnaa096 

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4. Seifert, A., Cotten, S. R., & Xie, B. (2020). A double burden of exclusion? digital and social exclusion of older adults in times of COVID-19. The Journals of Gerontology: Series B, 76(3), e99-e103. https://doi.org/10.1093/geronb/gbaa098

5. Xie, B., Charness, N., Fingerman, K., Kaye, J., Kim, M. T., & Khurshid, A. (2020). When going digital becomes a necessity: Ensuring older adults’ needs for information, services, and social inclusion during COVID-19. Journal of Aging & Social Policy, 32(4-5), 460-470. https://doi.org/10.1080/08959420.2020.1771237

6. Bangerter, L. R., Griffin, J., Harden, K., & Rutten, L. J. (2019). Health Information–seeking behaviors of family caregivers: Analysis of the Health Information National Trends Survey. JMIR Aging, 2(1), e11237. https://doi.org/10.2196/11237

7. Lindeman, D. A., Kim, K. K., Gladstone, C., & Apesoa-Varano, E. C. (2020). Technology and caregiving: Emerging interventions and directions for research. The Gerontologist, 60(Supplement_1), S41-S49. https://doi.org/10.1093/geront/gnz178

8. AARP. (2020). Caregiving in the U.S. https://www.aarp.org/content/dam/aarp/ppi/2020/05/full-report-caregiving-in-the-united-states.doi.10.26419-2Fppi.00103.001.pdf