Perceived Technology Usefulness for Caregiving among Unpaid Caregivers: A National Cross-Sectional Study

Matthew Lee Smith^1*Shinduk Lee²Malinee Neelamegam³Deborah Vollmer Dahlke¹Jodi L. Southerland⁴Zachary G Baker⁵Kris (Pui Kwan) Ma⁶Darina V Petrovsky⁷Zahra Rahemi⁸Justine S Sefcik⁹Juanita-Dawne Bacsu¹⁰Chung Lin Kew¹Marcia G Ory¹

• ¹Texas A and M University, College Station, United States
• ²The University of Utah, Salt Lake City, Utah, United States
• ³University of North Texas, Denton, Texas, United States
• ⁴East Tennessee State University, Johnson City, Tennessee, United States
• ⁵Arizona State University, Tempe, Arizona, United States
• ⁶University of Washington, Seattle, Washington, United States
• ⁷Duke University, Durham, North Carolina, United States
• ⁸Clemson University, Clemson, South Carolina, United States
• ⁹Drexel University, Philadelphia, Pennsylvania, United States
• ¹⁰Thompson Rivers University, Kamloops, British Columbia, Canada

Background: Technological advancements have the potential to improve caregiving quality and alleviate caregiver burden by providing tools for real-time communication, monitoring, and care coordination. To assist with technology adoption among the 53 million unpaid caregivers nationwide, efforts are needed to better understand caregivers' perceptions about the usefulness of certain technologies for caregiving. Methods: Data were analyzed from a national sample of 483 unpaid caregivers using an internet-delivered questionnaire. All unpaid caregivers were eligible if they provided at least eight hours of weekly care for a care recipient aged 50 years or older. The primary dependent variable was the Perceived Technology Usefulness for Caregiving (PTUC) Scale, which is a composite score of six items ranging from 0 to 100. PTUC item responses were summed and averaged, and the overall PTUC scores were transformed into statistical tertiles (higher scores indicating more perceived technology usefulness for caregiving). An ordinal regression model was fitted to identify factors associated with higher PTUC tertiles. Results: Across tertiles, unpaid caregivers who were younger (Beta=-0.018, P=0.030) and male (Beta=0.422, P=0.048) reported higher PTUC Scale scores. Compared to non-Hispanic white caregivers, Hispanic/Latino (Beta=0.779, P=0.010), African American (Beta=1.064, P<0.001), and Asian (Beta=0.958, P=0.010) caregivers reported higher PTUC Scale scores. Unpaid caregivers with lower financial insecurity (Beta=-0.010, P=0.003), higher caregiver strain (Beta=0.149, P<0.001), and more satisfaction with the support they receive for caregiving (Beta=0.009, P=0.002) reported higher PTUC Scale scores. Unpaid caregivers whose care recipients had less cognitive impairment reported higher PTUC Scale scores (Beta=-0.245, P=0.048). Conclusion: Findings indicate caregiver characteristics, caregiving dynamics, and available resources (financial and caregiving support) are associated with perceptions about the usefulness of technology for caregiving. The utility of technology for caregiving may be higher among unpaid caregivers with more caregiver strain or positive experiences with caregiving support.