Factors Impacting Family Caregivers’ Adoption of Digital and AI-Enabled Technologies for Care-Related Tasks
Niels Wu, Adam Felts, Alexa Balmuth, Chaiwoo Lee, Lisa D’Ambrosio, Samantha Brady, Sophia Ashebir, Joseph Coughlin

TL;DR
This study explores why family caregivers avoid using digital and AI technologies for caregiving, finding that physical strain, income, and care recipient conditions are key factors.
Contribution
The study identifies specific barriers to AI-enabled technology adoption among caregivers, including financial strain, education, and care recipient conditions.
Findings
High physical and financial strain correlates with more technology adoption barriers.
Lower income and education levels are linked to greater difficulty understanding caregiving technologies.
Caregivers for individuals with memory or mental health issues adopt fewer technologies.
Abstract
Family caregivers are critical to the delivery of care for older adults, but may experience physical, financial, and emotional strains from the caregiving role. Although existing research has established the capacity for digital technologies to ease these strains, adoption remains limited for some technologies that could support care-related tasks, especially for newer, AI-enabled technologies, indicating a need to explore where caregivers encounter barriers related to usability, cost, availability, or value. In this study, an online questionnaire was fielded to members of the MIT AgeLab’s CareHive Panel, an open membership panel of informal caregivers who either currently provide or formerly provided care to an adult family member. Current caregivers (n = 192) were asked about their reasons for avoidance or cessation of use for four AI-enabled technologies: home monitoring and security…
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Taxonomy
TopicsTechnology Use by Older Adults · Digital Mental Health Interventions · AI in Service Interactions
