Capturing multiple assistive technology use and its impact in later life: lessons learned from distinct measurement approaches

PurposeAssistive technology (AT) use is prevalent in older adulthood and can accommodate activity difficulties to support well-being. However, within the context of multiple activity difficulties and multiple technology use, it is unclear how to best assess their combined effects on older adults' health outcomes. This study proposed four distinct approaches to quantify multiple AT use and examined their respective impact in later life.Material and methodsUsing data from the 2015 round of the National Health and Aging Trends Study (n = 6,936), we compared four indices to summarize the state of multiple AT use among the U.S. older population: binary, item-specific, cumulative, and accommodative. Separate regression analyses tested the impact of each index on older adults' well-being and restricted participation in meaningful activities.ResultsIn 2015, 59.9% of the respondents were identified as AT users. Among these users, 53.8% reported using two or more technologies when performing daily self-care and mobility activities. The implications of multiple AT use for health outcomes varied across the four indices. Approaches that captured elements of person-technology fit provided the most nuanced and actionable insights on the benefits of using AT to support well-being.ConclusionsATs were commonly adopted by older adults in everyday activities. Overall, findings suggest that there are multiple approaches to conceptualize the independent, cumulative, or balanced effects of multiple AT use. Each measurement approach has unique implications for understanding the impacts of using ATs on older adults' health outcomes. Multiple assistive technology (AT) use is observed and prevalent in later life, highlighting that there is great need for older adults to deploy different technologies to help with different daily activities.The concept of multiple AT use can be approached in various ways (e.g., where effects of each AT are independent, cumulative, or dependent on fit), with each conceptualization based on distinct assumptions and capable of serving different purposes in rehabilitation research.This study demonstrates that information on person-technology fit plays a critical role in helping rehabilitation engineers and clinical practitioners assess the effects of AT use on health and well-being outcomes among older adults.