Factors Predicting Decisions About Technology Adoption Among Older Adults

Abstract

Abstract Background and Objectives Numerous technology applications are available that have the potential to improve the quality of life (QoL) of older adults. However, older adults are less likely to adopt new and emerging technologies and reap the potential benefits. This study examines factors that influence older adults’ decisions about the adoption of new technology. Research Design and Methods Fifty-two older adults participated in a mixed-method procedure, which entailed: (1) observing presentations detailing nine differing technologies, (2) assessing the technologies using tailored questionnaires, and (3) participating in focus group discussions. Participants were assigned into one of seven groups separated by age (65–74, 75+) and language (English, Spanish). The outcome was willingness to adopt technology. Predictors included self-assessed abilities (e.g., numeric ability), computer/Internet skills and knowledge, technology readiness, age, language, and technology ratings (e.g., perceived value). Analyses included Spearman’s ρ, t-tests, and regression analysis. Focus group discussions were examined for supportive examples. Results Self-assessed abilities and computer/Internet skills were predictive of willingness to adopt technologies although the relationship varied according to the technology examined. Technology readiness, age, and language group showed weak associations with the outcome. Of the technology ratings, perceived value, confidence in ability to learn the technology, and the perceived impact on QoL were the most robust predictors of willingness to adopt technology. Discussion and Implications Findings indicate that various stakeholders in technology adoption among older adults must be cognizant of a technology’s functionality and complexity as well as the characteristics and abilities of older adults. However, certain factors such as perceptions about the value of the technology and potential impact on QoL are also critically important to decisions regarding technology adoption among older people.