Abstract: Understanding the Role of a Technology Ecosystem to Advance the Quality of Life of Older Adults (Society for Social Work and Research 24th Annual Conference - Reducing Racial and Economic Inequality)

602P Understanding the Role of a Technology Ecosystem to Advance the Quality of Life of Older Adults

Sunday, January 19, 2020
Marquis BR Salon 6 (ML 2) (Marriott Marquis Washington DC)
* noted as presenting author
George Mois, MSW, Research Assistant, University of Georgia, Athens, GA
Tiffany Washington, PhD, Assistant Professor, University of Georgia, Athens, GA
Jenay Beer, PhD, Assistant Professor, University of Georgia, GA
Background and Purpose: Older adults are often consumers of technologies for healthcare, home maintenance, and activities of daily life. They often use multiple assistive technologies, which form a technology ecosystem, to help address a set of challenges affecting single or multiple characteristics of quality of life. Many home and healthcare technologies are designed and advertised as having a positive impact on the users quality of life. However, their use has been primarily studied outside of a technology ecosystem. Quality of life is frequently characterized by purposiveness, self-confidence, and continued engagement to improve health behavior patterns. However, currently little research provides insight on how a technology eco system impacts quality of life. The objective of this study is to investigate how the use of  a technology ecosystem can influence older adults’ quality of life.


Methods: The data used for this study was collected by the 2016 wave of the National Health and Aging Trends Study (NHATS).  A random sample of the Medicare enrollment database through random selection of zip-code clusters across the contiguous United States was selected by the NHATS. The sample includes older adults age 65+ (N=5,488). The dependent variables describing quality of life are: self-confidence, continue improving life, likes living arrangement, and self-determination. These variables were dichotomized. The variables used to measure technology use are: owns and uses a computer, owns and uses a cell phone, owns and uses a tablet, and internet use. Prior to proceeding with the full model,  the data were examined for sample size, outliers, ratio of cases to variables, independence of observations and multicollinearity, using univariate and bivariate analysis across all variables. The data from these variables was analyzed using four logistic regression models to answer the address the study objective.  


Results: Participants were mostly female, predominantly white, aged 70-74, and aging in place. Results indicate that older adults using the internet had higher odds  of self-determination (OR= 1.638, 95%CI=1.387-.1.933 p= .001), like living arrangement (OR= 1.974, 95%CI=1.277-3.051, p= .002), and continue improving life (OR= 1.786, 95%CI=1.508-2.116, p= .001). Older adults using a tablet had higher odds of continuing to improve their life (OR= 1.249, 95%CI=1.079-1.445, p= .003) and increased self-determination (OR= 1.174, 95%CI=1.017-1.355, p= .028). Older adults owning and using a cellphone had higher odds of having self-confidence (OR= 2.814, 95%CI=1.301-6.085, p= .009).


Conclusions and Implications: The findings indicate that the use of assistive technologies (e.g., tablets, internet, and cellphones) may improve the quality of life experienced by older adults, but the type of technology used varied across quality of life characteristic. These findings support the need of a technology ecosystem to improve the specific characteristics and overall quality of life and address challenges face by older adults. Findings can contribute the development of assistive technology educational programs for older adults wanting to age in place. Additionally, findings can contribute to development of social work interventions to improve access to assistive technologies.