Dissertation/Thesis Abstract

Predictors of satisfied users of assistive technology
by Warren, Joan E., Ph.D., University of Northern Colorado, 2007, 110; 3280281
Abstract (Summary)

In everyday activities, technology assists us. With so many uses for technology to assist and improve daily lives, further research was beneficial to look at the impact of assistive technology for those with disabilities. From the initial CR4AT study who used AT, 1,118 individuals were used to assess Satisfaction by disability group. Disability groups were those who had mental health issues, cognitive impairments, those who were blind or had low vision, those who were deaf and hard of hearing, and those who classified themselves as having a mobility disability. The purpose of this study was to conduct a correlational research. Two research questions were asked to address the potential for a predictor of Satisfaction with AT. The six characteristics in relation to satisfaction included: (a) the Group the individual belonged to based on their disability; (b) the ethnicity/race of the individual; (c) the education level of the individual; (d) who paid for the AT; (e) the income level of the individual using the AT; as well as, (f) how complicated the AT device was to use. Each of these characteristics were compared to the user's satisfaction to see if any or all of these characteristics could be used as a predictor of AT satisfaction.

Two research questions were asked to address the potential for a predictor of Satisfaction. ANOVA and a Multiple Regression were done ex post facto using secondary data from the initial CR4AT initial study. These methods allowed the researcher to determine the relationship of variables that predict variability in satisfaction based on disability type and to test a model predicting satisfaction with using assistive technology devices.

Results for this study showed that there were no significant characteristics that predicted satisfaction between persons with different disabilities, and a regression model did not significantly predict satisfaction with assistive technology, however, four significant individual effect coded predictors of satisfaction were found in the model (White race, income less than $9,999 per year, less than high school diploma, and some college without a diploma).

Indexing (document details)
Advisor: Scalia, Vinnie
School: University of Northern Colorado
School Location: United States -- Colorado
Source: DAI-B 68/08, Dissertation Abstracts International
Subjects: Health care, Immunology
Keywords: Assistive technology, Disabilities, Satisfied users
Publication Number: 3280281
ISBN: 978-0-549-21494-6
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