Abstract

Socially assistive robots (SAR) are autonomous machines equipped with sensors and software that allow them to interact socially with humans. SAR robots are commonly used in healthcare settings to provide patients with non-clinical support, such as conversation and emotional companionship. SARs can also deliver reminders, monitor vital signs, and provide educational information about health conditions or medications. Researchers have studied SAR applications in detail. Additionally, there has been prior research on SAR where users' sociodemographic factors and technology acceptance were studied. But even though the backbone of SAR is an advanced technology, no known research has been done on users' technology adoption propensity and SAR features. Hence, this quantitative study focuses on SAR users' technology adoption propensity index and SAR robot features.

This study will use a quantitative approach to collect data from hospital nurses regarding SARs. The data will be collected through surveys. The outcomes of this study can be used to enhance the design of SARs and their applications in hospitals. The importance of this study is twofold. First, this study will contribute to the research on using SARs in a hospital setting. Second, this study will provide insights into the design of SARs and their applications. This study can potentially improve the quality of life for nurses using SARs for patient care in hospital settings.

Library of Congress Subject Headings

Robotics in medicine; Patient-centered health care

Date of Award

2023

School Affiliation

Graduate School of Education and Psychology

Department/Program

Education

Degree Type

Dissertation

Degree Name

Doctorate

Faculty Advisor

Doug Leigh

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