Technology Acceptance and Usability of a Mobile Application to Support the Workflow of Health Care Aides who Provide Services to older adults residing in a care facility: A Pilot Mixed Methods Study
ABSTRACT
Background:
Health care aides are unlicensed support personnel who provide direct care, personal assistance and support to people who have health conditions. The shortage of health care aides has been attributed to recruitment challenges, high turnover, an aging population, the COVID-19 pandemic and low retention rates. Mobile applications are one of many information communication technologies (ICTs) that are paving the way for eHealth solutions to help address this workforce shortage by enhancing health care aides' workflow. In collaboration with Clinisys EMR Inc, we developed a mobile application (Mobile Smart Care System (mSCS)) to support the workflow of health care aides who provide services to older adult residents of a long-term care facility.
Objective:
The purpose of this study was to investigate the technology acceptance and usability of a mobile application in a real-world environment, while it is used by health care aides who provide services to older adults.
Methods:
We used a sequential explanatory (QUAN, qual) mixed methods approach. Our study included a pre and post paper-based questionnaire with no control group (QUAN). Toward the end of the study, were conducted two focus groups with a subsample of health care aides (qual, qualitative description design). Technology acceptance and usability questionnaires used a five-point Likert scale ranging from “disagree (1)” to “agree (5)”. The items included in the questionnaires had been validated in earlier research as having high levels of internal consistency for the Unified Theory of Acceptance and Use of Technology (UTAUT) constructs. Sixty (60) health care aides who provide services to older adults as a part of their routine caseloads used the mobile application for one month. Comparisons of the UTAUT constructs summative scores at pre-test and post-test were calculated using a paired t-test. We used the partial least squares structural regression model to determine what factors influenced the mobile application acceptance and usability for health care aides. The alpha level of significance for all the tests was set at P≤.05 (two-tailed).
Results:
We found that: (a) acceptance of the mSCS was high among health care aides; (b) performance expectancy construct was the strongest predictor of intention to use the mSCS; and (c) intention to use the mSCS predicted usage behaviour. The qualitative data support the quantitative findings and showed health care aides’ strong belief that the mSCS was useful, portable and reliable, although there were still opportunities for improvement, especially with regard to the mSCS user interface.
Conclusions:
Overall, these results support the assertion that mSCS technology acceptance and usability was high among health care aides. In other words, the healthcare aides perceived that mSCS assisted them in addressing their workflow issues. Clinical Trial: This is not a RCT
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