Literature DB >> 29500019

Patients' intention to use online postings of ED wait times: A modified UTAUT model.

Jennifer Jewer1.   

Abstract

BACKGROUND: As health care becomes more reliant on technology, a better understanding of the factors that contribute to acceptance and use of technology is now critical. The Unified Theory of Acceptance and Use of Technology (UTAUT) has been applied to study a variety of technologies in different settings, and it is one of the most cited theories in Information Systems (IS) research. However, there has been limited application of UTAUT to health IT and, in particular, to patients' IT use.
OBJECTIVES: The aim of this study is to adapt UTAUT to the context of patient acceptance and use of an Emergency Department (ED) wait-times website, and to empirically test the modified model and compare the results to those of the original UTAUT model. Specifically, it is proposed that there will be a significant relationship between facilitating conditions and behavioral intention.
METHODS: A survey of patients in the ED of a Canadian hospital was conducted, yielding 118 completed surveys, and subsequently analyzed using Partial least squares (PLS).
RESULTS: This study found that the modified UTAUT produced a substantial improvement in variance explained in behavioral intention compared to the original UTAUT (66% versus 46%). The modified-UTAUT model showed significant effects in performance expectancy (r = 0.302, p < 0.01) and facilitating conditions (r = 0.539, p < 0.001) on behavioral intention to use the website, while the effort expectancy impact was not significant.
CONCLUSIONS: This study provides empirical support for the modified-UTAUT in the context of patients' intention to use an ED wait times website. Some results of this study support prior research, while some differ, such as the non-significant relationship between effort expectancy and behavioral intention and the finding that performance expectancy is not the main driver of intention to use. As proposed, facilitating conditions - having the resources necessary to view the website and having the ability to find the website - were the most important factors influencing behavioral intention. UTAUT is a key theoretical advance in IS research and by modifying it to the context of patient use, we contribute to both IS and health research.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Emergency department wait times; Patients; Systems acceptance and use; UTAUT

Mesh:

Year:  2018        PMID: 29500019     DOI: 10.1016/j.ijmedinf.2018.01.008

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  11 in total

1.  Characterizing Consumer Behavior in Leveraging Social Media for E-Patient and Health-Related Activities.

Authors:  Ira Puspitasari; Alia Firdauzy
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2.  Factors Influencing Patients' Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey.

Authors:  Xia Li; Zhiguang Zhou; Yiyu Zhang; Chaoyuan Liu; Shuoming Luo; Yuting Xie; Fang Liu
Journal:  J Med Internet Res       Date:  2019-08-13       Impact factor: 5.428

3.  Patients' perceptions of teleconsultation during COVID-19: A cross-national study.

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Journal:  Technol Forecast Soc Change       Date:  2020-12-07

4.  Modifying UTAUT2 for a cross-country comparison of telemedicine adoption.

Authors:  Anne Schmitz; Ana M Díaz-Martín; Mª Jesús Yagüe Guillén
Journal:  Comput Human Behav       Date:  2022-01-07

5.  Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.

Authors:  Khondker Mohammad Zobair; Louis Sanzogni; Luke Houghton; Md Zahidul Islam
Journal:  PLoS One       Date:  2021-09-24       Impact factor: 3.240

6.  Impact of Actual Use Behavior of Healthcare Wearable Devices on Quality of Life: A Cross-Sectional Survey of People with Dementia and Their Caregivers in Ghana.

Authors:  Ebenezer Larnyo; Baozhen Dai; Abigail Larnyo; Jonathan Aseye Nutakor; Sabina Ampon-Wireko; Edmund Nana Kwame Nkrumah; Ruth Appiah
Journal:  Healthcare (Basel)       Date:  2022-01-30

7.  Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Authors:  Huixian Zha; Kouying Liu; Ting Tang; Yue-Heng Yin; Bei Dou; Ling Jiang; Hongyun Yan; Xingyue Tian; Rong Wang; Weiping Xie
Journal:  BMC Med Inform Decis Mak       Date:  2022-08-19       Impact factor: 3.298

8.  Design and Development of a Scale for Evaluating the Acceptance of Social Robotics for Older People: The Robot Era Inventory.

Authors:  Roberta Bevilacqua; Mirko Di Rosa; Giovanni Renato Riccardi; Giuseppe Pelliccioni; Fabrizia Lattanzio; Elisa Felici; Arianna Margaritini; Giulio Amabili; Elvira Maranesi
Journal:  Front Neurorobot       Date:  2022-07-07       Impact factor: 3.493

9.  Acceptance of E-mental health interventions and its determinants among psychotherapists-in-training during the first phase of COVID-19.

Authors:  Robert Staeck; Marie Drüge; Stefan Albisser; Birgit Watzke
Journal:  Internet Interv       Date:  2022-06-30

10.  Characterizing Wuhan residents' mask-wearing intention at early stages of the COVID-19 pandemic.

Authors:  Min Zhou; Piao Long; Nan Kong; Kathryn S Campy
Journal:  Patient Educ Couns       Date:  2020-12-25
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