Written by Ramin Ravangard, Zhila Kazemi, Somaye Zaker Abbasali, Roxana Sharifian, Hossein Monem
Parent Category: Year 2017, Volume 9
Category: Volume 9, Issue 2, February 2017
Introduction: One of the main stages for achieving the success is acceptance of technology by its users. Hence, identifying the effective factors in successful acceptance of information technology is necessary and vital. One such factor is usability. This study aimed to investigate the software usability in the "Unified Theory of Acceptance and Use of Technology 2 (UTAUT2)" model in patients’ use of medical diagnosis laboratories’ electronic portals in 2015.
Methods: This cross-sectional study was carried out on 170 patients in 2015. A 27-item questionnaire adopted from previous research and the Usability Evaluation questionnaire were used for data collection. Data were analyzed using Structural Equation Modeling (SEM), with Partial Least Squares approach by SPSS 20.0 and Smart-PLS V3.0.
Results: The results showed that the construct of intention to use had significant associations with price value (t-value=2.77), hedonic motivation (t-value=4.46), habit (t-value=1.99) and usability (t-value=5.2), as well as the construct of usage behavior with usability (t-value=3.45) and intention to use (t-value=2.03).
Conclusion: Considering the results of this study, the following recommendations can be made in order for the higher use of portals by the patients: informing patients about the advantages of using these portals, designing portals in a simple and understandable form, increasing the portals’ attractiveness, etc.
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Keywords: Laboratory portal, UTAUT2, Usability, Information technology acceptance
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TDR Clinical Research and Development Fellowships
Call for applications
Deadline for submission: 7 March 2019, 16:00 (GMT)
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Meta-Analysis Workshops in New York, USA, and London, UK, in April and May 2019
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About the Instructor
Dr. Michael Borenstein, one of the authors of Introduction to Meta-Analysis, is widely recognized for his ability to make statistical concepts accessible to researchers as well as to statisticians. He has lectured widely on meta-analysis, including at the NIH, CDC, and FDA. Read more: