Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments

Nadri, Hamed; Rahimi, Bahlol; Afshar, Hadi Lotfnezhad; Samadbeik, Mahnaz; Garavand, Ali

doi:10.1055/s-0038-1641595

Cited by 58 publications

(41 citation statements)

References 37 publications

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“…This result is consistent with the study by Hoque and Sorwar 37 and is inconsistent with studies by Schomakers et al 44 and Quaosar et al 48 It has been found that social influence has no significant influence on usage behavior, although some researchers have argued about the integrated social influence in models of adoption. 26,[49][50][51] We can conclude that opinions from family members and friends do not affect the decision to adopt mHealth between students because mobile devices and mobile applications are personal and confidential, but in elderly people, social influence factor can be a predictor of mHealth usage because of getting help from family members and friends for using mobile applications. This result is inconsistent with the results of the studies of Quaosar et al 48 and Hoque and Sorwar.…”

Section: Discussionmentioning

confidence: 91%

Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model

et al. 2019

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Background Students with complex health care services process face constant challenges with regard to health education. The mobile devices are an important tool that can install various applications for using information such as clinical guidelines, drug resources, clinical calculations, and the latest scientific evidence without any time and place limitations. And this happens only when students accept and use it. Objective The purpose of this article is to identify the factors influencing students in their intention to use mobile health (mHealth) by using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods A standard questionnaire was used to collect the data from nearly 302 Lorestan University of medical science students including nutrition and public health, paramedicine, nursing and midwifery, pharmacy, dentistry, and medical schools. The data were processed using LISREL (Scientific Software International, Inc., Lincolnwood, Illinois) and SPSS (IBM Corp., Armonk, New York) softwares and the statistical analysis technique was based on structural equation modeling (SEM). Result A total of 300 questionnaires including valid responses were used in this study. The results showed that mediator of age did not affect the predictors of intention to use mHealth, and the level of education and gender directly affected the intention to use. In addition, effort expectancy, facilitating condition, and behavioral intention directly and indirectly have effect on use, whereas the result revealed no significant relationship between two important processes of performance expectancy and social influence with students' behavioral intention to use the mHealth. Conclusions The present study provides valuable information on mobile health acceptance factors for widespread use of this device among students of universities of medical sciences as a base infrastructure for a variety of information about health services and learning. Review and comparison of results with other studies showed that mHealth acceptance factors were different from other end users (elderly, patients, and health professionals).

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Section: Discussionmentioning

confidence: 91%

Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model

et al. 2019

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“…19,20 Also, the TAM is one of the most popular research models to predict use, person's intention to perform a particular behavior, and acceptance of information systems and technology by individual users. 21,22 Originally, the TAM was derived from the social psychological theories of reasonable action (TRA) and planned behavior (TPB), 23 these three models focus on a person's intention to perform the behavior, 24 but the constructs of these three models are different and not exactly the same. The TAM has become the dominant model for investigating factors affecting users' acceptance of novel technical systems.…”

Section: Background and Significancementioning

confidence: 99%

A Systematic Review of the Technology Acceptance Model in Health Informatics

et al. 2018

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Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

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“…Therefore, it is reasonable to construct a research model based on technology acceptance theories, such as TAM, 25 which can explain 60% of technology acceptance. 26 Therefore, this study adopted and extended TAM2 24 to acquire participants' detailed opinions about their acceptance of and satisfaction with telehealth and explore significant factors behind endusers' responses to this program. 24,27 The conceptual framework is shown in ►Fig.…”

Section: Research Design and Frameworkmentioning

confidence: 99%

Factors Affecting Patients' Acceptance of and Satisfaction with Cloud-Based Telehealth for Chronic Disease Management: A Case Study in the Workplace

Huang

et al. 2020

Appl Clin Inform

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Objective Understanding patients' acceptance of and satisfaction with telehealth use is important for workplace health promotion. In this study, we used a questionnaire to measure patients' usage behavior and satisfaction with cloud-based telehealth services in the workplace. We empirically investigated the factors that influence patients' usage and satisfaction based on data collected from 101 participants. Methods As its main research framework, this study utilized a revised version of the technology acceptance model 2 that was based on the telehealth services provided for chronic disease management. Through integrating a cross-sectional research design with an author-developed structured questionnaire that was assessed using reliability and validity tests, an anonymous survey was conducted on selected participants. The proposed research model and hypotheses were validated through path analysis using SPSS. Results We found that users believe telehealth services can promote their workplace health management; that job relevance, result demonstrability, and perceived ease of use (PEOU) positively affect the perceived usefulness (PU), which implies that cognitive instrumental processes have the most significant impact on the PU of cloud-based telehealth; and that both PEOU and PU positively affect the intention to use (IU), but PU has a bigger influence than PEOU on users' intentions to continue using telehealth. In particular, the IU and actual usage behavior were critical to the patients' satisfaction with telehealth services. Conclusion This research contributes to the rapid developing field of technology acceptance research by examining workplace telemedicine engagement. Our results will provide researchers with useful advice and a user-centered strategy for promoting workplace health management, which benefits both health care providers and corporate managers.

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Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments

Cited by 58 publications

References 37 publications

Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model

Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model

A Systematic Review of the Technology Acceptance Model in Health Informatics

Factors Affecting Patients' Acceptance of and Satisfaction with Cloud-Based Telehealth for Chronic Disease Management: A Case Study in the Workplace

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