Literature DB >> 24141491

Understanding the mediating effects of relationship quality on technology acceptance: an empirical study of e-appointment system.

Shih-Chih Chen1, Shih-Chi Liu, Shing-Han Li, David C Yen.   

Abstract

This study extends the Technology Acceptance Model (TAM) by incorporating relationship quality as a mediator to construct a comprehensive framework for understanding the influence on continuance intention in the hospital e-appointment system. A survey of 334 Taiwanese citizens who were contacted via phone or the Internet and Structural Equation Modeling (SEM) is used for path analysis and hypothesis tests. The study shows that perceived ease of use (PEOU) and perceived usefulness (PU) have significant influence on continuance intention through the mediation of relationship quality, consisting of satisfaction and trust. The direct impact of relationship quality on continuance intention is also significant. The analytical results reveal that the relationship between the hospital, patients and e-appointment users can be improved via enhancing the continued usage of e-appointment. This paper also proposes a general model to synthesize the essence of PEOU, PU, and relationship quality for explaining users' continuous intention of e-appointment.

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Year:  2013        PMID: 24141491     DOI: 10.1007/s10916-013-9981-0

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  10 in total

1.  Mobile computing acceptance factors in the healthcare industry: a structural equation model.

Authors:  Jen-Her Wu; Shu-Ching Wang; Li-Min Lin
Journal:  Int J Med Inform       Date:  2006-08-08       Impact factor: 4.046

2.  Key functional characteristics in designing and operating health information websites for user satisfaction: an application of the extended technology acceptance model.

Authors:  Dohoon Kim; Hyejung Chang
Journal:  Int J Med Inform       Date:  2006-10-17       Impact factor: 4.046

3.  Physicians and electronic health records: a statewide survey.

Authors:  Steven R Simon; Rainu Kaushal; Paul D Cleary; Chelsea A Jenter; Lynn A Volk; E John Orav; Elisabeth Burdick; Eric G Poon; David W Bates
Journal:  Arch Intern Med       Date:  2007-03-12

4.  An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry.

Authors:  Feng-Cheng Tung; Su-Chao Chang; Chi-Min Chou
Journal:  Int J Med Inform       Date:  2007-07-23       Impact factor: 4.046

5.  Testing the technology acceptance model for evaluating healthcare professionals' intention to use an adverse event reporting system.

Authors:  Jen-Her Wu; Wen-Shen Shen; Li-Min Lin; Robert A Greenes; David W Bates
Journal:  Int J Qual Health Care       Date:  2008-01-25       Impact factor: 2.038

Review 6.  Technology acceptance among physicians: a new take on TAM.

Authors:  Amy K Yarbrough; Todd B Smith
Journal:  Med Care Res Rev       Date:  2007-08-23       Impact factor: 3.929

7.  Using a modified technology acceptance model in hospitals.

Authors:  Vassilios P Aggelidis; Prodromos D Chatzoglou
Journal:  Int J Med Inform       Date:  2008-08-03       Impact factor: 4.046

8.  Integrating technology readiness into the expectation-confirmation model: an empirical study of mobile services.

Authors:  Shih-Chih Chen; Ming-Ling Liu; Chieh-Peng Lin
Journal:  Cyberpsychol Behav Soc Netw       Date:  2013-06-21

9.  Evaluation of teledermatology adoption by health-care professionals using a modified Technology Acceptance Model.

Authors:  Estibalitz Orruño; Marie Pierre Gagnon; José Asua; Anis Ben Abdeljelil
Journal:  J Telemed Telecare       Date:  2011-08-15       Impact factor: 6.184

Review 10.  The technology acceptance model: its past and its future in health care.

Authors:  Richard J Holden; Ben-Tzion Karsh
Journal:  J Biomed Inform       Date:  2009-07-15       Impact factor: 6.317

  10 in total
  11 in total

1.  A Systematic Review of the Technology Acceptance Model in Health Informatics.

Authors:  Bahlol Rahimi; Hamed Nadri; Hadi Lotfnezhad Afshar; Toomas Timpka
Journal:  Appl Clin Inform       Date:  2018-08-15       Impact factor: 2.342

2.  Assessing the relationship between technology readiness and continuance intention in an E-appointment system: relationship quality as a mediator.

Authors:  Shih-Chih Chen; Din Jong; Min-Tsai Lai
Journal:  J Med Syst       Date:  2014-07-10       Impact factor: 4.460

3.  Barriers and Facilitators to Automated Self-Scheduling: Consensus from a Delphi Panel of Key Stakeholders.

Authors:  Elizabeth Woodcock
Journal:  Perspect Health Inf Manag       Date:  2022-01-01

4.  Feasibility study of a sensor-based autonomous load control exercise training system for COPD patients.

Authors:  Bianying Song; Marcus Becker; Matthias Gietzelt; Reinhold Haux; Martin Kohlmann; Mareike Schulze; Uwe Tegtbur; Klaus-Hendrik Wolf; Michael Marschollek
Journal:  J Med Syst       Date:  2014-11-16       Impact factor: 4.460

Review 5.  Web-Based Medical Appointment Systems: A Systematic Review.

Authors:  Peng Zhao; Illhoi Yoo; Jaie Lavoie; Beau James Lavoie; Eduardo Simoes
Journal:  J Med Internet Res       Date:  2017-04-26       Impact factor: 5.428

6.  Features of Online Hospital Appointment Systems in Taiwan: A Nationwide Survey.

Authors:  Po-Chin Yang; Feng-Yuan Chu; Hao-Yen Liu; Mei-Ju Shih; Tzeng-Ji Chen; Li-Fang Chou; Shinn-Jang Hwang
Journal:  Int J Environ Res Public Health       Date:  2019-01-09       Impact factor: 3.390

7.  The Determinants for Food Safety Push Notifications on Continuance Intention in an E-Appointment System for Public Health Medical Services: The Perspectives of UTAUT and Information System Quality.

Authors:  Yu-Ping Lee; Hsin-Yeh Tsai; Athapol Ruangkanjanases
Journal:  Int J Environ Res Public Health       Date:  2020-11-09       Impact factor: 3.390

Review 8.  Barriers to and Facilitators of Automated Patient Self-scheduling for Health Care Organizations: Scoping Review.

Authors:  Elizabeth W Woodcock
Journal:  J Med Internet Res       Date:  2022-01-11       Impact factor: 5.428

9.  Understanding Continuance Intention Determinants to Adopt Online Health Care Community: An Empirical Study of Food Safety.

Authors:  Jinxin Yang; Din Jong
Journal:  Int J Environ Res Public Health       Date:  2021-06-17       Impact factor: 3.390

10.  Questionnaire survey about use of an online appointment booking system in one large tertiary public hospital outpatient service center in China.

Authors:  MinMin Zhang; CongXin Zhang; QinWen Sun; QuanCai Cai; Hua Yang; YinJuan Zhang
Journal:  BMC Med Inform Decis Mak       Date:  2014-06-09       Impact factor: 2.796

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