This paper is in the following e-collection/theme issue:

Quality/Credibility of eHealth Information and Trust Issues (531)

Published on in Vol 13, No 4 (2011): Oct-Dec

Website Quality, Expectation, Confirmation, and End User Satisfaction: The Knowledge-Intensive Website of the Korean National Cancer Information Center

Website Quality, Expectation, Confirmation, and End User Satisfaction: The Knowledge-Intensive Website of the Korean National Cancer Information Center

Website Quality, Expectation, Confirmation, and End User Satisfaction: The Knowledge-Intensive Website of the Korean National Cancer Information Center

Authors of this article:

Chulmo Koo1 ;   Yulia Wati2 ;   Keeho Park3 ;   Min Kyung Lim3
Article Authors Cited by (28) Tweetations (2) Metrics

Journals

  1. Ghasemaghaei M, Hassanein K. A macro model of online information quality perceptions: A review and synthesis of the literature. Computers in Human Behavior 2016;55:972 View
  2. Kye S, Lee M, Yoo J, Oh K, Jun J. Factors affecting satisfaction with cancer information provided through the social networking services of the National Cancer Information Center in Korea. Epidemiology and Health 2017;39:e2017057 View
  3. Choi J, Shim K. Diagnosis of Advanced Gastric Cancer. The Korean Journal of Helicobacter and Upper Gastrointestinal Research 2013;13(3):133 View
  4. Ghasemaghaei M, Hassanein K. Dynamic model of online information quality perceptions and impacts: a literature review. Behaviour & Information Technology 2019;38(3):302 View
  5. Mitsutake S, Shibata A, Ishii K, Oka K. Association of eHealth Literacy With Colorectal Cancer Knowledge and Screening Practice Among Internet Users in Japan. Journal of Medical Internet Research 2012;14(6):e153 View
  6. Ghasemaghaei M, Hassanein K. Online information quality and consumer satisfaction: The moderating roles of contextual factors – A meta-analysis. Information & Management 2015;52(8):965 View
  7. Shin D, Lee S, Hwang Y. How do credibility and utility play in the user experience of health informatics services?. Computers in Human Behavior 2017;67:292 View
  8. Athanasopoulou C, Hätönen H, Suni S, Lionis C, Griffiths K, Välimäki M. An analysis of online health information on schizophrenia or related conditions: a cross-sectional survey. BMC Medical Informatics and Decision Making 2013;13(1) View
  9. Serrano C, Shah V, Abràmoff M. Use of Expectation Disconfirmation Theory to Test Patient Satisfaction with Asynchronous Telemedicine for Diabetic Retinopathy Detection. International Journal of Telemedicine and Applications 2018;2018:1 View
  10. Biduski D, Bellei E, Rodriguez J, Zaina L, De Marchi A. Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire. Computers in Human Behavior 2020;104:106169 View
  11. Mirabolghasemi M, Iahad N, Ramayah T. Influential Factors in Breast Cancer Patients' Performance Using Malaysian Social Network Support Groups. International Journal of Healthcare Information Systems and Informatics 2019;14(4):73 View
  12. Zhou W, Tsiga Z, Li B, Zheng S, Jiang S. What influence users’ e-finance continuance intention? The moderating role of trust. Industrial Management & Data Systems 2018;118(8):1647 View
  13. Liao G, Chien Y, Chen Y, Hsiung H, Chen H, Hsieh M, Wu W. What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study. JMIR mHealth and uHealth 2017;5(5):e65 View
  14. Wollmann K, der Keylen P, Tomandl J, Meerpohl J, Sofroniou M, Maun A, Voigt-Radloff S. The information needs of internet users and their requirements for online health information—A scoping review of qualitative and quantitative studies. Patient Education and Counseling 2021;104(8):1904 View
  15. Verkijika S. Assessing the Role of Simplicity in the Continuous Use of Mobile Apps. Journal of Organizational and End User Computing 2020;32(4):26 View
  16. Tseng L, Chang J, Zhu Y. What drives the travel switching behavior of Chinese Generation Z consumers. Journal of Tourism Futures 2024;10(1):131 View
  17. Galavi Z, Pourasad M, Norouzi S, Jahani Y, Khajouei R. Public Usage, Perceived Usefulness, and Satisfaction with E-health Services in COVID-19 Pandemic. Journal of Clinical Research in Paramedical Sciences 2023;11(2) View
  18. Nicol K, Lehman K, Carlini J, Tori K, Butler-Henderson K. Patient Expectations: Searching Websites on How to Apply to Access Medical Records. International Journal of Environmental Research and Public Health 2022;19(11):6503 View
  19. Ong A, Prasetyo Y, Sacro M, Artes A, Canonoy M, Onda G, Persada S, Nadlifatin R, Robas K. Determination of factors affecting customer satisfaction towards “maynilad” water utility company: A structural equation modeling-deep learning neural network hybrid approach. Heliyon 2023;9(3):e13798 View
  20. Ju B, Jung Y, Bourgeois J. Seeking Health Information in Wikipedia and Readers' Satisfaction. Proceedings of the Association for Information Science and Technology 2021;58(1):744 View
  21. Khan M, Saleh M. Facebook Users’ Satisfaction and Intention to Continue Using It: Applying the Expectation Confirmation Model. Social Science Computer Review 2023;41(3):983 View
  22. Shah A, Ali M, Qayyum A, Begum A, Han H, Ariza-Montes A, Araya-Castillo L. Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews. International Journal of Environmental Research and Public Health 2021;18(19):9969 View
  23. Ho K, Chou P, Chung M. Comparison of nursing diagnostic accuracy when aided by Knowledge-Based Clinical Decision Support Systems with Clinical Diagnostic Validity and Bayesian Decision Models for psychiatric care plan formulation among nursing students: a quasi-experimental study. BMC Nursing 2023;22(1) View

Books/Policy Documents

  1. Mirabolghasemi M, Iahad N. Information and Communication Technologies for Development. View
  2. Abraham M, Choe P. HCI International 2021 - Late Breaking Papers: Design and User Experience. View