Published on 02.11.11 in Vol 13, No 4 (2011): Oct-Dec
Works citing "Website Quality, Expectation, Confirmation, and End User Satisfaction: The Knowledge-Intensive Website of the Korean National Cancer Information Center"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.1574):
(note that this is only a small subset of citations)
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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
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Kye SY, Lee MH, Yoo J, Oh KH, Jun JK. 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
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Choi JY, Shim K. Diagnosis of Advanced Gastric Cancer. The Korean Journal of Helicobacter and Upper Gastrointestinal Research 2013;13(3):133
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Ghasemaghaei M, Hassanein K. Dynamic model of online information quality perceptions and impacts: a literature review. Behaviour & Information Technology 2019;38(3):302
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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
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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
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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
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Athanasopoulou C, Hätönen H, Suni S, Lionis C, Griffiths KM, 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)
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Serrano CI, Shah V, Abràmoff MD. 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
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Biduski D, Bellei EA, Rodriguez JPM, Zaina LAM, De Marchi ACB. 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
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Mirabolghasemi M, Iahad NA, 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
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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
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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
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Wollmann K, der Keylen PV, Tomandl J, Meerpohl JJ, 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
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. Assessing the Role of Simplicity in the Continuous Use of Mobile Apps. Journal of Organizational and End User Computing 2020;32(4):26
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Tseng L, Chang J, Zhu YL. What drives the travel switching behavior of Chinese Generation Z consumers. Journal of Tourism Futures 2021;
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Galavi Z, Pourasad MH, 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)
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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
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Ong AKS, Prasetyo YT, Sacro MCC, Artes AL, Canonoy MPM, Onda GKD, Persada SF, Nadlifatin R, Robas KPE. 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
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Ju B, Jung Y, Bourgeois JP. Seeking Health Information in Wikipedia and Readers' Satisfaction. Proceedings of the Association for Information Science and Technology 2021;58(1):744
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Khan MI, Saleh MA. Facebook Users’ Satisfaction and Intention to Continue Using It: Applying the Expectation Confirmation Model. Social Science Computer Review 2023;41(3):983
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Shah AM, 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
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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)
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.1574):