Modeling the adoption of personal health record (PHR) among individual: the effect of health-care technology self-efficacy and gender concern

References

• Arnrich B, Mayora O, Bardram J, et al. Pervasive healthcare: paving the way for a pervasive, user centered and preventive healthcare model. Methods Inf Med. 2010;49(1):1–12.
   Web of Science ®Google Scholar
• Falcao-Reis F, Costa-Pereira A, Correia ME. Access and privacy rights using web security standards to increase patient empowerment. Stud Health Technol Inform. 2008;137:275–285.
   Google Scholar
• Rechel B, Doyle Y, Grundy E, et al. How can health systems respond to population ageing? In: World health organization 2009 and world health organization, on behalf of the European observatory on health systems and policies. Vol. 16. Scherfigsvej, Denmark: WHO Regional Office for Europe; 2009.
   Google Scholar
• Tang PC, Ash JS, Bates DW, et al. Personal health records: definitions, benefits, and strategies for overcoming barriers for adoption. J Am Med Inform Assoc. 2006;13(2):121–126.
   PubMed Web of Science ®Google Scholar
• Zurita L, Nohr C. Patient opinion–EHR assessment from the users perspective. Stud Health Technol Inform. 2004;107(Pt 2):1333–1336.
   Google Scholar
• Schneider JH, Marcus E, Del Beccaro MA. Using personal health records to improve the quality of health care for children. Pediatrics. 2009;124(1):403–409.
   Web of Science ®Google Scholar
• Steinwachs DM, Roter D, Skinner EA, et al. A web-based program to empower patients who have schizophrenia to discuss quality of care with mental health providers. Psychiatr Serv. 2011;62:1296–1302.
   PubMed Web of Science ®Google Scholar
• Liu CF, Tsai YC, Jang FL. Patients’ acceptance towards a web-based personal health record system: an empirical study in Taiwan. Int J Environ Res Public Health. 2013;10:5191–5208.
   PubMed Web of Science ®Google Scholar
• Noblin AM, Wan TT, Fottler M. Intention to use a personal health record: a theoretical analysis using the technology acceptance model. IJHTM. 2013;14(1/2):73.
   Google Scholar
• Jian WS, Shabbir SA, Sood SP, et al. Factors influencing consumer adoption of USB-based personal health records in Taiwan. BMC Health Serv Res. 2012;12(277).
   Web of Science ®Google Scholar
• Vance B, Tomblin B, Studeny J, et al. Benefits and barriers for adoption of personal health records. Business and Health Administration Association Annual Conference, at the 51st Annual Midwest Business Administration Association International Conference; Chicago, IL. 2015.
   Google Scholar
• Venkatesh V, Morris MG, Davis GB, et al. User acceptance of information technology: toward a unified view. MIS Quarterly. 2003;27(3):425–478.
   Web of Science ®Google Scholar
• Burkey R, Kenney B, Kott K, et al. Success or failure: human factors in implementing new systems. 2001. Available from http://net.educause.edu/ir/library/pdf/EDU0152.pdf
   Google Scholar
• Gartrell K, Trinkoff AM, Storr CL, et al. Testing the electronic personal health record acceptance model by nurses for managing their own health. Appl Clin Inform. 2015;6:224–247.
   Web of Science ®Google Scholar
• Whetstone M, Goldsmith R. Factors influencing intention to use personal health records. Int J Pharm Healthc Marketing. 2009;3(1):8–25.
   Google Scholar
• Moon JW, Kim YG. Extending the TAM for a world-wide-web context. Inf Manag. 2001;38(4):217–230.
   Web of Science ®Google Scholar
• Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191e215.
   Web of Science ®Google Scholar
• Compeau DR, Higgins CA. Computer self-efficacy: development of a measure and initial test. MIS Quarterly. 1995;19(2):189e211.
   Web of Science ®Google Scholar
• Johnson RD, Marakas GM. Research report: the role of behavioral modeling in computer skills acquisition: toward refinement of the model. Inf Syst Res. 2000;11(4):402e417.
   Web of Science ®Google Scholar
• Rahman MS, Ko M, Warren J, et al. Healthcare Technology Self-Efficacy (HTSE) and its influence on individual attitude: an empirical study. Comput Human Behav. 2016;58:12–24.
   Web of Science ®Google Scholar
• Anderson CL, Agarwal R. The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information. Inf Syst Res. 2011;22(3):469e490.
   Web of Science ®Google Scholar
• Bansal G, Zahedi F, Gefen D. The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decis Support Syst. 2010;49(2):138e150.
   Web of Science ®Google Scholar
• Holden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159e172.
   Web of Science ®Google Scholar
• Hsu MH, Chiu CM. Internet self-efficacy and electronic service acceptance. Decis Support Syst. 2004;38(3):369e381.
   Web of Science ®Google Scholar
• Stakeholder CI. Perspectives on electronic health record adoption in Taiwan. Manage Rev. 2010;15(1):133–145.
   Google Scholar
• Jian WS, Hsu CY, Hao TH, et al. Building a portable data and information interoperability infrastructure framework for a standard Taiwan electronic medical record template. Comput Methods Programs Biomed. 2007;88:102–111.
   Web of Science ®Google Scholar
• Gefen D, Straub DW. Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Quarterly. 1997;21(4):389–400.
   Web of Science ®Google Scholar
• Chu RJ. How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults: analyses of gender and age differences. Comput Educ. 2010;55(1):255–264.
   Web of Science ®Google Scholar
• Ajzen I. From intentions to actions: A theory of planned behavior. Springer Series in Social Psychology. In: Kuhl J, Beckmann J, editor. Action Control. 1985;2:11–39.
   Google Scholar
• Ajzen I, Fishbein M. Understanding attitudes and predicting social behavior. New Jersey: Prentice-Hall; 1980.
   Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989;13(3):319–340.
   Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci. 2000;46(2):186–204.
   Web of Science ®Google Scholar
• Kowitlawalul Y, Chan SWC, Pulcini J, et al. Factors influencing nursing students’ acceptance of electronic health records for nursing education (EHRNE) software program. Nurse Educ Today. 2015;35:189–194.
   Web of Science ®Google Scholar
• Ortega Egea JM, Roman Gonzalez MV. Explaining physicians’ acceptance of EHCR systems: an extension of TAM with trust and risk factors. Comput Human Behav. 2011;27(1):319–332.
   Web of Science ®Google Scholar
• Lee HH, Chang E. Consumer attitudes toward online mass customization: an application of extended technology acceptance model. J Comput-Mediat Commun. 2011;16(2):171–200.
   Web of Science ®Google Scholar
• Wong CK, Yeung DY, Ho HC, et al. Chinese older adults’ Internet use for health information. J Appl Gerontol. 2012;32(8):1–20.
   Google Scholar
• Yun EK, Park H. Consumers’ disease information-seeking behaviour on the Internet in Korea. J Clin Nurs. 2010;19(19–20):2860–2868.
   PubMed Web of Science ®Google Scholar
• Hsieh HL, Kuo YM, Wang SR, et al. A study of personal health record user’s behavioral model based on the PMT and UTAUT Integrative Perspective. Int J Environ Res Public Health. 2017;14:8.
   Web of Science ®Google Scholar
• Shanko G, Negash S. Mobile healthcare services adoption. Twenty Second European Conference on Information Systems; Tel Aviv. 2014.
   Google Scholar
• Sun Y, Wang N, Guo X, et al. Understanding the acceptance of mobile health services: a comparison and integration of alternative models. J Electron Commerce Res. 2013;14(2):183–200.
   Web of Science ®Google Scholar
• Assadi V, Hassanein K. Consumer adoption of personal health record systems: a self-determination theory perspective. J Med Internet Res. 2017;19:7.
   Web of Science ®Google Scholar
• Vekiri I, Chronaki A. Gender issues in technology use: perceived social support, computer self-efficacy and value beliefs, and computer use beyond school. Computers Educ. 2008;51(3):1392–1404.
   Web of Science ®Google Scholar
• Kekkonen-moneta S, Moneta GB. E-learning in Hong Kong: comparing learning outcomes in online multimedia and lecture versions of an introductory computing course. Br J Educ Technol. 2002;33(4):423–433.
   Web of Science ®Google Scholar
• Uc E, Mh G, Hy L, et al. Intention to use e-government services in Malaysia: perspective of individual users. International Conference on Informatics Engineering and Information Science ICIEIS 2011: Informatics Engineering and Information Science. Springer Berlin Heidelberg. 2011;512–526. doi.org/10.1007/978-3-642-25453-6_43.
   Google Scholar
• Anderson JC, Gerbing DW. Structural equation modeling in practice: a review and recommended two step approach. Psychol Bull. 1998;103:411–423.
   Web of Science ®Google Scholar
• Hair JF, Anderson RE, Tatham RL, et al. Multivariate Data Analysis. NJ: Prentice-Hall, Inc; 1998.
   Google Scholar
• Bagozzi RP, Yi Y. On the evaluation of structural equation models. J Acad Marking Sci. 1988;16:74–94.
   Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Marketing Res. 1981;18:39–50.
   Web of Science ®Google Scholar
• Hair J, Black WC, Babin BJ, et al. Multivariate data analysis. 7th ed. Upper saddle River, New Jersey: Pearson Education International; 2010.
   Google Scholar
• MacKinnon DP. Introduction to statistical mediation analysis. New York: Erlbaum Press; 2008.
   Google Scholar
• Chau PYK, Hu PJH. Information technology acceptance by individual professionals: a model comparison approach. Decis Sci. 2001;32(4):699–719.
   Web of Science ®Google Scholar
• Durndell A, Hagg Z, Laithwaite H. Computer self-efficacy and gender: a cross cultural study of Scotland and Romania. Pers Individ Dif. 2000;28(6):1037–1044.
   Web of Science ®Google Scholar
• Durndell A, Hagg Z. Computer self-efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Comput Human Behav. 2002;18(5):521–535.
   Web of Science ®Google Scholar