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Sustaining Patient Portal Continuous Use Intention and Enhancing Deep Structure Usage: Cognitive Dissonance Effects of Health Professional Encouragement and Security Concerns

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Abstract

Sustaining patient portal use is a major problem for many healthcare organizations and providers. If this problem can be successfully addressed, it could have a positive impact on various stakeholders. Through the lens of cognitive dissonance theory, this study investigates the role of health professional encouragement as well as patients’ security concerns in influencing continuous use intention and deep structure usage among users of a patient portal. The analysis of data collected from 177 patients at a major medical center in the Midwestern region of the United States shows that health professional encouragement helps increase the continuous use intention and deep structure usage of the patient portal, while security concerns impede them. Interestingly, health professional encouragement not only has a direct positive influence on continuous use intention and deep structure usage but also lowers the negative impact of security concerns on them. The research model explains a substantial variance in continuous use intention (i.e., 40%) and deep structure usage (i.e., 32%). The paper provides theoretical implications as well as practical implications to healthcare managers and providers to improve patient portal deep structure usage and sustained use for user retention.

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References

  • Abd-alrazaq, A. A., Bewick, B. M., Farragher, T., and Gardner, P. (2019). "factors that affect the use of electronic personal health records among patients: A systematic review," International Journal of Medical Informatics (126), pp. 164-175.

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

    Article  Google Scholar 

  • Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324.

    Article  Google Scholar 

  • Ajzen, I., & Fishbein, M. (1972). Attitudes and normative beliefs as factors influencing behavioral intentions. Journal of Personality and Social Psychology, 21(1), 1–9.

    Article  Google Scholar 

  • Akareem, H. S., Ferdous, A. S., and Todd, M. (forthcoming). "Impact of patient portal behavioral engagement on subsistence consumers' wellbeing," International Journal of Research in Marketing).

  • Alhudaithy, A. I., & Kitchen, P. J. (2009). Rethinking models of technology adoption for internet banking: The role of website features. Journal of Financial Services Marketing, 14(1), 56–69.

    Article  Google Scholar 

  • Ancker, J. S., Barrón, Y., Rockoff, M. L., Hauser, D., Pichardo, M., Szerencsy, A., & Calman, N. (2011). Use of an electronic patient portal among disadvantaged populations. Journal of General Internal Medicine, 26(10), 1117–1123.

    Article  Google Scholar 

  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.

    Article  Google Scholar 

  • Anthony, D. L., Campos-Castillo, C., & Lim, P. S. (2018). Who isn’t using patient portals and why? Evidence and implications from a national sample of US adults. Health Affairs, 37(12), 1948–1954.

    Article  Google Scholar 

  • Archer, N., & Cocosila, M. (2014). Canadian patient perceptions of electronic personal health records: An empirical investigation. Communications of the Association for Information Systems, 34(20), 390–406.

    Google Scholar 

  • Bajracharya, A. S., Crotty, B. H., Kowoloff, H. B., Safran, C., & Slack, W. V. (2019). Patient experience with family history tool: Analysis of patients’ experience sharing their family health history through patient-computer dialogue in a patient portal. Journal of the American Medical Informatics Association, 26(7), 603–609.

    Article  Google Scholar 

  • Bera, A. K., & Jarque, C. M. (1981). Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo evidence. Economics Letters, 7(4), 313–318.

    Article  Google Scholar 

  • Bodenheimer, T., & Grumbach, K. (2003). Electronic technology: A spark to revitalize primary care? JAMA, 290(2), 259–264.

    Article  Google Scholar 

  • Bollen, K. A. (1984). Multiple indicators: Internal consistency or no necessary relationship? Quality and Quantity, 18(4), 377–385.

    Article  Google Scholar 

  • Bozan, K., Davey, B., & Parker, K. (2015). Social influence on health IT adoption patterns of the elderly: An institutional theory based use behavior approach. Procedia Computer Science, 63, 517–523.

    Article  Google Scholar 

  • Bozan, K., Parker, K., and Davey, B. (2016). "a closer look at the social influence construct in the UTAUT model: An institutional theory based approach to investigate health IT adoption patterns of the elderly," 2016 49th Hawaii International Conference on System Sciences (HICSS): IEEE, pp. 3105-3114.

  • Burton-Jones, A., & Straub Jr., D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246.

    Article  Google Scholar 

  • Butler, J., Speroff, T., Arbogast, P. G., Newton, M., Waitman, L. R., Stiles, R., Miller, R. A., Ray, W., & Griffin, M. R. (2006). Improved compliance with quality measures at hospital discharge with a computerized physician order entry system. American Heart Journal, 151(3), 643–653.

    Article  Google Scholar 

  • Byczkowski, T. L., Munafo, J. K., & Britto, M. T. (2014). Family perceptions of the usability and value of chronic disease web-based patient portals. Health Informatics Journal, 20(2), 151–162.

    Article  Google Scholar 

  • Cantor, J. D. (2001). Privacy protections for cybercharts: An update on the law. JAMA, 285(13), 1767–1767.

    Article  Google Scholar 

  • Chi, H., Yeh, H., & Hung, W.-C. (2012). The moderating effect of subjective norm on cloud computing users' perceived risk and usage intention. International Journal of Marketing Studies, 4(6), 95–102.

    Article  Google Scholar 

  • Chin, W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.

    Google Scholar 

  • Collins, S. A., Rozenblum, R., Leung, W. Y., Morrison, C. R., Stade, D. L., McNally, K., Bourie, P. Q., Massaro, A., Bokser, S., & Dwyer, C. (2017). Acute care patient portals: A qualitative study of stakeholder perspectives on current practices. Journal of the American Medical Informatics Association, 24(e1), e9–e17.

    Article  Google Scholar 

  • Cooper, J. (2007). Cognitive dissonance: 50 years of a classic theory. Sage.

  • Crotty, B. H., Winn, A. N., Asan, O., Nagavally, S., Walker, R. J., & Egede, L. E. (2019). Clinician encouragement and online health record usage. Journal of General Internal Medicine, 34(11), 2345–2347.

    Article  Google Scholar 

  • Dai, H., and Chen, Y. (2015). "effects of exchange benefits, security concerns and situational privacy concerns on mobile commerce adoption," journal of International Technology and Information Management (24:3), pp. 41-56.

  • Davis, F., Bagozzi, R., & Warshaw, P. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of Applied Social Psychology, 22(14), 1111–1132.

    Article  Google Scholar 

  • Detmer, D., Bloomrosen, M., Raymond, B., & Tang, P. (2008). Integrated personal health records: Transformative tools for consumer-centric care. BMC Medical Informatics and Decision Making, 8(1), 1–14.

    Article  Google Scholar 

  • Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.

    Article  Google Scholar 

  • Elston Lafata, J., Miller, C. A., Shires, D. A., Dyer, K., Ratliff, S. M., & Schreiber, M. (2018). Patients' adoption of and feature access within electronic patient portals. The American Journal of Managed Care, 24(11), e352–e357.

    Google Scholar 

  • Emani, S., Healey, M., Ting, D. Y., Lipsitz, S. R., Ramelson, H., Suric, V., and Bates, D. W. (2016). "awareness and use of the after-visit summary through a patient portal: Evaluation of patient characteristics and an application of the theory of planned behavior," Journal of Medical Internet Research (18:4), p. e77.

  • Emani, S., Peters, E., Desai, S., Karson, A. S., Lipsitz, S. R., LaRocca, R., Stone, J., Suric, V., Wald, J. S., & Wheeler, A. (2018). Perceptions of adopters versus non-adopters of a patient portal: An application of diffusion of innovation theory. BMJ Health & Care Informatics, 25(3), 149–157.

    Article  Google Scholar 

  • Fagerström, K.-O. (1984). Effects of nicotine chewing gum and follow-up appointments in physician-based smoking cessation. Preventive Medicine, 13(5), 517–527.

    Article  Google Scholar 

  • Featherman, M. S., Miyazaki, A. D., & Sprott, D. E. (2010). Reducing online privacy risk to facilitate e-service adoption: The influence of perceived ease of use and corporate credibility. Journal of Services Marketing, 24(3), 219–229.

    Article  Google Scholar 

  • Federal Reserve. (2016). "consumers and mobile financial services 2016," Board of Governors of the Federal Reserve System).

  • Festinger, L. (1957). Cognitive dissonance theory. Stanford University Press.

  • Festinger, L. (1962). Cognitive dissonance. Scientific American, 207(4), 93–106.

    Article  Google Scholar 

  • Figl, K., Kießling, S., Rank, C., & Vakulenko, S. (2019). Fake news flags, cognitive dissonance, and the believability of social media posts (pp. 1–9). International Conference on Information Systems.

  • Fishbein, M. (1979). A theory of reasoned action: Some applications and implications. Nebraska Symposium on Motivatio, 27, 65–116.

    Google Scholar 

  • Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

  • Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  • Fotuhi, O., Fong, G. T., Zanna, M. P., Borland, R., Yong, H.-H., & Cummings, K. M. (2013). Patterns of cognitive dissonance-reducing beliefs among smokers: A longitudinal analysis from the international tobacco control (ITC) four country survey. Tobacco Control, 22(1), 52–58.

    Article  Google Scholar 

  • Fowles, J. B., Kind, A. C., Craft, C., Kind, E. A., Mandel, J. L., & Adlis, S. (2004). Patients' interest in reading their medical record: Relation with clinical and sociodemographic characteristics and patients' approach to health care. Archives of Internal Medicine, 164(7), 793–800.

    Article  Google Scholar 

  • Fraccaro, P., Vigo, M., Balatsoukas, P., Buchan, I. E., Peek, N., & van der Veer, S. N. (2018). The influence of patient portals on users’ decision making is insufficiently investigated: A systematic methodological review. International Journal of Medical Informatics, 111, 100–111.

    Article  Google Scholar 

  • Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 91–109.

    Google Scholar 

  • Gel, Y. R., & Gastwirth, J. L. (2008). A robust modification of the Jarque–Bera test of normality. Economics Letters, 99(1), 30–32.

    Article  Google Scholar 

  • Goel, M. S., Brown, T. L., Williams, A., Cooper, A. J., Hasnain-Wynia, R., and Baker, D. W. (2011a). "patient reported barriers to enrolling in a patient portal," Journal of the American Medical Informatics Association (18:Supplement 1), pp. i8-i12.

  • Goel, M. S., Brown, T. L., Williams, A., Hasnain-Wynia, R., Thompson, J. A., & Baker, D. W. (2011b). Disparities in enrollment and use of an electronic patient portal. Journal of General Internal Medicine, 26(10), 1112–1116.

    Article  Google Scholar 

  • Hair, J., Black, W., Babin, B., and Anderson, R. (2010). Multivariate data analysis. Upper Saddle River, N.J.; London: Pearson.

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152.

    Article  Google Scholar 

  • Heath, S. (2018a). "patient portal access, use reach 52% of healthcare consumers." Patient Data Acceess News retrieved 10/29/2019, 2019, from https://patientengagementhit.com/news/patient-portal-access-use-reach-52-of-healthcare-consumers

  • Heath, S. (2018b). "patient portal adoption tops 90%, but strong patient use is needed." Patient Data Access News retrieved 10/29/2019, 2019, from https://patientengagementhit.com/news/patient-portal-adoption-tops-90-but-strong-patient-use-is-needed

  • Heath, S. (2020). "Was COVID-19 healthcare’s use case for the patient portal?" Patient Data Access News Retrieved 10/24/2020, 2020, from https://patientengagementhit.com/features/was-covid-19-healthcares-use-case-for-the-patient-portal

  • Hoogenbosch, B., Postma, J., Janneke, M., Tiemessen, N. A., van Delden, J. J., and van Os-Medendorp, H. (2018). "use and the users of a patient portal: Cross-sectional study," Journal of Medical Internet Research (20:9), p. e262.

  • Hsu, C., Lee, M.-R., and Su, C.-H. (2013). "the role of privacy protection in healthcare information systems adoption," Journal of Medical Systems (37:5), p. 9966.

  • Hsu, J., Huang, J., Kinsman, J., Fireman, B., Miller, R., Selby, J., & Ortiz, E. (2005). Use of e-health services between 1999 and 2002: A growing digital divide. Journal of the American Medical Informatics Association, 12(2), 164–171.

    Article  Google Scholar 

  • Huvila, I., Enwald, H., Eriksson-Backa, K., Hirvonen, N., Nguyen, H., & Scandurra, I. (2018). Anticipating ageing: Older adults reading their medical records. Information Processing & Management, 54(3), 394–407.

    Article  Google Scholar 

  • Ifinedo, P. (2012). Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory. Computers & Security, 31(1), 83–95.

    Article  Google Scholar 

  • Irizarry, T., Dabbs, A. D., and Curran, C. R. (2015). "patient portals and patient engagement: A state of the science review," Journal of Medical Internet Research (17:6), p. e148.

  • Kay, R. (2008). "exploring gender differences in computer-related behaviour: Past, present, and future," in Social information technology: Connecting society and cultural issues. Hershey, PA: IGI Global, pp. 12–30.

  • Kim, J., and Park, H.-A. (2012). "development of a health information technology acceptance model using consumers’ health behavior intention," Journal of Medical Internet Research (14:5), p. e133.

  • Kock, N. (2014). Advanced mediating effects tests, multi-group analyses, and measurement model assessments in PLS-based SEM. International Journal of e-Collaboration (IJeC), 10(1), 1–13.

    Article  Google Scholar 

  • Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10.

    Article  Google Scholar 

  • Kock, N., & Lynn, G. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546–580.

    Article  Google Scholar 

  • Kock, N., & Mayfield, M. (2015). PLS-based SEM algorithms: The good neighbor assumption, collinearity, and nonlinearity. Information Management and Business Review, 7(2), 113–130.

    Article  Google Scholar 

  • Kock, N., Moqbel, M., Barton, K., & Bartelt, V. (2016). Intended continued use of social networking sites: Effects on job satisfaction and performance. International Journal of Virtual Communities and Social Networking, 8(2), 28–46.

    Article  Google Scholar 

  • Kruse, C. S., Argueta, D. A., Lopez, L., and Nair, A. (2015a). "patient and provider attitudes toward the use of patient portals for the management of chronic disease: A systematic review," Journal of Medical Internet Research (17:2).

  • Kruse, C. S., Bolton, K., and Freriks, G. (2015b). "the effect of patient portals on quality outcomes and its implications to meaningful use: A systematic review," Journal of Medical Internet Research (17:2).

  • Li, H., Gupta, A., Zhang, J., & Sarathy, R. (2014). Examining the decision to use standalone personal health record systems as a trust-enabled fair social contract. Decision Support Systems, 57, 376–386.

    Article  Google Scholar 

  • Lian, J.-W., & Lin, T.-M. (2008). Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types. Computers in Human Behavior, 24(1), 48–65.

    Article  Google Scholar 

  • Liu, L., and Zhang, Y. (2014). "Enhancing teachers' professional development through reflective teaching," Theory and Practice in Language Studies (4:11), p. 2396.

  • Lowry, P., Gaskin, J., & Moody, G. (2015). Proposing the multi-motive information systems continuance model (MISC) to better explain end-user system evaluations and continuance intentions. Journal of the Association for Information Systems, 16(7), 515–579.

    Article  Google Scholar 

  • Lunney, A., Cunningham, N. R., & Eastin, M. S. (2016). Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114–120.

    Article  Google Scholar 

  • Marikyan, D., Papagiannidis, S., and Alamanos, E. (2020). "cognitive dissonance in technology adoption: A study of smart home users," Information Systems Frontiers), pp. 1-23.

  • McMaster, C., & Lee, C. (1991). Cognitive dissonance in tobacco smokers. Addictive Behaviors, 16(5), 349–353.

    Article  Google Scholar 

  • Merhi, M., Hone, K., & Tarhini, A. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust. Technology in Society, 59, 101151.

    Article  Google Scholar 

  • Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer Affairs, 35(1), 27–44.

    Article  Google Scholar 

  • Moqbel, M. (2012). Understanding workplace adoption of social networking sites: Employers’ perspective. Studies in Business and Economics, 16, 37–54.

    Article  Google Scholar 

  • Moqbel, M., Rahman, M., Cho, Y., & Hewitt, B. (2020). Sustaining patient engagement: The role of health emotion and personality traits in patient portal continuous use decision. AIS Transactions on Human-Computer Interaction, 12(4), 172–198.

    Article  Google Scholar 

  • Mukherjee, A., & Nath, P. (2003). A model of trust in online relationship banking. International Journal of Bank Marketing, 21(1), 5–15.

    Article  Google Scholar 

  • Nah, F. F.-H., & Tan, X. (2015). An emergent model of end-users' acceptance of enterprise resource planning systems: A grounded theory approach. Journal of Database Management, 26(4), 44–66.

    Article  Google Scholar 

  • Nicholas, D., Huntington, P., & Williams, P. (2003). Three years of digital consumer health information: A longitudinal study of the touch screen health kiosk. Information Processing & Management, 39(3), 479–502.

    Article  Google Scholar 

  • O’Connor, Y., & O’Reilly, P. (2018). Examining the infusion of mobile technology by healthcare practitioners in a hospital setting. Information Systems Frontiers, 20(6), 1297–1317.

    Article  Google Scholar 

  • Otte-Trojel, T., Bont, A. d., Aspria, M., Adams, S., Rundall, T. G., & Klundert, J. v. d., and Mul, M. d. (2015). Developing patient portals in a fragmented healthcare system. International Journal of Medical Informatics, 84(10), 835–846.

    Article  Google Scholar 

  • Otte-Trojel, T., de Bont, A., Rundall, T. G., & van de Klundert, J. (2016). What do we know about developing patient portals? A systematic literature review. Journal of the American Medical Informatics Association, 23(e1), e162–e168.

    Article  Google Scholar 

  • Patel, V., Barker, W., and Siminerio, E. (2015). "trends in consumer access and use of electronic health information," U.S. Department of Health and Human Services, HealthIT.gov dashboard.

  • Patel, V., & Johnson, C. (2018). Individuals’ use of online medical records and technology for health needs. The Office of the National Coordinator.

  • Pederson, L. L., Baskerville, J. C., & Wanklin, J. M. (1982). Multivariate statistical models for predicting change in smoking behavior following physician advice to quit smoking. Preventive Medicine, 11(5), 536–549.

    Article  Google Scholar 

  • Portz, J. D., Brungardt, A., Shanbhag, P., Staton, E. W., Bose-Brill, S., Lin, C.-T., Kutner, J. S., and Lum, H. D. (2020). "advance care planning among users of a patient portal during the COVID-19 pandemic: Retrospective observational study," Journal of Medical Internet Research (22:8), p. e21385.

  • Raghu, T. S., Frey, K., Chang, Y.-H., Cheng, M.-R., Freimund, S., & Patel, A. (2015). Using secure messaging to update medications list in ambulatory care setting. International Journal of Medical Informatics, 84(10), 754–762.

    Article  Google Scholar 

  • Rathert, C., Porter, T. H., Mittler, J. N., & Fleig-Palmer, M. (2019). Seven years after meaningful use: Physicians’ and nurses’ experiences with electronic health records. Health Care Management Review, 44(1), 30–40.

    Article  Google Scholar 

  • Razmak, J., & Bélanger, C. (2018). Using the technology acceptance model to predict patient attitude toward personal health records in regional communities. Information Technology & People, 31, 306–326.

    Article  Google Scholar 

  • Roblin, D. W., Houston, T. K., Allison, J. J., Joski, P. J., & Becker, E. R. (2009). Disparities in use of a personal health record in a managed care organization. Journal of the American Medical Informatics Association, 16(5), 683–689.

    Article  Google Scholar 

  • Sakaguchi-Tang, D. K., Bosold, A. L., Choi, Y. K., and Turner, A. M. (2017). "patient portal use and experience among older adults: Systematic review," JMIR Medical Informatics (5:4), p. e38.

  • Sarkar, U., Karter, A. J., Liu, J. Y., Adler, N. E., Nguyen, R., López, A., & Schillinger, D. (2010). The literacy divide: Health literacy and the use of an internet-based patient portal in an integrated health system—Results from the diabetes study of northern California (DISTANCE). Journal of Health Communication, 15(S2), 183–196.

    Article  Google Scholar 

  • Sarkar, U., Karter, A. J., Liu, J. Y., Adler, N. E., Nguyen, R., López, A., & Schillinger, D. (2011). Social disparities in internet patient portal use in diabetes: Evidence that the digital divide extends beyond access. Journal of the American Medical Informatics Association, 18(3), 318–321.

    Article  Google Scholar 

  • Sathye, M. (1999). Adoption of internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing, 17(7), 324–334.

    Article  Google Scholar 

  • Schickedanz, A., Huang, D., Lopez, A., Cheung, E., Lyles, C., Bodenheimer, T., & Sarkar, U. (2013). Access, interest, and attitudes toward electronic communication for health care among patients in the medical safety net. Journal of General Internal Medicine, 28(7), 914–920.

    Article  Google Scholar 

  • Seethamraju, R., Diatha, K. S., & Garg, S. (2018). Intention to use a mobile-based information technology solution for tuberculosis treatment monitoring–applying a UTAUT model. Information Systems Frontiers, 20(1), 163–181.

    Article  Google Scholar 

  • Serrano, A., Garcia-Guzman, J., Xydopoulos, G., & Tarhini, A. (2020). Analysis of barriers to the deployment of health information systems: A stakeholder perspective. Information Systems Frontiers, 22(2), 455–474.

    Article  Google Scholar 

  • Son, H. (2020). "Adult patients’ experience using patient portal: The impact of perceived usability on portal use behavior." University of Maryland Baltimore.

  • Son, H., Nahm, E. S., Zhu, S., Galik, E., Seidl, K. L., Van de Castle, B., & Russomanno, V. (2021). Testing a model of patient portal use in adult patients. Journal of Nursing Scholarship, 53(2), 143–153.

    Article  Google Scholar 

  • Tavares, J., and Oliveira, T. (2016). "electronic health record patient portal adoption by health care consumers: An acceptance model and survey," Journal of Medical Internet Research (18:3), p. e49.

  • Terry, N. (2014). Health privacy is difficult but not impossible in a post-HIPAA data-driven world. Chest, 146(3), 835–840.

    Article  Google Scholar 

  • Thambusamy, R., & Palvia, P. (2020). US healthcare provider capabilities and performance: The mediating roles of service innovation and quality. Information Systems Frontiers, 22(1), 91–111.

    Article  Google Scholar 

  • Turrietta, C. M. (2020). Using the health belief model to predict an individual's willingness to conduct genetic testing. Texas State University.

  • Venkatesh, V., and Goyal, S. (2010). "expectation disconfirmation and technology adoption: Polynomial modeling and response surface analysis," MIS Quarterly), pp. 281-303.

  • Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

    Article  Google Scholar 

  • Wade-Vuturo, A. E., Mayberry, L. S., & Osborn, C. Y. (2013). Secure messaging and diabetes management: Experiences and perspectives of patient portal users. Journal of the American Medical Informatics Association, 20(3), 519–525.

    Article  Google Scholar 

  • Wakefield, B. J., Turvey, C., Hogan, T., Shimada, S., Nazi, K., Cao, L., Stroupe, K., Martinez, R., and Smith, B. (2020). "impact of patient portal use on duplicate laboratory tests in diabetes management," Telemedicine and e-Health (26:10).

  • Wakefield, D. S., Kruse, R. L., Wakefield, B. J., Koopman, R. J., Keplinger, L. E., Canfield, S. M., & Mehr, D. R. (2012). Consistency of patient preferences about a secure internet-based patient communications portal: Contemplating, enrolling, and using. American Journal of Medical Quality, 27(6), 494–502.

    Article  Google Scholar 

  • Wang, X., Sun, J., Wang, Y., and Liu, Y. (2021). "deepen electronic health record diffusion beyond breadth: Game changers and decision drivers," Information Systems Frontiers), pp. 1-12.

  • Weingart, S. N., Rind, D., Tofias, Z., & Sands, D. Z. (2006). Who uses the patient internet portal? The PatientSite experience. Journal of the American Medical Informatics Association, 13(1), 91–95.

    Article  Google Scholar 

  • Yu, P. L., Balaji, M., & Khong, K. W. (2015). Building trust in internet banking: A trustworthiness perspective. Industrial Management & Data Systems, 115(2), 235–252.

    Article  Google Scholar 

  • Zailani, S., Iranmanesh, M., Nikbin, D., and Beng, J. K. C. (2015). "determinants of RFID adoption in Malaysia’s healthcare industry: Occupational level as a moderator," Journal of Medical Systems (39:1), p. 172.

  • Zhou, J., & George, J. M. (2001). When job dissatisfaction leads to creativity: Encouraging the expression of voice. The Academy of Management Journal, 44(4), 682–696.

    Google Scholar 

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Correspondence to Murad Moqbel.

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Appendix 1 Measurement instrument

Appendix 1 Measurement instrument

Construct

Items

Source

Health Professional Encouragement

Usage of MyChart is encouraged by my healthcare professional team (e.g., healthcare provider/doctor, office staff, practice administrators).

Zhou and George (2001)

My healthcare professional team endorses MyChart usage.

My healthcare professional team supports involvement in MyChart usage.

Security Concerns

I am concerned about submitting information on MyChart because of the potential for security breaches.

Dinev and Hart (2006)

I am concerned that information on MyChart could be accessed by unauthorized parties who hack into the system.

I am concerned about submitting information on MyChart because others might hack into the system.

Continuous Use Intention

I intend to continue using MyChart in the future.

Kock et al. (2016); Lowry et al. (2015)

I will always try to use MyChart in my daily life.

I plan to continue to use MyChart frequently.

Deep Structure Usage

When I was using MyChart, I used features that helped me to see my lab results.

Burton-Jones and Straub Jr. (2006)

When I was using MyChart, I used features that helped me to request a refill.

When I was using MyChart, I used features that helped me to send a message to my provider.

When I was using my MyChart, I used features that helped me to track my health progress over time.

When I was using my MyChart, I used features that helped me to learn more about my medical condition.

When I was using my MyChart, I used features that helped me to manage my healthcare.

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Moqbel, M., Hewitt, B., Nah, F.FH. et al. Sustaining Patient Portal Continuous Use Intention and Enhancing Deep Structure Usage: Cognitive Dissonance Effects of Health Professional Encouragement and Security Concerns. Inf Syst Front 24, 1483–1496 (2022). https://doi.org/10.1007/s10796-021-10161-5

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  • DOI: https://doi.org/10.1007/s10796-021-10161-5

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