Promoting Patient Portals: An Application of Social Cognitive Theory to Post-Adoption Patient Portal Use

References

• Abd-alrazaq, A. A., Bewick, B. M., Farragher, T., & Gardner, P. (2019). Factors that affect the use of electronic personal health records among patients: A systematic review. International Journal of Medical Informatics, 126, 164–175. https://doi.org/10.1016/j.ijmedinf.2019.03.014
   PubMed Web of Science ®Google Scholar
• Agarwal, R., Anderson, C., Zarate, J., & Ward, C. (2013). If we offer it, will they accept? Factors affecting patient use intentions of personal health records and secure messaging. Journal of Medical Internet Research, 15(2), e43. https://doi.org/10.2196/jmir.2243
   PubMed Web of Science ®Google Scholar
• Ahmed, A., Nasralah, T., Wahbeh, A., & Noteboom, C. (2019). Patients’ characteristics effecting the use of a MyChart patient portal. In Proceedings of the 52nd Hawaii International Conference on System Sciences (pp. 3974–3979). Washington DC, IEEE. http://hdl.handle.net/10125/59834
   Google Scholar
• Allison, P. D. (2001). Missing data (Vol. 136). Sage publications.
   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. https://doi.org/10.1007/s11606-011-1749-y
   PubMed Web of Science ®Google Scholar
• Avtgis, T. A., & Polack, E. P. (2007). Predicting physician communication competence by patient perceived information exchange and health locus of control. Human Communication, 10(2), 136–144. https://doi.org/citeseerx.ist.psu.edu/viewdoc/download?=10.1.1.629.7244&rep=rep1&type=pdf
   Google Scholar
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Inc.
   Google Scholar
• Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1
   PubMed Web of Science ®Google Scholar
• Bandura, A. (2004). Health promotion by social cognitive means. Health Education & Behavior, 31(2), 143–164. https://doi.org/10.1177/1090198104263660
   PubMed Web of Science ®Google Scholar
• Beach, M. C., Keruly, J., & Moore, R. D. (2006). Is the quality of the patient-provider relationship associated with better adherence and health outcomes for patients with HIV? Journal of General Internal Medicine, 21(6), 661–665. https://doi.org/10.1111/j.1525-1497.2006.00399.x
   PubMed Web of Science ®Google Scholar
• Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. Management Information Systems Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
   Web of Science ®Google Scholar
• Botelho, R. J. (1992). A negotiation model for the doctor-patient relationship. Family Practice, 9(2), 210–218. https://doi.org/10.1093/fampra/9.2.210
   PubMed Web of Science ®Google Scholar
• Bozan, K., & Datta, P. (2016). Satisfaction with health informatics system characteristics and their effect on openness to frequent use. In N. Wickramasinghe, I. Troshani, & J. Tan (Eds.), Contemporary consumer health informatics (pp. 125–152). Springer International Publishing.
   Google Scholar
• Brennan, P. F., Downs, S., & Casper, G. (2010). Project HealthDesign: Rethinking the power and potential of personal health records. Journal of Biomedical Informatics, 43(5), S3–S5. https://doi.org/10.1016/j.jbi.2010.09.001
   PubMed Web of Science ®Google Scholar
• Brown, S. D., Grijalva, C. S., & Ferrara, A. (2017). Leveraging EHRs for patient engagement: Perspectives on tailored program outreach. The American Journal of Managed Care, 23(7), e223–e230. https://www.ajmc.com/view/leveraging-ehrs-for-patient-engagement-perspectives-on-tailored-program-outreach
   PubMed Web of Science ®Google Scholar
• Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage.
   Google Scholar
• Byczkowski, T. L., Munafo, J. K., & Britto, M. T. (2011). Variation in use of internet-based patient portals by parents of children with chronic disease. JAMA Pediatrics, 165(5), 405–411. https://doi.org/10.1001/archpediatrics.2011.55
   Google Scholar
• Carter, M., & Petter, S. (2015). Leveraging consumer technologies: Exploring determinants of smartphone use behaviors in the workplace. Proceedings of the 48th Hawaii International Conference on System Sciences (pp. 4619–4628). Washington DC, IEEE. https://doi.org/10.1109/HICSS.2015.550
   Google Scholar
• Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160–175. https://doi.org/10.1016/j.compedu.2012.12.003
   Web of Science ®Google Scholar
• Cocosila, M., & Archer, N. (2018). Modeling consumer acceptance of electronic personal health records. Journal of Electronic Commerce Research, 19(2), 119–134. http://www.jecr.org/sites/default/files/2018vol19no2_Paper1.pdf
   Web of Science ®Google Scholar
• Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118–143. https://doi.org/10.1287/isre.6.2.118
   Web of Science ®Google Scholar
• Connecting for Health. (2004). Connecting Americans to their healthcare: Final report. https://www.markle.org/sites/default/files/CnctAmerHC_fullreport.pdf
   Google Scholar
• Davis, D. L. (1984). Medical misinformation: Communication between outport Newfoundland women and their physicians. Social Science & Medicine, 18(3), 273–278. https://doi.org/10.1016/0277-9536(84)90090-X
   PubMed Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
   Web of Science ®Google Scholar
• Duncan, T., Rahim, E., & Burrell, D. (2018). Challenges in healthcare post-EMR adoption. Proceedings of Midwest Association for Information Systems (MWAIS) Association for Information Systems (AIS) (pp. 1–6). St. Louis, MO.
   Google Scholar
• Dutta-Bergman, M. J. (2004). Primary sources of health information: Comparisons in the domain of health attitudes, health cognitions, and health behaviors. Health Communication, 16(3), 273–288. https://doi.org/10.1207/S15327027HC1603_1
   PubMed Web of Science ®Google Scholar
• Dutta-Bergman, M. J. (2005). The relation between health-orientation, provider-patient communication, and satisfaction: An individual-difference approach. Health Communication, 18(3), 291–303. https://doi.org/10.1207/s15327027hc1803_6
   PubMed Web of Science ®Google Scholar
• El Halabieh, R., Beaudry, A., & Tamblyn, R. (2017). Impacts of stress, satisfaction and behavioral intention on continued usage: Evidence from physicians transitioning to a new drug management system. Proceedings of the 50th Hawaii International Conference on System Sciences (pp. 3381–3390). Washington, DC: IEEE. http://hdl.handle.net/10125/41568
   Google Scholar
• Gebauer, L., Söllner, M., & Leimeister, J. M. (2013). Towards understanding the formation of continuous it use. Paper presented at the Thirty Fourth International Conference on Information Systems, Milan.
   Google Scholar
• Gilani, S. M., Iranmanesh, M., Nikbin, D., & Zailani, S. (2017). EMR continuance usage intention of healthcare professionals. Informatics for Health and Social Care, 42(2), 153–165. https://doi.org/10.3109/17538157.2016.1160245
   PubMed Web of Science ®Google Scholar
• Goel, M. S., Brown, T. L., Williams, A., Cooper, A. J., Hasnain-Wynia, R., & Baker, D. W. (2011). Patient reported barriers to enrolling in a patient portal. Journal of the American Medical Informatics Association, 18(Suppl. 1), i8–i12. https://doi.org/10.1136/amiajnl-2011-000473
   PubMed Web of Science ®Google Scholar
• Grogan, S., Conner, M., Willits, D., & Norman, P. (1995). Development of a questionnaire to measure patients’ satisfaction with general practitioners’ services. British Journal of General Practice, 45(399), 525–529. http://bjgp.org/content/45/399/525.abstract
   PubMed Web of Science ®Google Scholar
• Gunter, B. (1994). The question of media violence. In J. Bryant & D. Zillmann (Eds.), Media effects: Advances in theory and research (pp. 163–212). Erlbaum.
   Google Scholar
• Hall, J. A., & Dornan, M. C. (1988). What patients like about their medical care and how often they are asked: A meta-analysis of the satisfaction literature. Social Science & Medicine, 27(9), 935–939. https://doi.org/10.1016/0277-9536(88)90284-5
   PubMed Web of Science ®Google Scholar
• Hall, M. A., Zheng, B., Dugan, E., Camacho, F., Kidd, K. E., Mishra, A., & Balkrishnan, R. (2002). Measuring patients’ trust in their primary care providers. Medical Care Research and Review, 59(3), 293–318. https://doi.org/10.1177/1077558702059003004
   PubMed Web of Science ®Google Scholar
• Holden, R. J. (2012). Social and personal normative influences on healthcare professionals to use information technology: Towards a more robust social ergonomics. Theoretical Issues in Ergonomics Science, 13(5), 546–569. https://doi.org/10.1080/1463922X.2010.549249
   PubMedGoogle Scholar
• Hou, J., & Shim, M. (2010). The role of provider–patient communication and trust in online sources in internet use for health-related activities. Journal of Health Communication, 15(sup3), 186–199. https://doi.org/10.1080/10810730.2010.522691
   PubMed Web of Science ®Google Scholar
• Irizarry, T., DeVito Dabbs, A., & Curran, C. R. (2015). Patient portals and patient engagement: A state of the science review. Journal of Medical Internet Research, 17(6), e148–e148. https://doi.org/10.2196/jmir.4255
   PubMed Web of Science ®Google Scholar
• Jayanti, R. K., & Burns, A. C. (1998). The antecedents of preventive health care behavior: An empirical study. Journal of the Academy of Marketing Science, 26(1), 6–15. https://doi.org/10.1177/0092070398261002
   Web of Science ®Google Scholar
• Jiang, S., & Street, R. L. (2017). Factors influencing communication with doctors via the internet: A cross-sectional analysis of 2014 HINTS survey. Health Communication, 32(2), 180–188. https://doi.org/10.1080/10410236.2015.1110867
   PubMed Web of Science ®Google Scholar
• Jones, D. E., Carson, K. A., Bleich, S. N., & Cooper, L. A. (2012). Patient trust in physicians and adoption of lifestyle behaviors to control high blood pressure. Patient Education and Counseling, 89(1), 57–62. https://doi.org/10.1016/j.pec.2012.06.003
   PubMed Web of Science ®Google Scholar
• Kalton, G. (1983). Compensating for missing survey data. University of Michigan Press.
   Google Scholar
• Kalyanaraman, S., & Sundar, S. S. (2006). The psychological appeal of personalized content in web portals: Does customization affect attitudes and behavior? Journal of Communication, 56(1), 110–132. https://doi.org/10.1111/j.1460-2466.2006.00006.x
   Web of Science ®Google Scholar
• Kazley, A. S., & Ozcan, Y. A. (2007). Organizational and environmental determinants of hospital EMR adoption: A national study. Journal of Medical Systems, 31(5), 375–384. https://doi.org/10.1007/s10916-007-9079-7
   PubMed Web of Science ®Google Scholar
• Kellermann, A. L., & Jones, S. S. (2013). What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Affairs, 32(1), 63–68. https://doi.org/10.1377/hlthaff.2012.0693
   PubMed Web of Science ®Google Scholar
• Ketterer, T., West, D. W., Sanders, V. P., Hossain, J., Kondo, M. C., & Sharif, I. (2013). Correlates of patient portal enrollment and activation in primary care pediatrics. Academic Pediatrics, 13(3), 264–271. https://doi.org/10.1016/j.acap.2013.02.002
   PubMed Web of Science ®Google Scholar
• Kim, S., Lee, K. H., Hwang, H., & Yoo, S. (2016). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Medical Informatics and Decision Making, 16(1), 1–12. https://doi.org/10.1186/s12911-016-0249-8
   PubMedGoogle Scholar
• Kipping, S., Stuckey, M. I., Hernandez, A., Nguyen, T., & Riahi, S. (2016). A web-based patient portal for mental health care: Benefits evaluation. Journal of Medical Internet Research, 18(11), e294. https://doi.org/10.2196/jmir.6483
   PubMed Web of Science ®Google Scholar
• Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). Guilford.
   Google Scholar
• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.
   Google Scholar
• Kreuter, M. W., Bull, F. C., Clark, E. M., & Oswald, D. L. (1999). Understanding how people process health information: A comparison of tailored and nontailored weight-loss materials. Health Psychology, 18(5), 487–494. https://doi.org/10.1037/0278-6133.18.5.487
   PubMed Web of Science ®Google Scholar
• Kruse, C. S., Argueta, D. A., Lopez, L., & Nair, A. (2015). 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), e40. https://doi.org/10.2196/jmir.3703
   PubMedGoogle Scholar
• Kuo, T., Lu, I. Y., Huang, C. H., & Wu, G. C. (2005). Measuring users’ perceived portal service quality: An empirical study. Total Quality Management & Business Excellence, 16(3), 309–320. https://doi.org/10.1080/14783360500053824
   Web of Science ®Google Scholar
• Lazard, A. J., Watkins, I., Mackert, M. S., Xie, B., Stephens, K. K., & Shalev, H. (2015). Design simplicity influences patient portal use: The role of aesthetic evaluations for technology acceptance. Journal of the American Medical Informatics Association, 23(e1), e157–e161. https://doi.org/10.1093/jamia/ocv174
   PubMed Web of Science ®Google Scholar
• Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54(2), 506–516. https://doi.org/10.1016/j.compedu.2009.09.002
   Web of Science ®Google Scholar
• Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a technology continuance theory (TCT). International Journal of Information Management, 29(4), 309–320. https://doi.org/10.1016/j.ijinfomgt.2009.03.004
   Web of Science ®Google Scholar
• Lin, C., Lin, I. C., & Roan, J. (2012). Barriers to physicians’ adoption of healthcare information technology: An empirical study on multiple hospitals. Journal of Medical Systems, 36(3), 1965–1977. https://doi.org/10.1007/s10916-011-9656-7
   PubMed Web of Science ®Google Scholar
• Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. Wiley.
   Google Scholar
• Lyles, C. R., Sarkar, U., Ralston, J. D., Adler, N., Schillinger, D., Moffet, H. H., … Karter, A. J. (2013). Patient–provider communication and trust in relation to use of an online patient portal among diabetes patients: The diabetes and aging study. Journal of the American Medical Informatics Association, 20(6), 1128–1131. https://doi.org/10.1136/amiajnl-2012-001567
   PubMed Web of Science ®Google Scholar
• Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an electronic patient record in acute care settings: An extension of the UTAUT. International Journal of Medical Informatics, 84(1), 36–47. https://doi.org/10.1016/j.ijmedinf.2014.09.004
   PubMed Web of Science ®Google Scholar
• Miller, K. (2005). Communication theories. Macgraw-Hill.
   Google Scholar
• Mishuris, R. G., Stewart, M., Fix, G. M., Marcello, T., McInnes, D. K., Hogan, T. P., … Simon, S. R. (2015). Barriers to patient portal access among veterans receiving home-based primary care: A qualitative study. Health Expectations, 18(6), 2296–2305. https://doi.org/10.1111/hex.12199
   PubMed Web of Science ®Google Scholar
• Moorman, C., & Matulich, E. (1993). A model of consumers' preventive health behaviors: The role of health motivation and health ability. Journal of Consumer Research, 20(2), 208–228. https://doi.org/10.1086/209344
   Web of Science ®Google Scholar
• Morton, M. E., & Wiedenbeck, S. (2009). A framework for predicting EHR adoption attitudes: A physician survey. Perspectives in Health Information Management, 6(Fall), 1a–1a. https://perspectives.ahima.org/a-framework-for-predicting-ehr-adoption-attitudes-a-physician-survey/
   Google Scholar
• Muthén, L. K., & Muthén, B. O. (2012). Mplus user’s guide (1998–2012). Muthén & Muthén.
   Google Scholar
• Noblin, A. M., Wan, T. T., & Fottler, M. (2013). Intention to use a personal health record: A theoretical analysis using the technology acceptance model. International Journal of Healthcare Technology and Management, 14(1–2), 73–89. https://doi.org/10.1504/IJHTM.2013.055085
   Google Scholar
• Ong, L. M. L., de Haes, J. C. J. M., Hoos, A. M., & Lammes, F. B. (1995). Doctor-patient communication: A review of the literature. Social Science & Medicine, 4(7), 903–918. https://doi.org/10.1016/0277-9536(94)00155-M
   Google Scholar
• Or, C. K. L., Karsh, B. T., Severtson, D. J., Burke, L. J., Brown, R. L., & Brennan, P. F. (2010). Factors affecting home care patients’ acceptance of a web-based interactive self-management technology. Journal of the American Medical Informatics Association, 18(1), 51–59. https://doi.org/10.1136/jamia.2010.007336
   PubMed Web of Science ®Google Scholar
• Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication and persuasion: Central and peripheral routes to attitude change (pp. 1–24). Springer. https://link-springer-com.ezp1.villanova.edu/book/https://doi.org/10.1007/978-1-4612-4964-1#toc
   Google Scholar
• Pourrazavi, S., Allahverdipour, H., Jafarabadi, M. A., & Matlabi, H. (2014). A socio-cognitive inquiry of excessive mobile phone use. Asian Journal of Psychiatry, 10, 84–89. https://doi.org/10.1016/j.ajp.2014.02.009
   PubMedGoogle Scholar
• Rahimi, N., & Jetter, A. (2015, August). Explaining health technology adoption: Past, present, future. Paper presented at the 2015 Portland International Conference on Management of Engineering and Technology (PICMET), Portland. https://doi.org/10.1109/PICMET.2015.7273030
   Google Scholar
• Ralston, J. D., Rutter, C. M., Carrell, D., Hecht, J., Rubanowice, D., & Simon, G. E. (2009). Patient use of secure electronic messaging within a shared medical record: A cross-sectional study. Journal of General Internal Medicine, 24(3), 349–355. https://doi.org/10.1007/s11606-008-0899-z
   PubMed Web of Science ®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(2), 306–326. https://doi.org/10.1108/ITP-07-2016-0160
   Web of Science ®Google Scholar
• Schwartz, P. H., Caine, K., Alpert, S. A., Meslin, E. M., Carroll, A. E., & Tierney, W. M. (2015). Patient preferences in controlling access to their electronic health records: A prospective cohort study in primary care. Journal of General Internal Medicine, 30(S1), 25–30. https://doi.org/10.1007/s11606-014-3054-z
   PubMedGoogle Scholar
• Shaw, N., & Manwani, S. (2011). Extending feature usage: A study of the post-adoption of electronic medical records. Proceedings of the 19th European Conference on Information Systems (pp. 1–12). Helsinki, Finland, ECIS. https://aisel.aisnet.org/ecis2011/125
   Google Scholar
• Sundar, S. S., Bellur, S., Oh, J., Jia, H., & Kim, H. S. (2016). Theoretical importance of contingency in human-computer interaction: Effects of message interactivity on user engagement. Communication Research, 43(5), 595–625. https://doi.org/10.1177/0093650214534962
   Web of Science ®Google Scholar
• Sundar, S. S., Kalyanaraman, S., & Brown, J. (2003). Explicating web site interactivity: Impression formation effects in political campaign sites. Communication Research, 30(1), 30–59. https://doi.org/10.1177/0093650202239025
   Web of Science ®Google Scholar
• Tavares, J., & 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), e49. https://doi.org/10.2196/jmir.5069
   PubMed Web of Science ®Google Scholar
• Tieu, L., Sarkar, U., Schillinger, D., Ralston, J. D., Ratanawongsa, N., Pasick, R., & Lyles, C. R. (2015). Barriers and facilitators to online portal use among patients and caregivers in a safety net health care system: A qualitative study. Journal of Medical Internet Research, 17(12), e275. https://doi.org/10.2196/jmir.4847
   PubMed Web of Science ®Google Scholar
• Tsai, C. H. (2014). Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems. International Journal of Environmental Research and Public Health, 11(5), 4905–4925. https://doi.org/10.3390/ijerph110504905
   PubMed Web of Science ®Google Scholar
• Ueckert, F., Goerz, M., Ataian, M., Tessmann, S., & Prokosch, H. U. (2003). Empowerment of patients and communication with health care professionals through an electronic health record. International Journal of Medical Informatics, 70(2–3), 99–108. https://doi.org/10.1016/S1386-5056(03)00052-2
   PubMed Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Science Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
   Google Scholar
• Yarbrough, A. K., & Smith, T. B. (2007). Technology acceptance among physicians: A new take on TAM. Medical Care Research and Review, 64(6), 650–672. https://doi.org/10.1177/1077558707305942
   PubMed Web of Science ®Google Scholar