A survey-based study of factors that motivate nurses to protect the privacy of electronic medical records

Goldschmidt PG. HIT and MIS: Implications of health information technology and medical information systems. Comm ACM. 2005;48(10):68–74.

Institute of Medicine: The computer-based patient record: An essential technology for health care, Revised Edition: Washington, D.C.: The National Academies Press; 1997.

Leblanc G, Gagnon MP, Sanderson D. Determinants of primary care nurses’ intention to adopt an electronic health record in their clinical practice. Comput Informat Nurs. 2012;30(9):496–502.

Abbass I, Helton J, Mhatre S, Sansgiry SS. Impact of electronic health records on nurses’ productivity. Comput Informat Nurs. 2012;30(5):237–41.

van Bemmel JH, Musen MA. Handbook of medical informatics. Heidelberg: Springer Verlag; 1997.

Top M, Gider Ö. Nurses’ views on electronic medical records (EMR) in Turkey: An analysis according to use, quality and user satisfaction. J Med Syst. 2012;36(3):1979–88.

Kerr P. Protecting patient information in an electronic age: A sacred trust. Urol Nurs. 2009;29(5):315–8.

American Nurses Association (ANA): Code of ethics for nurses with interpretive statements: American Nurses Association (ANA); 2014. Retrieved September 2, 2014, from http://www.nursingworld.org/DocumentVault/Ethics_1/Code-of-Ethics-for-Nurses.html .

McBurney BH, Filoromo T. The nightingale pledge: 100 years later. Nurs Manag. 1994;25(2):72–4.

McGraw D. Building public trust in uses of Health Insurance Portability and Accountability Act de-identified data. J Am Med Informat Assoc. 2013;20(1):29–34.

Erickson JI, Millar S. Caring for patients while respecting their privacy: Renewing our commitment. Online J Issues Nur. 2005;10(2):2.

Rindfleisch TC. Privacy, information technology, and health care. Comm ACM. 1997;40(8):92–100.

U.S. Department of Health and Human Services: Breaches Affecting 500 or more Individuals. 2014 Retrieved September 2, 2014, from https://ocrportal.hhs.gov/ocr/breach/breach_report.jsf .

Taylor S, Todd PA. Understanding information technology usage - A test of competing models. Inform Syst Res. 1995;6(2):144–76.

Garets D, Davis M. Electronic medical records vs. electronic health records: Yes, there is a difference. In. Chicago: HIMSS Analytics, LLC; 2006.

Garret P, Seidman J: EMR vs EHR – What is the difference? 2011 Retrieved February 2, 2015, from http://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/emr-vs-ehr-diff/

Tang PC, Ash JS, Bates DW, Overhage JM, Sands DZ. Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption. J Am Med Informat Assoc. 2006;13(2):121–6.

AHIMA. The role of the personal health record in the EHR. J AHIMA. 2005;76(7):64A–D.

Charles, D, King, J, Patel, V, & Furukawa, M F. Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008-2012. ONC Data Brief 2013 Retrieved September 2, 2014, from http://www.healthit.gov/sites/default/files/oncdatabrief9final.pdf .

Ministry of Health and Welfare: Bulletin of EMRs adoption 2014 Retrieved 15th August, 2014, from http://emr.mohw.gov.tw/emrlist.aspx.

Yoshida Y, Imai T, Ohe K. The trends in EMR and CPOE adoption in Japan under the national strategy. Int J Med Informat. 2013;82(10):1004–11.

Shu T, Liu H, Goss FR, Yang W, Zhou L, Bates DW, et al. EHR adoption across China’s tertiary hospitals: A cross-sectional observational study. Int J Med Informat. 2014;83(2):113–21.

Accenture: Getting EMR back in the fast lane. Accenture; 2014 Retrieved September 2, 2014, from http://www.accenture.com/us-en/Pages/insight-getting-emr-back-fast-lane-summary.aspx .

Malhotra NK, Kim SS, Agarwal J. Internet users’ information privacy concerns (IUIPC): The construct, the scale, and a causal model. Inform Syst Res. 2004;15(4):336–55.

Rothstein MA. Health privacy in the electronic age. J Leg Med. 2007;28(4):487–501.

Agaku IT, Adisa AO, Ayo-Yusuf OA, Connolly GN. Concern about security and privacy, and perceived control over collection and use of health information are related to withholding of health information from healthcare providers. J Am Med Informat Assoc. 2014;21(2):374–8.

Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.

Hung SY, Ku YC, Chien JC. Understanding physicians’ acceptance of the Medline system for practicing evidence-based medicine: A decomposed TPB model. Int J Med Informat. 2012;81(2):130–42.

Glegg SM, Holsti L, Velikonja D, Ansley B, Brum C, Sartor D. Factors influencing therapists’ adoption of virtual reality for brain injury rehabilitation. Cyberpsych Beh Soc N. 2013;16(5):385–401.

Seyal AH, Turner R. A study of executives’ use of biometrics: An application of theory of planned behaviour. Behav Inform Tech. 2013;32(12):1242–56.

Chau PYK, Hu PJH. Information technology acceptance by individual professionals: A model comparison approach. Decis Sci. 2001;32(4):699–719.

Chau PYK, Hu PJH. Examining a model of information technology acceptance by individual professionals: An exploratory study. J Manag Inform Syst. 2002;18(4):191–229.

Chau PYK, Hu PJH. Investigating healthcare professionals’ decisions to accept telemedicine technology: An empirical test of competing theories. Inform Manag. 2002;39(4):297–311.

Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989;13(3):319–40.

Chen JV, Yen DC, Chen K. The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Inform Manag. 2009;46(4):241–8.

Hu PJH, Chau PYK, Sheng ORL, Tam KY. Examining the technology acceptance model using physician acceptance of telemedicine technology. J Manag Inform Syst. 1999;16(2):91–112.

Lin HF. Predicting consumer intentions to shop online: An empirical test of competing theories. Electron Commerce Res Appl. 2007;6(4):433–42.

Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS Quart. 2003;27(3):425–78.

Alwin DF. Feeling thermometers versus 7-point scales: Which are better? Socio Meth Res. 1997;25(3):318–40.

Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York: McGraw-Hill; 1994.

Colman AM, Morris CE, Preston CC. Comparing rating scales of different lengths: Equivalence of scores from 5-point and 7-point scales. Psychol Rep. 1997;80(2):355–62.

Dawes JG. Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. Int J Market Res. 2008;50(1):61–77.

Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879–903.

Ringle CM, Wende S, Will A: SmartPLS 2.0.M3. Hamburg: SmartPLS, 2005 Retrieved September 2, 2014, from http://www.smartpls.com .

Henseler J, Dijkstra TK, Sarstedt M, Ringle CM, Diamantopoulos A, Straub DW, et al. Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organ Res Methods. 2014;17(2):182–209.

Gefen D, Straub D. A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Comm Assoc Inform Syst. 2005;16(1):91–109.

Hair JF, Hult GTM, Ringle CM, Sarstedt M. A primer on partial least squares structural equation modeling (pls-sem). Thousand Oaks: Sage; 2013.

Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Market Res. 1981;18(1):39–50.

Wetzels M, Odekerken-Schröder G, Van Oppen C. Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quart. 2009;33(1):177–95.

Martínez-Caro E, Cegarra-Navarro JG, Solano-Lorente M. Understanding patient e-loyalty toward online health care services. Health Care Manag Rev. 2013;38(1):61–70.

Kaba B, Osei-Bryson KM. Examining influence of national culture on individuals’ attitude and use of information and communication technology: Assessment of moderating effect of culture through cross countries study. Int J Inform Manag. 2013;33(3):441–52.

Lee Y, Kozar KA, Larsen KRT. The technology acceptance model: Past, present, and future. Comm Assoc Inform Syst. 2003;12(1):752–80.

Kuo KM, Liu CF, Ma CC. An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC Med Informat Decis Making. 2013;13(1):88.

Cheung R, Vogel D. Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Comput Educ. 2013;63:160–75.

Wu JH, Wang SC. What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Inform Manag. 2005;42(5):719–29.

Tung FC, Chang SC, Chou CM. An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int J Med Informat. 2008;77(5):324–35.

Levett-Jones T, Lathlean J. ‘Don’t rock the boat’: Nursing students’ experiences of conformity and compliance. Nurse Educ Today. 2009;29(3):342–9.

Milholland DK. Privacy and confidentiality of patient information: Challenges for nursing. J Nurs Admin. 1994;24(2):19–24.

Shih YY, Fang K. The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Res. 2004;14(3):213–23.

Foltz CB, Schwager PH, Anderson JE. Why users (fail to) read computer usage policies. Ind Manag Data Syst. 2008;108(6):701–12.

Zhang J, Reithel BJ, Li H. Impact of perceived technical protection on security behaviors. Inform Manag Comput Secur. 2009;17(4):330–40.

Herath T, Rao HR. Protection motivation and deterrence: A framework for security policy compliance in organizations. Eur J Inform Syst. 2009;18(2):106–25.