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The Impact of Personality on Users' Specific Privacy Concerns Regarding Personal Health Information

Published:18 June 2018Publication History

ABSTRACT

The increased use of health information technology has made a wide range of personal health information available for practitioners and researchers alike. Notably, as more personal health information becomes available, there is increasing concern for the data's privacy. Personal electronic health information, i.e., digital report(s) of real-time patient-centered information, are a relatively new phenomenon for many of us to confront these days. Prior studies have examined the construct of privacy in-depth including cross-cultural perspective [1], analysis at different levels - organizational, group, and individual [2], literature reviews [3, 2] and more.

Expounding on these areas, research is now beginning to investigate the influence personal characteristics has on privacy. Rather than viewing privacy concerns as a single multidimensional consequence, our study examines the link between personality traits and individual privacy concern dimensions. A widely established proxy for privacy [4], known as the concern for information privacy (CFIP), consists of four components: collection, errors, unauthorized secondary use and improper access.

Unlike previous studies, we treat each of the privacy concern dimensions separately to determine how personality affects each specific concern. For some personality traits, we expect there to be a significant effect across all four dimensions; in others, the effect on some dimensions is expected to be significantly higher than others. In healthcare, the appropriate control of the information is viewed as an obligation of health care professionals from an ethics perspective but also as a function of their expertise, power and professional status [5]. We expect that characteristics such as the dynamic nature of healthcare and the private and intimate essence of patient information will highlight explicable relationships between personality traits and dimensions of privacy.

We have developed a Likert-scale-based survey instrument corresponding to the model, gathered data, and are currently analyzing the dataset using structural equation modeling. We hope that the results of our study (once completed) will be beneficial for subsequent studies as well as for practitioners interfacing with concerned users of health data.

References

  1. Markos, E., Milne, G. R., & Peltier, J. W. (2017). Information Sensitivity and Willingness to Provide Continua: A Comparative Privacy Study of the United States and Brazil. Journal of Public Policy & Marketing, 36(1), 79--96.Google ScholarGoogle ScholarCross RefCross Ref
  2. Smith, H. J., Dinev, T., & Xu, H. (2011). Information Privacy Research: An Interdisciplinary Review. MIS Quarterly, 35(4), 989--1016. Google ScholarGoogle ScholarCross RefCross Ref
  3. Bélanger, F., & Crossler, R. E. (2011). Privacy In The Digital Age: A Review Of Information Privacy Research In Information Systems. MIS Quarterly, 35(4), 1017--1042. Google ScholarGoogle ScholarCross RefCross Ref
  4. Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information Privacy: Measuring Individuals' Concerns About Organizational Practices. MIS Quarterly, 167--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Anthony, D. L., & Stablein, T. (2016). Privacy in practice: professional discourse about information control in health care. Journal of Health Organization and Management, 30(2), 207--226.Google ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          SIGMIS-CPR'18: Proceedings of the 2018 ACM SIGMIS Conference on Computers and People Research
          June 2018
          216 pages
          ISBN:9781450357685
          DOI:10.1145/3209626

          Copyright © 2018 Owner/Author

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          Publication History

          • Published: 18 June 2018

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