Disposition toward privacy and information disclosure in the context of emerging health technologies. (2nd April 2019)

• Record Type: Journal Article
• Authors: Schairer, Cynthia E; Cheung, Cynthia; Kseniya Rubanovich, Caryn; Cho, Mildred; Cranor, Lorrie Faith; Bloss, Cinnamon S
• Is Part Of: Journal of the American Medical Informatics Association. Volume 26:Number 7(2019)
• Page Start: 610
• Page End: 619
• Publication Date: 2019-04-02
• Subjects: privacy -- confidentiality -- patient data privacy -- disclosure -- social values; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocz010
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: We sought to present a model of privacy disposition and its development based on qualitative research on privacy considerations in the context of emerging health technologies. Materials and Methods: We spoke to 108 participants across 44 interviews and 9 focus groups to understand the range of ways in which individuals value (or do not value) control over their health information. Transcripts of interviews and focus groups were systematically coded and analyzed in ATLAS.ti for privacy considerations expressed by respondents. Results: Three key findings from the qualitative data suggest a model of privacy disposition. First, participants described privacy related behavior as both contextual and habitual. Second, there are motivations for and deterrents to sharing personal information that do not fit into the analytical categories of risks and benefits. Third, philosophies of privacy, often described as attitudes toward privacy, should be classified as a subtype of motivation or deterrent. Discussion: This qualitative analysis suggests a simple but potentially powerful conceptual model of privacy disposition, or what makes a person more or less private. Components of privacy disposition are identifiable and measurable through self-report and therefore amenable to operationalization and further quantitative inquiry. Conclusions: We propose this model as the basis for a psychometric instrument that can be used to identify types of privacy dispositions, with potential applications in research, clinical practice, system design, and policy.