Keywords

self-disclosure, sensitive information, sensitive question, data collection methods

Abstract

Building on the literature that approaches selfdisclosure as a decision-making process, we proposed a selfreported Sensitive Information Disclosure (SID) measure and tested the measure’s reliability and validity in two studies across a variety of interview modes and settings. We used theory to identify potential dimensions of sensitive information disclosures, created potential scale items, performed two separate card sorts, and validated the resulting pool of items in two separate experiments. Participants answered the SID scale items following an interview involving sensitive information, potential risk, and after-disclosure vulnerability. Study 1 was a laboratory experiment conducted with 165 university students. Exploratory factor analysis results revealed a twofactor structure, Personal Discomfort and Revealing Personal Information. Study 2 replicated these procedures using confirmatory factor analysis to confirmthe factor structure and demonstrate the scale’s reliability and validity, with a sample of 77 students and 275 participants from Amazon’s M-Turk. Together, these results demonstrate that the proposed 11- item SID scale has good convergent and discriminant validity as well as good reliability. A quasi-experimental application of the measure is illustrated using the substantive findings from Study 2. This research fills a gap in the literature by developing a topic-free scale to measure SID as a dependent variable. The ability to accurately measure sensitive information disclosure is an important and necessary step toward developing a more thorough understanding of how people feel and react when asked to provide personal information in diverse interview settings.

Original Publication Citation

Pickard, Matt D., Wilson, David W., & Roster, Catherine A. “Development and application of a self-report measure for assessing sensitive information disclosures across multiple modes,” (2018) Behavior Research Methods, 50, pp. 1734-1748.

Document Type

Peer-Reviewed Article

Publication Date

2017

Publisher

Behavior Research Methods

Language

English

College

Marriott School of Business

Department

Information Systems Management

University Standing at Time of Publication

Assistant Professor

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