Evaluating 'Prefer not to say' Around Sensitive Disclosures

Warner, Mark, Kitkowska, Agnieszka, Gibbs, Jo, Maestre, Juan F. and Blandford, Ann (2020) Evaluating 'Prefer not to say' Around Sensitive Disclosures. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI’20): April 25–30, 2020, Honolulu, HI, USA. Association for Computing Machinery, Inc, New York, NY. ISBN 9781450367080

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Abstract

As people's offline and online lives become increasingly entwined, the sensitivity of personal information disclosed online is increasing. Disclosures often occur through structured disclosure fields (e.g., drop-down lists). Prior research suggests these fields may limit privacy, with non-disclosing users being presumed to be hiding undesirable information. We investigated this around HIV status disclosure in online dating apps used by men who have sex with men. Our online study asked participants (N=183) to rate profiles where HIV status was either disclosed or undisclosed. We tested three designs for displaying undisclosed fields. Visibility of undisclosed fields had a significant effect on the way profiles were rated, and other profile information (e.g., ethnicity) could affect inferences that develop around undisclosed information. Our research highlights complexities around designing for non-disclosure and questions the voluntary nature of these fields. Further work is outlined to ensure disclosure control is appropriately implemented around online sensitive information disclosures.

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