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  • Title: ➤  Online Self-Disclosure Paradox: How Interactivity Affects Privacy Perception And User Experience
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  • Internet Archive ID: osf-registrations-rwy2f-v1

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Personalization has been widely applied in mobile health applications to provide appropriate health services and a better user experience. To enable personalization, health apps tend to request users to share personal information at the app sign-up stage. However, users may be concerned with this early privacy disclosure without knowing the true value of the service. According to a U.S. nationwide survey, half of Americans give up using a website or online service to avoid sharing personal information (Perrin, 2020). When personalization is the core service of an app, through what kind of interface design, users would feel more comfortable with such information requests? In other words, what type of interface design or user-system interaction might trigger privacy concerns preventing users from further engaging with the service? In the field of communication technology, the majority of studies focused on investigating the positive effects of online interactivity (e.g., Yang & Shen, 2018). However, we have little understanding of the effect of interactivity in non-reciprocal conditions (I.e., asking for private information without providing benefit right away). Also, the interaction of two types of interactivities, message interactivity and modality interactivity, does not get enough attention yet. Hence, this study seeks to untangle the elusive effects of interactivity on privacy-related perceptions and behaviors. By understanding users' psychological mechanisms when disclosing private information on health apps, we are able to suggest a better interactive design to help users make informed decisions in the private information disclosure procedures.

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"Online Self-Disclosure Paradox: How Interactivity Affects Privacy Perception And User Experience" is available for download from The Internet Archive in "data" format, the size of the file-s is: 0.18 Mbs, and the file-s went public at Tue Oct 31 2023.

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  • Source: Internet Archive
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  • Number of Files: 5
  • Number of Available Files: 5
  • Added Date: 2023-10-31 09:01:13
  • Scanner: Internet Archive Python library 1.9.9

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