The impact of privacy enhancing technologies in online mental health platforms on users’ disclosure intention

Purpose This study aims to examine and compare the effects of four types of privacy enhancing technologies (i.e. ephemerality, anonymity, voice modulation and image tampering) in online mental health platforms and their combinations on users’ disclosure intention of private information. Design/methodology/approach This research conducts two scenario-based experiments to demonstrate the role of single factor and multiple factors of privacy enhancing technologies, further building on the privacy calculus model to explore the underlying behavioral mechanism through perceived costs (i.e. privacy risk and privacy concerns) and perceived benefits (i.e. privacy control, trust and psychological distance). Findings The single-factor analysis results show the different effects of these four technologies on privacy disclosure intention. Specifically, anonymity and image tampering have greater influences on privacy disclosure intention than ephemerality and voice modulation. The multi-factor analysis results demonstrate that users in the scenario of combining ephemerality, anonymity, voice modulation and image tampering are more willing to disclose their personal information. Practical implications This research advances the theoretical understanding of privacy enhancing technologies (PETs) in online mental health services, further explaining users’ behavioral mechanisms through the privacy calculus model and provides actionable insights for privacy protection settings design on the platforms. Originality/value Limited studies investigated the effects of different privacy enhancing technologies and their combinations on users’ privacy disclosure intentions. This study provides a new perspective to deepen the understanding of PETs’ effects through the underlying behavioral mechanisms.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2025-11-04
DOI
https://doi.org/10.1108/imds-05-2025-0662
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
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article

The impact of privacy enhancing technologies in online mental health platforms on users’ disclosure intention

Younghoon Chang, Lin Jia, Yingbin Zhu, Xinran Hu et al.
Industrial Management & Data Systems
Privacy, Security, and Data Protection
article

The impact of privacy enhancing technologies in online mental health platforms on users’ disclosure intention

Younghoon Chang, Lin Jia, Yingbin Zhu, Xinran Hu, Keníchi Takahashi, Yingfu Zhu
article en

Abstract

Purpose This study aims to examine and compare the effects of four types of privacy enhancing technologies (i.e. ephemerality, anonymity, voice modulation and image tampering) in online mental health platforms and their combinations on users’ disclosure intention of private information. Design/methodology/approach This research conducts two scenario-based experiments to demonstrate the role of single factor and multiple factors of privacy enhancing technologies, further building on the privacy calculus model to explore the underlying behavioral mechanism through perceived costs (i.e. privacy risk and privacy concerns) and perceived benefits (i.e. privacy control, trust and psychological distance). Findings The single-factor analysis results show the different effects of these four technologies on privacy disclosure intention. Specifically, anonymity and image tampering have greater influences on privacy disclosure intention than ephemerality and voice modulation. The multi-factor analysis results demonstrate that users in the scenario of combining ephemerality, anonymity, voice modulation and image tampering are more willing to disclose their personal information. Practical implications This research advances the theoretical understanding of privacy enhancing technologies (PETs) in online mental health services, further explaining users’ behavioral mechanisms through the privacy calculus model and provides actionable insights for privacy protection settings design on the platforms. Originality/value Limited studies investigated the effects of different privacy enhancing technologies and their combinations on users’ privacy disclosure intentions. This study provides a new perspective to deepen the understanding of PETs’ effects through the underlying behavioral mechanisms.

Industrial Management & Data Systems
Beijing Institute of Technology (CN), University of Nottingham Ningbo China (CN), Time Domain (United States) (US), Tsinghua University (CN)
Openalex Percentile: Top 58%
Privacy, Security, and Data Protection
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