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Mastering boundaries: differences in online privacy boundary phenomena across digital devices and years.

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Title: Mastering boundaries: differences in online privacy boundary phenomena across digital devices and years.
Authors: Wang, Laurent H., Rice, Ronald E., Liu, Xingyu, Hagen, Ingunn, Zamanzadeh, Nicole
Source: Behaviour & Information Technology. Sep2025, Vol. 44 Issue 15, p3750-3770. 21p.
Subjects: Social media, Safety, Pearson correlation (Statistics), Computers, Research funding, Focus groups, Cluster analysis (Statistics), Privacy, Content analysis, Cell phones, Behavior, Multivariate analysis, Descriptive statistics, Research methodology, Trust, Analysis of variance, Statistics, Psychology of college students, Comparative studies, Data analysis software, Medical ethics
Geographic Terms: United States
Abstract: Multiple digital communication devices provide varying capabilities and processes for self-disclosure, surveillance, and privacy management, therefore eliciting a variety of user privacy perceptions and behaviours. Drawing from the media mastery framework and the comparative privacy research framework, this study investigates similarities and differences in online privacy outcomes associated with computer and mobile phone use via content analysis of 12 focus groups conducted with US college students in 2006 and 2016. Findings reveal similarities and differences across device type and time and their combinations among selected privacy-related codes from the media mastery framework. Cluster analysis of the codes reveals several general themes such as crossing the boundary from private to public, and safety and trust. Contributions include the use of a reliable conceptual foundation for categorising online privacy boundary phenomena, the generation of discussions about these phenomena from a goal-free evaluation approach, and comparisons across devices and time. The discussion provides theoretical and practical implications. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Multiple digital communication devices provide varying capabilities and processes for self-disclosure, surveillance, and privacy management, therefore eliciting a variety of user privacy perceptions and behaviours. Drawing from the media mastery framework and the comparative privacy research framework, this study investigates similarities and differences in online privacy outcomes associated with computer and mobile phone use via content analysis of 12 focus groups conducted with US college students in 2006 and 2016. Findings reveal similarities and differences across device type and time and their combinations among selected privacy-related codes from the media mastery framework. Cluster analysis of the codes reveals several general themes such as crossing the boundary from private to public, and safety and trust. Contributions include the use of a reliable conceptual foundation for categorising online privacy boundary phenomena, the generation of discussions about these phenomena from a goal-free evaluation approach, and comparisons across devices and time. The discussion provides theoretical and practical implications. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=187842758
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/0144929X.2024.2448706
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 3750
    Subjects:
      – SubjectFull: Social media
        Type: general
      – SubjectFull: Safety
        Type: general
      – SubjectFull: Pearson correlation (Statistics)
        Type: general
      – SubjectFull: Computers
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Focus groups
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: Privacy
        Type: general
      – SubjectFull: Content analysis
        Type: general
      – SubjectFull: Cell phones
        Type: general
      – SubjectFull: Behavior
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Trust
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      – SubjectFull: Analysis of variance
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      – SubjectFull: Statistics
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      – SubjectFull: Psychology of college students
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      – SubjectFull: Comparative studies
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      – SubjectFull: Data analysis software
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      – SubjectFull: Medical ethics
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      – SubjectFull: United States
        Type: general
    Titles:
      – TitleFull: Mastering boundaries: differences in online privacy boundary phenomena across digital devices and years.
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            NameFull: Liu, Xingyu
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            NameFull: Hagen, Ingunn
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            – D: 15
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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