The Validation of the Perceived Surveillance Scale

Claire M. Segijn, Suzanna J. Opree, Iris van Ooijen

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Data-driven practices, such as personalized communication, computational advertising, and algorithmic decision making, are now commonplace. However, they have been criticized for (mis)uses of personal data and invasions of people's privacy. Recently, scholars have started to examine the concept of perceived surveillance to obtain more insight into the perceptions and effectiveness of data-driven communication. Despite the growing research interest in perceived surveillance, there is no validated scale to measure this concept. This study aimed to validate the Perceived Surveillance Scale. The reliability and validity of the scale were tested in two surveys (N = 137 and N = 1,008) and one experiment (N = 527). In all three studies, the scale showed good reliability. Regarding construct validity, the results showed that, as expected, the Perceived Surveillance Scale was positively related to privacy concerns, privacy risk perception, perceived vulnerability, perceived severity, creepiness, surveillance concerns, and perceived personalization. In line with the predictions, the scale was negatively related to personalization attitudes. The Perceived Surveillance Scale can assess differences in perceptions of or responses to data-driven communication in different communication domains.

Original languageEnglish (US)
Article number9
Issue number3
StatePublished - Jun 30 2022

Bibliographical note

Publisher Copyright:
© Author(s). The articles in Cyberpsychology: Journal of Psychosocial Research on Cyberspace are open access articles licensed under the terms of the Creative Commons BY-NC-ND 4.0 International License which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited


  • algorithmic decision making
  • data-driven communication
  • perceived surveillance
  • personalized communication
  • privacy
  • scale validation


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