ArticleSecurity journal2022
Exploring the determinants of victimization and fear of online identity theft: an empirical study.
Article in Security journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Patterns of Internet Use in People Diagnosed With Severe Mental Illness: Qualitative Interview Study.Journal of medical Internet research · 2025Article
- Detection of price manipulation fraud through rational choice theory: evidence for the retail industry in Taiwan.Security journal · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aims at understanding what factors contribute to the explanation of online identity theft (OIT) victimization and fear, using the Routine Activity Theory (RAT). Additionally, it tries to uncover the influence of factors such as sociodemographic variables, offline fear of crime, and computer perception skills. Data for the present study were collected from a self-reported online survey administered to a sample of university students and staff (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.