To SPB or not to SPB? A mixed methods analysis of self-protective behaviours to prevent repeat victimisation from cyber abuse

• Published in: Crime science Vol. 9; no. 1; pp. 1 - 18
• Main Authors: Vakhitova, Zarina I., Mawby, Rob I., Alston-Knox, Clair L., Stephens, Callum A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 11.11.2020; Springer Nature B.V; BMC
• Subjects: Bayesian variable selection; Community and Environmental Psychology; Criminology and Criminal Justice; Cyber abuse; Cyberbullying; Internet; Law and Criminolgy; Mixed methods research; Repeat victimisation; Self-protective behaviours; Signal,Image and Speech Processing; Stochastic search algorithm; Systems and Data Security; User training; Victimization; Stochastic search algorithm; Bayesian variable selection; Self-protective behaviours; Repeat victimisation; Cyber abuse
• ISSN: 2193-7680; 2193-7680
• DOI: 10.1186/s40163-020-00134-5

This paper presents the findings from a mixed-methods examination of self-protective behaviours (SPBs) adopted by victims of cyber abuse from the rational choice perspective. The data from a sample of the U.S. adults ( N = 746 ), members of an online opt-in panel, were analysed to first distinguish the types of SPBs adopted by victims of cyber abuse using a thematic analysis of open-ended responses. We then identified the factors associated with an increased likelihood of adopting SPBs and the specific identified types of SPBs using logistic regression with Bayesian variable selection and a stochastic search algorithm. Of the six identified types of SPBs, adjusting privacy settings was the most commonly reported response, and improving security (e.g. changing passwords, etc.) was the least common SPB. Older victims who reported higher than the average perceived impact from victimisation, were abused by a stranger and experienced either surveillance of their online activities or multiple types of abuse, were significantly more likely to adopt an SPB. Our findings inform strategies for both Internet user education and for preventing cyber abuse victimisation.