Journal article
Somebody that I (used to) know: Gender and dimensions of dark personality traits as predictors of intimate partner cyberstalking
Personality and individual differences, Vol.163, 110084
01/09/2020
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Source: InCites
Abstract
Intimate partner cyberstalking, a form of intimate partner stalking, is stalking behaviour perpetrated via technology. Experiencing intimate partner cyberstalking is associated with significant negative outcomes including depression, anxiety, sleep disturbances, and social isolation. In the current study, we aimed to (1) establish intimate partner cyberstalking as a controlling relationship behaviour and (2) explore the utility of gender and dimensions of the Dark Tetrad traits (i.e., narcissism, Machiavellianism, psychopathy, and sadism) to predict intimate partner cyberstalking. Participants (N = 405; 69.6% women) completed an online questionnaire measuring personality, online behaviour, and controlling relationship behaviours. Controlling relationship behaviours was a significant predictor of intimate partner cyberstalking. Further, gender (women), vulnerable narcissism, direct sadism (verbal and physical), and secondary psychopathy were significant, positive predictors of intimate partner cyberstalking. Importantly, significant gender differences appeared regarding predictors; vulnerable narcissism and direct verbal sadism were significant predictors for women, and only secondary psychopathy was a significant predictor for men. Results are discussed in terms of implications and gender differences in motivations for perpetrating this controlling relationship behaviour.
Details
- Title
- Somebody that I (used to) know: Gender and dimensions of dark personality traits as predictors of intimate partner cyberstalking
- Creators
- Evita March - Federation UniversityVerity Litten - Curtin UniversityDanny H. Sullivan - Swinburne University of TechnologyLouise Ward - La Trobe University
- Publication Details
- Personality and individual differences, Vol.163, 110084
- Publisher
- Elsevier Ltd
- Identifiers
- 991013126108002368
- Copyright
- © 2020 Elsevier Ltd. All rights reserved.
- Academic Unit
- Faculty of Health
- Language
- English
- Resource Type
- Journal article