Reyns & Fisher (2018)

Overview of the Study

  • Focus: Relationship between offline and online stalking victimization through a gendered approach.

  • Authors: Bradford W. Reyns (Weber State University), Bonnie S. Fisher (University of Cincinnati).

  • Sample: College students (N = 3,488) from a Midwest and a Southern university.

Key Findings

General Results

  • Offline Stalking Impact: Experiencing offline stalking increases the likelihood of online stalking.

  • Cyberstalking Impact: Experiencing cyberstalking does not significantly affect the chances of offline stalking.

Gender-Specific Analyses

  • Females: Cyberstalking less likely to lead to subsequent offline stalking.

  • Males: Cyberstalking more likely to result in subsequent offline stalking.

  • Predictive Power: Offline stalking is a significant predictor of online victimization for females, but not for males.

Definitions and Context

  • Stalking Victimization: Involves repeated and unwanted pursuit causing fear (e.g., following, contacting).

    • Estimated prevalence: 3% to 13% for offline stalking; 4% to 40% for online stalking (cyberstalking).

  • Importance of Gender: Females face a higher risk of victimization compared to males.

Research Context

  • The exploration of correlations and predictors has increased, but the relationship between offline and online stalking remains under-researched.

  • Call for integrative models that consider the interconnectedness of online and offline stalking victimization.

Methodology

Study Design

  • Conducted during Spring 2015, part of an NIH-funded project on interpersonal violence among college students.

  • Sample size: 10,000 students; response rate of 40.63% (3,488 completed the survey).

Variables

  • Dependent Variables:

    • Offline Stalking Victimization (time 2) based on fear for personal safety in unwanted situations.

    • Online Stalking Victimization (time 2) defined through online harassment, unwanted advances, and safety concerns.

  • Independent Variables: Prior incidents of offline and online stalking are assessed as predictors.

  • Control Variables: Demographics (age, race), substance use, and lifestyle behaviors are accounted for in analyses.

Theoretical Implications

  • Suggests a comprehensive approach to understand recurring victimization (state dependence and risk heterogeneity).

  • Gender moderates the relationship between stalking types and risk predictors, highlighting the need for gender-specific interventions.

Limitations

  • Findings may not be generalizable beyond the college student demographic.

  • Potential memory decay affecting respondents’ recall of past victimization events.

  • Models explain only a modest variance of victimization risk; further variables may need exploration.

Implications for Policy and Practice

  • Prevention Strategies: Increased emphasis on integrated stalking prevention efforts encompassing online and offline behaviors.

  • Importance for campuses to adopt comprehensive support frameworks for prior victims of stalking.