Exploring the Effects of Online Victimization in Rural Appalachia ... completed a broader survey on digital online privacy and security, as well as character ...
How Much Can Being Online Hurt? Exploring the Effects of Online Victimization in Rural Appalachia 1 Shalun ,
Exploring, Understanding, Overcoming.
1,2 Taylor ,
3 Mitchell ,
3 Jones ,
1,2 Hamby
Annya Elizabeth Kimberly Lisa & Sherry 1Life Paths Appalachian Research Center, 2University of the South, 3University of New Hampshire
Abstract Objective: Little attention has been directed toward how rural populations experience online victimizations. This study explores the range of online victimizations, including online-theft and cyberbullying, and how these experiences affect participants in rural Appalachia. Method: Our sample included 478 individuals (57.1% female), with an average age of 36 years old (ages ranged from 12-75), who participated in a survey that asked about internet use and online victimization. Results: We explored the differences between trauma symptoms and 14 online victimizations. Those who reported experiencing cyberbullying reported higher trauma symptoms than those who had not been cyberbullied. Additionally, those who reported the occurrence of cyber-theft reported higher trauma symptoms than those who did not experience cybertheft. When comparing the categories of online victimization, cyberbullying was reported overall as more traumatic than cyber-theft. Conclusion: Online victimization is a common problem that has lasting impact on victims. Our findings offer insight to where online safety strategies should be targeted, based on both prevalence and how affected participants were by the victimization.
Introduction • Previous research has linked online victimizations, mostly in the form of bullying and harassment, to negative psychological problems in adolescents and adults (Hawker & Boulton, 2000; Mitchell, Ybarra, & Finkelhor, 2007; Perren, Dooley, Shaw, & Cross, 2010; Sumter, Baumgartner, Valkenburg, & Peter, 2012; Ybarra 2004; Ybarra, Mitchell, Wolak, & Finkelhor, 2006). • “Relational aggression,” which attacks the victims’ social network, is related to higher likelihood of distress than online verbal and sexual harassment (Staude-Müller, Hansen, & Voss, 2012). • However, little attention has been directed toward the potential impact of cyber-theft, or explored the experiences of those living in rural areas. • Most previous research focuses on how and why individuals in rural communities access the internet, and less on online victimizations and their impact (Bell, Reddy, & Rainie, 2004). • We explored the following research questions: • What types of online victimizations are selfreported as the most upsetting? • Do people who report online victimizations have higher levels of trauma symptoms than others in this rural community?
Method
Participants: Participants were 478 participants from rural southeastern United States, ages 12 to 75 years old (M = 36.44, SD = 17.61), who completed a broader survey on digital online privacy and security, as well as character development. The sample was 57.5% female; most (84.9%) of the sample identified as White/European American (non-Latino), 5.7% as African American/Black (non-Latino), 4.0% as more than one race, 3.6% as Latino (any race), .8% as Asian (non-Latino), and .8% American Indian/Alaska Native (non-Latino).
Procedure: The survey was administered by the research team as a computer-assisted self-interview with an audio option, using the Snap11 software platform on computer tablets. The majority of participants (65.7%) were recruited through word-of-mouth. On average, the survey took 31 minutes to complete and each participant received a $20 Walmart gift and was provided with information on local community resources. All procedures were approved by the IRB of the host institution.
Measures: The Traumatic Symptoms Index is a 10-item scale which asked how true each category was for individual’s in the last month on a 4point Likert scale (1 = not true about me, 4 = mostly true about me). Sample items included “Feeling lonely in the last month,” “Feeling sad in the last month,” and “Feeling like shouting at people in the last month.” Internal consistency (coefficient alpha) was .89. Validity was established in our sample with moderate to strong correlations with other outcome measures (r = -.43); higher scores on the Traumatic Symptoms Scale are indicative of more trauma symptoms.. The Digital Poly-victimization Scale includes 11 items with an coefficient alpha of .70. Validity was established with moderate to strong correlations with other measures, such as the Traumatic Symptoms Scale (r = .31). Items were categorized into 2 constructs: cyberbullying and cyber-theft. Participants were asked about their online victimization experiences and how upsetting they found each of these instances. We examined the Digital Poly-victimization Scale at the item-level with the original 14 items.
Results
Cyber-theft and privacy invasions Table 1. Prevalence rates & percentages of individuals “very upset” with cyber-theft victimizations Victimization
Tricked into giving money. Information or money stolen from hacking. Tricked into giving personal information.
% of sample who experienced this victimization (prevalence rate) 2.3% 12.1%
% of victims who were “very upset”
81.8% 77.2%
12.4%
64.9%
Cyberbullying
Victimization
% of sample who experienced this victimization (prevalence rate) 12.9%
% of victims who were “very upset”
Someone pretended to be me.
9.6%
66.7%
Someone told lies or spread rumors about me online.
67.2%
3.4%
62.5%
Someone said mean things about me online.
14.5%
61.8%
12.7%
61.7%
12.1%
57.9%
6.7%
53.3%
Someone forwarded embarrassing texts or pics.
Ads or offers with personal information.
26.7%
39.7%
35.6%
34.5%
Someone sent me a lot of messages that I didn’t want.
Sharing information to get apps or programs I need.
52.0%
28%
Someone kept me out of online groups.
7.5%
Yes (M, SD)
No (M, SD)
Tricked into giving money.
18.88 (7.25)
15.78 (5.85)
Information or money stolen from hacking.** Tricked into giving personal information.
18.00 (6.40)
15.50 (5.71)
16.90 (6.68)
15.68 (5.78)
Victimization
Tricked out of items, money, or credits in an online game. Someone used my login without permission.* Someone tracked my location online.** Ads or offers with personal information.*** Sharing information to get apps or programs I need.* Note: *** p ≤ .001. ** p ≤ .01, * p ≤ .05
16.86 (5.97) 17.54 (5.88) 18.46 (6.23) 17.72 (5.97) 16.38 (5.91)
15.83 (5.91) 15.62 (5.85) 15.65 (5.82) 14.83 (5.62) 15.34 (5.80)
• Individuals who reported experiencing cyberbullying or cyber-theft generally reported higher trauma symptoms than those who have not been cyberbullied or experienced cyber-theft. • Among cyberbullying victimization items, having someone tell lies or spread rumors about them was the most upsetting. Among cyber-theft victimization types, being tricked into giving money was the most upsetting in the moment, but was not associated with elevated trauma symptoms, perhaps because of the low base rate. • Although cyber-theft was not as strongly and consistently associated with trauma symptoms as cyberbullying, many forms were associated with trauma symptoms, even some legal invasions of privacy. • These results suggest that online victimization concerns expand beyond merely avoiding cyberbullying, but that online vigilance while navigating diffuse social networks is imperative as well.
Table 2. Prevalence rates & percentages of individuals “very upset” with cyberbullying victimizations
Tricked out of items, money, or credits in an online game. Someone used my login without permission. Someone tracked my location online.
Table 3. Trauma symptom scores as a function of cyber-theft victimization and privacy invasions
Discussion
Limitations and Future Directions 22.9%
Table 4. Trauma symptom scores as a function of cyberbullying victimization Yes (M, SD)
No (M, SD)
Someone told lies or spread rumors about me online.***
18.52 (6.49)
15.48 (5.69)
Someone pretended to be me.***
19.11 (6.79)
15.50 (5.68)
Victimization
Someone said mean things about me online.*** Someone forwarded embarrassing texts or pics.***
• Although our study sample focused on the understudied population of rural Appalachia, our sample lacked diversity in terms of race. Future research should explore these issues in other populations. • Our data provides a unique framework to further explore the impact of online experiences in understudied populations. Future research would benefit from exploring possible protective factors from the adverse impact of online victimization.
References 20.21 (5.86)
15.11 (5.58)
Bell, P., Reddy, P., & Rainie, L. (2004). Rural areas and the Internet. Washington, DC: Pew Internet & American Life Project, 7-37. Hawker, D. S. J., & Boulton, M. J. (2000). Twenty years' research on peer victimization and psychosocial maladjustment: A meta‐analytic review of cross‐sectional studies. Journal of child psychology and psychiatry, 41(4), 441-455.
18.00 (6.40)
15.50 (5.71)
Mitchell, K. J., Ybarra, M., & Finkelhor, D. (2007). The relative importance of online victimization in understanding depression, delinquency, and substance use. Child maltreatment, 12(4), 314-324. Perren, S., Dooley, J., Shaw, T., & Cross, D. (2010). Bullying in school and cyberspace: Associations with depressive symptoms in Swiss and Australian adolescents. Child and adolescent psychiatry and mental health, 4(1), 28. Sumter, S. R., Baumgartner, S. E., Valkenburg, P. M., & Peter, J. (2012). Developmental trajectories of peer victimization: Off-line and online experiences during adolescence. Journal of Adolescent Health, 50(6), 607-613.
Someone sent me a lot of messages that I didn’t want.** Someone kept me out of online groups.** Note: *** p ≤ .001. ** p ≤ .01, * p ≤ .05
15.45 (5.76)
17.04 (6.10)
Ybarra, M. L. (2004). Linkages between depressive symptomatology and Internet harassment among young regular Internet users. CyberPsychology & Behavior, 7(2), 247-257. Ybarra, M. L., Mitchell, K. J., Wolak, J., & Finkelhor, D. (2006). Examining characteristics and associated distress related to Internet harassment: findings from the Second Youth Internet Safety Survey. Pediatrics, 118(4), e1169-e1177. Staude-Müller, F., Hansen, B., & Voss, M. (2012). How stressful is online victimization? Effects of victim's personality and properties of the incident. European Journal of Developmental Psychology, 9(2), 260-274.
19.00 (6.92)
15.57 (5.69)
This project was made possible through the support of a grant from the Digital Trust Foundation.
