ادراکات و اسنادات تماشاگران نسبت به زورگویی سایبری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|36788||2014||7 صفحه PDF||سفارش دهید||6203 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers in Human Behavior, Volume 38, September 2014, Pages 1–7
Abstract Bystanders play a critical role in the maintenance or reduction of bullying behavior. The potentially unlimited audience in the online world suggests that the role of bystanders may be particularly important in cyber bullying. However, little is known about the perceptions of bystanders or the situational factors that can increase or decrease their support for victims. In this study, bystanders’ perceptions of control, attributions of responsibility and blame for a hypothetical same-gender victim of cyber bullying were examined within a blog. Participants included 1105 middle school students who were assigned to one of three experimental conditions that manipulated the victim’s response (passive, active, reactive). In all conditions, a negative outcome resulted (cyber bullying continued). A 3 × 2 MANCOVA tested effects of Response Type × Gender on bystanders’ perceptions and attributions. Results indicate that passive responses elicited stronger perceptions of control, attributions of responsibility and blame than active or reactive responses, particularly for male bystanders. Bystanders may be less likely to offer assistance to victims of cyber bullying who respond passively to their experience. The findings have implications for understanding the factors that can increase or decrease bystander support in real-life cyber bullying situations.
1. Introduction Socialization patterns among adolescents have changed dramatically in the last decade as a result of the growth and proliferation of electronic communication devices (e.g., Internet and cell phones). In particular, social networking sites such as Facebook have become increasingly popular for adolescents to communicate with their friends at any time of the day or night (Kowalski, Limber, & Agatston, 2012). An unintended consequence of the increasing access to and use of these forms of technology is cyber bullying. Cyber bullying refers to “an aggressive, intentional act carried out by a group or individual, using electronic forms of contact, repeatedly and over time against a victim who cannot easily defend him or herself” (Smith et al., 2008, p. 376). Findings from reviews of the literature (Kowalski et al., 2014, Patchin and Hinduja, 2012 and Tokunaga, 2010) and several large scale studies (Kowalski and Limber, 2007, Mishna et al., 2010 and Williams and Guerra, 2007) suggest that cyber bullying is a significant concern for adolescents, particularly during the middle school years. However, large discrepancies in these reports (e.g., sampling, measurement, time frame, etc.) have made it difficult to determine the actual rate of cyber bullying among adolescents (Sabella, Patchin, & Hinduja, 2013). For example, Patchin and Hinduja (2012) reviewed the findings from 35 studies and reported that victimization rates vary between 5.5% and 72% with an average victimization rate of 24.4%. Many victims of cyber bullying also suffer psychological and emotional distress as a result of their experience (Kowalski et al., 2012 and Tokunaga, 2010). In these situations, adolescents indirectly involved in the situation (e.g., bystanders) may be needed to help the victim reduce the bullying and associated distress. The potentially unlimited audience in the online world which differentiates cyber bullying from traditional face-to-face bullying represents a unique opportunity for bystander intervention. However, a greater presence of bystanders does not necessarily relate to a greater likelihood of intervention (e.g., bystander effect; Latane & Darley, 1970). Bystanders may also believe that they do not need to assist the victim because someone else will (e.g., diffusion of responsibility). Even though bystanders play a critical role in the maintenance or reduction of bullying behavior, little is known about the perceptions of bystanders to cyber bullying or the situational factors that can increase or decrease their support for victims. To bridge these gaps in the literature, the current study utilized an attributional framework to examine the perceptions and attributions of bystanders to cyber bullying. The response by adolescents when they experience bullying is an important situational factor that can influence the perceptions of bystanders (Kochenderfer-Ladd, 2003). Victims of cyber bullying typically respond to their experience by using ‘passive’ (e.g., doing nothing or trying to ignore the behavior), ‘active’ (e.g., reporting the behavior) or ‘reactive’ (e.g., confronting the bully) strategies ( Africak et al., 2008, Dehue et al., 2008, Mishna et al., 2010, Price and Dalgleish, 2010 and Tokunaga, 2010). Passive strategies may be most effective for minor forms of cyber bullying (e.g., receiving harassing e-mail messages) whereas more active strategies are often needed for more serious forms of cyber bullying (e.g., embarrassing pictures or videos) or when the behavior persists ( Hinduja and Patchin, 2009 and Tokunaga, 2010). Responses that are ineffective or do not actually reduce the bullying can increase the level of psychological distress experienced by victims ( Kochenderfer-Ladd & Skinner, 2002) and can influence the perceptions of bystanders and their subsequent willingness to assist victims. In the current study, the response by a hypothetical victim of cyber bullying was manipulated to examine the effects on bystanders’ perceptions and attributions for the victim.
نتیجه گیری انگلیسی
5. Results 5.1. Preliminary analyses Table 1 provides the descriptive statistics and bivariate correlations for all study variables. The overall mean ratings for the victim’s perceived level of control, attributions of responsibility, and attributions of blame were below the midpoint (i.e., lower levels of control, responsibility, and blame). The majority of participants (67.5%) considered the situation to be ‘definitely’ cyber bullying and more than half (57.2%) rated cyber bullying as a ‘very serious experience’. Table 1. Descriptive statistics and bivariate correlations. Variable M (n) SD (%) 2 3 4 5 6 7 1. Response type −.007 −.02 −.04 −.07⁎⁎ −.006 .007 Ignored the behavior (371) (34%) Reported the behavior (379) (34%) Confronted the bully (355) (32%) 2. Gender .002 −.11⁎ −.14⁎ .13⁎ .16⁎ Males (562) (51%) Females (543) (49%) 3. Perceived control 2.54 1.55 .22⁎ .20⁎ −.14⁎ −.13⁎ 4. Attributions of responsibility 2.71 1.59 .36⁎ −.15⁎ −.05 5. Attributions of blame 2.17 1.40 −.12⁎ −.15⁎ 6. Consider situation CB 6.26 1.35 .37⁎ 7. Seriousness of CB 6.23 1.16 Note: CB = cyber bullying. ⁎ p < 0.001. ⁎⁎ p < 0.05. Table options An open-ended question was used to explore the causal attributions given by bystanders for the student’s mistreatment (Table 2). Responses were categorized into themes and grouped by gender to facilitate interpretation. Causal explanations that reflected either internal (i.e., victim characteristics) or external (i.e., bully characteristics) attributions emerged. Of the 67% of respondents to the question, 67.0% of boys and 54.4% of girls indicated that student was mistreated because of their internal characteristics. The most endorsed internal attribution was the behaviors or actions (i.e., he/she did something first to provoke the bully) of the student (31.5% boys and 28.4 girls). More than one-third of boys (35.5%) and one-fourth of girls (25.0%) endorsed internal attributions considered to be both stable and uncontrollable such as being different (i.e., easy target, weird, strange, gay, disabled, new to school, weak, or religion), unpopular or unattractive/unintelligent. Conversely, many bystanders (30.6% of boys and 42.7% of girls) provided external attributions for the student’s experience. Jealousy was endorsed most frequently by both boys (12.7%) and girls (22.3%) followed by the bully’s temperament (9.7% boys, 13.1% girls) or for entertainment (8.2% boys, 7.3% girls). A small proportion of bystanders (2.4% boys, 2.9% girls) suggested that there was no actual reason for the student’s mistreatment. Table 2. Frequency of causal attributions for cyber bullying. Causal Attribution Gender Males (%) Females (%) Internal attributions (victim) Unpopular 16.4 9.5 Different 17.0 13.6 Unattractive/unintelligent 2.1 2.9 Behaviors or actions 31.5 28.4 Total 67.0 54.4 External attributions (bully) Fun and entertainment 8.2 7.3 Jealousy 12.7 22.3 Temperament 9.7 13.1 Total 30.6 42.7 Other No actual reason 2.4 2.9 n 330 412 Table options 5.2. Main analyses The main objective of the study was to examine bystanders’ perceptions and attributions for a hypothetical student’s cyber bullying experience. A 3 × 2 multivariate analysis of covariance (MANCOVA) was used to test the effects of Response Type (ignored the behavior, reported the behavior, confronted the bully) × Gender (male, female) on the perceptions of control, attributions of responsibility, and attributions of blame for the blogger’s cyber bullying outcome (i.e., cyber bullying continued). Significant main effects emerged in the overall MANCOVA for Response Type [Wilks’s λ = .987, F(6, 2132) = 2.30, p = .03, ηp2 = .006] and for Gender [Wilks’s λ = .979, F(3, 1066) = 7.46, p < .001, ηp2 = .021]. The interaction between Response Type × Gender was not significant [Wilks’s λ = .997, F(6, 2132) = .45, ns]. Follow-up univariate analyses of covariance (ANCOVAs) were used to probe main effects for each dependent measure. 5.2.1. Perceptions of control A significant main effect for Response Type emerged in the ANCOVA for perceptions of control. The blogger was perceived as having more control after being cyber bullied when he/she ignored the behavior than when he/she reported the behavior (Ms = 2.65 vs. 2.36), F(2, 1068) = 4.01, p = .02, ηp2 = .007. There was no main effect for Gender on perceived control (Ms = 2.53 boys vs. 2.53 girls), F(1, 1068) = .77, ns. 5.2.2. Attributions of responsibility There was a significant main effect for Gender on attributions of responsibility. Male participants held the male blogger as more responsible for their experience than female participants’ rating of the female blogger (Ms = 2.87 vs. 2.52), F(1, 1068) = 10.78, p = .001, ηp2 = .01. Even though there was not a significant main effect for Response Type, the results trended toward the bloggers being viewed as more responsible if they ignored the behavior (M = 2.81) versus if they reported the behavior (M = 2.68) or if they confronted the bully (M = 2.65). 5.2.3. Attributions of blame A significant main effect for Gender emerged on attributions of blame. Male participants assigned greater blame to the male blogger than female participants’ assigned to the female blogger (Ms = 2.37 vs. 1.98), F(1, 1068) = 13.95, p < .001, ηp2 = .013. There was also a significant main effect for Response Type, F(2, 1068) = 3.28, p = .04, ηp2 = .006. Simple contrast results indicated that the ‘ignored the behavior’ group differed significantly from the ‘reported the behavior’ group (Ms = 2.32 vs. 2.09, 95% CI for difference [.15, .49], p < .001). Thus, greater blame was assigned to the blogger when he/she responded by ignoring the behavior than if he/she reported the behavior.