The selectivity of moral disengagement in defenders of cyberbullying: Contextual moral disengagement

Computers in Human Behavior 93 (2019) 318–325

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Full length article

The selectivity of moral disengagement in defenders of cyberbullying: Contextual moral disengagement☆

T

Aileen Luo∗, Kay Bussey Department of Psychology, Macquarie University, NSW 2109, Australia

ARTICLE INFO

ABSTRACT

Keywords: Cyberbullying Moral disengagement Context Contextual moral disengagement Defenders Defending self-efficacy

The lack of defending in bystanders to cyberbullying has been linked with the process of moral disengagement, which allows bystanders to justify the morality of their inactivity after witnessing a cyberbullying episode. Context is central in this process as individuals assess the specific contextual cues present within each episode, and it is this assessment that informs their subsequent behavior. Despite the importance of context in moral disengagement, researchers have yet to take this factor into account. To address this gap in literature, the present study examines the role of contextual factors on moral disengagement in specific cyberbullying episodes, and how this process influences cyber defending. This study also consolidates inconsistent results from studies examining moral disengagement and defending by examining defending as a multifaceted construct involving aggressive and constructive defending. To examine these issues, 540 Grade 7 and 9 students completed a survey assessing moral disengagement and defending self-efficacy in two cyberbullying scenarios. Results revealed that in both scenarios, contextualized moral disengagement is shown to be associated with aggressive and constructive defending self-efficacy above and beyond general moral disengagement. Higher levels of contextual moral disengagement are also related to greater aggressive defending self-efficacy whereas lower contextual moral disengagement is linked with greater pro-social defending self-efficacy. These results call for an increased focus on contextual factors when examining morality in cyberbullying and highlight the need to differentiate between pro-social and aggressive forms of defending.

1. Introduction Increased Internet and social media use have been accompanied by an increase in cyberbullying, which can severely impact the mental health of youth (Hamm et al., 2015; Kowalski, Giumetti, Schroeder, & Lattanner, 2014; Ortega et al., 2012). Researchers have recently focused on defenders in cyberbullying (bystanders who intervene to help victims) rather than on perpetrators and victims, as defenders may hold the power to minimize bullying occurrence (Salmivalli, Voeten, & Poskiparta, 2011). It has been proposed that examining influences that encourage bystander action may be one way to reduce the incidence of cyberbullying. However, although cyberbullying is witnessed by many in the peer group, few observers step in to defend the victim. One factor that has recently been linked with this lack of defending is moral disengagement (Allison & Bussey, 2016; Thornberg & Jungert, 2013). Moral disengagement, which has been extensively studied in its association with aggression and bullying, enables perpetrators to bully and aggress by justifying the morality of their behavior and feeling little remorse for it (Barchia & Bussey, 2011; Gini, Pozzoli, & Bussey, 2015).

Potential defenders may justify their lack of action in cyberbullying contexts by similarly employing moral disengagement mechanisms. Although there is some support for the role of moral disengagement in attenuating defending, the findings are inconsistent (e.g. Allison & Bussey, 2017; Thornberg, Pozzoli, Gini, & Jungert, 2015). One aim of this study is to resolve these inconsistent findings by examining the influence of context in the activation of moral disengagement mechanisms. Context is central to the employment of moral disengagement as the process is selective based on an interpretation of contextual cues that occur in any particular cyberbullying episode. Despite the contextual nature of the process (Bandura, 2016), this factor has yet to be examined in moral disengagement research on defending. The main aim of the present study therefore is to examine the influence of contextual factors on moral disengagement in cyber defending. 1.1. Moral disengagement and context Moral disengagement refers to the process by which individuals detach their personal moral standards from their immoral behaviors

This research did not receive any specific grant from funding agencies in the public, commercial, or non-for-profit sectors. Corresponding author. 4 First Walk, Room 730, Macquarie University, NSW 2109, Australia. E-mail address: [email protected] (A. Luo).

☆ ∗

https://doi.org/10.1016/j.chb.2018.12.038 Received 8 September 2018; Received in revised form 13 December 2018; Accepted 23 December 2018 0747-5632/ © 2018 Elsevier Ltd. All rights reserved.

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(Bandura, 1991, 2016). The phenomenon is closely linked with aggression and bullying (Gini et al., 2015; Gini, Pozzoli, & Hymel, 2014), allowing perpetrators of cyberbullying to bully others without feeling remorse (Kowalski et al., 2014; Tanrikulu & Campbell, 2015). The process involves eight mechanisms that fall into four loci of behavior that enable individuals to regulate their conduct. These loci include: justifying the behavior, displacing agential influence, downplaying harmful outcomes, and shifting causal focus onto the victim (Bandura, 2002). Selective employment of these mechanisms allows individuals to justify the morality of their immoral conduct. As moral disengagement is a contextually based construct, the specific contextual factors in a cyberbullying scenario may influence the degree to which an individual morally disengages (Bandura, 2015, 2016). Context is pertinent in the cyberbullying domain as the phenomenon occurs over a range of mediums (e.g. social media sites, text messaging, and phone calls). These mediums also vary greatly, such as the publicity of the cyberbullying act or the anonymity of the perpetrator (Rice et al., 2015). With large variations in how cyberbullying is enacted, contextual factors may be salient when an individual is assessing external cues. Most of the extant research, however, has not addressed moral disengagement from a contextual perspective. Rather, the focus in moral disengagement research has been on the assessment of individual (personal self-sanctions of immoral conduct) and peer level factors (group-level sanctions) (Allison & Bussey, 2017). As cyberbullying varies by incident, considering the contextual differences between episodes is crucial. The first aim of the present study is therefore to examine contextual factors that may influence the activation of moral disengagement in different cyberbullying scenarios, such as the medium of bullying through social media and text messaging.

Fitzpatrick, 2018). The distinction between the different styles of defending is crucial as although both styles share the goal of helping the victim, responding aggressively may not be the most appropriate strategy to resolve conflict (Xu et al., 2018). Furthermore, moral disengagement may differentially influence defenders, whereby aggressive defending is expected to be associated with higher levels of moral disengagement, and constructive defending is expected to be linked with lower levels moral disengagement. Despite the need to differentiate between the types of defending, most extant studies often view the behavior as a singular construct. The influence of moral disengagement on the multifaceted nature of defending will therefore be explored in this study. 1.4. Present study As outlined above, the first aim of this study is to examine whether contextualized moral disengagement impacts defending. Specifically, whether contextual moral disengagement is associated with defending self-efficacy above and beyond general moral disengagement, and whether this association differs depending on the specific cyberbullying context. To systematically vary the different contexts in which cyber defending occurs, two hypothetical cyberbullying scenarios were developed. These scenarios depicted cyberbullying occurring on a Facebook platform and a text message platform as not only are these platforms the most widely used amongst adolescents (Anderson, 2015; Lenhart, 2015), but the highest cyberbullying rates are reported on these platforms (Rice et al., 2015). It is hypothesized that contextual moral disengagement will uniquely contribute to defending self-efficacy in both contexts. It is further hypothesized that this association will be present after accounting for general forms of moral disengagement. A second aim is to examine whether moral disengagement differentially impacts aggressive and constructive defending. It is hypothesized that in line with research linking moral disengagement with aggression (Gini, Pozzoli, & Hymel, 2014), the two forms of moral disengagement (general and contextual) would be negatively associated with constructive defending self-efficacy, and positively associated with aggressive defending self-efficacy. In this study, defending self-efficacy, the belief in one's ability to defend when witnessing a cyberbullying event, is used as the dependent variable rather than a frequency measure of defending (Bandura, 1997). This approach was selected as individuals may be capable of defending, but may not have had the opportunity to enact this behavior. Furthermore, low levels of defending self-efficacy inhibit individuals from intervening, regardless of moral disengagement (Thornberg & Jungert, 2013), which stresses the importance of measuring defending self-efficacy in research on moral disengagement.

1.2. Moral disengagement and defending In terms of the application of moral disengagement to cyber bystanding and defending, bystanders can detach their own inaction from their self-sanctions of immoral conduct, which minimizes the need to intervene when witnessing a cyberbullying event. As bystanders may morally disengage to justify their inaction, it is expected that defenders would be less morally disengaged. Studies examining the link between moral disengagement and defending, however, have produced conflicting results. Specifically, findings have shown negative relationships between moral disengagement and defending (Caravita, Gini, & Pozzoli, 2012; DeSmet et al., 2014; Thornberg et al., 2015; Thornberg, Wänströ;m, Hong, & Espelage, 2017), no association (Gini et al., 2015), and even a positive association (Allison & Bussey, 2017). These contrasting results suggest that the link between moral disengagement and cyber defending is complex. One possibility for these inconsistencies may be the problematic view of moral disengagement as a general process that is engaged similarly in all situations. In particular, measures of moral disengagement have been adapted from the bullying field rather than developed specifically for defenders. To overcome this shortcoming, this study examines moral disengagement from the perspective of defenders, and considers contextual factors that vary depending on the cyberbullying scenario.

2. Method 2.1. Participants Participants were 344 students from Grade 7 (194 female; Mage = 12.65, SD = 0.42), and 196 students from Grade 9 (110 female; Mage = 14.63, SD = 0.45). The sample primarily identified as Anglo/ Celtic (67.2%), followed by European (15.9%), and East/South East Asian (6.7%). Participants were predominately from an upper to middle class socioeconomic backgrounds (Australian Curriculum Assessment and Reporting Authority, 2016). Schools mainly located in a major metropolitan city in New South Wales, Australia were approached to participate in the 40-min questionnaire. Principals from 14 independent, co-educational schools consented to students' recruitment. After obtaining principal consent, parental consent to participate in the study was also obtained and student assent was obtained on the day of testing.

1.3. Aggressive and constructive defending Apart from considering the context in resolving the inconsistencies in the relations between cyber defending and moral disengagement, the second aim of this research is to consider cyber defending as a multifaceted construct. Specifically, although the aim of defenders is to help the victim, they may do so in a variety of ways that vary in their effectiveness to stop the bullying. In particular, defenders may intervene in a constructive (e.g. telling a teacher about the bullying), or in an aggressive manner (e.g. making threats to the bully) (Bussey & Fitzpatrick, 2016; Macháčková & Pfetsch, 2016; Xu, Bussey, & 319

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2.2. Measures

completed the survey in groups during Term 2 of the school year under supervision of a teacher or researcher. The survey was administered online via Qualtrics or in a paper format depending on the school's access to technology. A total of 17% of participants completed the paper survey (n = 94). Each student was provided with an identification number, login code, and a URL to access the survey. After accessing the URL, an online consent form (or paper for those completing the paper format) was provided and students were required to actively agree to participate. Students then input their identification number and login code in an authenticator to ensure only participants whose parents provided consent completed the survey. To establish uniform understanding of bullying, students were required to read a brief definition of traditional and cyber bullying prior to commencing the survey, sourced from Solberg and Olweus (2003). Students then answered demographic information relating to their grade, gender, date of birth, and ethnicity. Upon survey completion, students were provided with a debrief statement advising that if they experienced distress while completing the survey, they could contact a researcher to make an appointment with their school counsellor. Fourteen students indicated that they wanted to make an appointment.

2.2.1. Contextualized vignettes Two hypothetical scenarios depicting cyberbullying on a Facebook platform and a group text message platform were developed to measure the contextualized factors. Scenarios depicting relational aggression were chosen due to strong correlates with cyberbullying (Modecki, Minchin, Harbaugh, Guerra, & Runions, 2014), and each vignette was matched to the participant's gender to enhance identification with the vignette characters. 2.2.1.1. Constructive defending self-efficacy. Four items examining one's ability to defend constructively was designed for the purposes of this study (e.g. “tell a teacher about the cyberbullying”). Items were rated on a 5-point Likert (1 = not well at all, to 5 = extremely well) through the prompt “if you had to intervene in this situation, how well can you intervene in the following ways?”, and names and pronouns in items were tailored to reflect the respective vignettes. Cronbach's alphas for the Facebook and text message contexts were 0.77 and 0.75, respectively. 2.2.1.2. Aggressive defending self-efficacy. Similar to constructive defending self-efficacy, four items were developed to assess an individual's aggressive defending self-efficacy (e.g. “making threats to the bully”). Items were also rated on a 5-point Likert (1 = not well at all, to 5 = extremely well), and Cronbach's alphas for the Facebook and text message contexts were 0.79 and 0.77, respectively.

2.4. Data management 2.4.1. Missing data Missing data between items ranged between 0% and 6.5%. These items were imputed using the expectation-maximization procedure in SPSS as this approach was deemed as the preferred method when imputing data that is not completely missing at random within a linear model (Schafer & Graham, 2002).

2.2.1.3. Contextual moral disengagement. Contextual moral disengagement was measured with 8-items, where each item represented one of the eight moral disengagement mechanisms rated on a 5-point scale (1 = strongly disagree to 5 = strongly agree). An example diffusion of responsibility item is “no one else is doing anything about it so why should I do something”. Wording of items were tailored to suit the context (i.e. type of platform, and vignette character names and pronouns). Strong internal consistency for both Facebook and text message contexts was present, with Cronbach's alphas equaling .86 and .85 respectively.

2.4.2. Scale transformation As continuous measures were positively skewed, scores were log 10 transformed in SPSS to rectify this issue. Skewness and kurtosis were improved, thus reducing but not entirely resolving non-normality. 3. Results

2.2.1.4. Context severity. Following the vignettes, participants indicated how severe they would rate each cyberbullying act on a 5point Likert (1 = not severe at all, 5 = extremely severe). The two contexts were matched on severity (t (539) = 0.63, p = .531).

3.1. Data analytic strategy Results are presented in four sections: exploratory factor analyses, analyses of variance (ANOVAs), correlations, and hierarchical regressions. First, factor analyses for the defending self-efficacy and contextual moral disengagement scales for each context are presented. Second, ANOVAs assessing the role of grade and gender on constructive defending self-efficacy, aggressive defending self-efficacy, and the two forms of moral disengagement within each context are shown. Third, correlations between continuous variables controlling for grade and gender are reported. Lastly, hierarchical regressions investigating influences of general and contextual moral disengagement on constructive and aggressive defending self-efficacy between contexts are presented. To examine possible clustering effects of responding within schools, linear mixed modelling was used to investigate whether participant responding was independent of belonging to a particular school. This analysis was conducted for each dependent variable in the study and school was added as a random factor. No significant clustering effects of schools were shown and so school effects were not accounted for in subsequent analyses.

2.2.2. General moral disengagement General moral disengagement was assessed using Bussey, Fitzpatrick, and Raman (2015)'s Cyber Bullying Moral Disengagement Scale, adapted from Bandura, Barbaranelli, Caprara, and Pastorelli (1996)'s Mechanisms of Moral Disengagement scale to reflect the cyber context. It consisted of 16 items, with two items representing each of the eight moral disengagement mechanisms (e.g. “it's okay to email a mean message to another kid because posting it on Facebook for everyone to see is worse”). Students indicated how much they agreed with each statement by rating their responses on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Reliability for this scale is 0.91 (Allison & Bussey, 2017). In the present study, α = 0.91. Due to a computer error, items 2 to 16 were presented as a 7-point scale to some participants who completed the survey online. This issue was rectified through prorating item scores to a 5-point scale and analyses were rerun using the raw data. No significant differences in results were found.

3.2. Exploratory factor analysis

2.3. Procedure

To examine the structure of the measures developed in this study, four principal axis factor analyses with Oblimin rotation were conducted on the 8-item defending self-efficacy scale and 8-item contextual moral disengagement scale within each context.

Ethics approval was granted by the authors' university Human Research Ethics Committee and consent to conduct the study was obtained from principals, parents, and students prior to testing. Students 320

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two contexts, Facebook and text message. A table of estimated marginal means and standard deviations is shown in Table 3.

Table 1 Factor structure for defending self-efficacy scales. Factors and loaded items

Factor Loadings 1

Constructive defending (Facebook) 1. Tell a teacher about the cyberbullying 2. Tell the bully to stop picking on Alex 3. Be there for Alex 4. Talk to Alex about the situation Aggressive defending (Facebook) 1. Make threats to the bully 2. Say mean things about the bully 3. Post the bully's personal information online 4. Make up rumors about the bully Constructive defending (text message) 1. Tell a teacher about the cyberbullying 2. Tell the bullies to stop picking on Charlie 3. Be there for Charlie 4. Talk to Charlie about the situation Aggressive defending (text message) 1. Make threats to the bullies 2. Say mean things about the bullies 3. Post the bullies' personal information online 4. Make up rumors about the bullies

3.3.1. Facebook context For constructive defending self-efficacy beliefs, Grade 7 students reported higher self-efficacy beliefs than did Grade 9 students and females reported higher self-efficacy beliefs than did males. For aggressive defending self-efficacy, males reported higher self-efficacy beliefs that did females. There were no grade differences in aggressive defending selfefficacy beliefs. For contextual moral disengagement, males scored higher than did females and there were no grade differences.

2

.76 .80 .80 .81 .76 .80 .78 .80

3.3.2. Text message context As for the Facebook context, constructive defending self-efficacy in Grade 7 students were reportedly higher than students in Grade 9, and females reported higher levels of defending self-efficacy than did males. For aggressive defending self-efficacy, males reported higher levels of defending self-efficacy than did females and there were no grade differences in reported defending self-efficacy levels. For contextual moral disengagement, males reported higher moral disengagement than did females and there were no grade differences for this form of moral disengagement.

.59 .74 .84 .85 .74 .80 .76 .80

3.3.3. General moral disengagement Grade 9 students reported higher levels of general moral disengagement than did Grade 7 students, and males scored higher than did females.

3.2.1. Defending self-efficacy For both contexts, factor analyses for defending self-efficacy yielded a two-factor model, which loaded onto the two forms of defending, constructive and aggressive. All items loaded higher than 0.50 and no cross-loadings were present. In the Facebook context, Cronbach's alphas were moderate for the constructive (α = 0.77) and aggressive (α = 0.79) subscales. Similar results were found for the text message context, yielding alphas of .75 and .77 respectively (see Table 1 for loadings).

3.4. Correlations Table 4 reports partial Pearsons correlations among the independent and dependent variables, controlling for grade and gender. These consisted of the contextualized variables – constructive and aggressive defending self-efficacy, and contextual moral disengagement, as well as general moral disengagement. In both contexts, aggressive defending self-efficacy was positively correlated with the two forms of moral disengagement, while constructive defending self-efficacy was negatively correlated with the two forms of moral disengagement. Aggressive defending self-efficacy was also correlated with constructive defending self-efficacy in the respective contexts.

3.2.2. Contextual moral disengagement Separate principal axis factor analyses with Oblimin rotation were also conducted for the 8-item moral disengagement scales for each context. Items for each analysis loaded onto one factor, indicating an overall measure of moral disengagement for each context (Facebook and text message) (see Table 2). All items loaded higher than 0.40 and cross-loadings were not present, thus no items were eliminated. Cronbach's alpha for the Facebook context was 0.86, and for the text message context, α = 0.85.

3.5. Hierarchical regression analyses Separate hierarchical regressions were conducted to investigate the impact of moral disengagement on constructive and aggressive defending self-efficacy. These analyses were repeated in each of the two contexts. The final four analyses each involved a four-step model and all independent variables were centered before analyses were conducted (Aiken & West, 1991).

3.3. Grade and gender effects Analyses of Variance (ANOVAs) were conducted to investigate effects of grade and gender on defending self-efficacy (constructive and aggressive), and moral disengagement (general and contextual), in the Table 2 Factor loadings for the contextual moral disengagement scales.

Factor Loadings Items

Facebook

Text message

1. A Facebook post/text messages don't really hurt anyone 2. No one else is doing anything about it so why should I do something 3. This post is just teaching Alex/Charlie a lesson 4. Alex/Charlie did something to deserve it 5. Posting a Facebook message/saying something through text isn't as bad as physical bullying 6. This post is alright as Alex/Charlie did something mean to Sam/them in the first place 7. If these things get posted it's their parent's fault for not monitoring them 8. Alex/Charlie deserves it for being a jerk

.66 .66 .78 .79 .65

.63 .65 .75 .77 .64

.81

.81

.49 .82

.47 .81

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Table 3 Estimated marginal means and standard errors. Variables Facebook Constructive DSE Aggressive DSE Contextual MD Text message Constructive DSE Aggressive DSE Contextual MD General MD

Grade 7

Grade 9

F

Male

Female

F

Total

1.07 (.16) .73 (.17) 1.11 (.17)

1.03 (.17) .74 (.16) 1.14 (.17)

7.37∗ .15 3.20

1.03 (.18) .79 (.19) 1.16 (.18)

1.08 (.15) .69 (.13) 1.08 (.15)

10.28∗∗ 41.72∗∗ 32.71∗∗

1.06 (.16) .74 (.17) 1.12 (.17)

1.08 (.15) .74 (.18) 1.11 (.17) 1.33 (.16)

1.04 (.18) .73 (.15) 1.11 (.17) 1.37 (.17)

11.11∗∗ 1.43 .43 5.93∗

1.03 (.18) .79 (.19) 1.16 (.17) 1.39 (.17)

1.09 (.14) .70 (.13) 1.07 (.15) 1.31 (.15)

19.64∗∗ 26.55∗∗ 48.39∗∗ 34.65∗∗

1.06 (.16) .74 (.17) 1.11 (.17) 1.35 (.16)

Note. Standard errors are in parentheses. DSE = defending self-efficacy, MD = moral disengagement. Degrees of freedom for each analysis = 536. ∗ p < .015, ∗∗p < .001. Table 4 Partial correlations controlling for grade and gender. Variables Facebook context 1. Constructive DSE 2. Aggressive DSE 3. Contextual MD Text message context 4. Constructive DSE 5. Aggressive DSE 6. Contextual MD

2.

Table 5 Hierarchical regressions (Facebook).

General MD

1.

3.

-.15 .38 .68

– .10 -.20

– .34

–

-.12 .32 .65

.89 .14 -.16

.11 .65 .35

-.18 .23 .68

4.

– .20 -.15

5.

– .27

6.

Variable

Grade Gender Aggressive defending self-efficacy General moral disengagement Contextual moral disengagement R2 ΔR2

–

Note. DSE = defending self-efficacy, MD = moral disengagement. All correlations were significant at p < .05.

Constructive defending self-efficacy Step 1

Step 2

Step 3

Step 4

-.04∗∗ .05∗∗ – – – .04

-.04∗∗ .06∗∗ .07 – – .04 .01

-.03∗ .04∗∗ .15∗∗ -.23∗∗ – .08 .04∗∗

-.03∗ .04∗∗ .17∗∗ -.11∗ -.20∗∗ .11 .02∗∗

Aggressive defending self-efficacy Grade Gender Constructive defending self-efficacy General moral disengagement Contextual moral disengagement R2 ΔR2

3.5.1. Facebook context The role of moral disengagement in constructive defending self-efficacy was first examined. As significant grade and gender effects were present, these factors were entered as control variables in Step 1. Aggressive defending self-efficacy (Facebook) was entered at Step 2 also as a control variable. General moral disengagement was entered at Step 3, followed by contextual moral disengagement (Facebook) at Step 4. This model was reproduced with aggressive defending self-efficacy as the dependent variable, and the constructive defending rather than aggressive defending self-efficacy measure entered at Step 2 as a control variable. Table 5 displays analysis coefficients. The overall model predicting to constructive defending self-efficacy was highly significant (F (5,534) = 12.54, p < .0005). In the final model, effects of gender, aggressive defending self-efficacy, general moral disengagement, and contextual moral disengagement emerged as significant predictors. Contextual moral disengagement was also significant even when general moral disengagement was accounted for. Specifically, they were both linked with greater constructive defending self-efficacy. Interestingly, general moral disengagement was a significant predictor for constructive defending self-efficacy when controlling for grade and gender, but was less significant when contextual moral disengagement was included in the model. The overall model predicting to aggressive defending self-efficacy was also highly significant (F (5,534) = 32.87, p < .0005). The model retained significance within all iterations, with gender, constructive defending self-efficacy, and the two forms of moral disengagement significantly predicting to aggressive defending self-efficacy. Greater general moral disengagement was linked with greater aggressive defending self-efficacy. Contextual moral disengagement was also shown to be significant beyond general levels of moral disengagement. These findings show that the two forms of moral disengagement (general and contextual) independently account for variance in aggressive defending self-efficacy for the Facebook context. It is also notable that although contextual moral disengagement is negatively linked with constructive defending (B = −0.20, t = −3.72, p < .0005) and positively linked with aggressive defending self-

.01 -.10∗∗ – – – .09

.01 -.10∗∗ .07 – – .09 .00

.00 -.07∗∗ .13∗∗ .38∗∗ – .21 .12∗∗

.00 -.07∗∗ .15∗∗ .26∗∗ .19∗∗ .24 .02∗∗

Note. Based on centered continuous variables. Gender was coded as 0 = Male, 1 = Female and Grade was coded as 0 = Grade 7, 1 = Grade 9. ∗ p ≤ .05, ∗∗p ≤ .01.

efficacy (B = 0.19, t = 3.95, p < .0005), the relative strength of this effect remains similar for both forms of defending. That is, within the Facebook context, the strength of the association between contextual moral disengagement is similar for aggressive and for constructive defending. 3.5.2. Text message context Similar analyses to those conducted for the Facebook context were conducted for the text message context for each form of defending. Specifically, grade and gender were entered at Step 1, constructive or aggressive defending self-efficacy (depending on the dependent variable) was entered at Step 2, and general moral disengagement and contextual moral disengagement (text message) were entered in subsequent steps. Table 6 shows the regression coefficients. The overall model predicting to constructive defending self-efficacy (F (5,534) = 15.48, p < .0005) was highly significant and retained significance within all iterations. In the final model, constructive defending self-efficacy was significantly predicted by grade, gender, aggressive defending self-efficacy, and contextual moral disengagement. General moral disengagement was also significant when controlling for grade and gender, whereas this factor lost significance when contextual moral disengagement was accounted for. Similar to the Facebook context, contextual moral disengagement was significant even after controlling for general moral disengagement, where lower contextual moral disengagement scores related to greater constructive defending self-efficacy. 322

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however, general moral disengagement was not a significant predictor within either context. Interestingly, general moral disengagement was significant in earlier iterations of the analyses, whereas no significant influences were evident when contextual moral disengagement was accounted for in the model. This result suggests that only in the presence of the contextual measure of moral disengagement does general moral disengagement become non-significant. In this study, the contextual measure thus acted as an even stronger predictor of constructive defending self-efficacy than general levels of moral disengagement. This finding stresses the importance of taking into account contextual factors when examining cyber defending. Furthermore, given that general moral disengagement was significant in one form of defending (aggressive) and not the other (constructive), the need to view defending self-efficacy as two distinct forms is further highlighted. In the present study, viewing defending self-efficacy as a multifaceted construct showed that moral disengagement varied with the form of defending employed. These findings reconcile inconsistencies in the extant literature that examine the relationship between moral disengagement and cyber defending. It is therefore apparent that there is a need to differentiate between the two forms of defending (constructive and aggressive) in subsequent studies of cyber defending.

Table 6 Hierarchical regressions (text message). Constructive defending self-efficacy Variable

Step 1

Step 2

Step 3

Step 4

Grade Gender Aggressive defending self-efficacy General moral disengagement Contextual moral disengagement R2 ΔR2

-.05 .06∗∗ – – – .05

-.04 .08∗∗ .18∗∗ – – .08 .03∗∗

-.04 .06∗∗ .23∗∗ -.19∗∗ – .11 .03∗∗

-.04∗ .06∗∗ .25∗∗ -.10 -.15∗∗ .13 .02∗∗

∗∗

∗∗

∗∗

Aggressive defending self-efficacy Grade Gender Constructive defending self-efficacy General moral disengagement Contextual moral disengagement R2 ΔR2

-.01 -.09∗∗ – – – .07

.00 -.10∗∗ .18∗∗ – – .10 .03∗∗

-.01 -.07∗∗ .22∗∗ .33∗∗ – .19 .10∗∗

-.01 -.06∗∗ .24∗∗ .22∗∗ .20∗∗ .22 .02∗∗

Note. Based on centered continuous variables. Gender was coded as 0 = Male, 1 = Female and Grade was coded as 0 = Grade 7, 1 = Grade 9. ∗ p ≤ .05, ∗∗p ≤ .01.

4.2. Contextual moral disengagement and defending self-efficacy

For aggressive defending self-efficacy, the overall model was highly significant (F (5,534) = 29.66, p < .0005), and significance was retained within all iterations. In the final model, gender, constructive defending self-efficacy, general, and contextual moral disengagement were significant predictors. The two forms of moral disengagement also independently accounted for additional variance in the text message context, where higher moral disengagement scores were linked with greater aggressive defending self-efficacy. In this context, the effect of contextual moral disengagement was stronger in aggressive forms of defending (B = 0.20, t = 3.96, p < .0005) compared with constructive forms defending (B = −0.15, t = 2.98, p = .003). This result highlights that in contrast with the Facebook context, contextual moral disengagement is more strongly associated with aggressive defending (positively) than in constructive defending (negatively) in the text message context.

Contextual moral disengagement was linked with defending selfefficacy beyond general levels of moral disengagement. Greater levels of moral disengagement in the specific contexts was linked with lower belief in ability to defend in a constructive manner and greater belief in ability to defend in an aggressive manner. Consistent with the social cognitive conceptualization of selectivity in moral disengagement, this finding indicates that contextual factors in moral disengagement independently contribute towards individual's beliefs in their ability to defend. Essentially, these results stress the importance of considering contextual factors when conducting research in moral disengagement. Furthermore, the observation that contextual moral disengagement is an even stronger predictor of constructive defending self-efficacy than general moral disengagement additionally highlights the need to account for contextual factors. 4.3. Strengths, limitations, and study implications

4. Discussion

This study was the first to investigate moral disengagement in cyberbullying at a contextual level. Furthermore, the contextual element of the cyberbullying platform was systematically manipulated, and moral disengagement was measured using the same scales with items tailored to suit the respective context. Matching pronouns of characters within each scenario to the participant's recorded gender also enhanced participant engagement with the individual vignettes and maximized relevance of the measure to the contextualized phenomenon that was assessed. The present study also differentiated between constructive and aggressive defending self-efficacy. One major point to take into consideration is that aggressive forms of defending can be linked with cyber perpetration. Unlike constructive defending, the trends of moral disengagement in aggressive defending unsurprisingly reflect those found in studies on cyber aggression. Essentially, this finding suggests that aggressive forms of defending are linked more closely to cyber perpetration than to constructive defending. Aggressive defending can potentially be considered a cyberbullying act, particularly as reacting aggressively towards a cyberbullying incident, such as posting mean things about the bully online, can be considered cyber perpetration despite the motive to defend the victim. This conclusion has implications for the potential negative outcomes of aggressive defending, which may reflect the impact of cyberbullying on perpetrators such as greater levels of stress, and higher risk of depression and anxiety

The present study builds on previous research by introducing a context-specific view of moral disengagement, and how this concept affects defending self-efficacy. Contextual moral disengagement was shown to differentially affect defending self-efficacy above general levels of moral disengagement. Within this domain, higher levels of moral disengagement (general and contextual) were shown to be linked with greater aggressive defending self-efficacy, whereas lower levels of moral disengagement were related to greater constructive defending self-efficacy. Overall, these results empirically stress the importance of considering contextual factors when examining moral disengagement and highlight the need to view defending as a multifaceted construct. 4.1. General moral disengagement and defending self-efficacy Findings showed that moral disengagement (general and contextual) similarly affected the two forms of defending self-efficacy (constructive and aggressive). General moral disengagement was positively associated with aggressive defending self-efficacy in both contexts. That is, individuals with greater levels of general moral disengagement had stronger beliefs in their ability to defend aggressively. This result is in line with traditional bullying research that has consistently linked high levels of moral disengagement with aggression (Gini, Pozzoli, & Hymel, 2014). For constructive defending self-efficacy, 323

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References

(Campbell, Slee, Spears, Butler, & Kift, 2013). Further research, however, is needed to establish this proposal. This study, however, is not without limitations. Firstly, due to a Qualtrics error, some participant scores on the general moral disengagement scale were prorated from a 7-point scale to a 5-point, in line with the previously validated Cyber Bullying Moral Disengagement Scale (Bussey et al., 2015). To assess the impact of this error on overall findings, regression analyses used in the present study were rerun using the raw data. Results yielded no significant difference in results and therefore it is unlikely that this error impacted the results. A further limitation is that this study was cross-sectional study. As social cognitive theory suggests bidirectional effects between personal, behavioral, and environmental factors, it is important to assess the influence of contextual moral disengagement on defending self-efficacy and vice versa. Clarifying these influences with a longitudinal design may also allow insight into the extent to which defending self-efficacy prompts future defending behavior. Although efficacy is shown to be a good proxy for actual behavior (Bandura, 1997), it is also crucial to examine how well efficacy predicts defending action. Moreover, only one vignette for each context was presented. Therefore, it can be argued that the findings of the present study were due to the vignette context rather than platform effects. The present study took measures to minimize this possibility through equating contexts on anonymity (both contexts depicted visible perpetrator names) and severity (participant scores on perceived severity of each incident did not significantly differ). Future research examining contextual effects on moral disengagement and defending would benefit from using multiple vignettes per cyberbullying platform. Despite its limitations, this study provides a significant contribution to the body of research on moral disengagement and cyber defending. It uniquely demonstrates that the two types of moral disengagement (general and contextual) are independently linked with the two forms of defending self-efficacy (constructive and aggressive). These results are in line with social cognitive theory, emphasizing the role of individual-level moral factors in defending self-efficacy and introducing the unique impact of contextual information on moral disengagement. This study thus highlights the need to consider contextual factors in cyberbullying and to view defending as a multifaceted construct. These findings have implications for intervention strategies to increase constructive defending in cyberbullying. Results underline the need to intervene not only at the individual level, but at the group level as suggested by whole school approaches to bullying intervention (Williford et al., 2013). It is particularly important that interventions to reduce cyberbullying to target context specific mediums in which cyberbullying occurs. This will involve tailoring intervention strategies around these specific contexts, for example, Facebook and text messages as investigated in this study. Addressing specific contexts in interventions will need to change as new platforms gain popularity. Further research examining contextual influences for each of the moral disengagement mechanisms separately and thus understanding how these mechanisms are differentially employed between contexts may be crucial in the development and implementation of future cyberbullying awareness and cyber safety programs. Future studies should also consider the impact of context not only at the individual level, but also in the wider social group. Specifically, moral disengagement has recently extended to account for the group in which bullying occurs, known as collective moral disengagement (Gini, Pozzoli, & Bussey, 2014; White, Bandura, & Bero, 2009). An individual's propensity to defend is likely to be impacted by how much they perceive their peers to justify not defending in particular contexts.

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