Mediation of moral disengagement on cyberbullying perpetration influenced by emotional intelligence and anonymity of Indonesian adolescents on social media Текст научной статьи по специальности «Социологические науки»

Research article

UDC 159.9.072

https://doi.org/10.21702/rpj.2022A15

Mediation of Moral Disengagement on Cyberbullying Perpetration Influenced by Emotional Intelligence and Anonymity of Indonesian Adolescents on Social Media

Ahmad Yazid Lubis1*, Hera Lestari Mikarsa2, Inge Andriani3

11 2' 3 Gunadarma University, Jakarta, Indonesia

* ahmad_yazid@taff.gunadarma.ac.id

Abstract: Introduction. The use of social media in a scope of adolescents confirms that without any sufficientdigital literacy, it shall leads to an increased dysfunctional behavior. Adolescents who feel anonymousand think that attacking others on social media shall not violate morals will make them portrayed as the cyberbullying perpetrator, even though they have any good emotional intelligence as well. This research aims to examine the mediating role of moral disengagement on cyberbullying perpetration which is influenced by emotional intelligence and anonymity of Indonesian adolescents on social media. Methods. The measurement applied on this research uses Adolescent Cyber-Aggressor Scale,Schutte Self-Report Emotional Intelligence Test, Anonymity Scale, and Moral Disengagement Scale. All scales have good reliability and have been tested for validity using confirmatory factor analysis (CFA). The structural model was tested by path analysis using the Amos program and the mediating effect was tested by using the Sobel test. Results. The results show the goodness of fit structural model with Chi-square = 2.604 (p > 0.05), RMSEA = 0.068, GFI = 0.996, AGFI = 0.963, dan TLI = 0.916. The acceptance on the hypothesis shows that moral disengagement significantly mediates the effect of emotional intelligence and anonymity on cyberbullying perpetration, whereas moral disengagement has the strongest direct effect. Discussion. The mechanism of moral disengagement in cyberbullying perpetrators can occur at the behavioral, agency, effect, and victim locus. Instilling awareness of moral values and increasing digital literacy in adolescents is very important to do to suppress any cyberbullying perpetration.

Keywords: cyberbullying perpetration, moral disengagement, emotional intelligence, anonymity, adolescents, social media, internet aggression, digital literacy, confirmatory factor analysis, path analysis

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

Highlights:

> The influence of emotional intelligence and anonymity through the mediation of moral disengagement was investigated in 346 adolescents (by mean age = 19.81 years) who were cyberbullying perpetrator on social media, which were selected using purposive sampling technique.

> Anonymity and moral disengagement have a direct influence on the cyberbullying perpetration of Indonesian adolescents on social media.

> The emotional intelligence of participants is in the high category and the majority have anonymous accounts on social media.

For citation: Lubis, A. Ya., Mikarsa, H. L., & Andriani, I. (2022). Mediation of moral disengagement on cyberbullying perpetration influenced by emotional intelligence and anonymity of Indonesian adolescents on social media. Russian Psychological Journal, 19(4), 231-242. https://doi.org/m21702/rpj.2022.415

Introduction

The lack of digital literacy in Indonesia during the rapid penetration of information and communication technology (Humaira, 2022), make adolescent internet users are actually way of abuse it to behave deviantly such as in terms of cyberbullying. Cyberbullying is an act of aggression that uses internet-based digital devices (Kowalski et al., 2012; Langos, 2012; Smith et al., 2012), so in this case digital literacy which includes digital skills, digital ethics, digital culture, and digital safetyis very important. Digital literacy reflects how the use of new media technology appeared as should be, as a fence to prevent dysfunctional behavior in cyberspace (Livingstone, 2008; Leung & Lee, 2012; Miao et al., 2020).

Data released by We Are Social and Kepios in 2022 (Kemp, 2022), shows that internet penetration in Indonesia reaches 73.7 % of the total population, while social media users in the age range of 13-17 years are 22 % and those aged 18-24 years reach 32 %, bringing a total of 83.2 million social media users. The number of adolescent social media users in Indonesia raises concerns because it is not be accompanied by any sufficient digital literacy along the way, coupled with the absence of assistance and supervision from parents because they think that adolescents are old enough to use any kinds of social media. In fact, adolescents are the group that most closely related to cyberbullying perpetration (Kowalski et al., 2012; Robson & Witenberg, 2013; Balakrishnan, 2015).

Digital Civility Index (DCI) data released by Microsoft in 2020 shows that the level of digital civility of Indonesian netizens is the lowest in Southeast Asia, the civility in question is related to hate speech, trolling, and others cyberbullying perpetration (Mazrieva, 2021). Cyberbullying perpetration is very contrary to the universally believed values of goodness, so that cyberbullying perpetrators carry out moral disengagement, a cognitive mechanism to justify their actions and distort the effects of guilt caused (Bandura, 2016). This moral disengagement mechanism occurs at the behavioral, agency, effect, and victim locus (Bandura, 2016). For example, the perpetrator only feels criticizing the victims, compares his actions with others, feels he is just joining in, sees his actions as a joke, and may also think that the victims deserve to be attacked. Several studies (e.g. Robson & Witenberg, 2013; Gini et al., 2014; Kowalski et al., 2014) have shown that moral disengagement is indeed positively correlated with any cyberbullying behavior.

Basically, adolescents who do not have the ability to manage emotions will tend to be easier to attack and hurt others (Krahe, 2005). In addition, if using an anonymous account, adolescents

will feel safer to carry out their actions (Suler, 2004; Nixon, 2014). However, this may not happen if the teenager realizes that the act is not good and is against social rules and moral standards. Several previous researches have shown emotional intelligence to have a negative relationship with cyberbullying perpetration (e.g. Elipe et al., 2015; Adiyanti et al., 2020) and moral disengagement (e.g.Marin-Lopez et al., 2020; Parlangeli et al., 2019). Meanwhile, anonymity has been shown to have a positive relationship with cyberbullying perpetration in several researches (e.g. Barlett, 2015; Barlett et al., 2016) and moral disengagement (e.g. Wang & Ngai, 2020).

The impact of cyberbullying perpetration is very dangerous for teenagers, both perpetrators and victims. Victims can experience psychological problems such as depression which can trigger suicide (Hinduja & Patchin, 2010). Several cases of suicide have occurred in Indonesia (Edward, 2013; Prastiwi, 2020). On the other hand, perpetrators will tend to be aggressive, violent, irritable, impulsive, want to dominate, and lack of empathy (Nixon, 2014). Victims are also very likely to become perpetrators when retaliating with similar acts of cyberbullying (Ak et al., 2015). Based on astudy by the Indonesian Internet Service Providers Association (APJII), 7.9 % of cyberbullying victims in Indonesia responded with the same action (Pratomo, 2019). Thus, cyberbullying can become a continuous cycle.

Based on the description that has been stated, this research aims to determine the role of moral disengagement on cyberbullying perpetration committed by adolescent on social media users in Indonesia. This research hypothesizes that moral disengagement mediates the effect of emotional intelligence and anonymity on cyberbullying perpetration (Figure 1).

Figure 1

Research hypothesis model

Methods

Participants

Participants are Indonesian adolescents who are indeed be part of cyberbullying perpetrators on social media such as Facebook, Instagram1, TikTok, YouTube2, Snapchat, and other social me-

1 Editorial note: Facebook and Instagram are online social media owned by Meta Platforms, recognized as extremist organizations, and banned in Russia since 2022.

2 Editorial note: Site that violates Russian legislation.

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

dia applications. The sampling technique used purposive sampling by sending a direct message containing a request to be willing to become a respondent to adolescents aged 17-21 years who were caught doing cyberbullying perpetration on social media. Collecting data using an online questionnaire, a total of 346 participants (133 males) with an average age of 19.81 (SD = 1.03) were collected.

Measurement Validity and Reliability

Measurements using the Adolescent Cyber-Aggressor Scale (18 items CYB-AGS; Buelga et al., 2020), Schutte Self-Report Emotional Intelligence Test (33 items SSEIT; Schutte et al., 1998), Anonymity: Unlinkability, Pseudonymity, Unobservability (8 items ANO-UPU; Lee et al., 2013), and the Moral Disengagement: A Framework for Understanding Bullying Among Adolescents (18 items MD-FUBA; Hymel et al., 2005). All scales were tested for reliability using SPSS (ver.22). Furthermore, the construction validity of each scale was tested by confirmatory factor analysis (CFA) with a minimum factor loading value of 0.4 (Harrington, 2009). All scales produce a fit model with good validity and reliability (Table 1).

Table 1

Validity and reliability of measuring instrument

Scale Cronbach alpha Chi-square RMSEA GFI AGFI Factor loading range Total Valid Item

CYB-AGS 0.761 41.602* 0.024 0.979 0.966 0.44-0.83 10

SSEIT 0.932 91.157* 0.025 0.967 0.953 0.42-0.87 14

ANO-UPU 0.850 7.975* 0.029 0.993 0.976 0.54-0.88 6

MD-FUBA 0.919 53.566* 0.017 0.977 0.963 0.45-0.86 12

Note: * p > 0.05.

Data Analysis Technique

The initial analysis examined differences in cyberbullying perpetration, emotional intelligence, anonymity, and moral disengagement based on gender, and tested the correlation of each variable using SPSS (ver.22). The hypothesis model was tested by path analysis using the Amos program (ver.22). The criteria used were Chi-square, p > 0.05, RMSEA < 0.08, GFI > 0.9, and AGFI > 0.9 (Haryono & Wardoyo, 2012). Finally, the mediating effect was tested using the Sobel test with the criteria of statistical value > 1.967, and p < 0.05 (Widhiarso, n.d.).

Results

Descriptive Analysis and Variable Correlation

The results of the descriptive analysis of the measurements showed, although not much different, the empirical mean of male cyberbullying perpetration (M = 14.81, SD = 4.92) was higher than that of female (M = 14.75, SD = 4.77). The results of the correlation test show that emotional intelligence is negatively correlated with cyberbullying perpetration, while anonymity and moral disengagement are positively correlated with cyberbullying perpetration (Table 2). Regarding anonymity, the data shows that 68.8 % of participants (N = 346) have anonymous accounts on social media (Table 3).

Table 2

Means, standard deviations, and correlations of the main study variables

Variables Male Female 1 2 3 4

M SD M SD

1. CBP 14.81 4.92 14.75 4.77 1

2. EI 44.10 7.36 43.96 6.76 -0.154** 1

3. ANO 14.43 4.46 14.86 4.58 0.259** 0.031 1

4. MD 22.12 7.89 22.53 8.18 0.307** -0.330** 0.267** 1

Note: ** p < 0.01, N = 346, CBP: Cyberbullying Perpetration, EI: Emotional Intelligence, ANO: Anonymity, MD: Moral Disengagement.

Table 3

Anonymous account on social media

Have an anonymous account Male Female Total

Yes 79 No 54 159 54 238 (68.8 %) 108 (31.2 %)

Note: N = 346.

Model test Results

Based on model test result with the Amos program (ver.22), the research hypothesis was proven to be accepted. The model meets the goodness of fit criteria with Chi-square = 2.604, p > 0.05, RMSEA = 0.068, GFI = 0.996, AGFI = 0.963, and TLI = 0.916 (Figure 2).

Figure 2

Model test results

Chi-square = 2.604 p = 0.107 RMSEA = 0.068 GFI = 0.996 AGFI = 0.963 TLI = 0.916

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

Table 4

Estimates regression weights

Estimate S.E. C.R.

Emotional Intelligence —» Moral Disengagement -0.391*** 0.056 -6.965

Anonymity —» Moral Disengagement 0.492*** 0.086 5.699

Moral Disengagement — Cyberbullying Perpetration 0.153*** 0.031 4.908

Anonymity — Cyberbullying Perpetration 0.202*** 0.055 3.649

Note: *** p < 0.001, N = 346.

Table 5

Standardized direct, indirect, total effect, and Sobel test result

Direct effect Indirect effect Total effect Sobel test

EI — MD -0.339***

ANO — MD 0.277***

EI — CBP -

ANO — CBP 0.190***

MD — CBP 0.256***

EI — MD — CBP -0.087*** -0.087 -4.030***

ANO — MD — CBP 0.071*** 0.261 3.737***

Note: *** p < 0.001, N = 346, CBP: Cyberbullying Perpetration, EI: Emotional Intelligence, ANO: Anonymity, MD: Moral Disengagement.

Moral disengagement has the strongest influence on cyberbullying perpetration (ß = 0.256, p < 0.001). Emotional intelligence and anonymity significantly predict moral disengagement (ß = -0.339,p < 0.001 and ß = 0.277, p < 0.001). The results of the mediation test show that moral disengagementsignificantly mediates emotional intelligence on cyberbullying perpetration (Sobel test = -4.030, p < 0.001), so that the indirect effect of emotional intelligence on cyberbullying perpetration is -0.087. Moral disengagement also significantly mediates anonymity on cyberbullying perpetration (Sobel test = 3.737, p < 0.001), so that the indirect effect of anonymity on cyberbullying perpetration is 0.261.

Discussion

The results show that cyberbullying perpetration that appears in adolescents is a contribution from emotional intelligence, anonymity, and moral disengagement. Moral disengagement significantly mediates the effect of emotional intelligence and anonymity on cyberbullying perpetration. Anonymity and moral disengagement are known to have a direct influence on cyberbullying perpetration, where moral disengagement has the strongest direct effect.

Adolescence is the most vulnerable period to experience any emotional fluctuations (Santrock, 2004), so it will escalates the tendency to act aggressively because of the uncontrolled emotions (Krahe, 2005). Individuals with good emotional management will have the ability to empathize and build relationships with other people (Goleman, 2009), automatically lowering the possibility of doing harm or hurting others, including cyberbullying perpetration. However, this does not seem to be the case when the moral disengagement mechanism occurs, the findings of this study prove this. The results show that moral disengagement mediates the effects of emotional intelligence and cyberbullying perpetration, while it can be seen that participants who are cyberbullying perpetrators have high emotional intelligence (Table 2). This means that even though adolescents have high emotional intelligence, it does not necessarily guarantee that adolescents will not engage in cyberbullying perpetration.

The occurrence of a moral disengagement mechanism will make the perpetrator lose a sense ofempathy for the victim (Bandura, 2016) which automatically increases cyberbullying perpetration. In other words, moral disengagement plays its role as a mediator. The findings of this study are in line with the research of Nusantara et al. (2020) and Fang et al. (2020). The findings of research conducted by Nusantara et al. (2020) showed that moral disengagement mediates one aspect of emotional intelligence, namely empathy with cyberbullying behavior, where empathy has a significant negative relationship with moral disengagement and cyberbullying behavior. Fang et al. (2020) in their research also found that moral disengagement mediates a positive relationship between callous-unemotional traits and cyberbullying behavior, where callous-unemotional traits characterize adolescents who have no remorse or guilt, and do not care about the negative consequences of their actions.

The factor of the difference in interactions in social media compared to the real world on the other hand is a catalyst for the role of moral disengagement. According to Pornari & Wood (2010), virtual world interactions can create a user's perspective that all actions taken in cyberspace will not harm and only think of it as a joke or fun thing, so that it can trigger an increase in moral disengagement. In the context of social media, the implementation of the perpetrator's emotional intelligence level can shift due to the lack of non-verbal messages when interacting (Pornari & Wood,2010; Runions & Bak, 2015; Marin-Lopez et al., 2020). For example, cyberbullying

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

perpetrators cannot see the victim's actual emotional responses and expressions, thus eliminating the possibility of the perpetrator's empathy for the victim.

The findings of this study indicate that anonymity directly predicts cyberbullying perpetration, this finding is in line with the research of Barlett (2015) and Barlett et al. (2016). Anonymity is one of the characteristics of interactions on social media that allows users not to display their real identity (Suler, 2004; Nixon, 2014), this situation makes adolescents who are cyberbullying perpetrators feel freer without fear of being identified. Research conducted by Barlett (2015) shows that anonymity develops an individual's positive attitude towards cyberbullying, which in itself predicts cyberbullying behavior. Barlett et al. (2016) in their study also showed the perception of anonymity was related to cyberbullying behavior, where the higher the sense of anonymity online, the more likely it was to cyberbully others.

The results of the mediation test also show that moral disengagement is significant as a mediator of the influence of anonymity on cyberbullying perpetration, where the effect of anonymity becomes stronger through mediation. In addition, descriptive analysis (Table 3) also shows that the majority of participants have anonymous accounts on social media. According to Suler (2004), anonymity on theinternet can trigger behavior that has never been done in the real world because they feel they can't be monitored, so that perpetrators ignore rules and a sense of responsibility. This is in line with the moral disengagement mechanism stated by Bandura (2016). The results of this study are in line with the research of Wang & Ngai (2020) which shows that moral disengagement acts as a mediator of anonymity and cyberbullying behavior. However, there are differences related to the direct effect of anonymity, Wang & Ngai (2020) in their research show that anonymity does not have a direct effect on cyberbullying behavior, there is no significant relationship related to the mediating effect of moral disengagement (Wang & Ngai, 2020).

In addition to significantly mediating emotional intelligence and anonymity, the results of this study indicate that moral disengagement has the strongest direct effect on cyberbullying perpetration. This finding strengthens the previous research conducted by Gini et al. (2014), and Kowalski et al. (2014). The meta-analysis study conducted by Kowalski et al. (2014) showed that moral disengagement was the most strongly associated factor with cyberbullying behavior compared to other factors. While Gini et al. (2014) in their meta-analysis study also found that moral disengagement was strongly related to aggressive behavior in adolescents and children, including cyberbullying.

Cyberbullying perpetrators will consider the act of attacking and hurting others on social media as a natural thing and not an immoral act because many social media users engage in similar behavior. This is supported by research by Robson & Witenberg (2013) who found diffusion of responsibility at the agency locus of moral disengagement, predicting cyberbullying behavior. On the other hand, it is possible that the perpetrator actually knows that his action is not right, but the perpetrator activates the moral disengagement mechanism to reconstruct his own mind by assuming that his act is not a bad thing with the aim of reducing uncomfortable effects such as feeling guilty or feeling like a bad person.

Referring to Bandura (2016), the mechanism of moral disengagement in cyberbullying perpetrators can occur at the behavioral locus, agency locus, effect locus, and victim locus. At the behavioral locus, the perpetrator will justify his actions as right. For example, the perpetrator thinks that the victim is the one who did bad things, so the perpetrator feels that he only gives good criticism. Perpetrators will also compare their actions with the actions of others who are

worse. At the agency locus, the perpetrator will think that he/she is not the one who should be responsible because he is just joining in on cyberbullying or just sharing and forwarding, the perpetrator will think that the first content creator must be responsible. At the locus of effect, the perpetrator will feel that his/her actions will not have a negative impact on the victim and perceive it as a joke or fun thing. While at the victim locus, the perpetrator will assume that his actions occurred due to the victim's own fault. For example, the perpetrator thinks that the victim's content on social media deserves to be blasphemed.

Adolescents in the digital age spend most of their time on social media. Meanwhile, adolescents tend to still not be able to understand their identity and are easily influenced by the environment (Santrock, 2004). The use of social media that is not accompanied by digital literacy and supervision makes teenagers think that intimidating, blaspheming, demeaning, or insulting others on social media is an act that does not violate social rules and norms, by itself will trigger teenagers to do cyberbullying, several studies have shown this (e.g. Stodt et al., 2016; Tao et al., 2022). In addition, the virtual world, which knows no boundaries of time and place, has made cyberbullying a continuous threat to victims (Tokunaga, 2010; Kowalski et al., 2012; Langos, 2012).

Conclusions

Based on the results of the research, moral disengagement was proven to mediate the effect of emotional intelligence and anonymity on cyberbullying perpetration in Indonesian adolescents on social media. It can also be seen that the role of moral disengagement has a vital role related to cyberbullying perpetration. The advice that shall be given is the importance of efforts to reduce the level of moral disengagement by instilling awareness of moral values in adolescents in order to reducethe possibility of cyberbullying. Future research is expected to be able to be conducted and proved this. In addition, it is necessary to escalates any digital literacy in adolescents which includes digital skills, digital ethics, digital culture, and digital safety, especially in developing countries such as Indonesia.

References

Adiyanti, M. G., Nugraheni, A. A., Yuliawanti, R., Ragasukmasuci, L. B., & Maharani, M. (2020). Emotion regulation and empathy as mediators of self-esteem and friendship quality in predicting cyberbullying tendency in Javanese-Indonesian adolescents. International Journal of Adolescence and Youth, 25(1), 251-263. https://doi.org/10.1080/02673843.2019.1614079 Ak, S., Özdemir, Y., & Kuzucu, Y. (2015). Cybervictimization and cyberbullying: The mediating role of anger,

don't anger me! Computers in Human Behavior, 49, 437-443. https://doi.org/10.1016/j.chb.2015.03.030 Balakrishnan, V. (2015). Cyberbullying among young adults in Malaysia: The roles of gender, age and Internet frequency. Computers in Human Behavior, 46, 149-157. https://doi.org/10.1016/j. chb.2015.01.021

Bandura, A. (2016). Moral disengagement: How people do harm and live with themselves. Worth Publishers, Macmillan Learning. https://www.macmillanlearning.com/college/us/product/ Moral-Disengagement

Barlett, C. P. (2015). Anonymously hurting others online: The effect of anonymity on cyberbullying frequency. Psychology of Popular Media Culture, 4(2), 70-79. https://doi.org/10.1037/a0034335 Barlett, C. P., Gentile, D. A., & Chew, C. (2016). Predicting cyberbullying from anonymity. Psychology of Popular Media Culture, 5(2), 171-180. https://doi.org/10.1037/ppm0000055

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

Buelga, S., Postigo, J., Martinez-Ferrer, B., Cava, M.-J., & Ortega-Barón, J. (2020). Cyberbullying among adolescents: Psychometric properties of the CYB-AGS Cyber-Aggressor Scale. International Journal of Environmental Research and Public Health, 77(9). https://doi.org/10.3390/ijerph17093090 Edward, J. (2013). Kicauan terakhir ketua panitia locstock sebelum bunuh diri. Liputan 6.https://www.

liputan6.com/showbiz/read/596694/kicauan-terakhir-ketua-panitia-locstock- sebelum-bunuh-diri Elipe, P., Mora-Merchán, J. A., Ortega-Ruiz, R., & Casas, J. A. (2015). Perceived emotional intelligence as a moderator variable between cybervictimization and its emotional impact. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.00486 Fang, J., Wang, X., Yuan, K.-H., Wen, Z., Yu, X., & Zhang, G. (2020). Callous-Unemotional traits and cyberbullying perpetration: The mediating role of moral disengagement and the moderating role of empathy. Personality and Individual Differences, 757. https://doi.org/10.1016/j.paid.2020.109829 Gini, G., Pozzoli, T., & Hymel, S. (2014). Moral disengagement among children and youth: A meta-analytic review of links to aggressive behavior. Aggressive Behavior, 40(1), 56-68. https://doi.org/10.1002/ab.21502 Goleman, D. (2009). Kecerdasan emosional (T. Hermaya, Ed.). Gramedia Pustaka Utama. https://

www.gramedia.com/products/kecerdasan-emosional-cetak-ulang Harrington, D. (2009). Confirmatory factor analysis. Oxford University Press. https://doi.org/10.1093/

acprof:oso/9780195339888.001.0001 Haryono, S., & Wardoyo, P. (2012). Structural equation modeling AMOS 18.00. PT. Intermedia Personalia Utama.

Hinduja, S., & Patchin, J. W. (2010). Bullying, cyberbullying, and suicide. Archives of Suicide Research,

14(3), 206-221. https://doi.org/10.1080/13811118.2010.494133 Humaira, F. R. (2022). Indeks literasi digital berdasarkan wilayah di Indonesia. Kata Data.https://databoks.

katadata.co.id/datapublish/2022/07/12/indeks-literasi-digital-berdasarkan- wilayah-di-indonesia Hymel, S., Rocke-Henderson, N., & Bonnano, R. A. (2005). Moral disengagement: A framework for understanding bullying among adolescents. Journal of the Social Science, 8(1), 1-11. https:// psycnet.apa.org/record/2018-24434-001 Kemp, S. (2022). Digital2022: Indonesia. We Are Social & Kepios Data Reportal. https://datareportal.

com/reports/digital-2022-indonesia Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140(4), 1073-1137. https://doi.org/10.1037/a0035618 Kowalski, R. M., Limber, S. P., & Agatston, P. W. (2012). Cyberbullying: Bullying in the digital age

(2nd ed.). Wiley-Blackwell Publishing. Krahe, B. (2005). Perilaku agresif: Buku panduan psikologi sosial. (H. Soetjipto, Ed.). Pustaka Pelajar.

https://onesearch.id/Record/I0S1.INLISM00000000011266 Langos, C. (2012). Cyberbullying: The challenge to define. Cyberpsychology, Behavior, and Social

Networking, 75(6), 285-289. https://doi.org/10.1089/cyber.2011.0588 Lee, H., Choi, J., & Kim, K. K. (2013). Impact of anonymity (unlinkability, pseudonymity, unobservability)

on information sharing. PACIS Proceedings, 70. https://aisel.aisnet.org/pacis2013/70 Leung, L., & Lee, P. S. N. (2012). The influences of information literacy, internet addiction and parenting styles on internet risks. New Media & Society, 14(1), 117-136. https://doi. org/10.1177/1461444811410406 Livingstone, S. (2008). Internet literacy: Youngs people's negotiation of new online opportunities. In T. McPherson (Eds.), Digital youth, innovation, and the unexpected (pp. 101-122). The MIT

Press. https://mitpress.mit.edu/9780262633598/digital-youth-innovation-and-the-unexpected/ Marin-Lopez, I., Zych, I., Ortega-Ruiz, R., Monks, C. P., & Llorent, V. J. (2020). Empathy online and moral disengagement through technology as longitudinal predictors of cyberbullying victimization and perpetration. Children and Youth Services Review, 116. https://doi.org/10.1016/j. childyouth.2020.105144

Mazrieva, E. (2021). Indeks Keberadaban Digital: Indonesia Terburuk se-Asia Tenggara. VOA Indonesia. https://www.voaindonesia.com/a/indeks-keberadaban-digital-indonesia-terburuk-se-asia-tenggara/5794123.html Miao, T.-C., Gu, C.-H., Liu, S., & Zhou, Z. K. (2020). Internet literacy and academic achievement among Chinese adolescent: A moderated mediation model. Behaviour & Information Technology. https://doi.org/10.1080/0144929X.2020.1831074 Nixon, C. L. (2014). Current perspectives: The impact of cyberbullying on adolescent health.

Adolescent Health, Medicine and Therapeutics, 5, 143-158. https://doi.org/10.2147/AHMT.S36456 Nusantara, B. A., Sugiharto, D. Y. P., & Mulawarman, M. (2020). The effects of empathy on cyberbullying mediated by moral disengagement. Jurnal Bimbingan Konseling, 9(2), 116-122. https://journal.unnes.ac.id/sju/index.php/jubk/article/view/37473 Parlangeli, O., Marchigiani, E., Bracci, M., Duguid, A. M., Palmitesta, P., & Marti, P. (2019). Offensive acts and helping behavior on the internet: An analysis of the relationships between moral disengagement, empathy and use of social media in a sample of Italian students. Work, 63(3), 469-477. https://doi.org/10.3233/W0R-192935 Pornari, C. D., & Wood, J. (2010). Peer and cyber aggression in secondary school students: The role of moral disengagement, hostile attribution bias, and outcome expectancies. Aggressive Behavior, 36(2), 81-94. https://doi.org/10.1002/ab.20336 Prastiwi, D. (2020). 5 hal terkait bunuh diri pelajar di Jakarta Timur. Liputan 6. https://www.

liputan6.com/news/read/4161425/5-hal-terkait-bunuh-diri-pelajar-di-jakarta-timur Pratomo, Y. (2019). 49 persen netizen di indonesia pernah mengalami "bullying" di medsos. Kompas. com. https://tekno.kompas.com/read/2019/05/16/08290047/49-persen-netizen-di- indonesia-pernah-mengalami-bullying-di-medsos Robson, C., & Witenberg, R. T. (2013). The influence of moral disengagement, morally based self-esteem, age, and gender on traditional bullying and cyberbullying. Journal of School Violence, 12(2), 211-231. https://doi.org/10.1080/15388220.2012.762921 Runions, K. C., & Bak, M. (2015). Online moral disengagement, cyberbullying, and cyberaggression. Cyberpsychology, Behavior, and Social Networking, 18(7), 400-405. https://doi.org/10.1089/ cyber.2014.0670

Santrock, J. W. (2004). Adolescence: Perkembangan remaja. https://onesearch.id/Record/IOS14827. ai:slims-325

Schutte, N. S., Malouff, J. M., Hall, L. E., Haggerty, D. J., Cooper, J. T., Golden, C. J., & Dornheim, L. (1998). Development and validation of a measure of emotional intelligence. Personality and Individual Differences, 25(2), 167-177. https://doi.org/10.1016/S0191-8869(98)00001-4 Smith, P. K., del Barrio, C., & Tokunaga, R. S. (2012). Definitions of bullying and cyberbullying: How useful are the terms? In S. Bauman, D. Cross, & J. Walker (Eds.), Principles of cyberbullying research: Definition, measures, and methods (pp. 29-40). Routledge.https://doi.org/10.4324/9780203084601 Stodt, B., Wegmann, E., & Brand, M. (2016). Predicting dysfunctional internet use: The role of age, conscientiousness, and internet literacy in internet addiction and cyberbullying. International

СОЦИАЛЬНАЯ ПСИХОЛОГИЯ

Journal of Cyber Behavior, Psychology and Learning (IJCBPL), 6(4), 28-43. https://doi.org/10.4018/ IJCBPL.2016100103

Suler, J. (2004). The online disinhibition effect. CyberPsychology and Behavior, 7(3), 321-326.

https://doi.org/10.1089/1094931041291295 Tao, S., Reichert, F., Law, N., & Rao, N. (2022). Digital technology use and cyberbullying among primary school children: Digital literacy and parental mediation as moderators. Cyberpsychology, Behavior, and Social Networking, 25(9), 571-579. https://doi.org/10.1089/cyber.2022.0012 Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26(3), 277-287. https://doi. org/10.1016/j.chb.2009.11.014 Wang, L., & Ngai, S. S. (2020). The effects of anonymity, invisibility, asynchrony, and moral disengagement on cyberbullying perpetration among school-aged children in China. Children and Youth Services Review, 119. https://doi.org/10.10167j.childyouth.2020.105613 Widhiarso, W. (n.d.). Menghitung signifikansi peranan tidak langsung program AMOS. https:// widhiarso.staff.ugm.ac.id/files/Menghitung%20Signifikansi%20Peranan%20Tidak%20Langsung%20 Program%20AM0S.pdf

Received: September 18, 2022 Revision received: October 09, 2022 Accepted: October 11, 2022

Author Contribution

Ahmad Yazid Lubis contributed to conceptualizing and designing research, finding respondents and collecting data, statistical analysis and interpreting the results, writing and editing research report manuscripts as well.

Hera Lestari Mikarsa contributed to the conceptualization of the research, preparing the theory and literature reviews, compiling and validating the measurement scales, and interpreting the results.

Inge Andriani contributed to planning research and data collections, analyzing data and interpreting results, and writing the research reports as well.

Author Details

Ahmad Yazid Lubis - M.Si. (Communication Psychology), Candidate of Dr. (Psychology) at Doctoral Program of Psychology Science, Gunadarma University, Jakarta, Indonesia; ORCID: https://orcid. org/0000-0001-5667-917X; e-mail: ahmad_yazid@taff.gunadarma.ac.id

Hera Lestari Mikarsa - Ph.D (Psychology), Professor at Doctoral Program of Psychology Science, Gunadarma University, Jakarta, Indonesia; Scopus Author ID: 22635041300; e-mail: hera@staff. gunadarma.ac.id

Inge Andriani - Dr. (Psychology), Lecturer at Doctoral Program of Psychology Science, Gunadarma University, Jakarta, Indonesia; ORCID: https://orcid.org/0000-0002-1529-772X; e-mail: inge_andriani@ staff.gunadarma.ac.id

Conflict of Interest Information

The authors have no conflicts of interest to declare.