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

Abstract

BACKGROUND:

The phenomenon of cyberbullying is on the rise among adolescents and in schools.

OBJECTIVE:

To evaluate the relationship between personality characteristics such as empathy, the tendency to implement cognitive mechanisms aimed at moral disengagement, and the use of social media.

PARTICIPANTS:

Italian students from first to fifth year in high school classes (n = 264).

METHODS:

A questionnaire was used to gather information on the sociodemographic characteristics of the participants, their use of social media, their level of empathy (Basic Empathy Scale, BES), and mechanisms of moral disengagement (Moral Disengagement Scale MDS). Two questions were included to determine whether each participant had ever been a victim of or witness to cyberbullying.

RESULTS:

Results suggest that offensive behaviors are related to mechanisms of moral disengagement and to interaction using forms of communication that allow anonymity. In addition, offensive behavior appears to be related to forms of Internet addiction, while prosocial behavior is linked with cognitive empathy.

CONCLUSION:

In order to promote the establishment of prosocial behavior, it would seem necessary for the various players involved – schools, parents, social network developers – to make an effort to implement educational environments and virtual social networks based on a hypothesis of “design for reflection”, educating young people about the need to take the time to understand their feelings and relationships expressed via social media.

Keywords

Cyberbullying educational environments reflective thinking internet addiction ethics

1 Introduction

All areas of daily life are increasingly real-virtual contexts within which new ways of performing old behaviors emerge. Even training environments are now a mixture of virtuality and reality, and blended learning environments may be considered the norm today [1]. Schools often provide opportunities to connect to the Internet in order to explore new content or to implement social learning. However, this process of “educational virtualization” is not always governed by teaching institutions, and, apart from a few rare exceptions, many students now go to class with their smartphones, without any supervision, and without using them as a tool for learning. In a recent study conducted by OssCom, the Research Center on media and communication of the Catholic University in Milan, it was reported that 97% of Italian boys and girls aged 15–17 and 51% of Italian children aged 9–10 use a smartphone daily to go online, and that 26% of Italian boys and girls between 9 and 17 use the Internet every day at school [2]. This means that even in school, there are opportunities for reprehensible behaviors [3] such as harassing, attacking or degrading another who is for some reason perceived as less powerful. In 2012 a study [4] highlighted alarming data indicating that 37% of students from a middle school in Texas, US, have experienced cyberbullying, and that more than half of the sample (56%) had witnessed it. Other research reports a trend toward increasing cyberbullying [2].

Cyberbullying is a form of aggressive behavior that can take place in a number of different contexts and that occurs when one or more people perform actions aimed at harming, insulting or deliberately offending other people using electronic means [5 –7]. Research has attempted to specify the salient features of cyberbullying, which can be summarized as follows: a) it is a form of relational aggression, b) it is based on the awareness of the person who implements it, c) it is based on asymmetric relations, d) it most likely does not end in a single event, and, e) it occurs on the Internet or, in any case, through electronic means [5 , 9]. In this definition, the qualifying relevance of the use of information and communication technology (ICT) seems absolute. However, focusing on the features of the virtual media and contexts in which cyberbullying takes place casts light on only one aspect of the phenomenon. It is clear that bullying and cyberbullying are social behaviors that must be understood not only with reference to the objective opportunities that make them possible (namely, the means used), but also with reference to the affective and thinking mechanisms that make them viable [10 –12].

Focusing on the personality factors that are likely to interact with other variables in giving rise to offensive actions, various studies [13 –18] claim that empathy is fundamental in the moral development of the individual as it can inhibit the manifestation of aggressive behavior. As a consequence, lower empathic abilities could lead to a more frequent manifestation of behaviors that are offensive to other people [19]. However, aggressive behavior has a counterpart in behavior aimed at helping others, and analysis of this type of behavior reveals that speaking of empathy in a general sense is not sufficient for understanding behavior aimed at aggression or help. In fact, according to more recent studies, in order to understand prosocial behavior it is necessary to associate the study of empathy with its components, and therefore distinguish between affective empathy [20] and cognitive empathy [21 –23]. The two components of empathy must, in turn, be associated with the reasoning and motivation that drives individuals to modulate their behavior in a variety of contexts [24 –26].

Through discrimination between the effects of emotional and cognitive empathy, it has been reported that cognitive empathy plays an even more fundamental role in aggressive behavior: both boys and girls with a low level of cognitive empathy are more likely to implement behaviors that can be qualified as cyberbullying [13]. Emotional correspondence with other people is thus mediated by cognitive elaborations on the mental and affective state of other individuals and on the environments and the circumstances within which these interactions take place [27, 28].

It appears that the cognitive component of empathic abilities can be inhibited by a number of different factors while on the Internet, including the primary factors of “time” and “anonymity”. For example, a number of studies also conducted in the field of neuroscience have reported that the so-called moral or social emotions, e.g. admiration and compassion, involve a slower form of information processing due to a more demanding request for reflection and cognitive appraisal [29 –31]. Contrary to this need, digital communication is very rapid, and does not normally give the individual time to process information carefully [29]. In addition, a study reported that, among those who declared themselves victims of cyberbullying, just under half knew who had perpetrated the aggression [32]. Hiding one’s identity is really very easy on the web, sometimes practically encouraged by the media, and this can have consequences for the representation of self and for relationships established with others. Apparently, the possibility of concealing one’s identity raises the level of moral disengagement and permits easy recourse to thought mechanisms which are tilted towards justifying bad behavior and silencing the conscience [1 , 33–35]. A number of studies have already highlighted how moral disengagement can be related to cyberbullying behavior among young adolescents [10 , 37]. By putting into play moral cognitive mechanisms of disengagement - going from moral justification to dehumanization of the victim, from attribution of blame to distortion of consequences - we manage to detach ourselves morally and to ensure that emotions such as guilt do not emerge, or are somewhat mitigated. On the contrary, avoiding reprehensible actions requires more complex and slower cognitive processing: the negative emotions that will be felt after the bad behavior must be simulated, prefigured in advance of the actions. It is thanks to the fact that we are able to anticipate social emotions – negative ones such as regret, shame and guilt, or positive ones such as pride and satisfaction – that we avoid committing actions which are considered ethically deplorable or risky for the individual [38]. Reflective cognitive processes, which imply an evaluation of the self, encourage us to evaluate our behavior according to an internal standard (our moral identity) or an external one (the perception that others have of us). In other words, they provide support for moral behavior or justification for violations [15, 39]. When these reflective or critical thought mechanisms are not fully exercised, or are hindered by particular operational contexts [40], the conditions are created for implementing unethical behaviors or formulating justifications that will mitigate their negative aspects [15 , 42]. This can be particularly true when interacting with information and communication technology (ICT) [43]. The Internet can be used to excess, up to the point of prefiguring forms of dependence that can interact negatively with the capacity for reflection and can represent the beginning of a series of relationship problems for the present generation of young adolescents. The continuous development of social media and their increasingly frequent use, to the point of becoming pervasive, make it necessary to clarify how cyberbullying can manifest itself in these environments [44, 45].

2 Method

The aim of this study is to investigate the complex relationship between socio-cognitive and contextual factors, which intervene in the context of antisocial and pro-social behavior. More specifically, we will analyze the use of social media to try to understand whether this correlates with behaviors that can be qualified as cyberbullying and how mechanisms of moral disengagement and empathic abilities come into play in this complex phenomenon.

2.1 Study design

The study was conducted using a questionnaire, which was administered online to students attending different high schools in the Tuscany region of Italy. The study was conducted in the first three months of 2018, after obtaining the authorization of the Board of the Department of Social, Political and Cognitive Sciences, which assessed its ethical consistency (report no.10/2017 of 27 September 2017).

Participants took part in the study on a voluntary basis. They were invited to participate in e-mails sent to the head teachers in their schools. The aim of the study was made explicit in the e-mail, and a link to a Google Forms webpage where participants could complete the survey online was provided. The data collected were stored in a secure database for subsequent analysis. Participants were assured that they could fill in the questionnaire anonymously, that they could complete it at any time, that it would take about 15–20 minutes to complete, and that they could interrupt the process at any time. Contact information for the researchers conducting the study was provided in case participants wished to contact them or request additional information. No compensation was offered for participation.

2.2 Participants

Two hundred and ninety-seven surveys were completed. We filtered out data from respondents who had completed the questionnaire answering less than 95% of the questions. The resulting sample included 264 participants who were Italian adolescents (114 male, 43.2%, and 150 female, 56.8%). Their age varied between 14 and 25 years. They were all students from first to fifth year classes. In this sample, 191 (73.55%) students reported attending either the Scientific, the Classical, or the Human Sciences High School. 69 students reported that they attended Technical schools (26.5%).

2.3 Measures

The questionnaire was structured with 73 items in five sections. The first section concerned personal data such as age, gender, and type of school attended. The second section investigated the use of social media, essentially asking which social media they used (“Which social media do you use most often?”). Participants could select more than one response, from a list of ten forms of social media: Facebook, Pinterest, Yahoo!answers, twitter, ask.fm, Tumblr, google+, snapchat, YouTube, and Instagram. There were also questions about the number of profiles the participant had on Facebook (“On Facebook I have”: a) more than one profile, b) only one profile c) no profile), on the number of Facebook friends (“On Facebook I have a total of”: a) “less than 10 friends”, b) “10 to 50 friends”, c) 50 to 100 friends, d) 100 to 200 friends, e) more than 200 friends), and which of these they considered true friends (“Of my Facebook friends, the number I do things with and consider real friends are”: a) less than 10, b) 10 to 50, c) 50 to 100, d) 100 to 200, e) more than 200). In this section they were also asked to provide information on specific relational issues such as “I feel on edge if I can’t use the Internet” (responses collected on the basis of a Likert scale, from 1 “strongly disagree” to 5 “strongly agree”) or “Sometimes I use one of my profiles to post content which cannot be seen by other users” (responses “Yes”/”No”) (see Table 1).

Table 1
Main results for socio-demographic variables and social network usage

Variable N %

Gender

Male 114 43.2

Female 150 56.8

Age

14–15 36 13.6

16–17 100 37.9

18–20 114 43.2

21–25 14 5.3

School attended

Scientific or classical high school 193 73.1

Technical high school 71 26.9

Started using internet from when I was

<6 years 6 2.3

6–10 years 65 24.6

11–14 years 176 66.7

>14 years 17 6.4

Using Facebook or other social networks

Never 3 1.1

t < 3 hours a day 199 75.4

t > 3 hours a day 62 23.5

I feel on edge if I can’t use the Internet

(1 strongly disagree – 5 strongly agree)

1 21 7.9

2 54 20.5

3 94 35.6

4 53 20.1

5 42 15.9

Sometimes I use one of my profiles to post content which cannot be seen by other users

Yes 55 20.1

No 206 78.9

Variable	N	%
Gender
Male	114	43.2
Female	150	56.8
Age
14–15	36	13.6
16–17	100	37.9
18–20	114	43.2
21–25	14	5.3
School attended
Scientific or classical high school	193	73.1
Technical high school	71	26.9
Started using internet from when I was
<6 years	6	2.3
6–10 years	65	24.6
11–14 years	176	66.7
>14 years	17	6.4
Using Facebook or other social networks
Never	3	1.1
t < 3 hours a day	199	75.4
t > 3 hours a day	62	23.5
I feel on edge if I can’t use the Internet
(1 strongly disagree – 5 strongly agree)
1	21	7.9
2	54	20.5
3	94	35.6
4	53	20.1
5	42	15.9
Sometimes I use one of my profiles to post content which cannot be seen by other users
Yes	55	20.1
No	206	78.9

The third section was aimed at measuring empathy through the Basic Empathy Scale (BES), a two-factor model scale of 20 items designed to measure both cognitive empathy and affective empathy [46 –48]. Answers were collected on a five-point Likert scale, in which 1 was “strongly disagree” and 5 was “strongly agree”. For this study, the Italian version of Albiero [49] was adopted. For the psychometric properties of BES, also refer to [50].

The third section aimed to evaluate moral disengagement through the Moral Disengagement Scale (MDS) [51], which comprises 32 items relating to eight different mechanisms of moral disengagement: moral justification, euphemistic language, advantageous comparison, displacement of responsibility, diffusion of responsibility, distortion of consequences, attribution of blame, dehumanization. The eight mechanisms were assessed through four different items each, and answers were collected on a five-point Likert agreement scale in which 1 corresponded to “strongly disagree” and 5 to “strongly agree” [37]. In addition to Bandura and colleagues [51], for the psychometric properties of MDS, also refer to [52].

The last section of the questionnaire investigated enacted antisocial or prosocial conduct. For this purpose, two questions were administered: i) “Have you ever published denigrating photos or images, offensive terms, etc.)” and ii) “Have you ever intervened in defense of someone who had been offended, denigrated, or publicly embarrassed on a social network?”. Here too, answers were collected on five-point Likert scales (1 = never; 5 = very often).

2.4 Statistical analysis

The data collected were first analysed through descriptive analysis. Averages were compared using non-parametric tests (Mann–Whitney U test, Kruskal-Wallis test and Chi-squared test). Correlational analyses were also performed (Pearson’s r index) on the relationship between BES and MDS, and between these scales and the responses to questions regarding antisocial and prosocial behavior. In all cases, statistical hypotheses were deemed significant if p values were less than 0.05.

3 Results

Socio-demographic and social media usage information is reported in Table 1. It should also be noted that 241 students (92.2%) reported having one or two profiles on Facebook. Most participants (68.6%) reported having more than 200 friends, but 43.6% considered only from 10 to 50 of these to be true friends. Most of the sample (86.7%) had only one profile on the social network, and only 20.8% said they had used one of these profiles to post content that could not be shared by others Internet users. Figure 1 reports the number of students who claimed they used each social media.

Fig.1

Number of students reporting use of each of the forms of social media taken into consideration in the study. Participants could select more than one option.

Results from a Mann-Whitney U test indicate, in agreement with former scientific evidence [53], that mean empathy scores differ significantly between males and females if the global value is considered (mean male = 3.53 and female = 3.76; p < .05), as do Affective Empathy scores (mean male = 3.33; female = 3.66; p < .01) (see Table 2 for mean scores). Mean values for moral disengagement also differ significantly (Mann–Whitney U test, p < .001) between males (mean = 2.22) and females (mean = 1.90) and for all the factors considered (p < .001) except “distortion of consequences” and “advantageous comparison” (see Table 2 for mean scores).

Table 2

Average participants’ scores on measures related to Empathy (Affective and Cognitive) and Moral Disengagement (MD)

Variable	Mean	Sd	M	Sd	F	Sd
Empathy tot.	3.66	0.50298	3.53	0.48728	3.76	0.49314
Affective Empathy	3.52	0.62438	3.33	0.59516	3.66	0.61042
Cognitive Empathy	3.84	0.56171	3.78	0.56270	3.87	0.55969
Moral Disengagement tot.	2.04	0.50716	2.22	0.49351	1.90	0.47262
Moral justification	2.46	0.90476	2.89	0.84347	2.15	0.81631
Euphemistic Labeling	2.03	0.70101	2.30	0.68480	1.83	0.64414
Dehumanization	2.92	1.0798	3.25	1.09570	2.66	0.99832
Attribution of blame	1.89	0.59620	2.07	0.60630	1.76	0.55311
Distortion of consequences	2.73	0.81558	2.75	0.80578	2.72	0.82526
Diffusion of Responsibility	1.91	0.62722	2.11	0.63754	1.76	0.57859
Displacement of Responsibility	1.95	0.71320	2.08	0.76311	1.86	0.65828
Advantageous comparison	1.34	0.53537	1.39	0.53632	1.30	0.53318

3.1 Correlations between empathy and moral disengagement

The results highlight a negative correlation between total empathy and the moral disengagement scale (r = .179; p < .006). In greater detail, the total empathy score has a negative correlation with the following five factors in moral disengagement: euphemistic labeling (r = –.155; p < .005); diffusion of responsibility (r = –.253; p < .000); advantageous comparison (r = –.127; p < .005;); dehumanization of the victim (r = –.169; p < .008) and moral justification (r = –.116; p < .007).

The results also highlight a negative correlation between affective empathy and the moral disengagement scale (r = –.213; p < .001). In this case too, we find a negative correlation with the same five factors of moral disengagement: euphemistic labeling (r = –.206; p < .001); diffusion of responsibility (r = –.28; p < .000); advantageous comparison (r = –.155; p < .005); dehumanization of the victim (r = –.248; p < .000); moral justification (r = –.196; p < .000).

No correlations were found between cognitive empathy and the moral disengagement scale.

3.2 Antisocial behavior and prosocial behavior on the net

With regard to the realization of aggressive and offensive behavior, 23.1% out of 260 (N = 60) participants say they have posted, at least once, embarrassing photos or offensive words of others (“Have you ever published embarrassing photos, or offensive words of others for everyone to see?”).

77% of the 260 participants reported that they had intervened in aid of someone who had been offended on social networks. Those who carry out offensive behavior online, posting photos or offensive comments, have a higher score for moral disengagement, since they differ significantly (Mann-Whitney U test) on all the values for moral disengagement parameters from those who say they have never offended anybody (see Table 3).

Table 3
Mean differences in moral disengagement strategies between those who report to have behaved offensively at least once and the other participants in the experimental sample

Moral Disengagement Strategies p value Mean diff

Advantageous comparison 0.022 –0.22

Attribution of blame 0.024 –0.20

Diffusion of responsibility 0.001 –0.32

Displacement of responsibility 0.049 –0.22

Euphemistic labelling 0.000 –0.47

Moral justification 0.001 –0.42

Distorting consequences 0.046 –0.21

Dehumanization 0.000 –0.65

Moral Disengagement Strategies	p value	Mean diff
Advantageous comparison	0.022	–0.22
Attribution of blame	0.024	–0.20
Diffusion of responsibility	0.001	–0.32
Displacement of responsibility	0.049	–0.22
Euphemistic labelling	0.000	–0.47
Moral justification	0.001	–0.42
Distorting consequences	0.046	–0.21
Dehumanization	0.000	–0.65

However, no significant difference in empathy (total, cognitive or affective) emerged between those who carry out offensive behavior and those who do not. What does emerge is a positive correlation between offensive behavior and moral disengagement (r = .354; p < .000), while helping behavior, on the other hand, correlates with cognitive empathy (r = .226; p < .002) and thus with total empathy (r = .221; p < .001).

A significant difference emerges for offensive behavior related to net dependency (“I feel on edge if I can’t use the Internet”; 1-strongly agree, 5-strongly disagree, mean = 3.16) among those who admit to having been offensive online (N = 60; mean = 2.87) and those who don’t (N = 199; mean = 3.27) (Mann-Whitney U test, p < .02). It would therefore seem logical to claim that higher dependency on the net is related to increased enacting of offensive behavior.

Where helping behavior is concerned, on the other hand (“have you ever intervened in defense of a person who has been offended or denigrated publicly on social networks?”), the results reveal that those who had intervened in favor of others had an average score which was significantly higher for cognitive empathy (N = 183; mean = 3.89) compared to those who tend not to intervene to defend victims of attack (N = 54; mean = 3.71), (Mann-Whitney U test, p < .02).

The results also highlight the way in which offensive behavior on the net is related to the number of hours spent online (t < 3 hours a day; t > 3 hours a day): the more time spent online, the more likely it is that a person will behave in a way that could offend or harm someone. The analysis shows a significant difference between the mean scores for offending and the number of hours spent on the Internet daily (t < 3 h; N = 199; mean = 2.82) and more than 3 hours (N = 60; mean = 3.02) (Kruskal-Wallis test, p < .002).

Differences are also found in relation to the type of school, in that virtual aggressive behavior was more likely to be reported by students attending technical school (Chi-squared test; p < .05). Fewer students from the scientific or classical high school (N = 38; 24,3%) reported having offended someone on the net at least once compared to students from the technical high school (N = 22; 32.9%). There are also differences in the social media used: ASK.fm and Snapchat are more frequently used by those who say they have been offensive on the net (Chi-squared test; p < .001 in both cases).

4 Conclusion

The results of the study suggest that an increasingly pervasive phenomenon like cyberbullying could be more easily identified, and possibly prevented, through observation of particular behaviors (e.g. the use of specific social media) in particular contexts (e.g. the type of school attended), in correlation with the consideration of certain moral disengagement strategies (e.g., moral justification, distorting consequences, and dehumanization).

The reasons underlying these hypotheses refer to the relationships between moral disengagement, empathy and aggressive or prosocial behavior, which are on the whole worthy of further study. Firstly, it appears that moral disengagement is related to affective empathy; this leads to the hypothesis that justification for disengagement stems from a detachment from what the victim is feeling. And this is true whether it is a case of euphemistic labeling, diffusion of responsibility or dehumanization of the victim, to offer just a few examples. This detachment is, however, emotive rather than cognitive: the motives of another person can be understood, but not his/her feelings. Behavior which victimizes does not seem to implicate either more or less cognitive involvement.

In line with recent research [54], the opposite seems to hold if we consider that when someone offers to help, they intervene because they can understand the victim’s point of view, and can see the world through his/her eyes. And in fact helping behaviors do seem to be related to cognitive empathic capacity.

All of this, though differently from a number of previous studies [55], must be viewed in the context of social relationships on the Internet. It must be underlined that in this study we find that those who are more likely to perpetrate offensive acts on the Internet tend also to be more dependent on use of the Internet and to frequent social networks for more hours per day [56, 57].

With this in mind, it seems important to underline three points. The first is related to the fact that social media on which cyberbullying seems to spread more frequently are those that, in some way, allow the offender not to be identified. ASK.fm is in fact a form of social media that allows individuals to register if they are 13 years old. In this environment you can follow your friends without them knowing and leave them anonymous messages. Snapchat, on the other hand, provides a sort of psychological shield due to the fact that messages can be made visible to the recipient for a limited amount of time only.

The second point, on the other hand, has to do with the evidence that the thought mechanism of moral disengagement put most frequently in place by the cyberbullies - i.e. dehumanization (e.g., “he is nothing more than an animal”) is the one least requiring the exercise of reflective abilities.

The third point concerns the fact that girls less frequently reported carrying out offensive behavior on the Internet (similar results have been found in the context of employment, [58]). This may imply, as often noted [59], that girls mature earlier, also from a moral point of view. It may also, however, signify that they are less willing than boys to talk about this type of behavior, demonstrating once again that they are more subject to the “desirability effect” [60], leading them to hide forms of self-expression that are not socially approved.

On the whole, the results of this study open up perspectives which may identify moderation of Internet use and online presence as a key to containing such unacceptable behaviors as cyberbullying. Intervention directed at regulating use of the Internet, and hopefully effort directed towards implementation of more transparent social media, would seem to be both necessary and technically feasible.

Intervention cannot, however, be limited to the implementation of technical solutions only; we need to engage in design of blended educational environments [1] for building a strong social network and close collaboration between family, school and society [61]. All stakeholders should be included in training courses on the use of technology and social media. Above all, schools [62] should encourage maximum social cohesion among students within the classroom with the aim of reducing antisocial behaviors among peers [63, 64] by providing emotional literacy that can help teenagers to talk about and recognize their own and others’ emotions and how to control them [3]. This learning path should be juxtaposed with forms of parental assistance aimed at establishing forms of interaction so as to reduce the amount of time adolescents spend on the Internet. Ultimately, in mixed real-virtual environments, efforts should be directed towards a form of “design for reflection” [65, 66] in order to educate young users to take the time to think about their feelings, thoughts, and interactions with communication media.

4.1 Limitations

This study presents a number of limitations. First of all, the size of the sample, though not negligible, is not large enough to allow the results obtained to be extended to other realities that may have very different socio-cultural and economic characteristics. It must also be emphasized that a part of the object of study, the use of social media, is inherently changeable, subject to continuous evolution. The frequencies of use of the various social media reported here, and which refer to 2018, may therefore already no longer apply. Furthermore, it should be emphasized that antisocial and prosocial behaviors were investigated through only two questions, which may not be sufficient to capture the complexity of the phenomenon. Above all, the whole study is based on data reported by the participants themselves; this may have diverted our results, perhaps significantly, towards a form of self-representation closer to stereotypes corresponding to greater social acceptability.

Conflict of interest

The authors declare that they have no conflict of interest.

References

Parlangeli

, Marchigiani

, Guidi

, Mesh

. Disentangled emotions in blended learning, Int J Human Factors and Ergonomics. 2012;1(1):41–57.

Mascheroni

, Ólafsson

. Accesso, usi, rischi e opportunitá di internet per i ragazzi italiani, I primi risultati di EU Kids Online 2017. EU Kids Online e OssCom; 2018.

Parlangeli

, Palmitesta

, Bracci

, Marchigiani

, Liston

. Stress, misconduct and reduced ability to express dissent: A study on a sample of students at the University of Siena, In: Arezes

, Baptista

, Barroso

, Carneiro

, Cordeiro

, Costa

, et al, editors. Occupational safety and hygiene VI, London: Taylor & Francis; 2018, pp. 443–446.

Pilkey

. The nature and impact of cyberbullying on the middle school student, Dissertation Abstracts International Section A: Humanities and Social Sciences. 2012;72(8-A):2744.

Kowalski

, Limber

, Agatston

. Cyberbullying: Bullying in the digital age., 2nd ed. Malden, MA: Wiley-Blackwell, 2012.

Ang

. Cyberbullying: Its Prevention and Intervention Strategies, In: Deb

Editor. Child Safety, Welfare and Well-being, India: Springer; 2016, pp. 25–38.

Ullah

, Siddiqui

, Zafar

, Iqbal

. Bullying experiences of dental interns working at four dental institutions of a developing country: A cross-sectional study, Work. 2018;61(1):91–1.

Hernandez Rodriguez

, Gregus

, Craig

, Pastrana

, Cavell

. Bullied children, In: Alfano

, Beidel

, Editors. Comprehensive evidence based interventions for children and adolescents, NJ, US: John Wiley & Sons; 2014, pp. 301–16.

Athanasiou

, Melegkovits

, Andrie

, Magoulas

, Tzavara

, Richardson

, Greydanus

, Tsolia

. Cross-national aspects of cyberbullying victimization among 14–17-year-old adolescents across seven European countries, BMC Public Health. 2018;18:800 https://doi.org/10.1186/s12889-018-5682-4.

10.

Hymel

, Rocke-Henderson

, Bonanno

. Moral disengagement: A framework for understanding bullying among adolescent, JSS. 2005;8:1–11.

11.

Hymel

, Bonanno

. Moral disengagement processes in bullying, Theor Pract. 2014;53(4):278–85.

12.

Wang

, Ryoo

, Swearer

, Turner

, Goldberg

. Longitudinal relationships between bullying and moral disengagement among adolescents, J Youth Adolescence. 2017;46(5):1304–17.

13.

Ang

, Goh

. Cyberbullying among adolescents: The role of affective and cognitive empathy and gender, Child Pyschiat Hum D. 2010;41:387–97.

14.

Blair

RJR

. Responding to the emotions of others: Dissociating forms of empathy through the study of typical and psychiatric populations, Conscious Cogn. 2005;14(4):698–718.

15.

Tangney

, Stuewing

, Mashek

. Moral emotions and moral behaviour, Annu Rev Psychol. 2007;58:345–72.

16.

Marshall

, Marshal

. Empathy and antisocial behavior, J Forensic Psychiatry Psychol. 2011;22(5):742–59.

17.

Mehrabian

. Relations among personality scales of aggression, violence, and empathy: Validational evidence bearing on the Risk of Eruptive Violence Scale, Aggress Behav. 1997;23(6):433–45.

18.

Zych

, Ttofi

, Farrington

. Empathy and callous–unemotional traits in different bullying roles: A systematic review and meta-analysis, Trauma Violence Abuse. 2016;1–19.

19.

Miller

, Eisenberg

. The relation of empathy to aggressive and externalizing/antisocial behavior, Psychol Bull. 1988;103(3):324–44.

20.

Edgar

, Nicol

, Clark

CCA

, Paul

. Measuring empathic responses in animals, Appl Anim Behav Sci. 2012;138(3–4):182–93.

21.

Batson

. The empathy-altruism hypothesis: Issues and implications, In: Decety

, editor. Empathy: From bench to bedside. Cambridge: MIT Press; 2012, pp. 41–54.

22.

Galinsky

, Moskowitz

. Perspective-taking: Decreasing stereotype expression, stereotype accessibility, and in-group favoritism, J Pers Soc Psychol. 2000;78(4):708–24.

23.

Nummenmaa

, Hirvonen

, Parkkola

, Hietanen

. Is emotional contagion special? An fMRI study on neural systems for affective and cognitive empathy, Neuro Image. 2008;43:571–80.

24.

Decety

. The neural pathways, development and functions of empathy, Curr Opin Behav Sci. 2015;3:1–6.

25.

Davidson

, Putnam

, Larson

. Dysfunction in the neural circuitry of emotion regulation – a possible prelude to violence, Science. 2000;289(5479):591–4.

26.

Herpertz

, Sass

. Emotional deficiency and psychopathy, Behav Sci Law. 2000;18(5):567–80.

27.

Carré

, Stefaniak

, D’Ambrosio

, Bensalah

, Besche-Richard

. The Basic Empathy Scale in adults (BES-A): Factor structure of a revised form, Psychol Assess. 2013;25(3):679–91.

28.

Steffgen

, konig

, Pfetsch

, Melzer

. Are cyberbullies less empathic? Adolescents’ cyberbullying behavior and empathic responsiveness, Cyberpsychol, Behav Soc Netw. 2011;14(11):643–8.

29.

Immordino-Yang

, McColl

, Damasio

. Neural correlates of admiration and compassion, PNAS. 2009;106(19):8021–6.

30.

Gross

, John

. Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being’, J Pers Soc Psychol. 2003;85:348–62.

31.

John

, Gross

. Healthy and unhealthy emotion regulation: Personality processes, individual differences and life span, J Pers Soc Psychol. 2004;72(6):1301–33.

32.

Kowalski

, Limber

. Electronic bullying among middle school students, J Adolesc Health. 2007;41(6 suppl 1):22–30.

33.

Bandura

. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs NJ: Prentice-Hall; 1986.

34.

Bandura

, Barbaranelli

, Caprara

, Pastorelli

. Mechanisms of moral disengagement in the exercise of moral agency, J Pers Soc Psychol. 1996;71(2):364–74.

35.

Liu

, Sui

. Exploring the spatiotemporal pattern of cyberbullying with Yik Yak, Prof Geogr. 2017;69(3):412–23. doi:10.1080/00330124.2016.1252273.

36.

Almeida

, Correia

, Marinho

, Garcia

D’J

. Virtual but not Less Real: A Study of Cyberbullying and Its Relations to Moral Disengagement and Empathy, In: Li

, Cross

, Smith

, editors. Cyberbullying in the global playground: Research from international perspectives Wiley-Blackwell; 2012, pp. 223–244.

37.

Perren

, Gutzwiller-Helfenfinger

. Cyberbullying and traditional bullying in adolescence: Differential roles of moral disengagement, moral emotions, and moral values, Eur J Dev Psychol. 2012;2:195–209.

38.

Parlangeli

, Bracci

, Guidi

, Marchigiani

, Duguid

. Risk perception and emotions regulation strategies in driving behaviour: An analysis of the self-reported data of adolescents and young adults, Int J Human Factors and Ergonomics. 2018;5(2):166–87.

39.

Haidt

. The moral emotions, In: Davidson

, Scherer

, Goldsmith

, editors. Handbook of affective sciences. Oxford: Oxford University Press; 2003, pp. 852–70.

40.

Tangney

, Stuewing

, Mashek

. Moral emotions and moral behaviour, Annu Rev Psychol. 2007;58:345–72.

41.

Parlangeli

, Chiantini

, Guidi

. A Mind in a disk: The attribution of mental state to technological systems, Work. 2012;41:1118–23.

42.

Parlangeli

, Guidi

, Marchigiani

, Bracci

, Liston

. Perceptions of Work-Related Stress and Ethical Misconduct Amongst Non-tenured Researchers in Italy, Sci Eng Ethics. published online, 2019, pp. 1–23.

43.

Gini

, Pozzoli

, Hymel

. Moral disengagement among children and youth: A Meta-Analytic review of links to aggressive behaviour, Aggressive Behav. 2014;40:56–68.

44.

Fuchs

. Social media: A critical introduction. Los Angeles, CA: Sage; 2017.

45.

Kemp

. Digital in 2017: Global overview. Retrieved October 8, 2017. Available from: https://wearesocial.com/uk/special-reports/digital-in-2017-global-overview.

46.

Joliffe

, Farrington

. Development and validation of the Basic Empathy scale, J Adolesc. 2006;29(4):589–611.

47.

Albiero

, Matricardi

, Speltri

, Toso

. The assessment of empathy in adolescence: A contribution to the Italian validation of the Basic Empathy Scale, J Adolesc. 2009;32(2):393–408.

48.

Albiero

, Matricardi

, Toso

. La Basic Empathy Scale, uno strumento per la misura della responsivitá empatica negli adolescenti: Un contributo alla validazione Italiana, Psicologia Clinica Dello Sviluppo. 2010;3:693–706.

49.

Pechorro

, Kahn

, Gonçalves

, Ray

. Psychometric properties of Basic Empathy Scale among female juvenile delinquents and school youths, Int J Law Psychiat. 2017;55:29–36.

50.

Bandura

, Barbaranelli

, Caprara

, Pastorelli

. Mechanisms of moral disengagement in the exercise of moral agency, J Pers Soc Psychol. 1996;71(2):364–74.

51.

Pelton

, Gound

, Forehand

, Brody

. The Moral Disengagement Scale: Extension With an American Minority, J Psychopathol Behav Assessment. 2004;26(1):31–9.

52.

Christov-More

, Simpson

, Coudé

, Grigaityte

, Iacoboni

, Ferrari

. Empathy: Gender effects in brain and behavior, Neurosci Biobehav Rev. 2014;46(4):604–27.

53.

Barlinska

, Szuster

, Winiewski

. Cyberbullying among adolescent bystanders: Role of affective versus cognitive empathy in increasing prosocial cyberbystander behavior, Front Psychol. 2018;9:799.

54.

Haddock

, Shimerson

. An examination of differences in moral disengagement and empathy among bullying participant groups, J Relat Res. 2017;8:e15.

55.

Keipi

, Kaakinen

, Oksanen

, Räsänen

. Social tie strength and online victimization: An analysis of young people aged 15–30 years in four nations, SM+S. 2017;3(1):1–13.

56.

Cerniglia

, Zoratto

, Cimino

, Laviola

, Ammaniti

, Adriani

. Internet addiction in adolescence: Neurobiological, psychosocial and clinical issues, Neurosci Biobehav R. 2017;76:174–84.

57.

Wang

, Hsieh

. Do gender differences matter to workplace bullying, Work. 2015;53(3):631–8.

58.

Casey

, Getz

, Galvan

. The adolescent brain, Dev Rev. 2008;28:42–77.

59.

Reynolds

. Development of reliable and valid short forms of the Marlowe-Crowne Social Desirability Scale, J Clin Psychol. 1982;38(1):119–25.

60.

Cohen-Almagor

. Social responsibility on the Internet: Addressing the challenge of cyberbullying, Aggress Viol Behav. 2018;39:42–52.

61.

Longobardi

, Iotti

, Jungert

, Settanni

. Student-teacher relationships and bullying: The role of student status, J Adolesc. 2018;63:1–10.

62.

Schultze-Krumbholz

, Schultze

, Zagorscak

, Wolfer

, Scheithauer

. Feeling cybervictims’ pain—the effect of empathy training on cyberbullying, Aggress Behav. 2016;42:147–56.

63.

van den Bos

, Crone

, Meuwese

, Guroğlu

. Social network cohesion in school classes promotes prosocial behavior, PLoS ONE. 2018;13(4):1–16.

64.

Bowler

, Mattern

, Knobel

. Developing Design Interventions for Cyberbullying: A Narrative-Based Participatory Approach, In: iConference Proceedings, Kindling

, Greifeneder

. (Ed.), iSchools, Illinois, 2014, pp. 153–62.

65.

Parlangeli

, Mengoni

, Guidi

. The effect of system usability and multitasking activities in distance learning. In: Proceedings of the CHItaly conference, Alghero, ACM Library; 2011, pp. 59–64.