chapter 5 research about cyberbullying

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v.5(3); 2019 Mar

Cyberbullying and its influence on academic, social, and emotional development of undergraduate students

This study investigated the influence of cyberbullying on the academic, social, and emotional development of undergraduate students. It's objective is to provides additional data and understanding of the influence of cyberbullying on various variables affecting undergraduate students. The survey sample consisted of 638 Israeli undergraduate students. The data were collected using the Revised Cyber Bullying Survey, which evaluates the frequency and media used to perpetrate cyberbullying, and the College Adjustment Scales, which evaluate three aspects of development in college students. It was found that 57% of the students had experienced cyberbullying at least once or twice through different types of media. Three variables were found to have significant influences on the research variables: gender, religion and sexual preferences. Correlation analyses were conducted and confirmed significant relationships between cyberbullying, mainly through instant messaging, and the academic, social and emotional development of undergraduate students. Instant messaging (IM) was found to be the most common means of cyberbullying among the students.

The main conclusions are that although cyberbullying existence has been proven, studies of cyberbullying among undergraduate students have not been fully developed. This particular population needs special attention in future research. The results of this study indicate that cyberbullying has an influence on the academic, social, and emotional development of undergraduate students. Additional Implications of the findings are discussed.

1. Introduction

Cyberbullying is defined as the electronic posting of mean-spirited messages about a person (such as a student) often done anonymously ( Merriam-Webster, 2017 ). Most of the investigations of cyberbullying have been conducted with students in elementary, middle and high school who were between 9 and 18 years old. Those studies focused on examining the prevalence and frequency of cyberbullying. Using “cyberbullying” and “higher-education” as key words in Google scholar (January, 2019) (all in title) yields only twenty one articles. In 2009, 2012 and 2013 one article appeared each year, since 2014 each year there were few publications. Of these articles only seven relates to effect of cyberbullying on the students, thus a gap in the literature exists in that it only minimally reports on studies involving undergraduate students. Given their relationship and access to technology, it is likely that cyberbullying occurs frequently among undergraduates. The purpose of this study is to examine the frequency and media used to perpetrate cyberbullying, as well as the relationship that it has with the academic, social and emotional development of undergraduate students.

Undergraduate students use the Internet for a wide variety of purposes. Those purposes include recreation, such as communicating in online groups or playing games; academics, such as doing assignments, researching scholarships or completing online applications; and practical, such as preparing for job interviews by researching companies. Students also use the Internet for social communication with increasing frequency.

The literature suggests that cyberbullied victims generally manifest psychological problems such as depression, loneliness, low self-esteem, school phobias and social anxiety ( Grene, 2003 ; Juvonen et al., 2003 ; Akcil, 2018 ). Moreover, research findings have shown that cyberbullying causes emotional and physiological damage to defenseless victims ( Akbulut and Eristi, 2011 ) as well as psychosocial difficulties including behavior problems ( Ybarra and Mitchell, 2007 ), drinking alcohol ( Selkie et al., 2015 ), smoking, depression, and low commitment to academics ( Ybarra and Mitchell, 2007 ).

Under great emotional stress, victims of cyberbullying are unable to concentrate on their studies, and thus their academic progress is adversely affected ( Akcil, 2018 ). Since the victims are often hurt psychologically, the depressive effect of cyberbullying prevents students from excelling in their studies ( Faryadi, 2011 ). The overall presence of cyberbullying victimization among undergraduate college students was found to be significantly related to the experience of anxiety, depression, substance abuse, low self-esteem, interpersonal problems, family tensions and academic underperformance ( Beebe, 2010 ).

1.1. Cyberbullying and internet

The Internet has been the most useful technology of modern times, which has enabled entirely new forms of social interaction, activities, and organizing. This has been possible thanks to its basic features such as widespread usability and access. However, it also causes undesirable behaviors that are offensive or threatening to others, such as cyberbullying. This is a relatively new phenomenon.

According to Belsey (2006, p.1) , “Cyberbullying involves the use of information and communication technologies such as e-mail, cell-phone and pager text messages, instant messaging, defamatory personal web sites, blogs, online games and defamatory online personal polling web sites, to support deliberate, repeated, and hostile behavior by an individual or group that is intended to harm others.” Characteristics like anonymity, accessibility to electronic communication, and rapid audience spread, result in a limitless number of individuals that can be affected by cyberbullying.

Different studies suggest that undergraduate students' use of the Internet is more significant and frequent than any other demographic group. A 2014 survey of 1006 participants in the U.S. conducted by the Pew Research Center revealed that 97% of young adults aged from 18 to 29 years use the Internet, email, or access the Internet via a mobile device. Among them, 91% were college students.

1.2. Mediums to perpetrate cyberbullying

The most frequent and common media within which cyberbullying can occur are:

Electronic mail (email): a method of exchanging digital messages from an author to one or more recipients.

Instant messaging: a type of online chat that offers real-time text transmission between two parties.

Chat rooms: a real-time online interaction with strangers with a shared interest or other similar connection.

Text messaging (SMS): the act of composing and sending a brief electronic message between two or more mobile phones.

Social networking sites: a platform to build social networks or social relations among people who share interests, activities, backgrounds or real-life connections.

Web sites : a platform that provides service for personal, commercial, or government purpose.

Studies indicate that undergraduate students are cyberbullied most frequently through email, and least often in chat rooms ( Beebe, 2010 ). Other studies suggest that instant messaging is the most common electronic medium used to perpetrate cyberbullying ( Kowalski et al., 2018 ).

1.3. Types of cyberbullying

Watts et al. (2017) Describe 7 types of cyberbullying: flaming, online harassment, cyberstalking, denigration, masquerading, trickery and outing, and exclusion. Flaming involves sending angry, rude, or vulgar messages via text or email about a person either to that person privately or to an online group.

Harassment involves repeatedly sending offensive messages, and cyberstalking moves harassment online, with the offender sending threatening messages to his or her victim. Denigration occurs when the cyberbully sends untrue or hurtful messages about a person to others. Masquerading takes elements of harassment and denigration where the cyberbully pretends to be someone else and sends or posts threatening or harmful information about one person to other people. Trickery and outing occur when the cyberbully tricks an individual into providing embarrassing, private, or sensitive information and posts or sends the information for others to view. Exclusion is deliberately leaving individuals out of an online group, thereby automatically stigmatizing the excluded individuals.

Additional types of cyberbullying are: Fraping - where a person accesses the victim's social media account and impersonates them in an attempt to be funny or to ruin their reputation. Dissing - share or post cruel information online to ruin one's reputation or friendships with others. Trolling - is insulting an individual online to provoke them enough to get a response. Catfishing - steals one's online identity to re-creates social networking profiles for deceptive purposes. Such as signing up for services in the victim's name so that the victim receives emails or other offers for potentially embarrassing things such as gay-rights newsletters or incontinence treatment. Phishing - a tactic that requires tricking, persuading or manipulating the target into revealing personal and/or financial information about themselves and/or their loved ones. Stalking – Online stalking when a person shares her personal information publicly through social networking websites. With this information, stalkers can send them personal messages, send mysterious gifts to someone's home address and more. Blackmail – Anonymous e-mails, phone-calls and private messages are often done to a person who bear secrets. Photographs & video - Threaten to share them publicly unless the victim complies with a particular demand; Distribute them via text or email, making it impossible for the victim to control who sees the picture; Publish the pictures on the Internet for anyone to view. Shunning - persistently avoid, ignore, or reject someone mainly from participating in social networks. Sexting - send sexually explicit photographs or messages via mobile phone.

1.4. Prevalence of cyberbullying

Previous studies have found that cyberbullying incidents among college students can range from 9% to 34% ( Baldasare et al., 2012 ).

Beebe (2010) conducted a study with 202 college students in United States. Results indicated that 50.7% of the undergraduate students represented in the sample reported experiencing cyberbullying victimization once or twice during their time in college. Additionally, 36.3% reported cyberbullying victimization on a monthly basis while in college. According to Dılmaç (2009) , 22.5% of 666 students at Selcuk University in Turkey reported cyberbullying another person at least once and 55.35% reported being a victim of cyberbullying at least once in their lifetimes. In a study of 131 students from seven undergraduate classes in United States, 11% of the respondents indicated having experienced cyberbullying at the university ( Walker et al., 2011 ). Of those, Facebook (64%), cell phones (43%) and instant messaging (43%) were the most frequent technologies used. Students indicated that 50% of the cyberbullies were classmates, 57% were individuals outside of the university, and 43% did not know who was cyberbullying them.

Data from the last two years (2017–18) is similar to the above. A research, of 187 undergraduate students matriculated at a large U.S. Northeastern metropolitan Roman Catholic university ( Webber and Ovedovitz, 2018 ), found that 4.3% indicated that they were victims of cyberbullying at the university level and a total of 7.5% students acknowledged having participated in bullying at that level while A survey (N = 338) at a large midwestern university conducted by Varghese and Pistole (2017) , showed that frequency counts indicated that 15.1% undergraduate students were cyberbully victims during college, and 8.0% were cyberbully offenders during college.

A study of 201 students from sixteen different colleges across the United States found a prevalence rate of 85.2% for college students who reported being victims of cyberbullying out of the total 201 responses recorded. This ranged from only occasional incidents to almost daily experiences with cyberbullying victimization ( Poole, 2017 ).

In A research of international students, 20.7% reported that they have been cyberbullied in the last 30 days once to many times ( Akcil, 2018 ).

1.5. Psychological impact of cyberbullying

Cyberbullying literature suggests that victims generally manifest psychological problems such as depression, anxiety, loneliness, low self-esteem, social exclusion, school phobias and poor academic performance ( DeHue et al., 2008 ; Juvonen and Gross, 2008 ; Kowalski and Limber, 2007 ; Grene, 2003 ; Juvonen et al., 2003 ; Rivituso, 2012 ; Varghese and Pistole, 2017 ; Na, 2014 ; Akcil, 2018 ), low self-esteem, family problems, school violence and delinquent behavior ( Webber and Ovedovitz, 2018 ), which brings them to experience suicidal thoughts as a means of escaping the torture ( Ghadampour et al., 2017 ).

Moreover, research findings have shown that cyberbullying causes emotional and physiological damage to defenseless victims ( Faryadi, 2011 ) as well as psychosocial problems including inappropriate behaviors, drinking alcohol, smoking, depression and low commitment to academics ( Walker et al., 2011 ).

The victims of cyberbullying, under great emotional stress, are unable to concentrate on their studies, and thus their academic progress is adversely affected ( Faryadi, 2011 ). Since the victims are often hurt psychologically, the depressive effect of cyberbullying prevents students from excelling in their studies ( Faryadi, 2011 ).

In a Malaysian university study with 365 first year students, the majority of the participants (85%) interviewed indicated that cyberbullying affected their academic performance, specifically their grades ( Faryadi, 2011 ). Also, 85% of the respondents agreed that bullying caused a devastating impact on students' emotions and equally caused unimaginable psychological problems among the victims. Heiman and Olenik-Shemesh (2018) report that for students with learning disabilities, predictors of cybervictimization were low social support, low self-perception, and being female, whereas for students without learning disabilities, the predictors were low social support, low well-being, and low body perception.

1.6. Academic, social, and emotional development of undergraduate students

The transition to academic institutions is marked by complex challenges in emotional, social, and academic adjustment ( Gerdes and Mallinckrodt, 1994 ; Parker et al., 2004 ).

The adaptation to a new environment is an important factor in academic performance and future achievement. Undergraduate students are not only developing academically and intellectually, they are also establishing and maintaining personal relationships, developing an identity, deciding about a career and lifestyle, and maintaining personal health and wellness. Many students are interacting with people from diverse backgrounds who hold different values and making new friends. Some are also adapting to living away from home for the very first time ( Inkelas et al., 2007 ).

The concept of academic development involves not only academic abilities, but motivational factors, and institutional commitment. Motivation to learn, taking actions to meet academic demands, a clear sense of purpose, and general satisfaction with the academic environment are also important components of the academic field ( Lau, 2003 ).

A second dimension, the social field, may be as important as academic factors. Writers have emphasized integration into the social environment as a crucial element in commitment to a particular academic institution ( Tinto, 1975 ). Becoming integrated into the social life of college, forming a support network, and managing new social freedoms are some important elements of social development. Crises in the social field include conflict in a living situation, starting or maintaining relationships, interpersonal conflicts, family issues, and financial issues ( McGrath, 2005 ), which are manifested as feelings of loneliness ( Clark et al., 2015 ).

In the emotional field, students commonly question their relationships, direction in life, and self-worth ( Rey et al., 2011 ). A balanced personality is one which is emotionally adjusted. Emotional adjustment is essential for creating a sound personality. physical, intellectual mental and esthetical adjustments are possible when emotional adjustment is made ( Ziapour et al., 2018 ). Inner disorders may result from questions about identity and can sometimes lead to personal crises ( Gerdes and Mallinckrodt, 1994 ). Emotional problems may be manifested as global psychological distress, somatic distress, anxiety, low self-esteem, or depression. Impediments to success in emotional development include depression and anxiety, stress, substance abuse, and relationship problems ( Beebe, 2010 ).

The current study is designed to address two research questions: (1) does cyberbullying affect college students' emotional state, as measured by the nine factors of the College Adjustment Scales ( Anton and Reed, 1991 ); (2) which mode of cyberbullying most affects students' emotional state?

2.1. Research settings and participants

The present study is set in Israeli higher education colleges. These, function as: (1) institutions offering undergraduate programs in a limited number of disciplinary fields (mainly the social sciences), (2) centers for training studies (i.e.: teacher training curricula), as well as (3) as creators of access to higher education. The general student population is heterogeneous, coming from the Western Galilee. In this study, 638 Israeli undergraduate students participated. The sample is a representative of the population of the Western galilee in Israel. The sample was 76% female, 70% single, 51% Jewish, 27% Arabs, 7% Druze, and 15% other ethnicity. On the dimension of religiosity, 47% were secular, 37% traditional, 12% religious, 0.5% very religious, and 3.5% other. On the dimension of sexual orientation, 71% were straight women, 23.5% straight men, 4% bisexual, 1% lesbians, and 0.5% gay males (note: according to the Williams Institute, approximately 4% of the population in the US are LGBT, [ Gates, 2011 ], while 6% of the EU population are LGBT, [ Dalia, 2016 ]).

2.2. Instrumentation

Two instruments were used to collect data: The Revised Cyber Bullying Survey (RCBS), with a Cronbach's alpha ranging from .74 to .91 ( Kowalski and Limber, 2007 ), designed to measure incidence, frequency and medium used to perpetrate cyberbullying. The survey is a 32-item questionnaire. The frequency was investigated using a 5-item scale with anchors ranging from ‘it has never happened to me’ to ‘several times a week’. Five different media were explored: email, instant messaging, chat room, text messaging, and social networking sites. Each medium was examined with the same six questions related to cases of cyberbullying (see Table 1 ).

Description of the Revised Cyber Bullying Survey (RCBS) variables.

Means of cyberbullying	N	Minimum	Maximum	Mean	SD	Reliability
Chat	610	.00	24	.48	1.64	0.87
Social networking	635	.00	20	.95	1.93	0.85
SMS	631	.00	12	.78	1.53	0.80
Instant messages	634	.00	13	.96	1.81	0.81
Email	637	.00	11	.41	1.05	0.68
Valid N (listwise)	608

Note: the theoretical range is between zero to twenty-four.

Table 1 shows the five variables that composed the RCBS questionnaire (all of the variables are composed of 6 statements). The results indicate that the levels of all the variables is very low, which means that the respondents experienced cyberbullying once or twice. The internal consistency reliability estimate based on the current sample suggested that most of the variables have an adequate to high level of reliability, with a Cronbach's alpha of 0.68–0.87.

The College Adjustment Scales (CAS) ( Anton and Reed, 1991 ), evaluated the academic, social, and emotional development of college students. Values were standardized and validated for use with college students. The validity for each subscale ranged from .64 to .80, noting high correlations among scales. Reliability of the scales ranged from .80 to .92, with a mean of .86. The instrument included 128 items, divided into 10 scales: anxiety, depression, suicidal ideation, substance abuse, self-esteem problems, interpersonal problems, family problems, academic problems, career problems, and regular activities (see Table 2 ). Students responded to each item using a four-point scale.

Description of CAS variables.

Variables	N	Minimum	Maximum	Mean	SD	Reliability
Academic problems	634	28	73	47.87	8.87	0.77
Anxiety	633	30	78	51.17	9.57	0.88
Career problems	632	36	80	55.47	8.63	0.87
Depression	633	27	78	53.27	9.14	0.81
Family problems	633	32	74	44.61	11.19	0.72
Interpersonal problems	633	29	77	52.51	8.38	0.72
Regular activities	624	27	78	57.10	8.80	0.69
Self-esteem problems	633	22	74	50.31	9.19	0.76
Substance abuse	633	39	75	49.72	8.45	0.78
Suicidal ideation	633	44	76	51.92	9.63	0.87
Valid N (listwise)	624

Anxiety: A measure of clinical anxiety, focusing on common affective, cognitive, and physiological symptoms.

Depression: A measure of clinical depression, focusing on common affective, cognitive, and physiological symptoms.

Suicidal Ideation: A measure of the extent of recent ideation reflecting suicide, including thoughts of suicide, hopelessness, and resignation.

Substance Abuse: A measure of the extent of disruption in interpersonal, social, academic, and vocational functioning as a result of substance use and abuse.

Self-esteem Problems: A measure of global self-esteem which taps negative self-evaluations and dissatisfaction with personal achievement.

Interpersonal Problems: A measure of the extent of problems in relating to others in the campus environment.

Family Problems: A measure of difficulties experienced in relationships with family members.

Academic Problems: A measure of the extent of problems related to academic performance.

Career Problems: A measure of the extent of problems related to career choice.

Participants also responded to a demographic questionnaire that included items on gender, birth year, marital status, ethnicity, and sexual orientation. As sexual orientation is a major cause for bullying ( Pollock, 2006 ; Cahill and Makadon, 2014 ), it was included in the background information.

Convenience sampling and purposive sampling were used for this study. Surveys with written instructions were administered in classrooms, libraries and online via Google Docs at the end of the semester.

The surveys were translated to Hebrew and back translated four times until sufficient translation was achieved. The research was approved by the Western Galilee College Research and Ethic Committee.

A sizeable percentage, 57.4% (366), of the respondents reported being cyber bullied at least once and 3.4% (22) reported being cyber bullied at least once a week. The types of bullies can be seen in Fig. 1 .

Types of bullies.

Three variables were found to have significant influences on the research variables: (1) gender (see Table 3 ); (2) religion (see Table 4 ); and (3) sexual preferences (see Table 5 ).

Results of independent t-tests for research variables by gender.

		M	SD	t
Depression	Male	51.82	8.08	1.99
Depression	Female	53.63	9.37	1.99
Regular activities	Male	55.66	8.82	2.05
Regular activities	Female	57.47	8.77	2.05
Self-esteem problems	Male	48.79	9.19	2.08
Self-esteem problems	Female	50.68	9.16	2.08
Suicidal ideation	Male	50.10	8.91	2.48
Suicidal ideation	Female	52.34	9.74	2.48

Note: n male = 127, n female = 510, *p < .05.

Results of independent t-tests for research variables by level of religion.

		M	SD	T
Depression	Secular	52.07	8.97	3.08
Depression	Religious	54.30	9.17
Family problemýs	Secular	43.60	11.16	2.09
Family problemýs	Religious	45.46	11.16
Interpersonal problems	Secular	51.77	8.80	2.04
Interpersonal problems	Religious	53.14	7.97
Suicidal ideation	Secular	50.13	8.85	4.42
Suicidal ideation	Religious	53.44	10.00

Note: n religious = 345, n secular = 293, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Results of independent t-tests for research variables by sexual preference.

		M	SD	t
Anxiety	Heterosexual	50.92	9.63	2.41
Anxiety	Other	54.60	8.12	2.41
Depression	Heterosexual	52.88	8.90	4.14
Depression	Other	58.86	10.59	4.14
Family problems	Heterosexual	44.11	10.94	4.20
Family problems	Other	51.52	12.42	4.20
Interpersonal problems	Heterosexual	52.26	8.31	2.80
Interpersonal problems	Other	56.00	8.80	2.80
Self-esteem problems	Heterosexual	50.07	9.14	2.44
Self-esteem problems	Other	53.64	9.28	2.44
Substance abuse	Heterosexual	49.34	8.19	3.48
Substance abuse	Other	54.98	10.27	3.48
Suicidal ideation	Heterosexual	51.33	9.34	5.88
Suicidal ideation	Other	60.14	9.89	5.88

Note: n heterosexual = 596, n other = 42, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Independent t-tests between the CAS variables and gender show significant differences between females and males (see Table 3 ).

Independent t-tests between the CAS variables and level of religiosity show significant differences between secular and religious persons, i.e., observant believers (see Table 4 ).

Independent t-tests between the CAS variables and sexual preference show significant differences between heterosexual individuals and others (see Table 5 ).

The research population was divided into three age groups having five year intervals. One respondent who was 14 years old was removed from the population.

For the variable “career problems” it was found that there was a significant difference between the 26–30 year age group [p < .05, F(2,5815) = 3.49, M = 56.55] and the 31–35 (M = 56.07) as well as the 20–25 (M = 54.58) age groups.

For the variable "depression" it was found that there was a significant difference between the 20–25 year age group [p < .05, F(2,5815) = 3.84, M = 54.56] and the 31–35 (M = 51.61) as well as the 26–30 (M = 52.83) age groups.

For the variable “interpersonal problems” it was found that there was a significant difference between the 20–25 year age group [p < .06, F(2,5815) = 3.84, M = 53.85] and the 31–35 (M = 51.29) as well as the 26–30 (M = 52.19) age groups.

For the variable “suicidal ideation” it was found that there was a significant difference between the 20–25 year age group [p < .06, F(2,5815) = 3.84, M = 55.45] and the 31–35 (M = 49.71) as well as the 26–30 (M = 50.13) age groups (see Table 6 ).

Results of one way Anova for research variables by age.

	Age Group	M	SD	F
Career problems	20–25	54.58	7.97	3.49
	26–30	56.55	8.36
	31–35	56.07	9.29
Depression	20–25	54.56	10.08	3.84
	26–30	52.83	8.62
	31–35	51.61	8.14
Interpersonal problems	20–25	53.58	8.23	2.87
	26–30	52.19	8.42
	31–35	51.29	8.06
Suicidal ideation	20–25	55.45	10.48	22.79
	26–30	50.13	8.67
	31–35	49.71	8.58

Note: n 20-25 = 216, n 26-30 = 287, n 31-35 = 82, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

To confirm that there was no effect among the independent variables, a Pearson correlation analysis of cyberbullying with CAS variables was run. As the correlations between the independent variables are weak, no multicollinearity between them was noted (see Table 7 ).

Pearson correlation of cyberbullying with CAS variables.

CAS Variables	Cyberbullying
CAS Variables	Mail	IM	Chat	SMS	Social Network
Academic problems	0.018	0.196***	0.079	0.141***	0.189***
Anxiety	0.042	0.216***	0.080*	0.159***	0.194***
Career problems	-0.007	0.089	-0.08	0.079	0.057
Depression	0.064	0.210***	0.122**	0.102*	0.172***
Family problems	0.142***	0.227***	0.081*	0.132**	0.156***
Interpersonal problems	0.054	0.150***	0.094	0.040	0.110**
Regular activities	-0.121**	-0.014	0.005-	-0.015	0.003
Self-esteem	0.041	0.229***	0.124**	0.171***	0.208***
Substance abuse	0.150***	0.235***	0.184***	0.161***	0.174***
Suicidal ideation	0.130**	0.230***	0.148***	0.093*	0.130**

Note: n = 638, ∼ p < .06, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Regression analyses on the effect of the cyberbullying variables on the CAS variables (see Fig. 2 ) show that an increase in cyberbullying by social networking and IM increases the academic problems variable. The model explained 6.1% of the variance (F (13,585) = 2.94, p < .001) and shows an increase in the suicidal ideation variable. There is also a marginal effect of cyberbullying by SMS on suicidal ideation, revealing that an increase in cyberbullying by SMS causes a decrease in suicidal ideation. The explained variance of the model is 24.8% (F (11,584) = 14.80, p < .001). Higher cyberbullying by social networking results in an increase in the anxiety variable. The explained variance of the model is 8.8% (F (13,584) = 4.32, p < .001). An increase in cyberbullying by chat and IM shows an increase in the substance abuse variable. The model explains 13% of the variance (F (13,584) = 6.71, p < .001). Increasing cyberbullying by social networking and IM increases the self-esteem problems variable. The explained variance of the model is 9% (F (13,584) = 4.43, p < .001). An increase of cyberbullying by email increases the problems students have with regular activities. The explained variance of the model is 5.2% (F (13,575) = 2.44, p < .01). Heightened cyberbullying by social networking and IM increases students' interpersonal problems. There is also an effect of cyberbullying by IM on suicidal ideation, such that an increase in cyberbullying by IM causes a decrease in interpersonal problems. The explained variance of the model is 8% (F (13,584) = 3.89, p < .001). An increase in cyberbullying by SMS decreases the family problems variable. The explained variance of the model is 11.4% (F (13,584) = 5.76, p < .001). And finally, heightened cyberbullying by IM and social networking decreases the depression variable. The variance explained by the model is 11.9% (F (13,584) = 6.04, p < .001).

The influence of academic cyberbullying variables on the CAS variables.

4. Discussion

The objective of this study was to fill an existing gap in the literature regarding the influence of cyberbullying on the academic, social, and emotional development of undergraduate students.

As has been presented, cyberbullying continues to be a disturbing trend not only among adolescents but also undergraduate students. Cyberbullying exists in colleges and universities, and it has an influence on the development of students. Fifty seven percent of the undergraduate students who participated in this study had experienced cyberbullying at least once during their time in college. As previous studies have found that cyberbullying incidents among college students can range from 9% to 50% ( Baldasare et al., 2012 ; Beebe, 2010 ) it seems that 57% is high. Considering the effect of smartphone abundance on one hand and on the other the increasing use of online services and activities by young-adults can explain that percentage.

Considering the effect of such an encounter on the academic, social and emotional development of undergraduate students, policy makers face a formidable task to address the relevant issues and to take corrective action as Myers and Cowie (2017) point out that due to the fact that universities are in the business of education, it is a fine balancing act between addressing the problem, in this case cyberbullying, and maintaining a duty of care to both the victim and the perpetrator to ensure they get their degrees. There is a clear tension for university authorities between acknowledging that university students are independent young adults, each responsible for his or her own actions, on one hand, and providing supervision and monitoring to ensure students' safety in educational and leisure contexts.

Although there are increasing reports on connections between cyberbullying and social-networks (see: Gahagan et al., 2016 ), sending SMS or MMS messages through Internet gateways ensures anonymity, thus indirectly supporting cyberbullying. A lot of websites require only login or a phone number that can also be made up ( Gálik et al., 2018 ) which can explain the fact that instant-messaging (IM) was found to be the most common means of cyberbullying among undergraduate students with a negative influence on academic, family, and emotional development (depression, anxiety, and suicidal ideation). A possible interpretation of the higher frequency of cyberbullying through IM may be that young adults have a need to be connected.

This medium allows for being online in ‘real time’ with many peers or groups. With the possibility of remaining anonymous (by creating an avatar – a fake profile) and the possibility of exposing private information that remains recorded, students who use instant messaging become easy targets for cyberbullying. IM apps such as WhatsApp are extremely popular as they allow messages, photos, videos, and recordings to be shared and spread widely and in real time.

Students use the Internet as a medium and use it with great frequency in their everyday lives. As more aspects of students' lives and daily affairs are conducted online, coupled with the fact that excessive use may have consequences, it is important for researchers and academic policy makers to study the phenomenon of cyberbullying more deeply.

Sexual orientation is also a significant factor that increases the risk of victimization. Similarly, Rivers (2016) documented the rising incidence of homophobic and transphobic bullying at university and argues strongly for universities to be more active in promoting tolerance and inclusion on campus. It is worth noting that relationships and sexual orientation probably play a huge role in bullying among university students due to their age and the fact that the majority of students are away from home and experiencing different forms of relationships for the first time. Faucher et al. (2014) actually found that same sex cyberbullying was more common at university level than at school. Nonetheless, the research is just not there yet to make firm conclusions.

Finally, cyberbullying is not only an adolescent issue. Although its existence has been proven, studies of cyberbullying among undergraduate students have not been fully developed. This particular population needs special attention in future research.

The results of this study indicate that cyberbullying has an influence on the academic, social, and emotional development of undergraduate students.

In the academic field, findings revealed a statistically significant correlation between cyberbullying perpetrated by email and academic problems. Relationships between academic problems and cyberbullying perpetrated by other media were not found. This suggests that cyberbullying through instant messaging, chat room, text messaging, and social networking sites, have not influenced academic abilities, motivation to learn, and general satisfaction with the academic environment. However, cyberbullying perpetrated by email has an influence on academics, perhaps because of the high use of this medium among undergraduate students.

With regard to career problems, correlations with cyberbullying were not found. This indicates that cyberbullying has no influence on career problems, perhaps because these kinds of problems are related to future career inspirations, and not to the day-to-day aspects of a student's life.

In the social field, it was found that interpersonal problems such as integration into the social environment, forming a support network, and managing new social freedoms, were related to cyberbullying via social networking sites. This finding is consistent with the high use of social networking sites, the purpose of the medium, and the reported episodes of cyberbullying in that medium.

Family problems were also related to cyberbullying perpetrated by all kinds of media. This may indicate that as cyberbullying through the use of email, instant messaging, chat rooms, text messaging, and social networking sites increases, so do family problems. This could be due to the strong influence that cyberbullying generates in all the frameworks of students, including their families.

Finally, in the emotional field, correlations between cyberbullying perpetrated by all kinds of media and substance abuse were found. This may indicate that as cyberbullying through the use of email, instant messaging, chat rooms, text messaging, and social networking sites increases, so does substance abuse. This is important because cyberbullying may be another risk factor for increasing the probability of substance abuse.

Depression and suicidal ideation were significantly related to the same media – email instant messaging and chat cyberbullying – suggesting that depression may lead to a decision of suicide as a solution to the problem. Previous findings support the above that being an undergraduate student – a victim of cyberbullying emerges as an additional risk factor for the development of depressive symptoms ( Myers and Cowie, 2017 ). Also Selkie et al. (2015) reported among 265 female college students, being engaged in cyberbullying as bullies, victims, or both led to higher rates of depression and alcohol use.

Relationships between anxiety and cyberbullying, through all the media, were not found although Schenk and Fremouw (2012) found that college student victims of cyberbullying scored higher than matched controls on measures of depression, anxiety, phobic anxiety, and paranoia. This may be because it was demonstrated that anxiety is one of the most common reported mental health problems in all undergraduate students, cyberbullied or not.

Self-esteem problems were significantly related to cyberbullying via instant messaging, social networking sites, and text messaging. This may suggest that as cyberbullying through instant messaging, social networking sites, and text messaging increases, so do self-esteem problems. This is an important finding, given that these were the media with more reported episodes of cyberbullying.

5. Conclusions

This findings of this study revealed that cyberbullying exists in colleges and universities, and it has an influence on the academic, social, and emotional development of undergraduate students.

It was shown that cyberbullying is perpetrated through multiple electronic media such as email, instant messaging, chat rooms, text messaging, and social networking sites. Also, it was demonstrated that students exposed to cyberbullying experience academic problems, interpersonal problems, family problems, depression, substance abuse, suicidal ideation, and self-esteem problems.

Students have exhibited clear preferences towards using the Internet as a medium and utilize it with great frequency in their everyday lives. As more and more aspects of students' lives are conducted online, and with the knowledge that excessive use may have consequences for them, it is important to study the phenomenon of cyberbullying more deeply.

Because college students are preparing to enter the workforce, and several studies have indicated a trend of cyberbullying behavior and victimization throughout a person's lifetime ( Watts et al., 2017 ), the concern is these young adults are bringing these attitudes into the workplace.

Finally, cyberbullying is not only an adolescent issue. Given that studies of cyberbullying among undergraduate students are not fully developed, although existence of the phenomenon is proven, we conclude that the college and university population needs special attention in future areas of research. As it has been indicated by Peled et al. (2012) that firm policy in regard to academic cheating reduces its occurrence, colleges should draw clear guidelines to deal with the problem of cyberbullying, part of it should be a safe and if needed anonymous report system as well as clear punishing policy for perpetrators.

As there's very little research on the effect of cyberbullying on undergraduates students, especially in light of the availability of hand held devices (mainly smartphones) and the dependence on the internet for basically every and any activity, the additional data provided in this research adds to the understanding of the effect of cyberbullying on the welfare of undergraduate students.

Declarations

Author contribution statement.

Yehuda Peled: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Competing interest statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

Akbulut Y., Eristi B. Cyberbullying and victimization among Turkish university students. Australas. J. Educ. Technol. 2011; 27 (7):1155–1170. [ Google Scholar ]
Akcil S. Kent State University; 2018. Cyberbullying-Victimization, Acculturative Stress, and Depression Among International College Students. Doctoral dissertation. [ Google Scholar ]
Anton D.W., Reed R.J. Psychological Assessment Resources, Inc; 1991. College Adjustment Scales. [ Google Scholar ]
Baldasare A., Bauman S., Goldman L., Robie A. Cyberbullying: voices of college students. Cutting Edge Technol. Higher Educ. 2012; 5 :127–155. https://studentaffairs.arizona.edu/assessment/documents/CyberbullyChapterFinal.pdf Retrieved from. [ Google Scholar ]
Beebe J.E. University of Northern Colorado; 2010. The Prevalence of Cyber Bullying Victimization and its Relationship to Academic, Social, and Emotional Adjustment Among College Students. https://eric.ed.gov/?id=ED517400 ProQuest LLC, Ph.D. Dissertation. [ Google Scholar ]
Belsey B. 2006. Cyber Bullying: an Emerging Threat to “Always on” Generation. http://www.cyberbullying.ca/pdf/Cyberbullying_Article_by_Bill_Belsey.pdf From. [ Google Scholar ]
Cahill S., Makadon H. Sexual orientation and gender identity data collection in clinical settings and in electronic health records: a key to ending LGBT health disparities. LGBT Health. 2014; 1 (1):34–41. [ PubMed ] [ Google Scholar ]
Clark D.M.T., Loxton N.J., Tobin S.J. Declining loneliness over time: evidence from American colleges and high schools. Pers. Soc. Psychol. Bull. 2015; 41 (1):78–89. [ PubMed ] [ Google Scholar ]
Dalia–Global consumer understanding . 2016. Counting the LGBT Population: 6% of Europeans Identify as LGBT. https://daliaresearch.com/counting-the-lgbt-population-6-of-europeans-identify-as-lgbt/ [ Google Scholar ]
DeHue F., Bolman C., Völlink T. Cyberbullying: youngsters' experiences and parental perception. Cyberpsychol. Behav. 2008; 11 (2):217–223. [ PubMed ] [ Google Scholar ]
Dılmaç B. Psychological needs as a predictor of cyber bullying: a preliminary report on college students. Educ. Sci. Theor. Pract. 2009; 9 (3):1307–1325. [ Google Scholar ]
Faryadi Q. Cyber bullying and academic performance. Int. J. Comput. Eng. Res. 2011; 1 (1):2250–3005. [ Google Scholar ]
Faucher C., Jackson M., Cassidy W. Cyberbullying among university students: gendered experiences, impacts, and perspectives. Educ. Res. Int. 2014 [ Google Scholar ]
Gálik S., Hladíková V., Pavlák L. Cyberbullying and opportunities for its prevention. Media Lit. Acad. Res. 2018; 1 (1):6–17. [ Google Scholar ]
Gahagan K., Vaterlaus J.M., Frost L.R. College student cyberbullying on social networking sites: conceptualization, prevalence, and perceived bystander responsibility. Comput. Hum. Behav. 2016; 55 :1097–1105. [ Google Scholar ]
Gates G.J. The Williams Institute, UCLA School of Law; 2011. How many People Are Lesbian, Gay, Bisexual and Transgender? https://escholarship.org/uc/item/09h684x2 [ Google Scholar ]
Gerdes H., Mallinckrodt B. Emotional, social, and academic adjustment of college students: a longitudinal study of retention. J. Couns. Dev. 1994; 72 (3):281–288. [ Google Scholar ]
Ghadampour F., Shafiei M., Heidarirad H. Relationships among cyberbullying, psychological vulnerability and suicidal thoughts in female and male students. J. Res. Psychol. Health. 2017; 11 :28–40. [ Google Scholar ]
Grene M.B. Counselling and climate change as treatment modalities for bullying in school. Int. J. Adv. Couns. 2003; 25 (4):293–302. [ Google Scholar ]
Heiman T., Olenik Shemesh D. Predictors of cyber-victimization of higher-education students with and without learning disabilities. J. Youth Stud. 2018:1–18. [ Google Scholar ]
Inkelas K.K., Daver Z.E., Vogt K.E., Leonard J.B. Living–learning programs and first-generation college students’ academic and social transition to college. Res. High. Educ. 2007; 48 (4):403–434. [ Google Scholar ]
Juvonen J., Graham S., Shuster M.A. Bullying among young adolescents: the strong, the weak, and the troubled. Paediatrics. 2003; 112 (6):1231–1237. [ PubMed ] [ Google Scholar ]
Juvonen J., Gross E.F. Extending the school grounds?—bullying experiences in cyberspace. J. Sch. Health. 2008; 78 (9):496–505. [ PubMed ] [ Google Scholar ]
Kowalski R.M., Limber S.P. Electronic bullying among middle school children. J. Adolesc. Health. 2007; 41 :S22–S30. [ PubMed ] [ Google Scholar ]
Kowalski R., Limber S.P., McCord A. A developmental approach to cyberbullying: prevalence and protective factors. Aggress. Violent Behav. 2018 [ Google Scholar ]
Lau L.K. Institutional factors affecting student retention. Education. 2003; 124 (1):126–137. [ Google Scholar ]
McGrath S. 2005. The Multiple Contexts of Vocational Education and Training in Southern Africa. Vocational Education and Training in Southern Africa: a Comparative Study; pp. 1–8. http://hdl.handle.net/20.500.11910/7250 URI: [ Google Scholar ]
Merriam-Webster . 2017. On-line Dictionary. https://www.merriam-webster.com/dictionary/cyberbullying [ Google Scholar ]
Myers C.A., Cowie H. Bullying at university: the social and legal contexts of cyberbullying among university students. J. Cross Cult. Psychol. 2017; 48 (8):1172–1182. [ Google Scholar ]
Na H. 2014. The Effects of Cyberbullying Victimization on Psychological Adjustments Among College Students. https://dspace-prod.lib.uic.edu/bitstream/handle/10027/11288/Na_Hyunjoo.pdf?sequence=1&isAllowed=y Doctoral dissertation. [ Google Scholar ]
Parker J.D., Summerfeldt L.J., Hogan M.J., Majeski S.A. Emotional intelligence and academic success: examining the transition from high school to university. Pers. Indiv. Differ. 2004; 36 (1):163–172. [ Google Scholar ]
Peled Y., Barczyk C., Sarid M. Institutional Characteristics and faculty perceptions of academic dishonesty. Educ. Pract. Theor. 2012; 34 (2):61–79. [ Google Scholar ]
Pollock S.L. Counsellor roles in dealing with bullies and their LGBT victims. Middle Sch. J. 2006; 38 (2):29–36. [ Google Scholar ]
Poole S.P. Vol. 115. 2017. The Experience of Victimization as the Result of Cyberbullying Among College Students: A Study of Demographics, Self-Esteem, and Locus of Control. http://scholarworks.sfasu.edu/etds/115 Electronic Theses and Dissertations. [ Google Scholar ]
Rey L., Extremera N., Pena M. Perceived emotional intelligence, self-esteem and life satisfaction in adolescents. Psychosoc. Interv. 2011; 20 (2) [ Google Scholar ]
Rivers I. Homophobic and transphobic bullying in universities. In: Cowie H., Myers C.-A., editors. Bullying Among university Students. Routledge; London, England: 2016. pp. 48–60. [ Google Scholar ]
Rivituso G. 2012. Cyberbullying: an Exploration of the Lived Experiences and the Psychological Impact of Victimization Among College Students an Interpretive Phenomenological Analysis. Education Doctoral Theses. Paper 21. [ Google Scholar ]
Selkie E.M., Kota R., Chan Y.F., Moreno M. Cyberbullying, depression, and problem alcohol use in female college students: a multisite study. Cyberpsychol. Behav. Soc. Netw. 2015; 18 (2):79–86. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Schenk A.M., Fremouw W.J. Prevalence, psychological impact, and coping of cyberbully victims among college students. J. Sch. Violence. 2012; 11 :21–37. [ Google Scholar ]
Tinto V. Dropout from higher education: a theoretical synthesis of recent research. Rev. Educ. Res. 1975; 45 (1):89–125. [ Google Scholar ]
Varghese M.E., Pistole M.C. College student cyberbullying: self-esteem, depression, loneliness, and attachment. J. Coll. Couns. 2017; 20 (1):7–21. [ Google Scholar ]
Walker C.M., Sockman B.J., Koehn S. An exploratory study of cyberbullying with undergraduate university students. TechTrends. 2011; 55 (2):31–38. [ Google Scholar ]
Watts L.K., Wagner J., Velasquez B., Behrens P.I. Cyberbullying in higher education: a literature review. Comput. Hum. Behav. 2017; 69 :268–274. [ Google Scholar ]
Webber M.A., Ovedovitz A.C. Cyberbullying among college students: a look at its prevalence at a U.S. Catholic University. Int. J. Educ. Methodol. 2018; 4 (2):101–107. [ Google Scholar ]
Ybarra M.L., Mitchell K.J. Prevalence and frequency of internet harassment instigation: implications for adolescent health. J. Adolesc. Health. 2007; 41 :189–195. [ PubMed ] [ Google Scholar ]
Ziapour A., Khatony A., Jafari F., Kianipour N. Correlation of personality traits with happiness among university students. J. Clin. Diagn. Res. 2018; 12 (4) [ Google Scholar ]

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In 2010, the International Cyberbullying Think Tank was held in order to discuss questions of definition, measurement, and methodologies related to cyberbullying research. The attendees’ goal was to develop a set of guidelines that current and future researchers could use to improve the quality of their research and advance our understanding of cyberbullying and related issues. This book is the product of their meetings, and is the first volume to provide researchers with a clear set of principles to inform their work on cyberbullying. The contributing authors, all participants in the Think Tank, review the existing research and theoretical frameworks of cyberbullying before exploring topics such as questions of methodology, sampling issues, methods employed so far, psychometric issues that must be considered, ethical considerations, and implications for prevention and intervention efforts. Researchers as well as practitioners seeking information to inform their prevention and intervention programs will find this to be a timely and essential resource.

Part | 20 pages, introduction, chapter | 18 pages, part | 25 pages, definitional questions, chapter | 3 pages, why it matters, chapter | 15 pages, definitions of bullying and cyberbullying, chapter | 5 pages, definitions, part | 39 pages, theoretical framework, chapter | 19 pages, theories of cyberbullying, potent ways forward, part | 93 pages, chapter | 4 pages, methodology, chapter | 13 pages, methods used in cyberbullying research, chapter | 16 pages, moving beyond tradition and convenience, chapter | 7 pages, ethical issues, chapter | 14 pages, emerging methodological strategies to address cyberbullying, part | 77 pages, measurement, psychometric considerations for cyberbullying research, chapter | 20 pages, cybervictimization and cyberaggression in eastern and western countries, what to measure, qualitative studies, part | 35 pages, implications, how research findings can inform legislation and school policy on cyberbullying, using research to inform cyberbullying prevention and intervention, part | 29 pages, going forward, chapter | 10 pages, future research questions in cyberbullying, chapter | 17 pages, summary and conclusions.

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Cyberbullying

First Online: 28 October 2022

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Michelle F. Wright 2

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Cyberbullying has become a major focus of not only youths, educators, and researchers, but also among the general population, due to high profile cases of cyberbullying victimization involving suicide and the increasing prevalence of these behaviors. The purpose of this chapter is to examine cyberbullying among children and adolescents, referred to as “youths” throughout the chapter. An extension of traditional bullying, cyberbullying is a form of bullying which takes place by means of electronic technologies, such as email, instant messaging, social networking websites, and text messaging through mobile devices. Drawing on research from a variety of disciplines, such as psychology, education, social work, sociology, and computer science, this chapter describes the definition of cyberbullying, the electronic technologies used, the prevalence rates, characteristics and risk factors, negative psychosocial and academic difficulties, theoretical frameworks, recommendations, and future directions.

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Cyberbullying Prevention and Intervention: Promising Approaches and Recommendations for Further Evaluation

Prevention of Cyberbullying: A Conceptual Review

Research on Cyberbullying: Strengths and Limitations

Ang, R. P. (2016). Cyberbullying: Its prevention and intervention strategies. In D. Sibnath (Ed.), Child safety, welfare and well-being: Issues and challenges (pp. 25–38). Springer.

Chapter Google Scholar

Aoyama, I., Utsumi, S., & Hasegawa, M. (2011). Cyberbullying in Japan: Cases, government reports, adolescent relational aggression and parental monitoring roles. In Q. Li, D. Cross, & P. K. Smith (Eds.), Bullying in the global playground: Research from an international perspective . Wiley-Blackwell.

Google Scholar

Aricak, T., Siyahhan, S., Uzunhasanoglu, A., Saribeyoglu, S., Ciplak, S., Yilmaz, N., & Memmedov, C. (2008). Cyberbullying among Turkish adolescents. CyberPsychology and Behavior, 11 , 253–261.

Article PubMed Google Scholar

Arslan, S., Savaser, S., Hallett, V., & Balci, S. (2012). Cyberbullying among primary school students in Turkey: Self-reported prevalence and associations with home and school life. CyberPsychology, Behavior, and Social Networking, 15 , 527–533.

Article Google Scholar

Ayas , T., & Horzum , M. B. (2010). Cyberbullg / victim scale development study . Retrieved from: http://www.akademikbakis.org

Barlett, C. P., & Gentile, D. A. (2012). Long-term psychological predictors of cyber-bullying in late adolescence. Psychology of Popular Media Culture, 2 , 123–135.

Barlett, C. P., Gentile, D. A., Anderson, C. A., Suzuki, K., Sakamoto, A., Yamaoka, A., & Katsura, R. (2013). Cross-cultural differences in cyberbullying behavior: A short-term longitudinal study. Journal of Cross-Cultural Psychology, 45 , 300–313.

Bauman, S., Toomey, R. B., & Walker, J. L. (2013a). Associations among bullying, cyberbullying, and suicide in high school students. Journal of Adolescence, 36 , 341–350.

Bauman, S., Underwood, M. K., & Card, N. A. (2013b). Definitions: Another perspective and a proposal for beginning with cyberaggression. In S. Bauman, D. Cross, & J. Walker (Eds.), Principles of cyberbullying research: Definitions, measures, methodology (pp. 26–40). Routledge.

Bayar, Y., & Ucanok, Z. (2012). School social climate and generalized peer perception in traditional and cyberbullying status. Educational Sciences: Theory & Practice, 12 , 2352–2358.

Beckman, L., Hagquist, C., & Hellstrom, L. (2012). Does the association with psychosomatic health problems differ between cyberbullying and traditional bullying? Emotional and Behavioural Difficulties, 17 , 421–434.

Bonanno, R. A., & Hymel, S. (2013). Cyber bullying and internalizing difficulties: Above and beyond the impact of traditional forms of bullying. Journal of Youth and Adolescence, 42 , 685–697.

Boulton, M., Lloyd, J., Down, J., & Marx, H. (2012). Predicting undergraduates’ self-reported engagement in traditional and cyberbullying from attitudes. Cyberpsychology, Behavior and Social Networking, 15 (3), 141–147.

Brighi, A., Guarini, A., Melotti, G., Galli, S., & Genta, M. L. (2012). Predictors of victimisation across direct bullying, indirect bullying and cyberbullying. Emotional and Behavioural Difficulties, 17 , 375–388.

Burton, K. A., Florell, D., & Wygant, D. B. (2013). The role of peer attachment and normative beliefs about aggression on traditional bullying and cyberbullying. Psychology in the Schools, 50 , 103–114.

Cappadocia, M. C., Craig, W. M., & Pepler, D. (2013). Cyberbullying: Prevalence, stability and risk factors during adolescence. Canadian Journal of School Psychology, 28 , 171–192.

Cassidy, W., Brown, K., & Jackson, M. (2012a). “Making kind cool”: Parents’ suggestions for preventing cyber bullying and fostering cyber kindness. Journal of Educational Computing Research, 46 , 415–436.

Cassidy, W., Brown, K., & Jackson, M. (2012b). “Under the radar”: Educators and cyberbullying in schools. School Psychology International, 33 , 520–532.

Corcoran, L., Connolly, I., & O’Moore, M. (2012). Cyberbullying in Irish schools: An investigation of personality and self-concept. The Irish Journal of Psychology, 33 , 153–165.

Curelaru, M., Iacob, I., & Abalasei, B. (2009). School bullying: Definition, characteristics, and intervention strategies . Lumean Publishing House.

Dehue, F., Bolman, C., & Vollink, T. (2008). Cyberbullying: Youngsters’ experiences and parental perception. Cyberpsychology and Behavior, 11 , 217–223.

Dehue, F., Bolman, C., Vollink, T., & Pouwelse, M. (2012). Cyberbullying and traditional bullying in relation to adolescents’ perceptions of parenting. Journal of Cybertherapy and Rehabilitation, 5 , 25–34.

deLara, E. W. (2012). Why adolescents don’t disclose incidents of bullying and harassment. Journal of School Violence, 11 (4), 288–305.

Diamanduros, T., & Downs, E. (2011). Creating a safe school environment: How to prevent cyberbullying at your school. Library Media Connection, 30 (2), 36–38.

Eden, S., Heiman, T., & Olenik-Shemesh, D. (2013). Teachers’ perceptions, beliefs and concerns about cyberbullying. British Journal of Educational Technology, 44 , 1036–1052.

Elledge, L. C., Williford, A., Boulton, A. J., DePaolis, K. J., Little, T. D., & Salmivalli, C. (2013). Individual and contextual predictors of cyberbullying: The influence of children’s provictim attitudes and teachers’ ability to intervene. Journal of Youth and Adolescence, 42 , 698–710.

Erdur-Baker, O. (2010). Cyberbullying and its correlation to traditional bullying, gender and frequent and risky usage of internet-mediated communication tools. New Media & Society, 12 , 109–125.

Fanti, K. A., Demetriou, A. G., & Hawa, V. V. (2012). A longitudinal study of cyberbullying: Examining risk and protective factors. European Journal of Developmental Psychology, 8 , 168–181.

Festl, R., Schwarkow, M., & Quandt, T. (2013). Peer influence, internet use and cyberbullying: A comparison of different context effects among German adolescents. Journal of Children and Media, 7 , 446–462.

Goebert, D., Else, I., Matsu, C., Chung-Do, J., & Chang, J. Y. (2011). The impact of cyberbullying on substance uses and mental health in a multiethnic sample. Maternal and Child Health Journal, 15 , 1282–1286.

Gradinger, P., Strohmeier, D., & Spiel, C. (2009). Traditional bullying and cyberbullying. Journal of Psychology, 217 , 205–213.

Grigg, D. W. (2012). Definitional constructs of cyberbullying and cyber aggression from a triagnulatory overview: A preliminary study into elements. Journal of Aggression, Conflict and Peace Research, 4 , 202–215.

Hinduja, S., & Patchin, J. W. (2007). Offline consequences of online victimization. Journal of School Violence, 6 , 89–112.

Hinduja, S., & Patchin, J. W. (2008). Cyberbullying: An exploratory analysis of factors related to offending and victimization. Deviant Behavior, 29 , 129–156.

Hinduja, S., & Patchin, J. W. (2010). Bullying, cyberbullying, and suicide. Archives of Suicide Research, 14 , 206–221.

Hinduja, S., & Patchin, J. W. (2012). Cyberbullying: Neither and epidemic nor a rarity. European Journal of Developmental Psychology, 9 , 539–543.

Hinduja, S., & Patchin, J. W. (2013). Social influences on cyberbullying behaviors among middle and high school students. Journal of Youth and Adolescence, 42 , 711–722.

Huang, Y., & Chou, C. (2010). An analysis of multiple factors of cyberbullying among junior high school students in Taiwan. Computers in Human Behavior, 26 , 1581–1590.

Jang, H., Song, J., & Kim, R. (2014). Does the offline bully-victimization influence cyberbullying behavior among youths? Application of general strain theory. Computers in Human Behavior, 31 , 85–93.

Joinson, A. (1998). Causes and implications of behavior on the Internet. In J. Gackenbach (Ed.), Psychology and the Internet: Intrapersonal, interpersonal, and transpersonal implications (pp. 43–60). Academic Press.

Kochenderfer-Ladd, B., & Pelletier, M. (2008). Teachers’ views and beliefs about bullying: Influences on classroom management strategies and students’ coping with peer victimization. Journal of School Psychology, 46 , 431–453.

Kowalski, R. M., & Limber, S. P. (2007). Electronic bullying among middle school students. Journal of Adolescent Health, 41 , 22–30.

Kwan, G. C. E., & Skoric, M. M. (2013). Facebook bullying: An extension of battles in school. Computers in Human Behavior, 29 (1), 16–25.

Laftman, S. B., Modin, B., & Ostberg, V. (2013). Cyberbullying and subjective health: A large-scale study of students in Stockholm, Sweden. Children and Youth Services Review, 35 , 112–119.

Lazuras, L., Barkoukis, V., Ourda, D., & Tsorbatzoudis, H. (2013). A process model of cyberbullying in adolescence. Computers in Human Behavior, 29 , 881–887.

Lenhart, A. (2015). Teens, social media & technology overview 2015 . Retrieved from: http://www.pewinternet.org/2015/04/09/teens-social-media-technology-2015/

Li, Q. (2007). Bullying in the new playground: Research into cyberbullying and cybervictimization. Australian Journal of Educational Technology, 23 , 435–454.

Li, Q. (2008). A cross-cultural comparison of adolescents’ experience related to cyberbullying. Educational Research, 50 , 223–234.

Machackova, H., Dedkova, L., Sevcikova, A., & Cerna, A. (2013). Bystanders’ support of cyberbullied schoolmates. Journal of Community & Applied Social Psychology, 23 (1), 25–36.

Mason, K. (2008). Cyberbullying: A preliminary assessment for school personnel. Psychology in the Schools, 45 , 323–348.

McKenna, K. Y. A., & Bargh, J. A. (2000). Plan 9 from cyberspace: The implications of the internet for personality and social psychology. Personality and Social Psychology Review, 4 , 57–75.

McQuade, C. S., Colt, P. J., & Meyer, B. N. (2009). Cyber bullying: Protecting kids and adults from online bullies . Praeger.

Mitchell, K. J., Ybarra, M., & Finkelhor, D. (2007). The relative importance of online victimization in understanding depression, delinquency, and substance use. Child Maltreatment, 12 , 314–324.

Mouttapa, M., Valente, T., Gallagher, P., Rohrbach, L. A., & Unger, J. B. (2004). Social network predictor of bullying and victimization. Adolescence, 39 , 315–335.

PubMed Google Scholar

Olenik-Shemesh, D., Heiman, T., & Eden, S. (2012). Cyberbullying victimization in adolescence: Relationships with loneliness and depresisve mood. Emotional and Behavioural Difficulties, 17 (3–4), 361–374.

Olweus, D. (1993). Bullying at school. What we know and what we can do . Blackwell Publishing.

Patchin, J. W., & Hinduja, S. (2006). Bullies move beyond the schoolyard: A preliminary look at cyberbullying. Youth Violence and Juvenile Justice, 4 , 148–169.

Perren, S., Dooley, J., Shaw, T., & Cross, D. (2010). Bullying in school and cyberspace: Associations with depressive symptoms in Swiss and Australian adolescents. Child and Adolescent Psychiatry and Mental Health, 4 , 1–10.

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 , 81–94.

Rideout, V. J., Roberts, D. F., & Foehr, U. G. (2005). Generation M: Media in the lives of 8-18-year-olds: Executive summary . Henry J. Kaiser Family Foundation.

Rosen, L. D. (2007). Me, Myspace, and I: Parenting the net generation . Palgrave Macmillan.

Sahin, M. (2010). Teachers’ perceptions of bullying in high schools: A Turkish study. Social Behavior and Personality, 38 , 127–142.

Sevcikova, A., Machackova, H., Wright, M. F., Dedkova, L., & Cerna, A. (2015). Social support seeking in relation to parental attachment and peer relationships among victims of cyberbullying. Australian Journal of Guidance and Counselling, 15 , 1–13. https://doi.org/10.1017/jgc.2015.1

Shapka, J. D., & Law, D. M. (2013). Does one size fit all? Ethnic differences in parenting behaviors and motivations for adolescent engagement in cyberbullying. Journal of Youth and Adolescence, 42 , 723–738.

Shariff, S., & Hoff, D. L. (2007). Cyber bullying: Clarifying legal boundaries for school supervision in cyberspace. International Journal of Cyber Criminology, 1 , 76–118.

Sijtsema, J. J., Ashwin, R. J., Simona, C. S., & Gina, G. (2014). Friendship selection and influence in bullying and defending. Effects of moral disengagement. Developmental Psychology, 50 (8), 2093–2104.

Sjurso, I. R., Fandream, H., & Roland, E. (2016). Emotional problems in traditional and cyber victimization. Journal of School Violence, 15 (1), 114–131.

Smith, P. K., Mahdavi, J., Carvalho, M., Fisher, S., Russell, S., & Tippett, N. (2008). Cyberbullying: Its nature and impact in secondary school pupils. Journal of Child Psychology and Psychiatry, 49 , 376–385.

Smith, P. K., Del Barrio, C., & Tokunaga, R. S. (2013). Definitions of bullying and cyberbullying: How useful are the terms? In S. Bauman, D. Cross, & J. Walker (Eds.), Principles of cyberbullying research: Definitions, measures, methodology (pp. 26–40). Routledge.

Sourander, A., Brunstein, A., Ikonen, M., Lindroos, J., Luntamo, T., Koskelainen, M., Ristkari, T., & Helenius, H. (2010). Psychosocial risk factors associated with cyberbullying among adolescents: A population-based study. Archives of General Psychiatry, 67 , 720–728.

Stoll, L. C., & Block, R. (2015). Intersectionality and cyberbullying: A study of cybervictimization in a Midwestern high school. Computers in Human Behavior, 52 , 387–391.

Strohmeier, D., Aoyama, I., Gradinger, P., & Toda, Y. (2013). Cybervictimization and cyberaggression in Eastern and Western countries: Challenges of constructing a cross-cultural appropriate scale. In S. Bauman, D. Cross, & J. L. Walker (Eds.), Principles of cyberbullying research: Definitions, measures, and methodology (pp. 202–221). Routledge.

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

Tangen, D., & Campbell, M. (2010). Cyberbullying prevention: One primary school’s approach. Australian Journal of Guidance and Counselling, 20 , 225–234.

Toledano, S., Werch, B. L., & Wiens, B. A. (2015). Domain-specific self-concept in relation to traditional and cyber peer aggression. Journal of School Violence, 14 (4), 405–423.

Totura, C. M. W., MacKinnon-Lewis, C., Gesten, E. L., Gadd, R., Divine, K. P., Dunham, S., & Kamboukos, D. (2009). Bullying and victimization among boys and girls in middle school: The influence of perceived family and school contexts. The Journal of Early Adolescence, 29 , 571–609.

Wade, A., & Beran, T. (2011). Cyberbullying: The new era of bullying. Canadian Journal of School Psychology, 26 , 44–61.

Williams, K. R., & Guerra, N. G. (2007). Prevalence and predictors of internet bullying. Journal of Adolescent Health, 41 , 14–21. https://doi.org/10.1016/j.jadohealth.2007.08.018

Wong, D. S., Chan, H. C. O., & Cheng, C. H. (2014). Cyberbullying perpetration and victimization among adolescents in Hong Kong. Children and Youth Services Review, 36 , 133–140.

Wright, M. F. (2013). The relationship between young adults’ beliefs about anonymity and subsequent cyber aggression. Cyberpsychology, Behavior, and Social Networking, 16 , 858–862.

Wright, M. F. (2015). Cyber victimization and perceived stress: Linkages to late adolescents’ cyber aggression and psychological functioning. Youth & Society, 47 (6), 789–810.

Wright, M. F. (2014a). Predictors of anonymous cyber aggression: The role of adolescents’ beliefs about anonymity, aggression, and the permanency of digital content. Cyberpsychology, Behavior, and Social Networking, 17 , 431–438.

Wright, M. F. (2014b). Longitudinal investigation of the associations between adolescents’ popularity and cyber social behaviors. Journal of School Violence, 13 , 291–314.

Wright, M. F. (2015). Adolescents’ cyber aggression perpetration and cyber victimization: The longitudinal associations with school functioning. Social Psychology of Education, 18 (4), 653–666.

Wright, M. F., & Li, Y. (2012). Kicking the digital dog: A longitudinal investigation of young adults’ victimization and cyber-displaced aggression. Cyberpsychology, Behavior, and Social Networking, 15 , 448–454.

Wright, M. F., & Li, Y. (2013a). Normative beliefs about aggression and cyber aggression among young adults: A longitudinal investigation. Aggressive Behavior, 39 , 161–170.

Wright, M. F., & Li, Y. (2013b). The association between cyber victimization and subsequent cyber aggression: The moderating effect of peer rejection. Journal of Youth and Adolescence, 42 , 662–674.

Wright, M. F., Kamble, S., Lei, K., Li, Z., Aoyama, I., & Shruti, S. (2015). Peer attachment and cyberbullying involvement among Chinese, Indian, and Japanese adolescents. Societies, 5 , 339–353.

Ybarra, M. L., & Mitchell, K. J. (2004). Online aggressor/targets, aggressors, and targets: A comparison of associated youth characteristics. Journal of Child Psychology and Psychiatry, 45 , 1308–1316.

Ybarra, M. L., Diener-West, M., & Leaf, P. (2007). Examining the overlap in internet harassment and school bullying: Implications for school intervention. Journal of Adolescent Health, 1 , 42–50.

Yilmaz, H. (2011). Cyberbullying in Turkish middle schools: An exploratory study. School Psychology International, 32 (6), 645–654.

Yousef, W. S. M., & Bellamy, A. (2015). The impact of cyberbullying on the self-esteem and academic functioning of Arab American middle and high school students. Electronic Journal of Research in Educational Psychology, 23 (3), 463–482.

Zhou, Z., Tang, H., Tian, Y., Wei, H., Zhang, F., & Morrison, C. M. (2013). Cyberbullying and its risk factors among Chinese high school students. School Psychology International, 34 , 630–647.

Key Terms & Definitions

Anonymity: The quality of being unknown or unacknowledged.

Anxiety: A mental health disorder which includes symptoms of worry, anxiety, and/or fear that are intense enough to disrupt one’s daily activities.

Collectivism: A cultural value that stressed the importance of the group over individual goals and cohesion within social groups.

Cyberbullying: Children’s and adolescents’ usage of electronic technologies to hostilely and intentionally harass, embarrass, and intimidate others.

Empathy: The ability to understand or feel what another person is experiencing or feeling.

Externalizing difficulties: Includes children’s and adolescents’ failure to control their behaviors.

Individualism: The belief that each person is more important than the needs of the whole group or society.

Loneliness: An unpleasant emotional response to isolation or lack of companionship.

Normative belief: Beliefs about the acceptability and tolerability of a behavior.

Parental mediation and monitoring: The strategies that parents use to manage the relationship between their children and media.

Parenting style:The standard strategies that parents use in their child rearing.

Peer attachment: The internalization of the knowledge that their peers will be available and responsive.

Peer contagion: The transmission or transfer of deviant behavior from one adolescent to another.

Provictim attitudes: The belief that bullying is unacceptable and that defending victims is valuable.

Social exclusion: The process involving individuals or groups of people block or deny someone from the group.

Traditional face-to-face bullying: The use of strength or influence to intimidate or physically harm someone.

Additional Reading

Bauman, S. (2011). Cyberbullying: What counselors need to know . American Counseling Association.

Bauman, S., Cross, D., & Walker, J. (2013). Principles of cyberbullying research: Definitions, measures, and methodology . Routledge.

Hinduja, S., & Patchin, J. W. (2015). Bullying beyond the schoolyard: Preventing and responding to cyberbullying . Sage Publications.

Li, Q., Cross, D., & Smith, P. K. (2012). Cyberbullying in the global playground . Blackwell Publishing.

Book Google Scholar

Menesini, E., & Spiel, C. (2012). Cyberbullying: Development, consequences, risk and protective factors . Psychology Press.

Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26 , 277–287.

Wright, M. F. (2016). A social-ecological approach to cyberbullying . NOVA Publisher.

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Chapter 5: Going Beyond Cyberbullying: Adolescent Online Safety and Digital Risks

Anthony T. Pinter; Arup Kumar Ghosh; and Pamela J. Wisniewski

In this chapter, we cover the broader research area of digital risks and online safety. We discuss three primary types of risks that adolescents frequently navigate in digitally mediated environments that extend beyond cyberbullying – 1) Sexual Solicitations and Risky Sexual Behavior , 2) Exposure to Explicit Content , and 3) Information Breaches and Privacy Violations . We discuss the competing perspectives around how to approach adolescent online risks. We also discuss how those perspectives tend to lead to abstinence-only versus resilience-based frameworks of addressing adolescent online safety. We close by highlighting the Western-centric nature of existing work and the need for more work addressing Eastern cultures. This includes Indian contexts to better understand how the existing work applies to and may differ to Indian-based researchers, educators, and policymakers.

Adolescent internet use has substantially grown across the world, particularly in developing nations. In Western contexts, approximately 95% of teenagers in the United States (U.S.) have access to a smartphone. 45% of them are online ‘almost constantly.’ [1] Adolescent internet access and use in Eastern contexts, and particularly in India, has also grown significantly in recent years. A 2020 CRY study [2] surveyed adolescents in Delhi-NCR and found that 93% of Indian adolescents had internet access at home, and 54% owned mobile devices. Half of the survey respondents had at least two internet-enabled devices. Social media usage is also prevalent among teens in the U.S. with some differences related to gender and/or ethnicity.

With the increased accessibility of the internet during the mid-to-late 2000s, researchers turned their attention to adolescents. They focused on understanding how adolescents were using the internet and the challenges that youth encounter online. While online harassment and cyberbullying have been at the forefront of adolescent online safety research, this chapter highlights and synthesizes research related to the three additional online risk types relevant to teens: 1) Sexual Solicitations and Risky Sexual Behavior , 2) Exposure to Explicit Content , and 3) Information Breaches and Privacy Violations . Accordingly, we offer an overview of work centered on these risks to better contextualize cyberbullying as a subject of study. The study should be such that it is important but does not stand alone within the field of adolescent online safety. We introduce four risk types and summarize relevant research on each topic.

Further, we highlight a trend towards a heavy prevalence of work focused on “abstinence-based” approaches of increasing parental control. We also discuss relational processes focused on the parent-teen relationship, to shield youth from experiencing online risks, [3] rather than more individualistic or resilience-based approaches. Resilience-based approaches emphasize youth self-regulation as an alternative strength-based approach that helps youth overcome the negative effects of online risk exposure and benefit from the opportunities the internet has to offer. [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] We compare and contrast these two different perspectives within the adolescent online safety literature. We also acknowledge that the individualistic and autonomy-based approach to adolescent online safety promoted in Westernized contexts may or may not be generalizable to Eastern cultures. In Eastern culture collectivism and authoritarian parenting styles are more common. [13] We close this chapter with a discussion of work related to digital safety in Western vs. Eastern contexts to highlight the overabundance of research being conducted in Western contexts and the need for more work that focuses on the lived experiences of Indian youth.

ADOLESCENT ONLINE SAFETY: RISKS AND PROTECTIVE FACTORS

A common theme in online safety literature has been to identify the factors that put adolescents at risk versus the protective factors that either mitigate exposure to online risks or the negative outcome associated with risk exposure. Therefore, we provide a brief definition of each digital risk posed to youth. We then discuss the risk and protective factors that have been identified in the literature for each risk type. Protective factors may occur at varying levels of the ecological model, ranging from the individual, relational, interactional, community, or societal levels.

ONLINE SEXUAL SOLICITATIONS AND SEXUAL RISK BEHAVIOR

Online sexual predation of youth is defined as unwanted sexual solicitations from others (regardless of age) or any solicitations of a sexual nature made by adults through internet-enabled technologies. [14] Meanwhile, risky online sexual behaviors involve youth engaging in technology-mediated sexual exchanges, such as sex talk, sharing sexual imagery, and meeting online contacts for offline sexual encounters. [15] , [16] Over half of youth in the U.S. (ages 10 to 17) have received at least one online sexual solicitation in the past year. [17] Meanwhile, 15% of teens reported receiving pornographic images via text message (“sexting”). 4% admitted sending such messages to others via their mobile devices. [18] Many news outlets have reported the increasing trend of sexting among Indian youth although no formal research studies have been conducted. [19] In one survey study, researchers found more than half of young adult respondents sent sexually explicit text messages to their friends. [20] Researchers have identified several factors that contribute to an adolescent’s likelihood of experiencing sexual solicitation or related risk exposures. The two largest risk factors were – (1) gender (with girls being more likely to experience online sexual solicitations) [21] , [22] , [23] , [24] , [25] and (2) frequently using the internet, [26] , [27] , [28] , [29] , [30] especially to access pornographic material . [31] Meanwhile, the line between offline and online sexual predation and abuse is blurred as many sex offenders who know their victims in person, also communicate with them online. [32]

Teens between the ages of 12 and 15, racial minorities, and girls are the most “at-risk” of being solicited and engaging in risky sexual behaviors online. [33] , [34] , [35] , [36] This also includes people who have histories of neglect, abuse, family instability, lack of parental involvement, emotional, behavioral, or cognitive problems. This risk exposure may lead to an increased likelihood of offline sexual encounters. [37] , [38] These can result in physical harm, teen pregnancy, sexual transmitted diseases, and in extreme cases, sexual abuse [39] , [40] , [41] or sex trafficking. [42] , [43] Both offline and online sexual abuse can negatively impact youths’ academic, cognitive, emotional, and psychological development. It has been associated with increased cyber-victimization, drug abuse, suicide, and death. [44] , [45] , [46]

Whittle et al.’s [47] comprehensive review of the online sexual grooming literature synthesized risk factors ( e.g. , gender, age, poor family relationships, etc. ) that make some youth more vulnerable to sexual predation risks than others. This work identified parental involvement as the primary protective factor against online sexual risks. This focus on parental mediation as a means of protecting teens from online risks is consistent with the broader literature on adolescent online safety. [48] , [49] , [50] , [51] In other words, researchers have found that teens who are most protected from online sexual solicitations had parents who actively mediated their internet use. [52] , [53] Teens were also protected through caution, including the fear of being punished or getting in trouble was often enough to significantly reduce the likelihood of being exposed to online sexual risks. [54]

To date, most interventions for preventing online sexual predation of at-risk youth have targeted understanding, identifying, and comprehending online sex predators [55] , [56] , [57] , [58] , [59] , rather than preventing youth from becoming victims. These prevention initiatives often occur at the societal or community level involving child protection and law enforcement organizations. As such, research in this domain focuses on victimized youth or individuals who have already suffered the consequences of sexual abuse. [60] , [61] , [62] However, Razi et al. [63] recently conducted an analysis of 4,180 posts made by teens (ages 12-17) on an online peer support mental health forum to understand what and how adolescents talk about their online sexual interactions. The researchers found that youth used the platform to seek support (83%), connect with others (15%), and give advice (5%) about sexting, their sexual orientation, sexual abuse, and explicit content. Thus, peer support, even from strangers, may also be an important protective factor. At the relational level of the ecological framework, this support can help teens navigate how to handle unwanted sexual solicitations and risky situations online.

EXPOSURE TO INAPPROPRIATE AND EXPLICIT CONTENT

The term “explicit content” covers a wide range of inappropriate online materials. This includes but is not limited to pornographic, violent, gruesome, or hateful content, as well as content that promotes harmful behaviors such as self-harm or eating disorders. [64] , [65] , [66] , [67] Work focused on explicit content exposure has identified two types of exposure: willful and accidental exposures. This means adolescents may intentionally seek out inappropriate content online, but some may be accidentally exposed. [68] According to the Youth Internet Safety Survey, [69] about a quarter of youth in the U.S. had been exposed to unwanted pornography. A multinational study of youth in the U.S., Finland, and Germany found that 17% of the youth had been exposed to online content involving eating disorders, 11% to self-injury content, and 8% to suicide. [70] A 2020 IGPP survey [71] found nearly 50% of the Indian youth respondents accepted to have watched online pornographic content. 40% recognized to know people who have watched pornographic content on the internet. Yet, a U.S. diary study of adolescents (ages 13-17) [72] found that teens reported being exposed to explicit content four times more often than they experienced cyberbullying, sexual solicitations, or information breaches online. The majority of the time exposure was accidental.

Even though exposure may be accidental, researchers have found a negative correlation between adolescents’ repeated viewing of explicit content and several negative outcomes. These negative outcomes include a link between pornography and committing dating violence [73] , [74] , acts of digital self-harm with increased non-suicidal self-harm and suicidal ideation, [75] and violent content embedded within video games linked to aggressive behavior. [76] However, some media scholars [77] , [78] , [79] argue that the negative effects of explicit content exposure on youth are largely over-claimed or biased, and therefore, should not be generalized.

The risk factors that make some youth more susceptible to explicit content exposure vary based on the type of content. For instance, male teens are more likely to seek out online pornography than females. The majority of teens who seek out sexual images online are 14 years of age or older. [80] This research suggests that concerns about younger children’s exposure to online pornography may be overstated. It also suggests that adolescence is a developmentally appropriate time to become curious about sex. Therefore, some researchers have encouraged making a distinction between problematic ( e.g. , compulsive or addictive use) and non-problematic pornography use. This distinction is especially needed among vulnerable youth populations, such as lesbian, gay, bisexual, transgender, and queer (LGBTQ) adolescents. Such communities may use such materials to learn about sexuality and develop their sexual identities. [81] Other studies found that female youth are more likely to see online content regarding eating disorders, while males are more likely to view violent, pro-self-harm, and pro-suicide content. [82]

While exposure to explicit content is quite prevalent among adolescent youth, the protective factors against such exposure are few. For instance, reducing the frequency of internet use is detrimental due to hindering the positive opportunities for online engagement. [83] , [84] Some researchers have found that filtering and blocking software can be effective. [85] For instance, Ybarra, et al. found that pop-up or spam blockers reduced the chances of teens being exposed to unwanted sexual material by 59%. They also found that filtering and monitoring software further reduced the chance of this risk exposure occurring by 65%. [86] Yet, others have found that such parental control software may be more appropriate for younger children [87] as adolescents resent restrictive parenting practices that hinder their desire for autonomy. [88] Parental control software has been shown to be ineffective, and even damaging, to the trust relationship between parents and teens. [89] , [90] , [91] , [92] Additionally, there is little evidence that these technologies actually keep teens safe online or teach them to effectively manage online risks. [93] Active mediation and instructive co-viewing is situation where a parent is aware of the online activities of their children and openly discusses inappropriate content in a non-judgmental way. It may be the best approach to support adolescents when exposed to explicit content online. [94] This protective strategy would occur at the relational and individual levels of the socio-ecological framework with parents directly supporting their children’s online experiences.

INFORMATION BREACHES AND PRIVACY VIOLATIONS

Information breaches or privacy violations involve the inappropriate sharing of sensitive information ( e.g. , account credentials or location information) online by the youth themselves or by others without the teen’s permission. [95] , [96] , [97] , [98] The online world creates a wide variety of options for collecting, processing, and distributing users’ personal information. Therefore, information privacy has been the target of considerable controversy [99] and research. [100] Yet, beyond the Child Online Privacy Protection Act, no existing law in the U.S. protects the online information privacy of teenagers. making them more vulnerable to information breaches and privacy violations. [101] The rapid emergence of social networking sites, such as Facebook, Instagram, and Snapchat are rife with opportunities for teens to reveal personal information. [102] , [103] As a result, teens share more personal information and still report relatively low levels of privacy concern. [104] In contrast, 81% of their parents are “somewhat” to “very” concerned about their teens’ online privacy. [105]

In examining factors that lead to information breaches and privacy violations, several predictive factors have been identified: frequency of internet use [106] , [107] , internet skill [108] , [109] , [110] , and privacy concern. [111] , [112] In other words, teens who use the internet more often, do more things online. But they lack the skills to protect themselves and are less concerned about their online privacy, encounter more information breaches. Other factors have been noted to either increase or decrease the likelihood of exposure to this risk type. From a socio-economic standpoint, adolescents who come from more affluent backgrounds are more likely to experience higher rates of privacy violations. [113] Perhaps connected with the frequency of use, adolescents from wealthier backgrounds may have more readily available Internet access in their homes. Perhaps they have internet access even in spaces that are more private from parents ( i.e. , spaces that are harder for parents to actively monitor, like adolescents’ bedrooms). However, other aspects of adolescents’ lives offer forms of protection from this type of risk exposure. For example, adolescents who are in a romantic relationship are less likely to experience information breaches. [114] Given that information privacy often co-occurs with or results from exposure to other risk types – particularly sexual solicitations. Being in a relationship may preclude teens from seeking out the types of content or connections online that result in information and privacy breaches.

Meanwhile, there have been mixed findings regarding how parents can mitigate these online risks. One study found that parental restrictions against giving out personal information online are associated with a higher likelihood that teens disclose such personal information. [115] Another study [116] confirmed that parental mediation was not significantly related to tweens’ (ages 9 – 12) willingness to disclose personal information online. The larger the discrepancy between parental and tween perceptions of online restrictive mediation, the more willing tweens were to make online disclosures. A study by Wisniewski et al. [117] found that direct intervention by parents was associated with teens making fewer online disclosures. However, active mediation through talking with teens, searching teens’ information, and responding directly to teens’ online posts was more effective in helping teach teens how to take appropriate risk-coping measures. The relationships between parenting practices and teen social media privacy behaviors are illustrated in Figure 7.

Boxes and lines to illustrate relationships

This research suggests that preventative and restrictive parenting practices may reduce teens’ overall information disclosures. But this can also limit their opportunities for engaging with others online in beneficial and meaningful ways. Therefore, taking a dual approach of some direct intervention combined with active mediation may be the best approach to help teens navigate information privacy risks. At the societal level, legislation, such as the Children’s Online Privacy Protection Act (COPPA) in the United States, and the General Data Protection Regulation (GDPR) in the European Union provide additional privacy protection for young internet users. However, most protective factors identified in the literature remain at the relational ( i.e. , parent-teen) and individual levels of the ecological framework.

Now that we have summarized some of the risk and protective factors that are associated with these three types of online risks, we now discuss two different approaches to promoting adolescent online safety.

ABSTINENCE-ONLY VERSUS RESILIENCE-BASED APPROACHES

Research has identified the risk and protective factors associated with the three risk types previously discussed. But less attention has been given to designing effective interventions to prevent exposure or mitigate the consequences of exposure, [118] or helping teens to be resilient in spite of encountering online risks. [119] Pinter et al. [120] conducted a comprehensive review of the adolescent online safety literature and concluded that research has traditionally advanced an “abstinence-based” framework of adolescent online safety and risk exposure. 69% of the studies reviewed focused on minimizing or eradicating online risk exposure, rather than teaching youth to effectively cope with these risks once they occur. [121] Researchers from EU Kids Online were among the first to argue that adolescent exposure to online risks does not necessarily equate to harm. [122] , [123] They found that youth who reported having more psychological problems and/or lower self-efficacy tended to become more bothered when experiencing these online risks while other teens remained unbothered. [124]

Wisniewski et al. [125] were one of the first to apply the adolescent resilience framework, at the individual-level, to teen risky behaviors that are linked to internet use. Resilience-based approaches differ from risk-averse approaches by “focusing on the assets and resources that enable adolescents to overcome the negative effects of risk exposure”, [126] rather than trying to limit exposure to risk. Another way of understanding the contrast is that the resilience perspective leads to a focus on teen strengths rather than their deficits. Wisniewski et al.’s [127] work showed evidence that resilience is a key factor in protecting teens from experiencing online risks, even when teens exhibit high levels of internet addiction. Resilience also neutralizes the negative psychological effects associated with internet addiction and online risk exposure. In Wisniewski et al.’s subsequent work, [128] they found that teens can potentially benefit from experiencing lower-risk online situations. This allows them to develop crucial interpersonal skills, such as boundary setting, conflict resolution, and empathy. Developmental psychology reminds us that some level of risk-taking and experiential learning is necessary for normal aspects of adolescent developmental growth. [129] Thus, we need to strike a healthy balance between allowing teens to learn how to safely engage online through experiencing some risk and protecting them from high-risk situations.

We emphasize the importance of designing solutions that foster teen resilience and strength building at the individual level, as opposed to solutions targeted toward parents ( i.e. , at the relational level) that often focus on restriction and risk prevention. Similarly, Hartikainen et al. [130] found that building parent-teen trust led to better communication. It in turn created more opportunities for positive outcomes when compared to more restrictive, control-based approaches. [131] boyd agreed, arguing that abstinence or control-based approaches prevent adolescents from learning self-protection or coping skills. [132] For instance, teen resilience can be promoted directly through web-based educational or counseling programs that help build resilience. [133] We can also promote this through interface designs that empower teens to take protective measures upon encountering online risks. For example, Facebook provides a “Family Safety Center” that offers tips for teens to develop better online safety practices. [134] Several researchers have called for new online safety solutions that move away from parental control toward promoting positive parent-teen relationships and teen self-regulation of their online behaviors ( e.g. , [135] , [136] , [137] , [138] ). Yet, few, if any, technological interventions for adolescent online safety have been developed to help teens self-regulate and manage online risks in a meaningful way. [139]

In the next section, we present a framework of Teen Online Safety Strategies (TOSS) that illustrates the tensions between promoting online safety from the perspectives of parental control versus teen self-regulation.

PARENTAL CONTROL VERSUS TEEN SELF-REGULATION STRATEGIES

The Teen Online Safety Strategies (TOSS) framework, [140] shown in Figure 8, is built upon the rationale that adolescent online safety can be framed as an outcome of effective parenting. It assumes that parents directly influence or control teens’ exposure to online risks. [141] , [142] , [143] , [144] This explains tensions between parental control and teen self-regulation when it comes to teens’ online behaviors, their desire for privacy, and online safety. [145] , [146] , [147] , [148] In the TOSS framework, parental control strategies include monitoring (passive surveillance of a teen’s online activities), restriction (placing rules and limits on a teen’s online activities), and active mediation (discussion between parents and teens regarding online activities). These strategies were based primarily on Valkenburg et al.’s [149] foundational work, which created scales assessing three styles of parental television mediation. They have since widely been adapted for use in the context of online parental mediation. [150] , [151] , [152] , [153] The framework also positions teen self-regulation strategies that work as resiliency factors and protect teens from online risks. Such resilience-based factors align with the individual-level processes of the ecological model of cyberbullying and online risks. Specifically, three of its key components – self-awareness (awareness of one’s own motivations and actions through self-observation), impulse control (inhibiting one’s short-term desires in favor of long-term consequences), and risk-coping (managing a negative event once it has occurred) – acknowledge the importance of and encourage teen self-regulation.

Wisniewski, Ghosh, and their co-authors [154] applied the TOSS framework to better understand the commercially available technical offerings that support adolescent online safety, and what teens thought about these applications. They found that an overwhelming majority of mobile app features (89%) supported parental control through monitoring (44%) and restriction (43%). Not much support was seen in these apps to facilitate parents’ active mediation or support any form of teen self-regulation. Further, many of the apps were extremely privacy invasive. They provided parents granular access to monitor and restrict teens’ intimate online interactions with others. This includes their browsing history, the apps installed on their phones, and the text messages teens sent and received. Teen risk coping was minimally supported by an “SOS feature” that teens could use to get help from an adult.

In a follow-up study, Ghosh, Wisniewski, and their co-authors [155] analyzed 736 reviews of these parental control apps that were publicly posted by teens and younger children on Google Play. They found that the majority (79%) of children overwhelmingly disliked the apps, while a small minority (21%) of reviews saw benefits to the apps. Children rated the apps significantly lower than parents. Teens, and even younger children, strongly disliked these apps because they felt that they were overly restrictive and invasive of their personal privacy. They negatively impacted their relationships with their parents. A takeaway from this research was that, as researchers and designers, we should consider listening to what teens have to say about the technologies designed to keep them safe online. We should conceptualize new solutions that engage parents and respect the challenges teens face growing up in a networked world.

Next, we discuss whether the resilience-based approaches aimed at promoting teen self-regulation are relevant and applicable to Indian youth and other Eastern contexts.

CROSS-CULTURAL COMPARISONS OF ADOLESCENT ONLINE SAFETY AND RISKS BETWEEN THE U.S. AND INDIA

According to Pinter et al.’s review of the adolescent online safety literature, [156] the majority (44%) of the studies originated from the U.S. [157] , [158] , [159] , [160] The second and third most prevalent countries of origin were the Netherlands and Great Britain., representing 9% and 8% of the articles, respectively. Canada had the fourth-highest representation in the sample with 5% of the articles, followed by Spain (3%) and Korea (3%). Only 5% of the studies in their sample studied adolescent online safety and risks multi-nationally. Of these, one compared adolescents in Canada and China, [161] another U.S. and Finland, [162] and the rest studied adolescents from multiple European countries. [163] , [164] , [165] A number of the multi-national studies across Europe were in conjunction with the initiative launched by EU Kids Online, a multinational research network. [166] , [167] , [168] Meanwhile, there is a dearth of research related to adolescent online safety and risks specifically from India.

With differing cultural norms, the Western-centric research on adolescent online safety may not be as applicable in other contexts, such as sub-Asian locales like India. Different cultures are likely to approach risk exposure, prevention, and coping differently, and a disparate focus on one nation limits research’s ability to understand adolescents’ risk experiences. It is not the most effective way for parents to intervene. For instance, parenting styles vary drastically across different cultures. Indian mothers in America are more likely to use authoritative parenting styles (an approach to child-rearing that combines warmth, sensitivity, and the setting of limits). Parents residing in India are more inclined to use authoritarian parenting styles (characterized by high demands and low responsiveness). [169] While authoritative parenting styles have been shown to have positive youth outcomes within Indian families, [170] more authoritarian parenting styles may be more effective within different cultures and ethnicities ( e.g. , [171] , [172] ). Therefore, families from Eastern cultures need to be better represented in research. For instance, Asian adolescents have recently come into the public eye as particularly susceptible to internet addiction. [173] , [174] Further, countries that are more collective than individualistic in culture may rely more heavily on relational, interactional, community, and societal level approaches when taking an ecological approach to risk prevention. They may focus less on individualistic approaches, such as fostering teen resilience and self-regulation. To date, this trend has been supported in the literature.

Recently, research on adolescent technology use has emerged from Eastern contexts. Garg and Sengupta [175] conducted a comparative study between U.S. and Asian Indian youth. They found both differences and similarities in parents’ attitudes about digital technology use. For example, Asian Indian families took more authoritarian approaches than White families when it came to deciding whether children below the age of 13 could have their own mobile phones. Parents across demographics allowed children above the age of 13 to have their own devices or permitted them to use the common family device or their parents’ devices. Both White and Indian children between ages 14-17 had at least one social media account. A few Indian parents created online profiles of their young children so that they could co-use and help maintain the bonds between grandparents (staying in India) and grandchildren. Working parents, irrespective of their race, did have concerns about the content children accessed online. White middle-class parents tried to enforce restrictions on children’s smartphone usage based on context and in a way that supports child self-regulation and autonomy. Their Indian counterparts were more rules dependent. As there are both differences and similarities in U.S. and Indian parents’ attitudes about digital technology use, it may be possible to apply some of the western approaches to Indian contexts. But it is not possible to be so sure without conducting more research work that focuses on the lived experiences of Indian youth. Additionally, more research needs to be done that extends beyond the parent-teen relationship to study interactional, community, and societal level factors that could promote the online safety of Indian youth more collectively.

With the growing concern in other contexts such as Indian adolescents, incorporating more resilience-based approaches may be beneficial to researchers, practitioners, and policymakers in protecting adolescents. But this should be done without impeding healthy growth and self-regulation behaviors.

In the next chapter we discuss the research and policy implications in India. Chapter Six addresses the more distal societal level factors identified by the model. We summarize how the current knowledge can be applied in India across multiple stakeholder groups, including public policy, law enforcement, school administration, health care providers, community-based organizations, tech industry, and research institutes. Also, we highlight the key gaps in knowledge to guide future research.

In this chapter, we introduce the broader field of adolescent online safety research beyond that of cyberbullying. We characterize four types of risks that online safety researchers have identified. We further discuss the prevalent framing of adolescent online safety as resulting from abstinence or preventative approaches instead of approaches encouraging resilience. We contrast that approach with more nascent framings of safety as being resilient in nature – encouraging teens to evaluate and make decisions for themselves and then designing and implementing approaches meant to encourage coping. Regardless of the approach taken, cultural norms and expectations undoubtedly play a role in how these framings are researched and put into action. However, the state of research in Indian and other Eastern contexts is severely lacking in comparison to Western contexts. The disparity in existing available work between Eastern and Western contexts provides ample opportunities for researchers to address. It is an issue that is timely as Indian adolescents access the Internet as much as (if not more than) their American counterparts. We argue that while cyberbullying is prevalent, there are other risks to be considered when mobilizing to address the lack of work on digital safety in Indian contexts. So more holistic examinations of adolescents’ experiences online in India will benefit not only Indian contexts but the state of the research as a whole.

KEY TAKEAWAYS

Digital risk and online safety encompass more than just cyberbullying and online harassment. Each risk type has unique factors that contribute to an adolescent’s likelihood of experiencing that risk. However, common factors across all four risk types include age, gender, level of Internet efficacy, and frequency of Internet use.
There are two principal approaches to understanding adolescent risk and safety online – abstinence-based and resilience-based approaches. Abstinence-based approaches dominate existing research, focusing on preventing risk exposure entirely via control and regulation.
Resilience-based approaches focus on encouraging coping and growth in the aftermath of risk exposure and encouraging adolescent self-regulation.
Much of the existing work focuses on Western contexts, particularly the United States. With the growing concern in other contexts such as Indian adolescents, incorporating more resilience-based approaches may be beneficial to researchers, practitioners, and policymakers in protecting adolescents while not impeding healthy growth and self-regulation behaviors.
Anderson M, Jiang J. Teens, Social Media & Technology 2018 [Internet]. Pew Research Center: Internet, Science & Tech. 2018 [cited 2018 Jul 15]. Available from: http://www.pewinternet.org/2018/05/31/teens-social-media-technology-2018/ ↵
Child Rights and You (CRY). Online Safety and Internet Addiction (A Study Conducted Amongst Adolescents in Delhi-NCR). New Delhi; 2020. ↵
Shin W, Ismail N. Exploring the Role of Parents and Peers in Young Adolescents’ Risk Taking on Social Networking Sites. Cyberpsychology, Behavior, and Social Networking. 2014 Sep;17(9):578–83. ↵
Wisniewski P, Ghosh AK, Rosson MB, Xu H, Carroll JM. Parental Control vs. Teen Self-Regulation: Is there a middle ground for mobile online safety? Proceedings of the 20th ACM Conference on Computer Supported Cooperative Work & Social Computing. 2017; ↵
Ghosh AK, Badillo-Urquiola K, Guha S, LaViola JJ, Wisniewski PJ. Safety vs. Surveillance: What Children Have to Say about Mobile Apps for Parental Control. In the Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI). 2018; ↵
Ghosh AK, Badillo-Urquiola K, Rosson MB, Xu H, Carroll J, Wisniewski P. A Matter of Control or Safety? Examining Parental Use of Technical Monitoring Apps on Teens’ Mobile Devices. In the Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI). 2018; ↵
Ghosh AK, Badillo-Urquiola K, Wisniewski P. Examining the Effects of Parenting Styles on Offline and Online Adolescent Peer Problems. In: Proceedings of the 2018 ACM Conference on Supporting Groupwork [Internet]. New York, NY, USA: Association for Computing Machinery; 2018 [cited 2020 Nov 7]. p. 150–3. (GROUP ’18). Available from: https://doi.org/10.1145/3148330.3154519 ↵
Ghosh AK, Badillo-Urquiola KA, Xu H, Rosson MB, Carroll JM, Wisniewski P. Examining Parents’ Technical Mediation of Teens’ Mobile Devices. In: Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing [Internet]. New York, NY, USA: ACM; 2017. p. 179–82. (CSCW ’17 Companion). Available from: http://doi.acm.org/10.1145/3022198.3026306 ↵
Ghosh AK. Taking a More Balanced Approach to Adolescent Mobile Safety. In: Proceedings of the 19th International Conference on Supporting Group Work [Internet]. New York, NY, USA: ACM; 2016. p. 495–8. (GROUP ’16). Available from: http://doi.acm.org/10.1145/2957276.2997025 ↵
Ghosh AK. Using a Value Sensitive Design Approach to Promote Adolescent Online Safety on Mobile Platforms. In: 2016 International Conference on Collaboration Technologies and Systems (CTS). 2016. p. 593–6. ↵
Ghosh AK, Wisniewski P. Understanding User Reviews of Adolescent Mobile Safety Apps: A Thematic Analysis. In: Proceedings of the 19th International Conference on Supporting Group Work [Internet]. New York, NY, USA: ACM; 2016 [cited 2017 Apr 26]. p. 417–20. (GROUP ’16). Available from: http://doi.acm.org/10.1145/2957276.2996283 ↵
Ghosh AK, Wisniewski PJ, Hughes CE. Circle of Trust: A New Approach to Mobile Online Safety for Families. In the Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI) [Internet]. 2020; Available from: https://dl.acm.org/doi/fullHtml/10.1145/3313831.3376747 ↵
Jambunathan S, Counselman K. Parenting Attitudes of Asian Indian Mothers Living in the United States and in India. Early Child Development and Care. 2002 Dec 1;172(6):657–62. ↵
Jones LM, Mitchell KJ, Finkelhor D. Trends in Youth Internet Victimization: Findings From Three Youth Internet Safety Surveys 2000–2010. Journal of Adolescent Health. 2012 Feb 1;50(2):179–86. ↵
Jonsson LS, Priebe G, Bladh M, Svedin CG. Voluntary sexual exposure online among Swedish youth – social background, Internet behavior and psychosocial health. Computers in Human Behavior. 2014 Jan;30:181–90. ↵
Noll JG, Shenk CE, Barnes JE, Haralson KJ. Association of Maltreatment With High-Risk Internet Behaviors and Offline Encounters. Pediatrics. 2013 Feb 1;131(2):e510–7. ↵
Mitchell K, Jones L, Finkelhor D, Wolak J. Trends in Unwanted Online Experiences and Sexting : Final Report. Crimes Against Children Research Center [Internet]. 2014 Feb 1; Available from: http://scholars.unh.edu/ccrc/49 ↵
Amanda Lenhart. Teens and Sexting [Internet]. Pew Research Center: Internet, Science & Tech. 2009 [cited 2016 Jul 13]. Available from: http://www.pewinternet.org/2009/12/15/teens-and-sexting/ ↵
Sexting culture fast catching up with Indian teens – Times of India [Internet]. The Times of India. [cited 2021 Feb 25]. Available from: https://timesofindia.indiatimes.com/home/science/sexting-culture-fast-catching-up-with-indian-teens/articleshow/14684015.cms ↵
Indian women outdo men in sexting and filming sexual video content: Survey | India News – Times of India [Internet]. The Times of India. [cited 2021 Feb 25]. Available from: https://timesofindia.indiatimes.com/india/indian-women-outdo-men-in-sexting-and-filming-sexual-video-content-survey/articleshow/30172628.cms ↵
Livingstone S, Helsper EJ. Balancing opportunities and risks in teenagers’ use of the internet: the role of online skills and internet self-efficacy. New Media & Society. 2010 Mar 1;12(2):309–29. ↵
Livingstone S, Kirwil L, Ponte C, Staksrud E. In their own words: What bothers children online? European Journal of Communication. 2014;29(3):271–88. ↵
Helweg-Larsen K, Schütt N, Larsen HB. Predictors and protective factors for adolescent Internet victimization: results from a 2008 nationwide Danish youth survey: Adolescent internet victimization. Acta Paediatrica. 2012 May;101(5):533–9. ↵
Pedersen S. UK young adults’ safety awareness online – is it a ‘girl thing’? Journal of Youth Studies. 2013 May;16(3):404–19. ↵
Pujazon-Zazik MA, Manasse SM, Orrell-Valente JK. Adolescents’ Self-presentation on a Teen Dating Web Site: A Risk-Content Analysis. Journal of Adolescent Health. 2012 May;50(5):517–20. ↵
Ybarra ML, Mitchell KJ. How Risky Are Social Networking Sites? A Comparison of Places Online Where Youth Sexual Solicitation and Harassment Occurs. PEDIATRICS. 2008 Jan 28;121(2):e350–7. ↵
Rice E, Winetrobe H, Holloway IW, Montoya J, Plant A, Kordic T. Cell Phone Internet Access, Online Sexual Solicitation, Partner Seeking, and Sexual Risk Behavior Among Adolescents. Archives of Sexual Behavior. 2015 Apr;44(3):755–63. ↵
Blau I. Comparing online opportunities and risks among Israeli children and youth Hebrew and Arabic speakers. New Review of Hypermedia and Multimedia. 2014 Oct 2;20(4):281–99. ↵
Doornwaard SM, ter Bogt TFM, Reitz E, van den Eijnden RJJM. Sex-Related Online Behaviors, Perceived Peer Norms and Adolescents’ Experience with Sexual Behavior: Testing an Integrative Model. Zeeb H, editor. PLOS ONE. 2015 Jun 18;10(6):e0127787. ↵
Ybarra ML, Mitchell KJ, Korchmaros JD. National Trends in Exposure to and Experiences of Violence on the Internet Among Children. PEDIATRICS. 2011 Dec 1;128(6):e1376–86. ↵
Doornwaard SM, Bickham DS, Rich M, Vanwesenbeeck I, van den Eijnden RJJM, ter Bogt TFM. Sex-Related Online Behaviors and Adolescents’ Body and Sexual Self-Perceptions. PEDIATRICS. 2014 Dec 1;134(6):1103–10. ↵
Wolak J, Finkelhor D, Mitchell KJ, Ybarra ML. Online “predators” and Their Victims: Myths, Realities, and Implications for Prevention and Treatment. Psychology of Violence. 2010 Aug 1;1(S):13–35. ↵
Jonsson LS, Svedin CG, Hydén M. “Without the Internet, I never would have sold sex”: Young women selling sex online. Cyberpsychology: Journal of Psychosocial Research on Cyberspace [Internet]. 2014 Mar 1 [cited 2017 May 24];8(1). Available from: https://journals.muni.cz/cyberpsychology/article/view/4297 ↵
Whittle H, Hamilton-Giachritsis C, Beech A, Collings G. A review of young people’s vulnerabilities to online grooming. Aggression and Violent Behavior. 2013 Jan;18(1):135–46. ↵
Schulz A, Bergen E, Schuhmann P, Hoyer J, Santtila P. Online Sexual Solicitation of Minors: How Often and between Whom Does It Occur? Journal of Research in Crime and Delinquency. 2016 Mar 1;53(2):165–88. ↵
Dombrowski SC, LeMasney JW, Ahia CE, Dickson SA. Protecting Children From Online Sexual Predators: Technological, Psychoeducational, and Legal Considerations. Professional Psychology: Research and Practice. 2004 Feb;35(1):65–73. ↵
Slavtcheva-Petkova V, Nash VJ, Bulger M. Evidence on the extent of harms experienced by children as a result of online risks: implications for policy and research. Information, Communication & Society. 2015 Jan 2;18(1):48–62. ↵
Ibanez M. Virtual Red Light Districts: Detecting Covert Networks and Sex Trafficking Circuits in the U.S. ProQuest LLC; 2015. ↵
Tidball S, Zheng M, Creswell J. Buying Sex On-Line from Girls: NGO Representatives, Law Enforcement Officials, and Public Officials Speak out About Human Trafficking-A Qualitative Analysis. Gender Issues. 2016 Mar;33(1):53–68. ↵
Baumgartner SE, Valkenburg PM, Peter J. Unwanted online sexual solicitation and risky sexual online behavior across the lifespan. Journal of Applied Developmental Psychology. 2010 Nov;31(6):439–47. ↵
Black PJ, Wollis M, Woodworth M, Hancock JT. A linguistic analysis of grooming strategies of online child sex offenders: Implications for our understanding of predatory sexual behavior in an increasingly computer-mediated world. Child Abuse & Neglect. 2015 Jun;44:140–9. ↵
Murphy M, Bennett N, Kottke M. Development and Pilot Test of a Commercial Sexual Exploitation Prevention Tool: A Brief Report. Violence and Victims; New York. 2016;31(1):103–10. ↵
Anderson M. Parents, Teens and Digital Monitoring [Internet]. Pew Research Center: Internet, Science & Tech. 2016 [cited 2016 May 22]. Available from: http://www.pewinternet.org/2016/01/07/parents-teens-and-digital-monitoring/ ↵
Crossler R, Belanger F, Hiller J, Aggarwal P, Channakeshava K, Bian K, et al. Parents and the Internet: Privacy Awareness, Practices, and Control. In 2007. ↵
Eastin MS, Greenberg BS, Hofschire L. Parenting the Internet. Journal of Communication. 2006;56(3):486–504. ↵
Kirwil L. Parental Mediation Of Children’s Internet Use In Different European Countries. Journal of Children and Media. 2009 Nov 1;3(4):394–409. ↵
Bryce J, Fraser J. The role of disclosure of personal information in the evaluation of risk and trust in young peoples’ online interactions. Computers in Human Behavior. 2014 Jan;30:299–306. ↵
Staksrud E, Livingstone S. CHILDREN AND ONLINE RISK: Powerless victims or resourceful participants? Information, Communication & Society. 2009 Apr;12(3):364–87. ↵
Pater JA, Miller AD, Mynatt ED. This Digital Life: A Neighborhood-Based Study of Adolescents’ Lives Online. In ACM Press; 2015. p. 2305–14. ↵
Ebrahimi M, Suen CY, Ormandjieva O. Detecting predatory conversations in social media by deep Convolutional Neural Networks. Digital Investigation. 2016 Sep;18:33–49. ↵
Laorden C, Galan-Garcia P, Santos I, Sanz B, Nieves J, Bringas PG, et al. Negobot: Detecting paedophile activity with a conversational agent based on game theory. Logic Journal of IGPL. 2015 Feb 1;23(1):17–30. ↵
Martellozzo E. Policing online child sexual abuse – the British experience. European Journal of policing Studies. 2015 Oct 6;3(1):32–52. ↵
Wolak J, Finkelhor D. Are Crimes by Online Predators Different From Crimes by Sex Offenders Who Know Youth In-Person? Journal of Adolescent Health. 2013 Dec;53(6):736–41. ↵
Whittle HC, Hamilton-Giachritsis CE, Beech AR. “Under His Spell”: Victims’ Perspectives of Being Groomed Online. Social Sciences. 2014 Aug 12;3(3):404–26. ↵
Williams A. Child sexual victimisation: ethnographic stories of stranger and acquaintance grooming. Journal of Sexual Aggression. 2015 Mar;21(1):28–42. ↵
Razi A, Badillo-Urquiola K, Wisniewski PJ. Let’s Talk about Sext: How Adolescents Seek Support and Advice about Their Online Sexual Experiences. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems [Internet]. New York, NY, USA: Association for Computing Machinery; 2020 [cited 2020 Oct 20]. p. 1–13. (CHI ’20). Available from: https://doi.org/10.1145/3313831.3376400 ↵
Dowdell EB. Risky Internet Behaviors of Middle-School Students: Communication With Online Strangers and Offline Contact. CIN: Computers, Informatics, Nursing. 2011 Jun;29(6):352–9. ↵
Wells M, Mitchell KJ. How Do High-Risk Youth Use the Internet? Characteristics and Implications for Prevention. Child Maltreatment. 2008 Feb 25;13(3):227–34. ↵
Wisniewski P, Xu H, Rosson MB, Perkins DF, Carroll JM. Dear Diary: Teens Reflect on Their Weekly Online Risk Experiences. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems [Internet]. New York, NY, USA: ACM; 2016 [cited 2017 May 25]. p. 3919–30. (CHI ’16). Available from: http://doi.acm.org/10.1145/2858036.2858317 ↵
Oksanen A, Näsi M, Minkkinen J, Keipi T, Kaakinen M, Räsänen P. Young people who access harm-advocating online content: A four-country survey. Cyberpsychology: Journal of Psychosocial Research on Cyberspace [Internet]. 2016 Jul 1 [cited 2021 Feb 12];10(2). Available from: https://cyberpsychology.eu/article/view/6179 ↵
Bohra AS. Patterns of Internet Usage Among Youths In India [Internet]. Social Media Matters. [cited 2021 Feb 25]. Available from: https://www.socialmediamatters.in/patterns-of-internet-usage-among-youths-in-india ↵
Rostad WL, Gittins-Stone D, Huntington C, Rizzo CJ, Pearlman D, Orchowski L. The Association Between Exposure to Violent Pornography and Teen Dating Violence in Grade 10 High School Students. Arch Sex Behav. 2019 Oct 1;48(7):2137–47. ↵
Rodenhizer KAE, Edwards KM. The Impacts of Sexual Media Exposure on Adolescent and Emerging Adults’ Dating and Sexual Violence Attitudes and Behaviors: A Critical Review of the Literature. Trauma, Violence, & Abuse. 2019 Oct 1;20(4):439–52. ↵
Dyson MP, Hartling L, Shulhan J, Chisholm A, Milne A, Sundar P, et al. A Systematic Review of Social Media Use to Discuss and View Deliberate Self-Harm Acts. PLOS ONE. 2016 May 18;11(5):e0155813. ↵
Verheijen GP, Burk WJ, Stoltz SEMJ, Berg YHM van den, Cillessen AHN. Friendly fire: Longitudinal effects of exposure to violent video games on aggressive behavior in adolescent friendship dyads. Aggressive Behavior. 2018;44(3):257–67. ↵
Ferguson CJ, Wang JCK. Aggressive Video Games are Not a Risk Factor for Future Aggression in Youth: A Longitudinal Study. J Youth Adolescence. 2019 Aug 1;48(8):1439–51. ↵
Markey PM, Ferguson CJ. Moral Combat: Why the War on Violent Video Games Is Wrong. BenBella Books, Inc.; 2017. 218 p. ↵
Peter J, Valkenburg P. Adolescents’ exposure to sexually explicit material on the Internet. Communication Research. 2006;33(2):178–204. ↵
Ybarra ML, Mitchell KJ. Exposure to Internet Pornography among Children and Adolescents: A National Survey. CyberPsychology & Behavior. 2005 Oct 1;8(5):473–86. ↵
Bőthe B, Vaillancourt-Morel M-P, Bergeron S, Demetrovics Z. Problematic and Non-Problematic Pornography Use Among LGBTQ Adolescents: a Systematic Literature Review. Curr Addict Rep. 2019 Dec 1;6(4):478–94. ↵
Wisniewski P, Jia H, Wang N, Zheng S, Xu H, Rosson MB, et al. Resilience Mitigates the Negative Effects of Adolescent Internet Addiction and Online Risk Exposure. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems [Internet]. New York, NY, USA: ACM; 2015 [cited 2016 Sep 21]. p. 4029–38. (CHI ’15). Available from: http://doi.acm.org/10.1145/2702123.2702240 ↵
Wisniewski P, Jia H, Xu H, Rosson MB, Carroll JM. “Preventative” vs. “Reactive”: How Parental Mediation Influences Teens’ Social Media Privacy Behaviors. In ACM Press; 2015. p. 302–16. ↵
Mitchell KJ, Finkelhor D, Wolak J. Protecting youth online: Family use of filtering and blocking software. Child Abuse & Neglect. 2005 Jul 1;29(7):753–65. ↵
Ybarra ML, Finkelhor D, Mitchell KJ, Wolak J. Associations between blocking, monitoring, and filtering software on the home computer and youth-reported unwanted exposure to sexual material online. Child Abuse & Neglect. 2009 Dec;33(12):857–69. ↵
Duerager A, Livingstone S. How can parents support children’s internet safety? [Internet]. 2012. Available from: http://www.lse.ac.uk/media@lse/research/EUKidsOnline/EU%20Kids%20III/Reports/ParentalMediation.pdf ↵
Erickson LB, Wisniewski P, Xu H, Carroll JM, Rosson MB, Perkins DF. The boundaries between: Parental involvement in a teen’s online world. Journal of the Association for Information Science and Technology. 2015;n/a-n/a. ↵
Ghosh AK, Badillo-Urquiola K, Guha S, LaViola JJ Jr, Wisniewski PJ. Safety vs. Surveillance: What Children Have to Say about Mobile Apps for Parental Control. In: Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems. Montréal, Canada: ACM; 2018. ↵
Shin W, Ismail N. Exploring the role of parents and peers in young adolescents’ risk taking on social networking sites. Cyberpsychol Behav Soc Netw. 2014 Sep;17(9):578–83. ↵
Ghosh AK, Badillo-Urquiola K, Rosson MB, Xu H, Carroll JM, Wisniewski PJ. A Matter of Control or Safety?: Examining Parental Use of Technical Monitoring Apps on Teens’ Mobile Devices. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems [Internet]. New York, NY, USA: ACM; 2018 [cited 2018 May 28]. p. 194:1-194:14. (CHI ’18). Available from: http://doi.acm.org/10.1145/3173574.3173768 ↵
Wisniewski P, Xu H, Rosson MB, Carroll JM. Parents Just Don’t Understand: Why Teens Don’t Talk to Parents About Their Online Risk Experiences. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing [Internet]. New York, NY, USA: ACM; 2017 [cited 2017 May 25]. p. 523–40. (CSCW ’17). Available from: http://doi.acm.org/10.1145/2998181.2998236 ↵
Christofides E, Muise A, Desmarais S. Hey Mom, What’s on Your Facebook? Comparing Facebook Disclosure and Privacy in Adolescents and Adults. Social Psychological and Personality Science. 2012 Jan 1;3(1):48–54. ↵
Mesch GS, Beker G. Are Norms of Disclosure of Online and Offline Personal Information Associated with the Disclosure of Personal Information Online? Human Communication Research. 2010 Sep 16;36(4):570–92. ↵
Lwin M O, Stanaland AJS, Miyazaki AD. Protecting children’s privacy online: How parental mediation strategies affect website safeguard effectiveness. Journal of Retailing. 2008 Jun;84(2):205–17. ↵
Leung L, Lee PSN. The influences of information literacy, internet addiction and parenting styles on internet risks. New Media & Society. 2012 Feb 1;14(1):117–36. ↵
Lee S-J, Chae Y-G. Balancing Participation and Risks in Children’s Internet Use: The Role of Internet Literacy and Parental Mediation. Cyberpsychology, Behavior, and Social Networking. 2012 May;15(5):257–62. ↵
Forte A, Dickard M, Magee R, Agosto DE. What do teens ask their online social networks?: social search practices among high school students. In ACM Press; 2014. p. 28–37. ↵
Agosto DE, Abbas J. High school seniors’ social network and other ICT use preferences and concerns. Proceedings of the American Society for Information Science and Technology. 2010;47(1):1–10. ↵
Feng Y, Xie W. Teens’ concern for privacy when using social networking sites: An analysis of socialization agents and relationships with privacy-protecting behaviors. Computers in Human Behavior. 2014 Apr;33:153–62. ↵
Pinter AT, Wisniewski PJ, Xu H, Rosson MB, Caroll JM. Adolescent Online Safety: Moving Beyond Formative Evaluations to Designing Solutions for the Future. In: Proceedings of the 2017 Conference on Interaction Design and Children [Internet]. Stanford California USA: ACM; 2017 [cited 2020 Nov 4]. p. 352–7. Available from: https://dl.acm.org/doi/10.1145/3078072.3079722 ↵
Wisniewski P. The Privacy Paradox of Adolescent Online Safety: A Matter of Risk Prevention or Risk Resilience? IEEE Security & Privacy. 2018 Apr;16(2):86–90. ↵
Hartikainen H, Iivari N, Kinnula M. Should We Design for Control, Trust or Involvement?: A Discourses Survey about Children’s Online Safety. In: Proceedings of the The 15th International Conference on Interaction Design and Children – IDC ’16 [Internet]. Manchester, United Kingdom: ACM Press; 2016 [cited 2020 Nov 10]. p. 367–78. Available from: http://dl.acm.org/citation.cfm?doid=2930674.2930680 ↵
boyd danah. It’s Complicated: The Social Lives of Networked Teens. 1 edition. New Haven: Yale University Press; 2014. 296 p. ↵
Collier A. Less parental control, more support of kids’ self-regulation: Study [Internet]. ConnectSafely. 2014 [cited 2017 Jul 18]. Available from: http://www.connectsafely.org/less-parental-control-more-support-of-kids-self-regulation-study/ ↵
Law DM, Shapka JD, Olson BF. To control or not to control? Parenting behaviours and adolescent online aggression. Computers in Human Behavior. 2010 Nov 1;26(6):1651–6. ↵
Schiano DJ, Burg C. Parental Controls: Oxymoron and Design Opportunity. In: HCI International 2017 – Posters’ Extended Abstracts [Internet]. Springer, Cham; 2017 [cited 2017 Jul 18]. p. 645–52. (Communications in Computer and Information Science). Available from: https://link.springer.com/chapter/10.1007/978-3-319-58753-0_91 ↵
NSF Award Search: Award#1618153 – TWC SBE: Small: Helping Teens and Parents Negotiate Online Privacy and Safety [Internet]. [cited 2017 Jul 31]. Available from: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618153&HistoricalAwards=false ↵
Wisniewski P, Ghosh AK, Rosson MB, Xu H, Carroll JM. Parental Control vs. Teen Self-Regulation: Is there a middle ground for mobile online safety? In: Proceedings of the 20th ACM Conference on Computer Supported Cooperative Work & Social Computing. Portland, OR, USA: ACM; 2017. ↵
Khurana A, Bleakley A, Jordan AB, Romer D. The protective effects of parental monitoring and internet restriction on adolescents’ risk of online harassment. J Youth Adolesc. 2015 May;44(5):1039–47. ↵
Lee S-J, Chae Y-G. Balancing participation and risks in children’s Internet use: the role of internet literacy and parental mediation. Cyberpsychol Behav Soc Netw. 2012 May;15(5):257–62. ↵
Livingstone S, Helsper EJ. Parental Mediation of Children’s Internet Use. Journal of Broadcasting & Electronic Media. 2008;52(4):581–99. ↵
Erickson LB, Wisniewski P, Xu H, Carroll JM, Rosson MB, Perkins DF. The boundaries between: Parental involvement in a teen’s online world. J Assn Inf Sci Tec. 2016 Jun 1;67(6):1384–403. ↵
Petronio S. Communication privacy management theory: What do we know about family privacy regulation? Journal of Family Theory & Review. 2010;2(3):175–96. ↵
Petronio S. Privacy binds in family interactions: The case of parental privacy invasion. In: Spitzberg WRCBH, editor. The dark side of interpersonal communication. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc; 1994. p. 241–57. (LEA’s communication series.). ↵
Valkenburg PM, Krcmar M, Peeters AL, Marseille NM. Developing A Scale to Assess Three Styles of Television Mediation: “Instructive Mediation,” “Restrictive Mediation,” and “Social Coviewing.” Journal of Broadcasting & Electronic Media. 1999;43(1):52–66. ↵
Mesch GS. Parental Mediation, Online Activities, and Cyberbullying. CyberPsychology & Behavior. 2009 Aug;12(4):387–93. ↵
Shin W, Huh J, Faber RJ. Tweens’ Online Privacy Risks and the Role of Parental Mediation. Journal of Broadcasting & Electronic Media. 2012 Oct;56(4):632–49. ↵
Li Q. A cross-cultural comparison of adolescents’ experience related to cyberbullying. Educational Research. 2008 Sep;50(3):223–34. ↵
Näsi M, Räsänen P, Oksanen A, Hawdon J, Keipi T, Holkeri E. Association between online harassment and exposure to harmful online content: A cross-national comparison between the United States and Finland. Computers in Human Behavior. 2014 Dec;41:137–45. ↵
Baumgartner SE, Sumter SR, Peter J, Valkenburg PM, Livingstone S. Does country context matter? Investigating the predictors of teen sexting across Europe. Computers in Human Behavior. 2014 May;34:157–64. ↵
Menesini E, Nocentini A, Palladino BE, Frisén A, Berne S, Ortega-Ruiz R, et al. Cyberbullying Definition Among Adolescents: A Comparison Across Six European Countries. Cyberpsychology, Behavior, and Social Networking. 2012 Sep;15(9):455–63. ↵
EU Kids Online. www.eukidsonline.net [Internet]. London School of Economics and Political Science. [cited 2020 Oct 31]. Available from: https://www.lse.ac.uk/media-and-communications/research/research-projects/eu-kids-online/home.aspx ↵
Sandhu GK, Sharma V. Social Withdrawal and Social Anxiety in Relation to Stylistic Parenting Dimensions in the Indian Cultural Context. Research in Psychology and Behavioral Sciences, Research in Psychology and Behavioral Sciences. 2015 Dec 29;3(3):51–9. ↵
Brody GH, Flor DL. Maternal Resources, Parenting Practices, and Child Competence in Rural, Single-Parent African American Families. Child Development. 1998 Jun 1;69(3):803–16. ↵
Greening L, Stoppelbein L, Luebbe A. The Moderating Effects of Parenting Styles on African-American and Caucasian Children’s Suicidal Behaviors. J Youth Adolescence. 2010 Apr 1;39(4):357–69. ↵
Child Online Protection in India [Internet]. International Centre for Missing & Exploited Children. 2016 [cited 2020 Oct 7]. Available from: https://www.icmec.org/child-online-protection-in-india/ ↵
Child Online Protection in India [Internet]. International Centre for Missing & Exploited Children. 2016 [cited 2020 Oct 8]. Available from: https://www.icmec.org/child-online-protection-in-india/ ↵
Garg R, Sengupta S. “When you can do it, why can’t I?”: Racial and Socioeconomic Differences in Family Technology Use and Non-Use. Proc ACM Hum-Comput Interact. 2019 Nov 7;3(CSCW):63:1-63:22. ↵

Cyberbullying and Digital Safety: Applying Global Research to Youth in India Copyright © 2022 by Anthony T. Pinter; Arup Kumar Ghosh; and Pamela J. Wisniewski is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Preventing Bullying Through Science, Policy, and Practice (2016)

Chapter: summary.

“I think in the early high school years I just tried to stay in the background, I was like ‘Hopefully no one notices me.’ And I would just walk through the halls like a ghost. And it seemed to work for a while but I mean with that you don’t get the full benefits of a social experience.”

—Young adult in a focus group discussing bullying

Bullying has long been tolerated by many as a rite of passage among children and adolescents. There is an implication that individuals who are bullied must have “asked for” this type of treatment, or deserved it. Sometimes, even the child who is bullied begins to internalize this idea. For many years, there has been a general acceptance when it comes to a child or adolescent with greater social capital or power pushing around a child perceived as subordinate—such that you can almost hear the justification: “kids will be kids.” The schoolyard bully trope crosses race, gender, class, ethnicity, culture, and generations, appearing in popular media ranging from Harry Potter to Glee , and Mean Girls to Calvin and Hobbes cartoons. Its prevalence perpetuates its normalization. But bullying is not a normal part of childhood and is now appropriately considered to be a serious public health problem.

Although bullying behavior endures through generations, the milieu is changing. Historically, bullying has occurred at school—the physical setting in which most of childhood is centered and the primary source for peer group formation—or really anywhere that children played or congregated. In recent years, however, the physical setting is not the only place bullying is occurring. Technology allows for a new type of digital electronic aggres-

sion, cyberbullying, which takes place through chat rooms, instant messaging, social media, and other forms of digital electronic communication.

Simultaneously, the demographics of cities and towns in the United States are in flux, with resulting major changes in the ethnic and racial composition of schools across the country. Numerical-minority ethnic groups appear to be at greater risk for being targets of bullying because they have fewer same-ethnicity peers to help ward off potential bullies. Ethnically diverse schools may reduce actual rates of bullying because the numerical balance of power is shared among many groups.

Composition of peer groups, shifting demographics, changing societal norms, and modern technology are contextual factors that must be considered to understand and effectively react to bullying in the United States. Youth are embedded in multiple contexts, and each of these contexts interacts with individual characteristics of youth in ways that either exacerbate or attenuate the association between these individual characteristics and being a target or perpetrator of bullying. Even the definition of bullying is being questioned, since cyberbullying is bullying but may not involve repetition—a key component in previous definitions of bullying—because a single perpetrating act on the Internet can be shared or viewed multiple times.

Although the public health community agrees that bullying is a problem, it has been difficult for researchers to determine the extent of bullying in the United States. However, the prevalence data that are available indicate that school-based bullying likely affects between 18 and 31 percent of children and youth, and the prevalence of cyber victimization ranges from 7 to 15 percent of youth. These estimates are even higher for some subgroups of youth who are particularly vulnerable to being bullied (e.g., youth who are lesbian, gay, bisexual, and transgender [LGBT]; youth with disabilities). Although these are ranges, they show bullying behavior is a real problem that affects a large number of youth.

STUDY CHARGE AND SCOPE

Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, a group of federal agencies and private foundations asked the National Academies of Sciences, Engineering, and Medicine to undertake a study of what is known and what needs to be known to reduce bullying behavior and its consequences. The Committee on the Biological and Psychosocial Effects of Peer Victimization: Lessons for Bullying Prevention was created to carry out this task under the Academies’ Board on Children, Youth, and Families and the Committee on

Law and Justice. The committee was charged with producing a comprehensive report on the state of the science on the biological and psychosocial consequences of peer victimization and the risk and protective factors that either increase or decrease peer victimization behavior and consequences (see Chapter 1 for the committee’s detailed statement of task).

This report builds on a workshop held in April 2014 and summarized in a report from the Institute of Medicine and National Research Council, Building Capacity to Reduce Bullying and Its Impact on Youth Across the Lifecourse . The committee that authored the current report, several members of which participated in the initial workshop, began its work in October 2014. The committee members represent expertise in communication technology, criminology, developmental and clinical psychology, education, mental health, neurobiological development, pediatrics, public health, school administration, school district policy, and state law and policy.

The committee conducted an extensive review of the literature pertaining to peer victimization and bullying and, in some instances, drew upon the broader literature on aggression and violence. To supplement its review of the literature, the committee held two public information-gathering sessions and conducted a site visit to a northeastern city. 1

Given the varied use of the terms “bullying” and “peer victimization” in both the research-based and practice-based literature, the committee chose to use a current definition for bullying developed by the Centers for Disease Control and Prevention (CDC):

Bullying is any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated. Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm.

Not only does this definition provide detail on the common elements of bullying behavior but it also was developed with input from a panel of researchers and practitioners. The committee also followed the CDC in focusing primarily on individuals between the ages of 5 and 18. The committee recognizes that children’s development occurs on a continuum, and so while it relied primarily on the CDC definition, its work and this report acknowledge the importance of addressing bullying in both early childhood and emerging adulthood. The committee followed the CDC in not including sibling violence, dating violence, and bullying of youth by adults, as those subjects were outside the scope of the committee’s charge.

___________________

1 The location of the city is not identified in order to protect the privacy of the focus group participants.

THE SCOPE AND IMPACT OF THE PROBLEM

While exact estimates of bullying and cyberbullying may be difficult to ascertain, how their prevalence is measured can be improved. The committee concluded that definitional and measurement inconsistencies lead to a variation in estimates of bullying prevalence, especially across disparate samples of youth. Although there is a variation in numbers, the national surveys show bullying behavior is a real problem that affects a large number of youth (Conclusion 2.1). Chapter 2 describes the definitional, measurement, and sampling issues that make it difficult to generate precise, consistent, and representative estimates of bullying and cyberbullying rates. Moreover, the national datasets on the prevalence of bullying focus predominantly on the children who are bullied. Considerably less is known about perpetrators, and nothing is known about bystanders in that national data (Conclusion 2.2). Further, there is currently a lack of nationally representative data for certain groups that are at risk for bullying, such as LGBT youth and youth with disabilities.

Although perceptions and interpretations of communications may be different in digital communities, the committee decided to address cyberbullying within a shared bullying framework rather than as a separate entity from traditional bullying because there are shared risk factors, shared negative consequences, and interventions that work on both cyberbullying and traditional bullying. However, there are differences between these behaviors that have been noted in previous research, such as different power differentials, different perceptions of communication, and differences in how to best approach the issue of repetition in an online context. These differences suggest that the CDC definition of traditional bullying may not apply in a blanket fashion to cyberbullying but that these entities are not separate species. The committee concludes cyberbullying should be considered within the context of bullying rather than as a separate entity. The Centers for Disease Control and Prevention definition should be evaluated for its application to cyberbullying. Although cyberbullying may already be included, it is not perceived that way by the public or by the youth population (Conclusion 2.3).

The committee also concludes that different types of bullying behaviors—physical, relational, cyber—may emerge or be more salient at different stages of the developmental life course (Conclusion 2.4). In addition, the committee concludes that the online context where cyberbullying takes place is nearly universally accessed by adolescents. Social media sites are used by the majority of teens and are an influential and immersive medium in which cyberbullying occurs (Conclusion 2.5).

As described in Chapter 3 , research to date on bullying has been largely descriptive. These descriptive data have provided essential insights into a

variety of important factors on the topic of bullying, including prevalence, individual and contextual correlates, and adverse consequences. At the same time, this descriptive approach has often produced inconsistencies due, in part, to a lack of attention to contextual factors that render individual characteristics, such as race/ethnicity, more or less likely to be related to bullying experiences. Youth are embedded in multiple contexts, ranging from peer and family to school, community, and macrosystem. Each of these contexts can affect individual characteristics of youth (e.g., race/ethnicity, sexual orientation) in ways that either exacerbate or attenuate the association between these individual characteristics and perpetrating and/or being the target of bullying behavior (Conclusion 3.1)

The committee also concludes that contextual factors operate differently across groups of youth, and therefore contexts that protect some youth against the negative effects of bullying are not generalizable to all youth. Consequently, research is needed to identify contextual factors that are protective for specific subgroups of youth that are most at risk of perpetrating or being targeted by bullying behavior (Conclusion 3.2).

Finally, the committee notes that stigma 2 plays an important role in bullying. In particular, the role of stigma is evident not only in the groups of youth that are expressly targeted for bullying (e.g., LGBT youth, youth with disabilities, overweight/obese youth) but also in the specific types of bullying that some youth face (i.e., bias-based bullying). Despite this evidence, the role of stigma and its deleterious consequences is more often discussed in research on discrimination than on bullying. In the committee’s view, studying experiences of being bullied in particular vulnerable subgroups (e.g., those based on race/ethnicity or sexual orientation) cannot be completely disentangled from the study of discrimination or of unfair treatment based on a stigmatized identity. These are separate empirical literatures (school-based discrimination versus school-based bullying) although often they are studying the same phenomena. There should be much more cross-fertilization between the empirical literatures on school bullying and discrimination due to social stigma (Conclusion 3.5).

Bullying is often viewed as just a normal part of growing up, but it has long-lasting consequences and cannot simply be ignored or discounted as not important. It has been shown to have long-term effects not only on the child who is bullied but also on the child who bullies and on bystanders. While there is limited information about the physical effects of bullying,

2 As noted in a 2016 report Ending Discrimination Against People with Mental and Substance Use Disorders: The Evidence for Stigma Change from the National Academies of Sciences, Engineering, and Medicine, some stakeholder groups are targeting the word “stigma” itself and the Substance Abuse and Mental Health Services Administration is shifting away from the use of this term. The committee determined that the word stigma was currently widely accepted in the research community and uses this term in the report.

existing evidence suggests that children and youth who are bullied experience a range of somatic disturbances, including sleep disturbances, gastrointestinal concerns, and headaches. Emerging research suggests that bullying can result in biological changes. The committee concludes that although the effects of being bullied on the brain are not yet fully understood, there are changes in the stress response systems and in the brain that are associated with increased risk for mental health problems, cognitive function, self-regulation, and other physical health problems (Conclusion 4.3).

As described in Chapter 4 , being bullied during childhood and adolescence has been linked to psychological effects, such as depression, anxiety, and alcohol and drug abuse into adulthood. The committee concludes that bullying has significant short- and long-term internalizing and externalizing psychological consequences for the children who are involved in bullying behavior (Conclusion 4.4). Studies suggest that individuals who bully and who are also bullied by others are especially at risk for suicidal behavior due to increased mental health problems. Individuals who are involved in bullying in any capacity (as perpetrators, targets, or both) are statistically significantly more likely to contemplate or attempt suicide, compared to children who are not involved in bullying. However, there is not enough evidence to date to conclude that bullying is a causal factor for youth suicides. Focusing solely on bullying as a causal factor would ignore the many other influences that contribute to youth suicides.

With regard to the linkages between bullying and school shootings, several characteristics of the research that has been conducted on school shootings bear mentioning. First, to date, research has not been able to establish a reliable profile or set of risk factors that predicts who will become a school shooter. Second, it is important to keep in mind that multiple-victim school shootings are low base rate events, and thus caution should be used in generalizing findings from these rare events to broad populations of students. There is also a lack of reliable evidence about school shootings that may have been successfully prevented or averted.

Given that school shootings are rare events, most of what is known about them comes from studies that aggregate events over many years. These studies mostly employ qualitative methods, including descriptive post-incident psychological autopsies of the shooters, analysis of media accounts, or in-depth interviews of a small subset of surviving shooters. Most investigations have concluded that bullying may play a role in many school shootings but not all. It is a factor, and perhaps an important one, but it does not appear to be the main influencing factor in a decision to carry out these violent acts. Further, there is not enough evidence to date (qualitative or quantitative) to conclude that bullying is a causal factor for multiple-homicide targeted school shootings nor is there clear evidence on how bullying or related mental health and behavior issues contribute to

school shootings. The committee concludes that the data are unclear on the role of bullying as one of or a precipitating cause of school shootings (Conclusion 4.5).

Although the research is limited, children and youth who do the bullying also are more likely to be depressed, engage in high-risk activities such as theft and vandalism, and have adverse outcomes later in life, compared to those who do not bully. However, whereas some individuals who bully others may in fact be maladjusted, others who are motivated by establishing their status within their peer group do not evidence negative outcomes. Thus, the research on outcomes for children who bully is mixed, with most research on the short- and long-term outcomes of bullying not taking into account the heterogeneity of children who bully. The committee concludes that individuals who both bully others and are themselves bullied appear to be at greatest risk for poor psychosocial outcomes, compared to those who only bully or are only bullied and to those who are not bullied (Conclusion 4.6).

Existing evidence suggests that both social-cognitive and emotion regulation processes may mediate the relation between being bullied and adverse mental health outcomes (Conclusion 4.8). Regardless of mechanism, being bullied seems to have an impact on mental health functioning during adulthood. Prior experiences, such as experiences with early abuse and trauma; a chronically activated stress system due to home, school, or neighborhood stress; the length of the bullying experience; and the child’s social support system, all interact to contribute to the neurobehavioral outcome of bullying.

A PIVOTAL TIME FOR PREVENTION: NEXT STEPS

This is a pivotal time for bullying prevention. Reducing the prevalence of bullying and minimizing the harm it imparts on children can have a dramatic impact on children’s well-being and development. Many programs and policies have been developed, but more needs to be known about what types of programs or investments will be most effective. The committee concludes that the vast majority of research on bullying prevention programming has focused on universal school-based programs; however, the effects of those programs within the United States appear to be relatively modest. Multicomponent schoolwide programs appear to be most effective at reducing bullying and should be the types of programs implemented and disseminated in the United States (Conclusion 5.1).

Universal prevention programs are aimed at reducing risks and strengthening skills for all youth within a defined community or school setting. Through universal programs, all members of the target population are exposed to the intervention regardless of risk for bullying. Examples

of universal preventive interventions include social–emotional lessons that are used in the classroom, behavioral expectations taught by teachers, counselors coming into the classroom to model strategies for responding to or reporting bullying, and holding classroom meetings among students and teachers to discuss emotionally relevant issues related to bullying or equity. They may also include guidelines for the use of digital media, such as youth’s use of social network sites.

Selective preventive interventions are directed either to youth who are at risk for engaging in bullying or to youth at risk of being a target of bullying. Such programs may include more intensive social–emotional skills training, coping skills, or de-escalation approaches for youth who are involved in bullying. Indicated preventive interventions are typically tailored to meet youth’s needs and are of greater intensity as compared to the universal or selective levels of intervention. Indicated interventions incorporate more intensive supports and activities for those who are already displaying bullying behavior or who have a history of being bullied and are showing early signs of behavioral, academic, or mental health consequences.

There is a growing emphasis on the use of multi-tiered approaches, which leverage universal, selective, and indicated prevention programs and activities. These combined programs often attempt to address at the universal level such factors as social skill development, social–emotional learning or self-regulation, which also tend to reduce the chances that youth would engage in bullying or reduce the risk of being bullied further. Multi-tiered approaches are vertical programs that increase in intensity, whereas multicomponent approaches could be lateral and include different elements, such as a classroom, parent, and individual components bundled together.

Research indicates that positive relationships with teachers, parents, and peers appear to be protective. The committee concludes that most of the school, family, and community-based prevention programs tested using randomized controlled trial designs have focused on youth violence, delinquency, social–emotional development, and academic outcomes, with limited consideration of the impacts on bullying specifically. However, it is likely that these programs also produce effects on bullying, which have largely been unmeasured and therefore data on bullying outcomes should be routinely collected in future research (Conclusion 5.2).

Families play a critical role in bullying prevention by providing emotional support to promote disclosure of bullying incidents and by fostering coping skills in their children. And some research points to an opportunity to better engage bystanders, who have the best opportunity to intervene and minimize the effects of bullying.

Chapter 5 offers a number of specific ways to improve the quality and efficacy of preventive interventions. As concluded by the committee, there has been limited research on selective and indicated models for bullying intervention programming, either inside or outside of schools. More at-

tention should be given to these interventions in future bullying research (Conclusion 5.3).

There remains a dearth of intervention research on programs related to cyberbullying and on programs targeted to vulnerable populations, such as LGBT youth, youth with chronic health problems such as obesity, or youth with developmental disabilities such as autism. Schools may consider implementing a multicomponent program that focuses on school climate, positive behavior support, social–emotional learning, or violence prevention more generally, rather than implementing a bullying-specific preventive intervention, as these more inclusive programs may reach a broader set of outcomes for students and the school environment.

Moreover, suspension and related exclusionary techniques are often the default response by school staff and administrators in bullying situations. However, these approaches do not appear to be effective and may actually result in increased academic and behavioral problems for youth. Caution is also warranted about the types of roles youth play in bullying prevention programs. The committee concludes that the role of peers in bullying prevention as bystanders and as intervention program leaders needs further clarification and empirical investigation in order to determine the extent to which peer-led programs are effective and robust against potentially iatrogenic effects (Conclusion 5.5).

As the consequences of bullying become clearer and more widely known, states are adopting new laws and schools are embracing new programs and policies to reduce the prevalence of bullying. As noted in Chapter 6 , over the past 15 years all 50 states and the District of Columbia have adopted or revised laws to address bullying. Forty-nine states and the District of Columbia include electronic forms of bullying (cyberbullying) in their statutes. The committee concludes that law and policy have the potential to strengthen state and local efforts to prevent, identify, and respond to bullying (Conclusion 6.1). However, there are few studies that have examined the actual effect of existing laws and policies in reducing bullying. The committee concludes that the development of model anti-bullying laws or policies should be evidence based. Additional research is needed to determine the specific components of an anti-bullying law that are most effective in reducing bullying, in order to guide legislators who may amend existing laws or create new ones (Conclusion 6.2). Further, evidence-based research on the consequences of bullying can help inform litigation efforts at several stages, including case discovery and planning, pleadings, and trial (Conclusion 6.6).

Some policies and programs have been shown to be ineffective in preventing bullying. The committee concludes there is emerging research that some widely used approaches such as zero tolerance policies are not effective at reducing bullying and thus should be discontinued, with the resources redirected to evidence-based policies and programs (Conclusion 6.7).

In Chapter 7 , the committee makes seven recommendations. The first three recommendations are directed to the cognizant federal agencies and their partners in state and local governments and the private sector, for improving surveillance and monitoring activities in ways that will address the gaps in what is known about the prevalence of bullying behavior, what is known about children and youth who are at increased risk for being bullied, and what is known about the effectiveness of existing policies and programs. Another four recommendations are either directed at fostering the development, implementation, and evaluation of evidence-based preventive intervention programs and training or directed to social media companies and federal partners to adopt, implement, and evaluate policies and programs for preventing, identifying, and responding to bullying on their platforms. The committee’s recommendations are provided below:

Recommendation 7.1: The U.S Departments of Agriculture, Defense, Education, Health and Human Services, and Justice, and the Federal Trade Commission, which are engaged in the Federal Partners in Bullying Prevention interagency group, should foster use of a consistent definition of bullying.

Recommendation 7.2: The U.S. Departments of Education, Health and Human Services, and Justice, and other agencies engaged in the Federal Partners in Bullying Prevention interagency group should gather longitudinal surveillance data on the prevalence of all forms of bullying, including physical, verbal, relational, property, cyber-, and bias-based bullying, and the prevalence of individuals involved in bullying, including perpetrators, targets, and bystanders, in order to have more uniform and accurate prevalence estimates.

Recommendation 7.3: The U.S. Department of Education’s Office of Civil Rights, the state attorneys general, and local education agencies together should (1) partner with researchers to collect data on an ongoing basis on the efficacy and implementation of anti-bullying laws and policies; (2) convene an annual meeting in which collaborations between social scientists, legislative members, and practitioners responsible for creating, implementing, enforcing, and evaluating antibullying laws and policies can be more effectively facilitated and in which research on anti-bullying laws and policies can be reviewed; and (3) report research findings on an annual basis to both Congress and the state legislatures so that anti-bullying laws and policies can be strengthened and informed by evidence-based research.

Recommendation 7.4: The U.S. Departments of Education, Health and

Human Services, and Justice, working with other relevant stakeholders, should sponsor the development, implementation, and evaluation of evidence-based programs to address bullying behavior.

Recommendation 7.5: The U.S. Departments of Education, Health and Human Services, and Justice, working with other relevant stakeholders, should promote the evaluation of the role of stigma and bias in bullying behavior and sponsor the development, implementation, and evaluation of evidence-based programs to address stigma- and bias-based bullying behavior, including the stereotypes and prejudice that may underlie such behavior.

Recommendation 7.6: The U.S. Departments of Education and Health and Human Services, working with other partners, should support the development, implementation, and evaluation of evidence-informed bullying prevention training for individuals, both professionals and volunteers, who work directly with children and adolescents on a regular basis.

Recommendation 7.7: Social media companies, in partnership with the Federal Partners for Bullying Prevention Steering Committee, should adopt, implement, and evaluate on an ongoing basis policies and programs for preventing, identifying, and responding to bullying on their platforms and should publish their anti-bullying policies on their Websites.

In addition, the committee identified a set of current research gaps and recognized the value of future research in addressing issues raised in the report and important for a more comprehensive understanding of bullying behavior, its consequences, and factors that can ameliorate the harmful effects of bullying and foster resilience. These research needs are listed in Table 7-1 and are connected to general topics addressed in the report such as “Law and Policy,” “Prevalence of Bullying,” and “Protective Factors and Contexts.”

The study of bullying behavior is a relatively recent field, and it is in transition. Over the past few decades, research has significantly improved understanding of what bullying behavior is, how it can be measured, and the critical contextual factors that are involved. While there is not a quick fix or one-size-fits-all solution, the evidence clearly supports preventive and interventional policy and practice. Tackling this complex and serious public health problem will require a commitment to research, analysis, trial, and refinement, but doing so can make a tangible difference in the lives of many children.

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Bullying has long been tolerated as a rite of passage among children and adolescents. There is an implication that individuals who are bullied must have "asked for" this type of treatment, or deserved it. Sometimes, even the child who is bullied begins to internalize this idea. For many years, there has been a general acceptance and collective shrug when it comes to a child or adolescent with greater social capital or power pushing around a child perceived as subordinate. But bullying is not developmentally appropriate; it should not be considered a normal part of the typical social grouping that occurs throughout a child's life.

Although bullying behavior endures through generations, the milieu is changing. Historically, bulling has occurred at school, the physical setting in which most of childhood is centered and the primary source for peer group formation. In recent years, however, the physical setting is not the only place bullying is occurring. Technology allows for an entirely new type of digital electronic aggression, cyberbullying, which takes place through chat rooms, instant messaging, social media, and other forms of digital electronic communication.

Composition of peer groups, shifting demographics, changing societal norms, and modern technology are contextual factors that must be considered to understand and effectively react to bullying in the United States. Youth are embedded in multiple contexts and each of these contexts interacts with individual characteristics of youth in ways that either exacerbate or attenuate the association between these individual characteristics and bullying perpetration or victimization. Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, this report evaluates the state of the science on biological and psychosocial consequences of peer victimization and the risk and protective factors that either increase or decrease peer victimization behavior and consequences.

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A Majority of Teens Have Experienced Some Form of Cyberbullying

59% of U.S. teens have been bullied or harassed online, and a similar share says it’s a major problem for people their age. At the same time, teens mostly think teachers, social media companies and politicians are failing at addressing this issue.

Table of contents.

Acknowledgments
Methodology
Appendix A: Detailed tables

Bulk of the 50 most-recommended videos in this analysis were music videos, TV competitions, children's content or 'life hacks'

For the latest survey data on teens and cyberbullying, see “ Teens and Cyberbullying 2022 .”

Name-calling and rumor-spreading have long been an unpleasant and challenging aspect of adolescent life. But the proliferation of smartphones and the rise of social media has transformed where, when and how bullying takes place. A new Pew Research Center survey finds that 59% of U.S. teens have personally experienced at least one of six types of abusive online behaviors. 1

The most common type of harassment youth encounter online is name-calling. Some 42% of teens say they have been called offensive names online or via their cellphone. Additionally, about a third (32%) of teens say someone has spread false rumors about them on the internet, while smaller shares have had someone other than a parent constantly ask where they are, who they’re with or what they’re doing (21%) or have been the target of physical threats online (16%).

While texting and digital messaging are a central way teens build and maintain relationships, this level of connectivity may lead to potentially troubling and nonconsensual exchanges. One-quarter of teens say they have been sent explicit images they didn’t ask for, while 7% say someone has shared explicit images of them without their consent. These experiences are particularly concerning to parents. Fully 57% of parents of teens say they worry about their teen receiving or sending explicit images, including about one-quarter who say this worries them a lot, according to a separate Center survey of parents.

The vast majority of teens (90% in this case) believe online harassment is a problem that affects people their age, and 63% say this is a major problem. But majorities of young people think key groups, such as teachers, social media companies and politicians are failing at tackling this issue. By contrast, teens have a more positive assessment of the way parents are addressing cyberbullying.

These are some of the key findings from the Center’s surveys of 743 teens and 1,058 parents living in the U.S. conducted March 7 to April 10, 2018. Throughout the report, “teens” refers to those ages 13 to 17, and “parents of teens” are those who are the parent or guardian of someone in that age range.

Similar shares of boys and girls have been harassed online – but girls are more likely to be the targets of online rumor-spreading or nonconsensual explicit messages

Teen boys and girls are equally likely to be bullied online, but girls are more likely to endure false rumors, receive explicit images they didn't ask for

When it comes to the overall findings on the six experiences measured in this survey, teenage boys and girls are equally likely to experience cyberbullying. However, there are some differences in the specific types of harassment they encounter.

Overall, 60% of girls and 59% of boys have experienced at least one of six abusive online behaviors. While similar shares of boys and girls have encountered abuse, such as name-calling or physical threats online, other forms of cyberbullying are more prevalent among girls. Some 39% of girls say someone has spread false rumors about them online, compared with 26% of boys who say this.

Girls also are more likely than boys to report being the recipient of explicit images they did not ask for (29% vs. 20%). And being the target of these types of messages is an especially common experience for older girls: 35% of girls ages 15 to 17 say they have received unwanted explicit images, compared with about one-in-five boys in this age range and younger teens of both genders. 2

Online harassment does not necessarily begin and end with one specific behavior, and 40% of teens have experienced two or more of these actions. Girls are more likely than boys to have experienced several different forms of online bullying, however. Some 15% of teen girls have been the target of at least four of these online behaviors, compared with 6% of boys.

In addition to these gender differences, teens from lower-income families are more likely than those from higher-income families to encounter certain forms of online bullying. For example, 24% of teens whose household income is less than $30,000 a year say they have been the target of physical threats online, compared with 12% whose annual household income is $75,000 or more. However, teens’ experiences with these issues do not statistically differ by race or ethnicity, or by their parent’s level of educational attainment. (For details on experiences with online bullying by different demographic groups, see Appendix A .)

The likelihood of teens facing abusive behavior also varies by how often teens go online. Some 45% of teens say they are online almost constantly , and these constant users are more likely to face online harassment. Fully 67% of teens who are online almost constantly have been cyberbullied, compared with 53% of those who use the internet several times a day or less. These differences also extend to specific kinds of behaviors. For example, half of teens who are near-constant internet users say they have been called offensive names online, compared with about a third (36%) who use the internet less frequently.

A majority of teens think parents are doing a good job at addressing online harassment, but smaller shares think other groups are handling this issue effectively

Today, school officials, tech companies and lawmakers are looking for ways to combat cyberbullying. Some schools have implemented policies that punish students for harassing messages even when those exchanges occur off campus. Anti-bullying tools are being rolled out by social media companies, and several states have enacted laws prohibiting cyberbullying and other forms of electronic harassment. In light of these efforts, Pew Research Center asked young people to rate how key groups are responding to cyberbullying and found that teens generally are critical of the way this problem is being addressed.

A majority of teens think parents are doing a good job in addressing online harassment, but are critical of teachers, social media companies and politicians

Indeed, teens rate the anti-bullying efforts of five of the six groups measured in the survey more negatively than positively. Parents are the only group for which a majority of teens (59%) express a favorable view of their efforts.

Young people have an especially negative view of the way politicians are tackling the issue of cyberbullying – 79% of teens say elected officials are doing only a fair or poor job of addressing this problem. And smaller majorities have unfavorable views of how groups such as social media sites (66%), other users who witness harassment happening online (64%) or teachers (58%) are addressing harassment and cyberbullying.

Teens’ views on how well each of these groups is handling this issue vary little by their own personal experiences with cyberbullying – that is, bullied teens are no more critical than their non-bullied peers. And teens across various demographic groups tend to have a similar assessment of how these groups are addressing online harassment.

About six-in-ten parents worry about their own teen getting bullied online, but most are confident they can teach their teen about acceptable online behavior

Parents believe they can provide their teen with the appropriate advice to make good online decisions. Nine-in-ten parents say they are at least somewhat confident they can teach their teen how to engage in appropriate online behavior, including 45% who say they are very confident in their ability to do so.

About six-in-ten parents worry about their teen getting bullied online, exchanging explicit images, but this varies by race, ethnicity and the child's gender

But even as most parents are confident they can educate their child about proper online conduct, notable shares are concerned about the types of negative experiences their teen might encounter online. Roughly six-in-ten parents say they worry at least somewhat about their teen being harassed or bullied online (59%) or sending or receiving explicit images (57%). In each case, about one-in-four parents say they worry a lot about one of these things happening to their child.

These parental concerns tend to vary by race and ethnicity, as well as by a child’s gender. Among parents, whites and Hispanics are more likely than blacks to say they worry about their teen being cyberbullied. Hispanic parents also are more inclined than black parents to say they worry about their child exchanging explicit images. At the same time, parents of teen girls are somewhat more likely than those with a teenage boy to say they worry about their teen being bullied online (64% vs. 54%) or exchanging explicit images (64% vs. 51%). (For details on these parental concerns by demographic group, see Appendix A .)

Pew Research Center measured cyberbullying by asking respondents if they had ever experienced any of six online behaviors. Respondents who selected yes to one or more of these questions are considered to be targets of cyberbullying in this study. Throughout the report the terms “cyberbullying” and “online harassment” are used interchangeably. ↩
A 2017 Pew Research Center survey of U.S. adults also found age and gender differences in receiving nonconsensual explicit images; women ages 18 to 29 are especially likely to encounter this behavior. ↩

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What Are the Different Types of Bullying?

Bullying can come in many different forms

Ridofranz / Getty Images

6 Types of Bullying

Mental Health Effects

When you think of bullying, the physically and verbally aggressive behavior that school children endure from their peers might be what immediately springs to mind. However, it's important to recognize that bully can come in many different forms. Just because it doesn't involve physical or verbal aggression doesn't mean that it doesn't count as bullying. In fact, there are actually six different kinds of bullying: physical, verbal, relational, cyber, sexual, and prejudicial.

These types of bullying often overlap. Bullies frequently use more than one form to abuse a victim. Moreover, bullying isn't limited to kids and teenagers. Adults can also be guilty of bullying, too.

At a Glance

Bullying is a common problem among school-age kids, but it can affect anyone of any age. This intentional aggressive behavior is often about intimidation and control, and it can range from overt acts of violence to more subtle forms of emotional intimidation. Being able to recognize the different forms that bullying can take, including physical, verbal, relational, cyber, sexual, and prejudicial, is important. It can take a heavy toll on victims, so spotting the signs and taking action is crucial.

What Exactly Is Bullying?

Bullying is defined as any intentional, repeated aggressive behavior directed by a perpetrator against a target in the same age group.

One of the most noteworthy components of bullying is an imbalance of power between the bully and the victim.

Sometimes, the power imbalance is obvious when, for example, a bigger, stronger kid bullies a weaker, smaller kid or when a group of people bullies a single individual. However, sometimes the power imbalance is more difficult to discern because it involves less obvious factors, such as differences in popularity, intelligence, or ability, or knowledge of the information the victim finds embarrassing.

Bullying falls into six categories, some of which are more obvious than others. They include:

Physical bullying
Verbal bullying
Relational bullying

Cyberbullying

Sexual bullying
Prejudicial bullying

Physical Bullying

Physical bullying is the most obvious type of bullying and what many people think of when they imagine this kind of aggression .

Physical bullying involves any assault on a person's body, including hitting, kicking, tripping, or pushing. It can also extend to inappropriate hand gestures or stealing or breaking a victims' belongings.

Physical bullying is perpetrated by an individual or group of individuals who are bigger or stronger than the individual being targeted.

If a physical altercation happens between two people of similar size and strength, it's not considered physical bullying.

Studies have shown that boys are more likely to be involved in physical bullying than girls. For example, research has found that boys are more likely to be both the perpetrators and victims of physical bullying.

Some research suggests that such differences stem from gender differences in socialization. Boys are socialized to use direct aggression, whereas girls are socialized to express aggression indirectly.

Verbal Bullying

Verbal bullying involves using spoken or written words to insult or intimidate a victim. It includes name-calling, teasing, and even threats.

One study found that verbal bullying was the most common form of bullying. Boys experienced this type of bullying at a slightly higher rate than girls, and most were bullied by their own friends.

Verbal bullying isn't always easy to recognize because it often takes place when authority figures aren't around. Moreover, a bully can pass it off as good-natured ribbing between friends. As a result, it can be difficult for the victim to prove. Therefore, this form of bullying can become a long-term source of stress and anxiety.

Relational Bullying

Relational bullying, which is also referred to as relational aggression or social bullying, involves actions intended to harm a victim's reputation or relationships. It can include embarrassing the victim in public, spreading rumors, purposely leaving them out of social situations, or ostracizing them from a group.

Unlike more overt types of bullying, it is especially sly and insidious because it involves social manipulation.

Relational bullying is often associated with so-called "mean girls." However, while research has shown girls are more often the victims of relational bullying than boys, both boys are more likely to be perpetrators of this type of bullying.

On the other hand, studies suggest that girls who engage in relational bullying have worse adjustment problems , including issues maintaining fulfilling and positive relationships.

Relational bullying can lead to isolation , loneliness , depression, and social anxiety. Unfortunately, research indicates that teachers, school counselors, and other educational staff tend to feel relational bullying is less serious and have less empathy for victims of relational bullying than victims of physical and verbal bullying.

This may be because the severity of relational bullying is more challenging to detect. Physical and verbal bullying results in disciplinary action toward the perpetrator around 50% of the time, whereas this response only happens 10% of the time with relational bullying

Cyberbullying is bullying that happens via electronic devices like computers, smart phones, and tablets. It can take place over text messages, social media, apps, or online forums and involves posting or sending harmful content, including messages and photos, and sharing personal information that causes humiliation.

Research by the Cyberbullying Research Center shows that 15% of 9- to 12-year-olds and 37% of 13- to 17-year-olds have experienced cyberbullying at some point in their lives.

In-person bullying is still more prevalent than cyberbullying but cyberbullying is a growing problem. Not only are perpetrators of cyberbullying less likely to be caught, but the online nature of cyberbullying can also be especially damaging to victims.

People have their devices on them all day, every day, so if they're being cyberbullied, they never get a break, even in their homes.

Similarly, targets of cyberbullying may be constantly reminded of the online bullying they've endured because, even if they block the cyberbully, others may see and share the evidence.

Sexual Bullying

Sexual bullying is online or in-person bullying that involves sexual comments or actions, including sexual jokes and name-calling, crude gestures, spreading sexual rumors, sending sexual photos or videos, and touching or grabbing someone without permission.

Sexual bullying and harassment are remarkably widespread. A 2019 study found that 81% of women and 43% of men experienced sexual harassment or assault at some point in their lifetime.

Meanwhile, sexting, sending or receiving sexually explicit messages or images between electronic devices, is becoming increasingly common.

Research shows that among kids between the ages of 11 and 17, 15% of them sent sexts and 27% received sexts; the prevalence of the behavior increases as adolescents age.

When sexts are sent without consent, such as when private nude photos or videos of an individual are widely shared among a peer group, it can lead to sexual bullying and even sexual assault .

Prejudicial Bullying

Prejudicial bullying involves online or in-person bullying based on the target's race, ethnicity, religion, or sexual orientation . It is based on stereotypes and is often a result of the belief that some people deserve to be treated with less respect than others.

Though prejudicial bullying has been studied less than other types of bullying, research indicates that ethnic and sexual minorities are more likely to be bullied than their peers.

However, ethnic minorities that attend more ethnically diverse schools experience less bullying than those in schools that are more ethnically homogenous.

How Common Is Bullying?

Bullying is widespread and can negatively impact both bullying victims and the bullies themselves. A 2019 survey by the Centers for Disease Control and Prevention (CDC) found that 19.5% of ninth through twelfth graders were bullied on school property in the 12 months prior to completing the questionnaire.

Moreover, a study by the World Health Organization (WHO) conducted in 2013 and 2014 in 42 countries in Europe and North America found that, on average, 14% of 11-year-old boys and 11% of 11-year-old girls were bullied at least twice in the previous two to three months.

Mental Health Effects of Bullying

People who are bullied can experience a plethora of short- and long-term problems , including depression and anxiety, social withdrawal , substance abuse, difficulties at school or work such as underachieving and poor attendance, and even suicide .

In addition, children who are targets of bullying may become victims or perpetrators of violence later in life. Meanwhile, those who bully others are more likely to get into fights and vandalize property, abuse drugs and alcohol, have criminal convictions in adulthood , and abuse their romantic partners and children .

Even people who simply observe bullying can experience issues, including mental health difficulties and increased substance use.

Bullying can have lasting mental health effects, which is why it's so important to recognize it and address it as soon as possible. While physical and verbal bullying are the most recognizable forms, other types are also common and often occur together. Relational, cyber, sexual, and prejudicial bullying are other types of bullying that are sometimes less readily apparent (but just as damaging).

If you are having suicidal thoughts, contact the National Suicide Prevention Lifeline at 988 for support and assistance from a trained counselor. If you or a loved one are in immediate danger, call 911.

For more mental health resources, see our National Helpline Database .

Krešić Ćorić M, Kaštelan A. Bullying through the Internet - Cyberbullying . Psychiatr Danub . 2020;32(Suppl 2):269-272.

Arseneault L. Annual research review: The persistent and pervasive impact of being bullied in childhood and adolescence: implications for policy and practice . Journal of Child Psychology and Psychiatry . 2018;59(4):405-421. doi:10.1111/jcpp.12841

StopBullying.gov. What is bullying ?

Armitage R. Bullying in children: impact on child health . BMJ Paediatr Open . 2021;5(1):e000939. doi:10.1136/bmjpo-2020-000939

Elmahdy M, Maashi NA, Hakami SO, et al. Prevalence of bullying and its association with health-related quality of life among adolescents in Jazan: A cross-sectional study . Cureus . 2022;14(8):e28522. doi:10.7759/cureus.28522

Orpinas P, McNicholas C, Nahapetyan L. Gender differences in trajectories of relational aggression perpetration and victimization from middle to high school . Aggress Behav . 2015;41(5):401-412. doi:10.1002/ab.21563

Centifanti LCM, Fanti KA, Thomson ND, Demetriou V, Anastassiou-Hadjicharalambous X. Types of relational aggression in girls are differentiated by callous-unemotional traits, peers and parental overcontrol . Behavioral Sciences . 2015;5(4):518-536. doi:10.3390/bs5040518

Cook EE, Nickerson AB, Werth JM, Allen KP. Service providers’ perceptions of and responses to bullying of individuals with disabilities . J Intellect Disabil . 2017;21(4):277-296. doi:10.1177/1744629516650127

Kumar VL, Goldstein MA. Cyberbullying and adolescents . Curr Pediatr Rep . 2020;8(3):86-92. doi:10.1007/s40124-020-00217-6

Cyberbullying Research Center. Tween Cyberbullying in 2020 .

Cyberbullying Research Center. 2019 Cyberbullying Data .

Graber D. Raising Humans in a Digital World: Helping Kids Build a Healthy Relationship with Technology . HarperCollins Leadership; 2019.

Stop Street Harassment. National studies .

Madigan S, Ly A, Rash CL, Van Ouytsel J, Temple JR. Prevalence of multiple forms of sexting behavior among youth: A systematic review and meta-analysis . JAMA Pediatr . 2018;172(4):327-335. doi:10.1001/jamapediatrics.2017.5314

Menesini E, Salmivalli C. Bullying in schools: The state of knowledge and effective interventions . Psychology, Health & Medicine . 2017;22(sup1):240-253. doi: 10.1080/13548506.2017.1279740

Centers for Disease Control and Prevention. YRBSS | Youth Risk Behavior Surveillance System | Data | Adolescent and School Health . Cdc.gov. 2019.

World Health Organization. Health Behaviour In School-Aged Children (HBSC) .

StopBullying.gov. Effects of Bullying .

By Cynthia Vinney, PhD Cynthia Vinney, PhD is an expert in media psychology and a published scholar whose work has been published in peer-reviewed psychology journals.

IMAGES

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Effects Of Cyberbullying To Students
(PDF) Bullying, Cyberbullying, and Suicide
ch. 5 cyberbullying research 2 .docx
Essay About Cyberbullying With Introduction Body And Conclusion
(PDF) Cyberbullying involvement and mental health problems among late

COMMENTS

(PDF) CHAPTER 5 SUMMARY, CONCLUSIONS, IMPLICATIONS AND ...
The conclusions are as stated below: i. Students' use of language in the oral sessions depicted their beliefs and values. based on their intentions. The oral sessions prompted the students to be ...
PDF Chapter 5: Going Beyond Cyberbullying: Adolescent Online Safety and
In this chapter, we cover the broader research area of digital risks and online safety. We discuss three primary types of risks that adolescents frequently navigate in digitally mediated environments that extend beyond cyberbullying - 1) Sexual Solicitations and Risky Sexual Behavior, 2) Exposure to Explicit Content, and 3) Information ...
Chapter 5
Recognized as a pioneer of bullying research, Olweus defined bullying as a sub-set of aggressive behavior, which is intended to cause harm to a less powerful victim, over a repeated period, inflicted by one or more individuals (Olweus, 1978). While the definition includes three distinct criteria: (1) intention to cause harm, (2) repetition, and ...
Cyberbullying Among Adolescents and Children: A Comprehensive Review of
The number of studies on cyberbullying has surged in the last 5 years, especially those related to risk factors and protective factors of cyberbullying. However, research on effective prevention is insufficient and evaluation of policy tools for cyberbullying intervention is a nascent research field.
Cyberbullying and its influence on academic, social, and emotional
A research, of 187 undergraduate students matriculated at a large U.S. Northeastern metropolitan Roman Catholic university (Webber and Ovedovitz, 2018), found that 4.3% indicated that they were victims of cyberbullying at the university level and a total of 7.5% students acknowledged having participated in bullying at that level while A survey ...
(PDF) Cyberbullying: A Review of the Literature
cyberbullying, in which individuals or groups of individuals use the media to inflict emotional distress on. other individuals (Bocij 2004). According to a rece nt study of 743 teenager s and ...
PDF Recommendations for Cyberbullying Prevention Methods: Offline and
exists, the research paper will be able to make recommendations for cyber bullying prevention programs that are grounded in empirical research. Key Findings In order to prevent cyberbullying, both online and offline prevention programs are necessary. Adolescence is a developmentally crucial time, which is why it is the
Conclusions
As discussed in Chap. 5, there is a wealth of studies that have examined the concurrent associations between involvement in cyberbullying and some of the consequences of this involvement.The research has reported a range of associations, including psychosocial adjustment, general adjustment, and further involvement in cyberbullying for both the perpetrators and the targets of cyberbullying.
Research on Cyberbullying: Strengths and Limitations
Prevalence rates vary hugely (Kowalski et al., 2014; Modecki et al., 2014), even when limiting studies to self-reports of peer cyber bullying/victimization (the most common source).Relatively low rates are reported in some studies. For example Olweus (), for the period 2007 to 2010, quoted cyber victim rates of around 4-5% for 8-19 year olds in the U.S.A., and of around 3-4% for 9-17 ...
Cyberbullying Prevention and Intervention Efforts: Current Knowledge
Research findings on the prevalence of cyberbullying in Canada vary. 3 For example, according to a national study in Canada, which consisted of 1001 children ages 10 to 17 years, 14% of children reported being cyberbullied once or more in the past month. 4 Other studies 5-8 reported much higher rates of cyberbullying than the aforementioned study. Li's study, 6 which includes a sample of ...
Chapter 5 Cyberbullying
Chapter 5 DOI: 10.4018/978-1-5225-4168-4.ch005 ABSTRACT The purpose of this literature review is to describe youths involvement in cyberbullying. The term youths refers to individuals in elementary school, middle school, and high school. The chapter begins by providing a description of cyberbullying and the de nition of cyberbullying.
Cyberbullying, Bullying, and Victimization among Adolescents: Rates of
Cyberbullying has evolved from the increasing use of technology, specifically electronic communication and social networking. Cyberbullying is defined as a means of bullying in which peers use electronic devices "to taunt, insult, threaten, harass, and/or intimidate a peer" (Raskauskas & Stoltz, 2007, p. 565). This could occur through a
Cyberbullying in schools: A research study on school policies and
Cyberbullying in Schools: A Research Study on School Policies and Procedures . by Brian Wiseman Dr. Pamela Salazar, Ed.D., Examination Committee Chair Professor of Educational Leadership University of Nevada, Las Vegas A mixed-methods research design first using quantitative then qualitative data was
Principles of Cyberbullying Research
ABSTRACT. In 2010, the International Cyberbullying Think Tank was held in order to discuss questions of definition, measurement, and methodologies related to cyberbullying research. The attendees' goal was to develop a set of guidelines that current and future researchers could use to improve the quality of their research and advance our ...
Cyberbullying
Abstract. Cyberbullying has become a major focus of not only youths, educators, and researchers, but also among the general population, due to high profile cases of cyberbullying victimization involving suicide and the increasing prevalence of these behaviors. The purpose of this chapter is to examine cyberbullying among children and ...
PDF Cyberbullying by Partial Fulfillment of the Approved: 2 Semester Credits
This literature review addressed three research questions: the prevalence and. of cyberbullying~ differences between males and females when it comes tocy. A cyberbullying study by the National Crime Prevention Council and Harris. Interactive~ Inc. found that 43% of the 824 middle school and high school-aged students.
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In this chapter, we cover the broader research area of digital risks and online safety. We discuss three primary types of risks that adolescents frequently navigate in digitally mediated environments that extend beyond cyberbullying - 1) Sexual Solicitations and Risky Sexual Behavior , 2) Exposure to Explicit Content , and 3) Information ...
PDF Chapter 5: Cyberbullying in the United Kingdom and Ireland
5 or embarrassing posts and/or pictures about an individual or the creation of public forums targeting the victim specifically. Media reports of several cases of teenage suicide, attributed to ...
Preventing Bullying Through Science, Policy, and Practice
Social media sites are used by the majority of teens and are an influential and immersive medium in which cyberbullying occurs (Conclusion 2.5). As described in Chapter 3, research to date on bullying has been largely descriptive. These descriptive data have provided essential insights into a
Frontiers
Although cyberbullying is still a relatively new field of research, cyberbullying among adolescents is considered to be a serious public health issue that is closely related to adolescents' behavior, mental health and development (16, 17). The increasing rate of Internet adoption worldwide and the popularity of social media platforms among the ...
A Majority of Teens Have Experienced Some Form of Cyberbullying
A new Pew Research Center survey finds that 59% of U.S. teens have personally experienced at least one of six types of abusive online behaviors. 1. The most common type of harassment youth encounter online is name-calling. Some 42% of teens say they have been called offensive names online or via their cellphone.
What Are the Different Types of Bullying?
Research by the Cyberbullying Research Center shows that 15% of 9- to 12-year-olds and 37% of 13- to 17-year-olds have experienced cyberbullying at some point in their lives. In-person bullying is still more prevalent than cyberbullying but cyberbullying is a growing problem. Not only are perpetrators of cyberbullying less likely to be caught ...
Bullying Chapter 5
Chapter 5: Summary Conclusions and Recommendations This Chapter presents the summary of findings conclusions and Recommendations.What is the impact of bullying on academic performance? The first research question explored the impact of bullying on academic performance.

Cyberbullying and its influence on academic, social, and emotional development of undergraduate students

1. Introduction

1.1. Cyberbullying and internet

1.2. Mediums to perpetrate cyberbullying

1.3. Types of cyberbullying

1.4. Prevalence of cyberbullying

1.5. Psychological impact of cyberbullying

1.6. Academic, social, and emotional development of undergraduate students

2.1. Research settings and participants

2.2. Instrumentation

4. Discussion

5. Conclusions

Declarations

Funding statement

Competing interest statement

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Chapter 5: Going Beyond Cyberbullying: Adolescent Online Safety and Digital Risks

ADOLESCENT ONLINE SAFETY: RISKS AND PROTECTIVE FACTORS

ONLINE SEXUAL SOLICITATIONS AND SEXUAL RISK BEHAVIOR

EXPOSURE TO INAPPROPRIATE AND EXPLICIT CONTENT

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ABSTINENCE-ONLY VERSUS RESILIENCE-BASED APPROACHES

PARENTAL CONTROL VERSUS TEEN SELF-REGULATION STRATEGIES

CROSS-CULTURAL COMPARISONS OF ADOLESCENT ONLINE SAFETY AND RISKS BETWEEN THE U.S. AND INDIA

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59% of U.S. teens have been bullied or harassed online, and a similar share says it’s a major problem for people their age. At the same time, teens mostly think teachers, social media companies and politicians are failing at addressing this issue.

Similar shares of boys and girls have been harassed online – but girls are more likely to be the targets of online rumor-spreading or nonconsensual explicit messages

A majority of teens think parents are doing a good job at addressing online harassment, but smaller shares think other groups are handling this issue effectively

About six-in-ten parents worry about their own teen getting bullied online, but most are confident they can teach their teen about acceptable online behavior

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WhatsApp and Facebook dominate the social media landscape in middle-income nations

Research Topics

What Are the Different Types of Bullying?

6 Types of Bullying

At a Glance

What Exactly Is Bullying?

Cyberbullying

Physical Bullying

Verbal Bullying

Relational Bullying

Sexual Bullying

Prejudicial Bullying

How Common Is Bullying?

Mental Health Effects of Bullying

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