Impact of Cyberbullying on the Mental Health of Mexican Young Adults

Gloria Margarita Gurrola Peña^1*, Patricia Balcázar Nava¹, José Luis Ybarra Sagarduy², Luz Adriana Orozco Ramírez² & Priscila Montañez Alvarado³

¹Autonomous University of Mexico State, Mexico
²Autonomous University of Tamaulipas, Mexico
³Autonomous University of Ciudad Juárez, Mexico

*Correspondence to: Dr. Gloria Margarita Gurrola Peña, Autonomous University of Mexico State, Mexico.

Copyright © 2018 Dr. Margarita Gurrola Peña, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction
With the rapid increase of information and communication technologies in recent decades, as well as easy access to electronic devices such as computers, mobile phones and tablets at younger ages by children and young adults, the incorporation of the Internet into daily life is a fact, as nowadays it is used by groups of all ages for different purposes, from children who use it for research or to submit their school homework, to adults who use it to make purchases or perform their work [1].

The speed with which the Internet and Social Networks have been installed in people’s daily lives has created a space from which, with relative anonymity and impunity, harmful behaviours can be carried out towards others, transcending geographical barriers and involving a large number of people.

The definition of Cyberbullying is not specific; however, based on the definition by several authors, it can be understood that it refers to the deliberate and constant use over time of electronic technologies (text messages, e-mails, chats, social networks, etc.) as means to carry out hostile and aggressive activities (threats, harassment, disrespect, social exclusion, spreading rumors, publication of videos or embarrassing photos or false profiles) which are made repeatedly and deliberately towards a person or group of people who cannot defend themselves [2-5]. In view of the above, Jenaro, Flores and Frías (2017) [6] indicate that the main components of cyberbullying are: a relational aggression, which makes it fall into the category of interpersonal violence according to the classification provided by the World Health Organization [7]. It is intentional, occurs in situations of asymmetrical power, it is not a single event as it tends to repeat itself and is carried out through information and communication technologies.

Ortega-Ruíz, Del Rey and Casas (2013) [8], highlight the most significant elements of cyberbullying: 1) it can happen at any time, anywhere, with the consequent difficulty of disconnecting from the context, 2) the aggression can be observed by a large number of people an indefinite number of times, and 3) it is possible that the victims never get to know their aggressors due to the anonymity allowed by the means being used.

In this regard, Willar (2007) [9] as well as Kota, Schoobs, Benson and Moreno (2014) [10], have created a taxonomy of cyberbullying that includes: 1) flaming (causing fights online or publishing disagreements between friends or couples), 2) harassment (recurrent sending of offensive or threatening messages to the victims), 3) outing and trickery (obtaining information about the victim and disseminating it), 4) exclusion (blocking the victim), 5) identity theft (posting comments about others on behalf of the victim or publishing false information about the victim), and 6) sexting (distribution of photos or videos of the victim in compromising situations).

The worldwide research shows that the prevalence rates of Cyberbullying vary from 10% to 53% depending on its definition, period of time over which information is requested, and the age of the group being tested [11-13]. In this regard, the rates of victimization in children and adolescents varies from 2.38% according to Schenk, Fremow and Keelan (2013) [14] to 90.86% according to Peluchete, Karl, Wood and Williams (2016) [15]. It should be noted that the prevalence also varies significantly in different countries; higher top percentages of victimization have been detected, both casual and systematic, in the United States and Asia (55%), compared to the rest of American countries (22%), Canada (25%), Oceania (25%), or Europe (30%) [6].

Although Cyberbullying is a growing concern, there is little research that focuses on the study of the phenomenon in university students. The prevalence studies place it in the ranges between 8% and 56% [16,17]. however, most of the university studies have been carried out in the United States and Europe, and in said studies the main form of victimization found is the spread of rumors and lies online [18]. Recently, this phenomenon has started being studied in other countries [19], although it is incipient in Mexico.

In this regard, the few available data place the phenomenon in a range between 20% and approximately 40% of victims, with insults, threats, taunts, password theft, expressions of sexual harassment and dissemination of embarrassing photos and videos being the main forms of cyberbullying in young Mexican university students [20] (Willard, 2006).

On the other hand, as with the younger population, university students are not immune to the effects of cyberbullying. The university students report impacts at the psychological and social levels in the form of feelings of frustration, stress, sadness, anger, concentration difficulties, social anxiety, depression and suicidal thoughts [21,14]. In addition, feelings of isolation, fear of physical harm, feeling of being ridiculed, relational problems and poor psychological well-being are being reported [22,23].

In terms of physical health, the reported impacts indicate physical signs of stress, sleep disorders, stomach aches and weight loss. With regard to self-perception, it is indicated that cyberbullying impacts self-confidence, self-esteem and self-image. In terms of personal life at home and outside of the university, it has been found that the victims tend to avoid certain people, places and websites. Finally, regarding the feeling of security, it is reported that the victims feel insecure personally and in relation to the people closest to them [24-26].

Based on the foregoing, university students can also be considered a high-risk population for cyberbullying, given the high use of the Internet and other forms of information technology and their reduced parental control. In addition, due to its high prevalence and the deterioration of mental health, it threatens to become a serious public health issue.

Therefore, the purpose of this study was to determine the prevalence of cyberbullying in a sample of university students and to identify its impact on their mental health.

Materials and Methods

Participants
The sample consists of 507 students from four universities in Central and Northern Mexico participated in the study, 66% of the sample are women and 34% men. The average age was 20.85 years old in a range between 17 and 26 years old. Participants signed informed consent and responded both questionnaires in Spanish. The exclusion criteria was not be Mexican and there was a attrition rate of 1.3 percent.

Instruments
Checklist of Symptoms-90-Revised SCL-90-R Spanish version [27], which consists of 90 reagents with 5 response options ranging from Nothing to A lot. Martínez, Stillerman and Waldo (2005) in order to determine if the instrument is appropriate for use with Hispanic college student investigated the psychometric properties. The reported properties for the Hispanic population were 41% of the variance explained and a Cronbach’s alpha coefficient of 0.90 for the total instrument. The instrument reports 9 sub scales; Somatization, (e.g., Headaches) Obsession-Compulsion (e.g., Having to do things very slowly to be sure you do them), Interpersonal Sensitivity (e.g., Being too sensitive or having your feelings hurt easily), Depression (e.g., Having low energy or weakness), Anxiety (e.g., All of a sudden being afraid for no reason), Hostility (e.g., getting irritated or angry easily), Phobic Anxiety (e.g., Being afraid to leave the house alone), Paranoid Ideation (e.g. The idea that one cannot trust other people), and Psychoticism (e.g., Having the idea that another person can control your thoughts)as well as a global index of severity of symptoms indicating the degree of psychological distress.

Cyberbullying Victimization Questionnaire (CBQ-V) [28]. It is a unifactorial questionnaire developed in Spanish which consists of 11 items that describe different forms of CB; for example, receiving threatening or insulting messages by e-mail or posting humiliating comments on the Internet. The scale is Likert-type (0 = never, 1 = sometimes and 2 = often) depending on the frequency with which they have suffered the aggression. Also, several items include open questions describing the behaviors performed. For example, in item 4 (“Post comments about me on the Internet”), if the answer is yes, it must be written. The confirmatory analysis of the scale showed a good adjustment, χ2 (44, N = 1433) = 406, RMSEA = 0.07 (0.063- 0.077), NNFI = 0.99, CFI = 0.99. All the factorial loads of the items were statistically different from zero and oscillated between 0.76 and 0.96. Cronbach’s alpha coefficient was 0.95 [28].

According to the authors of the questionnaire, all those who have suffered some kind of cyber-attack and therefore have a score higher than zero are considered victims. Taking into account the response options those people who score with an average of one to eleven would be considered as low exposure and those who score from twelve to thirty-three would be considered as high exposure.

Data Analysis
First, descriptive analyses were conducted to how the prevalence of cyberbullying and to compare the psychopathological symptoms in the participants who reported having suffered cyberbullying and those who do not experience it. Then, the total cyberbullying indexes were correlated with the psychopathological symptoms.

Finally, a linear stepwise regression was performed to estimate the weight and direction of independent variable identity theft, isolation from social networks and receiving threatening an insulting message via mobile phone), on the appearance of psycho-pathological symptoms (Overall symptom severity index) in young victims of community violence.

Results
It was found that 913 (60.6%) of the participants have not been victims of cyberbullying and 594 (39.4%) of them have been victims. Regarding prevalence, the comparison by sex did not show statistically significant differences.

Low levels of total cyber-victimization were identified (M = 2.30, D.E. 2.29) which corresponds to a not very frequent exposure, with the most frequent forms of cyberbullying being receiving of threatening and insulting messages via mobile phone (42.%), receiving threatening and insulting e-mails (37.1%), identity theft (26.1%) and isolation from social networks (32.4%).

When comparing the groups of young people who have suffered some form of cyberbullying with those who have not lived it, the Levene test indicates that equal variances must be assumed. Statistically significant differences were found between the two groups with cyberbullying victims showing the highest average in all the subscales of psychopathological symptoms (Table 1).

**p<.001

Among the group of participants who had experienced cyberbullying, a comparison was made of psychopathological symptoms by sex, and significant differences were found in all the symptom scales, with women being the most affected, except for the symptoms of fear-hostility, where men showed an average slightly higher than that of the women (Table 2).

*p<.05

Regarding the relationship between the victimization and the symptoms, significant positive correlations were statistically found, from weak to moderate, with the relationship with anxiety, fear, hostility, psychoticism and the global index of severity (Table 3) being the highest.

*p<.05. **p=001

The models resulting from the stepwise regression of the predictor variables for the development of psychopathological symptoms indicate that the third model composed of identity theft, isolation in social networks and threatening or insulting messages via cell phone, explains 21.3% of the phenomenon being studied (Table 4).

a. Predictors: identity theft.
b. Predictors: identity theft, isolation in social networks.
c. Predictors: identity theft, isolation in social networks, threatening or insulting messages via cell phone.
d. Dependent variable: global index of severity.

Table 5 shows the results obtained from the predictor variables related to the appearance of psychopathological symptoms, with a moderate positive value.

Discussions
Cyberbullying is a phenomenon of growing concern and high impact on the mental health of the victims. The results of this study indicate that in contrast to what is indicated in the sense that cyberbullying decreases with age or school grade [29,30,5] the 39.4% prevalence in Mexican university students falls in the range of what was reported for children and adolescents [11-15], being higher than what was reported for other American countries, Canada, Oceania and Europe [6].

Regarding victimization by sex, no statistically significant differences were found, which coincides with what was reported by Alvarez-Garcia et. al, [29] and Hinduja and Patchin (2007) [11] in contrast to what was found by Garaigordobil (2011) [31], where differences are observed. The inconsistency of the results suggests the need for more extensive studies where the role of the gender is defined, since at a given moment it can be a predictor of cyberbullying or act as a moderating variable of its impact.

The relationships found between cyberbullying indices and psychopathological symptoms confirm what was found by various authors [14,22-24,26,32] in the sense that the mental health of the victims is affected and the victims tend to present various symptoms. It should be noted that the symptoms of anxiety, fearhostility, psychoticism and the global index of severity are the signs that show stronger correlations with cyberbullying. In this sense, the victims showing anxiety present symptoms of nervousness, tension, panic attacks and fears. Regarding the symptoms of fear-hostility, they are related to thoughts, feelings and actions characteristic of the presence of negative feelings of anger. In terms of psychoticism, symptoms related to loneliness, schizoid lifestyle, and thought control are included. Finally, a higher correlation between the levels of victimization by cyberbullying and the Global Index of Severity (IGS) could be confirmed, which combines the number of symptoms reported with the level of perceived discomfort and distress, which makes it a good indicator of the current level of severity of psychological distress [33].

In this study, gender differences were found in all subscales of symptoms, as well as in the general index of psychological distress, with women showing higher levels of distress than men. The foregoing reinforces the findings of Kim et al. (2017) [25] and Hammen (2009) [34] in the sense that women, compared to men, tend to experience a more intense and prolonged tension as a result of interpersonal stress, which places them at an increased risk of developing depressive symptoms and other disorders after experiencing a relational online aggression such as cyberbullying [35]. Another element that helps to explain these differences is the fact that women are more likely to think constantly about their experiences of relational aggression, which, due to the rumination, leads to more psychopathological symptoms [18]. The foregoing highlights the importance of understanding the differences by gender of the impact of cyberbullying, and reinforces the importance of developing personalized interventions with an approach and strategies based on sex.

Considering that the purpose of this study was to explore and quantify the relationship between a dependent variable and various independent or predictor variables, as well as the limited evidence existing about the differential impact of the various forms of cyberbullying and their impact on the mental health of young university students, a stepwise linear regression analysis was carried out. For the above-mentioned, the four variables that showed the highest prevalence in the studied sample were considered: receiving threatening and insulting messages via mobile phone, receiving threatening and insulting e-mails, identity theft and isolation from social networks.

In model 1, the identity theft variable was introduced, and it was shown as a predictor of the global index of severity of psychopathological symptoms. In models 2 and 3, the isolation in social networks and receiving threatening or insulting messages via cell phone were also shown as predictor variables in a significantly positive way, leaving receiving threatening and insulting e-mails outside the global model. The resulting model with three predictor variables predicts 21.3% of the psychological distress reported by university students.

Regarding the first variable, which refers to identity theft, it is a term traditionally used to indicate crimes involving the fraudulent use of the personal information of another person for criminal purposes without the knowledge of the victim [36]. However, in the scope of cyberbullying, assuming the identity of another person responds to various reasons, since it does not pursue a monetary benefit, for example, create false profiles to give a false impression of their victims or simply create problems for them, they can also assume the personality of the victim to post negative comments about people who are important to the victim. Regarding the psychological impact, due to the fact that identity theft is usually a shock that affects health, emotional well-being, and relationships with others, causing the appearance of symptoms of depression, anxiety, loss of confidence, insomnia, emotional volatility, difficulty eating and loss of motivation [37].

Regarding the second predictor variable, which refers to isolation in social networks, it is recognized that the experience of social exclusion or ostracism is an aversive situation that may threaten the human needs of belonging, self-esteem, sense of a meaningful existence and/or control. When social exclusion or ostracism is experienced, people perceive the breaking of the link with others as threatening; they become frustrated when they have no control over an answer to their messages and assume that they have done something wrong and thus deserve the experience of feeling nonexistent, which decreases positive mood and increases levels of anger [38-41].

The third predictor variable corresponds to threatening or insulting messages via cell phone, which falls into the category of harassment or bullying [9,10] and belongs to the category of direct cyberbullying [37]. In this regard, since the use of mobile phones with Internet access is so popular nowadays, it can make the victims of these messages feel that their molester is chasing them everywhere and at all times. The foregoing can cause a wide range of symptoms in the victims, from feelings of helplessness, anxiety and fear to feelings of hostility.

Conclusions
In conclusion, the results of this study allow for indicating that the consequences of cyberbullying demand social responses. First, educational approaches promoting equity, respect and tolerance are required, as well awareness of the appropriate and responsible use of communication technologies. Another response to the problem must come from the platform providers that regulate the privacy controls. Also, it is necessary to open legal possibilities to be able to act against the perpetrators. Finally, in the psychological area, it is necessary to design interventions that take into account the age, gender and circumstances of the victims.

Acknowledgments: this project is the result of the work of the National Network of Studies in Violence and Health which is funded by the Teacher Professional Development Program of the Ministry of Public Education.

Acknowledgements
This project is the result of the work of the National Network of Studies in Violence and Health, which is funded by the Teacher Professional Development Program of the Ministry of Public Education.

Conflicts of Interests
The authors declare no conflict of interest.

Bibliography

1. Miller, K. (2017). Cyberbullying and its consequences: How Cyberbullying is contorting the minds of victims and bullies alike, and the Law's limited available redress. Suthern California Interdisciplinary Law Journal, 26, 379-405.
2. Chapin, J. & Coleman, G. (2017). The cycle of cyberbullying: Some experiences required. Social Science Journal, 54(3), 314-316.
3. Mason, K. L. (2008). Cyberbullying: A preliminary assesment for school personel. Psychology in the School, 45(4), 323-348.
4. Smith, P. K. (2000). What good schools can do about bullying. Childhood, 7(2), 193-212.
5. Tokunaga, R. S. (2010). Following you home from school. A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26(3), 277-287.
6. Jenaro, C., Flores, N. & Frías, C. P. (2017). Systematic review of empirical studies on cyberbullying in adults: What we know and what we should investigate. Agression and Violent Behavior, 38, 113-122.
7. WHO. (2002). World Report on Violence and Health: Abstract. Washington, DC: Organization.World Health Organization.
8. Ortega-Ruíz, R., Del-Rey, R. & Casas, J. A. (2013). La Convivencia Escolar: clave en la predicción del Cyberbullying. (School Coexistence: key in the prediction of Cyberbullying). Revista Iberoamericana de Evaluación Educativa, 6(2), 97-102.
9. Willar, N. E. (2007). Cyberbullying and cyberthreats: Responding to the challenge of online social agression,threats, and distress. Champaing, IL.: Research Press.
10. Kota, R., Schoobs, S., Benson, M. & Moreno, M. A. (2014). Characterizing Cyberbullying among College Students: Kacking, Dirty Laundry, and Mocking. Societies, 4(4), 549-560.
11. Hinduja, S. & Patchin, J. W. (2007). Offline consequences of online victimization. Journal of School Violence, 6(3), 89-112.
12. Wang, J., Nansel, T., R. & Ianotti, R. J. (2011). Cyber and traditional bullting: differential association with depression. Journal of Adolescent Health, 48(4), 415-417.
13. Williams, K. R. & Guerra, N. G. (2007). Prevalence and predictors of Internet bullying. Journal of Adolescent Health, 41(6 suppl 1), 14-21.
14. Schenk, A. M., Fremow, W. J. & Keelan, C. M. (2013). Cgaracteristics of college cyberbullies. Computers in Human Behavior, 29(6), 2320-2327.
15. Peluchette, J. V., Karl, K., Wood, C. R. & Williams, J. (2016). Cyberbullying victimization: Do victim' personality and risky social network behaviors contribute to the problem? Computers in Human Behavior, 52, 424-435.
16. Slovak, K., Crabbs, H. & Stryffeler, B. (2015). Perceptions and Experiences of Cyberbullying at a Faith-Based University. Social Work & Christianity, 42(2), 149-164.
17. Wesley, K. & Campbell, M. (2012). Heterosexual and nonheterosesual young university students involvement in traditional and cyber forms of bullying. Cyberpsychology Behavior and Social Networking, 15(2), 649-654.
18. Yubero, S., Navarro, R., Elche, M., Larrañaga, E. & Ovejero, A. (2017). Cyberbullying victimization in higuer education: An exploratory analysis of its association with social and emotional factors among Spanish students. Computers in Human Behavior, 75, 439-449.
19. Duran, M. & Martínez-Pecino, R. (2015). Cyberbullying through Mobile Phone and the Internet in Dating Relationship among Young People. Media Education Research Journal, XXIII(44), 159-167.
20. Prieto, M. T., Carrillo, J. C. & Lucio, L. A. (2015). Violencia virtual y acoso escolar entre estudiantes universitarios: el lado oscuro de las redes sociales. (Virtual violence and bullying among university students: the dark side of social networks). Innovación Educativa, 15(68), 33-47.
21. Faucher, C., Jackson, M., & Cassidy, W. (2014). Cyberbullying among university students. Gendered experiences, Impacts and Perspectives. Educ. Res. Int., 2014(698545), 1-10.
22. Adams, F., & Laerence, G. (2011). Cyberbullying victims: The effects last into college. American Secondary Education, 40(1), 4-13.
23. Aricak, O. T. (2016). The relationship between mental health and cyberbullying. In H. Cowie. & C. A. Myers. (Eds.), Bullying among University Students Cross National Perspectives (pp. 76-90.). London: Routledge.
24. Cassidy, W., Faucher, C. & Jackson, M. (2017). Adversity in University: Cyberbullying and its Impacts on Students, Faculty and Administrators. International Journal of Enviromental Research and Public Health, 14(8), 1-10.
25. Kim, S., Boyle, M. H. & Georgiades, K. (2017). Cyberbullying victimization and its association with health across the life course: A canadian population study. Revue Canadienne de Santé Publique, 108(5-6), 468-474.
26. Lindsay, M. & Krysik, J. (2012). Online Harassment among college students. Inf. Commun. Soc., 15(5), 703-719.
27. Derogatis, J. C. & Cleary, P. (1977). Confirmation of the dimensional structure of the SCL-90: A study in construct validation. Journal of Clinical Psychology, 33(4), 981-989.
28. Estévez, A., Villardón, L., Calvete, E., Padilla, P. & Orue, I. (2010). Adolescent victims of Cyberbullying: Prevalence and Characteristics. Behavioral Psychology, 18(1), 73-89.
29. Alvarez-García, D., Nuñez, J. C., Alvares, L., Dobarro, A., Rodríguez, C., & Gonzalez-Castro, P. (2011). Violencia a través de las tecnologías de la información y la comunicación en estudiantes de secundaria (Violence through information and communication technologies in high school students). Anales de Psicología, 27(1), 221-230.
30. Ortega, R., Calmaestra, J. & Mora-Merchán, J. A. (2008). Cyberbullying. International Journal of Psychology and Psychological Therapy, 8(2), 183-192.
31. Garaigordobil, M. (2011). Prevalencia y consecuencias del cyberbullying: una revisión. International Journal of Psychological Therapy, 11(2), 233-254.
32. Kim, S., Colwell, B. R., Kata, A., Boyle, M. H. & Georgiades, K. (2017). Cyberbullying Victimization and Adolescent Mental Health: Evidence of Differential Effects by Sex and Mental Health Problem Type. Journal of Youth Adolescence, 47(3), 661-672.
33. Casullo, M. M. (2004). Psycho-Pathological Symptoms in Urban Adults. Psychology and Social Science, 6(1), 49-57.
34. Hammen, C. (2009). Adolescent depression stressful interpersonal contexts and risk for recurrence. Current Directions in Psychological Science, 18(4), 200-204.
35. Bor, W., Dean, A., J., Najman, J. & Haydthankhish, R. (2014). Are child and adolescent mental health problems increasing in the 21st Century? A systematic review. Australian and New Zealand Journal of Psychiatry, 48(7), 606-616.
36. Reyns, B. W. (2013). Online Routines and Identity Theft Victimization: Further Expanding Routine Activity Theory beyond Direct-Contact Offenses. Journal of Research in Crime and Delinquency, 50(2), 216-238.
37. Acevedo, J. M. (2016). Intentional infliction of emotional distress torts as the best legal option for victims: When cyberbullying conduct falls throught the cracks of the U.S. Law System, 85, 127-168.
38. Benenson, J. F., Markovits, H., Thompson, M. E., & Wrangham, R. W. (2011). Under threat of social exclusion females exclosure more than males. Psychol. Sci, 22(4), 538-544.
39. Seidel, E. M., Silani, G., Thaler, H., Lamm, C., Gur, R. C., et al. (2013). The impact of social exclusion vs. inclusion on subjective and hormonal reactions in females and males. Psychoneuroendocrinology, 38(12), 2925-2933.
40. William, K. D. (2001). Ostracism: The power of silence. New York: Guldford Press.
41. William, K. D. (2007). Ostracism. Annu. Rev. Psychol, 58, 425-452.