Abstract

This research study attempted to explore the effects of cyber harassment and traditional harassment on the academic performance of university students. Likewise, investigating the influence of this harassment on substance usage was another prime objective of the study. For this purpose, students of four Lahore based universities (2 public, 2 private) were taken as population. Similarly, using convenience sampling, 150 respondents from each university were selected to meet a total sample of 600 students. For data collection, a cross-sectional survey method was used; however, for data analysis, a one-way analysis of variance was done so that demographics differences could be checked. Whereas Pearson product-moment correlation was applied to tests the relationships between IVs and DVs. Results evidently found that the majority of the students faced one or both types of harassment, i.e. traditional and cyber, which resulted in their indulgence in substance usage practices.

Key Words

Traditional Harassment, Cyber Harassment, Academic Performance, Substance Usage, Drug Abuse, University Students

Introduction

Cyber harassment is relatively a new phenomenon; however, traditional harassment throughout the world is known as one of the most serious issues. Traditional harassment is known as the practice of sharing offensive or threatening content that aims to hit others either by strangers or friends, and it is known as cyber harassment when it is attempted through electronic means, including mobile phones and the internet (Broody & Vangelisti, 2016; Lee & Shin, 2017). Cyber harassment is somehow seen as a result of those online interactions which people usually have using the internet and social networking sites (Izabela, Baldry, Farrington & Llorenta, 2018). It includes mocking, kicking, taunting, hitting, name-calling, making offensive comments, inappropriate messaging and emailing and sending humiliating images via the internet or cell phone (Olweus & Limber, 2018). 

Harassment revolves around three major contributing factors which differentiate it from other fights among friends or relatives, and these include the intention of doing harmful acts to others, repetition of such acts, and power differences (Palermiti, Servidio, Bartolo & Costabile, 2017). Here, the power imbalance is given a special emphasis that talks about the victim’s inability of defending himself (Lee & Shin, 2017). 

Victims of both cyber and traditional harassment face emotional and physical negative effects, which are depression, truancy, anxiety, headaches, tiredness, social isolation, delinquency, sleep disorders, drug usage, suicide ideation and suicide attempts (Sampasa-Kanyinga, 2017; and Zych, Baldry, Farrington & Llorenta, 2019). It is observed that the prevalence of harassment decreases as the person grows up; however, victims who do not address their issues are more likely to face more academic failures (Sampasa-Kanyinga, 2017). And these negative effects sometimes move from adolescence to adulthood (Iranzo, Buelga, Cava & Ortega-Baron, 2019). It’s very unfortunate either to a have very small number of youngsters, mostly students who report their problems to concerned authorities (Yubero, Navarro, Maldonado, Gutiérrez-Zornoza, Elche & Larrañaga, 2019) due to which officials remain completely unaware of harassment issues at their premises (Brody & Vangelisti, 2016).  

Available literature patently shows that most students are the victims of traditional and cyber-harassment. However, research on harassment is still in the infancy stage in Pakistan. For that reason, this study is important to find out the prevalence rate of both traditional and cyber harassment among university students in Pakistan. Secondly, it would intend to know that how these psychological effects then further affect academic performance and substance usage among the students. 

Literature Review

Harassment research finds its roots back to the 1970s when it was initially conducted in Scandinavian countries. However, in 1982, it was given special attention when three old boys of 10-14 years from Norway attempted suicide as a result of the harassment. This incident led to having a countrywide campaign so that Norwegian schools could properly address and resolve this issue (Olweus, 1993). Similarly, in many other countries like Japan, the Netherland, the United States of America, the United Kingdom and Australia, harassment gained more research funding and public attention in the late 1980s and early 1990s.

Traditional harassment has attempted to be defined in multiple ways. Olweus (1996) explains harassment by giving an example of a student who is victimized or harassed getting exposed to negative actions of other students over and over again. He, on the other hand, discusses the power difference phenomenon between victim and harasser. This power imbalance is set on the basis of status, size and strength, which a stronger student possess, whereas a weaker student lacks in it.  

Reed et al. (2019) explain in their study that almost 32% of the students in the age group 12-18 years have reported experiences of harassment during their previous educational year. In a meta-analysis study conducted by Iranzo, Buelga, Cava and Ortega-Baron (2019), the prevalence rate of harassment among youth is approximately 35%, and that is very high. Another meta-analysis of the studies related to harassment elaborates that most harassment cases occur within the premises of schools, colleges, universities or even on their grounds and buses. Even cyber harassment is mostly caused by students’ peers at educational institutes (Gaffney, Farrington & Ttofi, 2019). 

Other than the above-mentioned effects, physical effects like dizziness, stomach aches, headaches, and numbness and sleep disorders are also noticeable among young victims of harassment on a frequent basis (Iranzo, Buelga, Cava & Ortega-Baron, 2019). Moreover, the consequences of harassment are not only limited to effects on the physical and psychological health of the victims; it also manifests their academic performance, class attendance and their withdrawal from the educational institutions (Gaffney, Farrington & Ttofi, 2019). 

Cyber harassment similarly has various definitions, and most of these encompass both types of harassment. As Hinduja and Patchin (2019) define, cyber harassment is an intentional act of harming others through the use of mobile phones, computers and various other available technological devices in a repeated manner. However, Chen (2020) define cyber harassment as an exhibit of cruelty towards others using electronic devices. Further, they define cruelty as sending insulting messages to others, posting or sharing material that is harmful to others, or engaging in any other activity that causes physical or psychological harm to others. 

Hinduja and Patchin are known as the experts in the field of research regarding cyber-harassment as they have been conducting and replicating their studies since 2002 on the topic, and they have surveyed approximately 15,000 students over the years to collect data about their cyber-harassment experiences. In their study conducted in 2015 concluded that the average rate of harassment prevalence among students, from their last few studies, is 26% approximately. 

Thus keeping in mind the already available research studies on this topic, it is concluded that a lot of research has been done in this area, but it is still in the infancy stage in the Pakistani scenario, so it is very important to record the instances of traditional and cyber harassment faced by university students and the effect of these experiences on their academic performances or leading them to substance abuse.




Significance of the Study

Previous studies on the topic conclude that harassment is a public issue that has devastating and tragic consequences on the physical and mental health of victims. Respective governments of countries are now focusing on developing specific laws in order to cater for this issue on a serious level. However, already available research related to harassment are either about the prevalence and/or its psychological, emotional, physical effects. This specific study is different in the sense that traditional harassment and cyber harassment both are taken as independent variables in this research. While academic performance and substance usage among university students are considered as dependent variables of the study. Another significance of this study is that it will contribute to theoretical based literature available on harassment as most of the studies available on the topic lack a theoretical base.




The rationale of the topic

Like other countries, harassment is very common in Pakistan, and the children, youth and women are usually vulnerable to such experiences. But this area is under-researched, and few studies have been conducted until now regarding harassment in Pakistan. This makes it very important to explore this area and is the prime motive to select this topic for research. Furthermore, youth are mostly victims of harassment, but less research has been done on university students, which also serve to be the rationale for selecting university students as the population of the research. 

The objectives of the study are developed as follows: 

i. To find out the effects of cyber harassment and traditional harassment on academic performance.

ii. To explore the influence of cyber harassment and traditional harassment on substance usage.

iii. To examine the role of demographic characteristics in the experiences of traditional and cyber harassment.

The developed research hypotheses for the study are as follows: 

H1: Harassment has a positive relationship with substance usage.

H1a: Cyber harassment positively affects substance usage.

H1b: Traditional harassment positively affects substance usage.

H2: Harassment has a negative relationship with academic performance.

H2a: Cyber harassment negatively affects academic performance.

H2b: Traditional harassment negatively affects academic performance.

H3: Experiences of harassment vary on the basis of age.

H3a: The level of experience of traditional harassment varies with age.

H3b: The level of experiences of cyber harassment varies with age.

Theoretical Framework

The routine activities theory developed by Felson and Cohen (1980) is considered as a subsidiary or supplementary of rational choice theory, and it is further an expansion to lifestyle exposure theory which deals with traditional victimization and cyber victimization (Kennedy & Silverman, 1990). It primarily demands three elements to be present for a crime to occur, i.e. a very motivated offender who carries both criminal intentions as well as skills to perform actions accordingly, a vulnerable target or victim and most importantly, absence of guardians or witnesses who can play their significant role in the prevention of crime (Choi, 2008). 

Meithe and Meier (1994) further elaborate on this point that the routine activities and life of people create situations for them to become a victim of any crime or get involved in the crime themselves.  Similarly, Kalia and Aleem (2017) emphasize the point that the availability of the suitable victim further instigates the already motivated offender to get involved in the crime, and with the absence of a guardian at the offender’s end or/and victim’s end further converts situation to an opportunity for the offender. However, Song, Lynch, Cochran (2016) explains the concept of “suitable victim” with the duration and purpose of internet usage, i.e. people who use the internet for more duration and are involved in different activities that make them susceptible to crime.

This theory is going to learn about the experiences of cyber harassment and traditional harassment faced by University students. Then further, this study will explore the direct effects of these experiences on their academic performance and substance usage. Routine activities theory basically elaborates the factors that are the reason behind any crime incident and also elaborates what makes any person get involved in crime as a culprit or a victim. This theory will guide the research by uncovering the reasons and their activities by which students who have experienced cyber-harassment or traditional harassment became vulnerable to that incident. 

Figure 1

Relationships between Independent and Dependent Variables



Methodology

In accordance with Day, Fish, Perez-Brumer, Hatzenbuehler and Russell (2017), research methodology is basically a science that aims to provide a pathway that how the research would be conducted or a research problem can be resolved. However, a quantitative approach (survey method) has been used in this study. The survey is the method that allows the researchers to draw a representative sample from the population and collect the data on specific research areas through standardized questionnaires (Throsby, Zwar & Morgan, 2017). In the present research, a cross-sectional survey method was used for data collection from the selected sample.

Students enrolled in different public, and private sector universities of Lahore were the universe of this study. While students from all the universities of Lahore was the population for the survey method, who have experienced traditional bullying/cyberbullying or both.

As universities students of Lahore are the population of this study, the HEC ranking of universities was obtained from its official website and keep in mind some points, i.e. universities must be Lahore-based, must have sub-campuses, and must be ranked in the ‘General’ category. 2 universities were selected from the public sector (University of the Punjab and University of Education) as well as 2 universities from the private sector (University of Management & Technology and the University of Central Punjab). After getting the total enrolment of these universities, the evaluated sample size is 600.




Tool for Data Collection

In the present research, the cross-sectional survey method is used for data collection from the selected sample. The proposed survey for this research study has 5 different sections, including Demographics, the Victimization Questionnaire for Traditional harassment, the Cyber Victimization Questionnaire, Academic Performance measurement and the Substance Usage Scale, each of which has its own set of indicators.

The first section of the questionnaire was about the demographics of respondents, including age, gender, education, university etc. The second part was about the experiences of respondents regarding traditional harassment, which was comprised of 11 questions. It was the adapted version of the Bullying & Cyberbullying Scale for Adolescents developed by Ammar (2021). However, the original scale was divided into two sections as ‘Traditional Harassment’ and ‘Cyber Harassment’. Where the second section comprised 9 questions recording the experiences of cyber harassment among university students. The response set for both sections was a 5-point Likert scale (Strongly Disagree to Strongly Agree). Cronbach alpha was applied to calculate the reliability, which was measured as 0.837 for traditional harassment while it was 0.855 for cyber harassment. 

Moreover, the third section of the tool was about the measurement of academic performance of the university students after experiencing traditional harassment, cyber-harassment or both. It was a self-developed questionnaire comprised of 11 questions with an additional question, ‘Grades you usually get’. The reliability obtained for this part is 0.849. In the last, a section for substance usage was developed to find out the drug usage patterns of students after the experience of harassment. It included 10 questions, and reliability for this section was assessed to be 0.859.




Pretesting and Reliability of the Scale

Data are gathered from 50 respondents in order to measure scales’ applicability for the selected population through the application of Cronbach Alpha, and the achieved value is 0.882.

Data Analysis

After collecting the data, SPSS version 26 was used for data entry and its systematic coding for further analysis and interpretation. One-way analysis of variance was applied to check the demographic differences, while Pearson product-moment correlation was applied to tests the relationships between IVs and DVs.

 

Variables

This study takes cyber-harassment and traditional harassment as independent variables during students’ academic performance and their indulgence in substance usage as dependent variables.

 

Cyber Harassment

The use of technology, i.e. mobile phones or/and internet, as a powerful way to reach suitable targets in order to exert their power and control over selected targets is known as cyber harassment (Wang, Chang, Yang, Hu & Yen, 2019). Cyber harassment in the context of this specific study includes practices like transmitting angry messages electronically, cyberstalking (stalking someone’s profile), sending threatening or insulting messages, spreading fake rumors about that person, revealing someone else’s information without permission, and lastly, pretending to be that someone and disseminating wrong messages to damage his/her reputation.

 

Traditional Harassment

Without the use of any technology, harassment that occurs through the physical proximity between victim and culprit is known as traditional harassment (Wang, Chang, Yang, Hu & Yen, 2019). In this research study, traditional harassment will include contacting other people repeatedly without any reason, insulting him/her, threats, touching, bad commenting, and offensive language on the basis of gender or any other specific physical or behavioral characteristic.

 

Academic Performance

The level to which students achieve their educational goals these goals can either be short-term or long-term goals. For instance, completion of a specific degree, diploma or a program etc. (Thakur & Paul, 2017). This research focuses on University students, and their GPA/cgpa before and after the experience of harassment will be compared to measure their academic performance.

 

Substance Usage

It refers to the use of different drugs or alcohol usage to the point of addiction (Ybarra & Mitchell, 2004). In this particular study, substance usage is taken as the usage of different drugs to alter your moods and to get escape from tensed situations to the extent which is not recommended and is harmful to your health.




 

Data Analysis

Table 1. Pearson Product Moment between Traditional Harassment and Substance Usage

		THT	SUST
THT	Pearson Correlation	1	.321**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).

 




Table 1 presents the results of Pearson Product Moment, which was applied to find out the association between traditional harassment and substance usage by the university students as a result. According to the

Table, there found a positive association between the measured variables. Results intricate that experiences of traditional harassment lead the students to substance usage.

However, the obtained R-value shows a moderate correlation (0.321) between the traditional harassment and substance usage as R-value between 0.5-1 is considered to be strong, between 0.30-0.49 is moderate, while below 0.29 is a weak correlation.




 

Table 2. Pearson Product Moment between Cyber Harassment and Substance Usage

		SUST	CHT
SUST	Pearson Correlation	1	.323**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).

 




Table 2 shows the results for Pearson Product Moment, applied to explore the association between cyber-harassment and substance usage by university students. Results present that there found a positive association between the measured variables, which means that experiences of cyber harassment also lead the students to substance usage. However, the obtained R-value shows a moderate correlation (0.323) between traditional harassment and substance usage.




 

Table 3. Pearson Product Moment between Traditional Harassment and Academic Performance

		THT	APT
THT	Pearson Correlation	1	.550**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).

 




Pearson Product Moment test was performed using SPSS to find out the association between traditional harassment and academic performance of the university students, and the results are presented in the above table. The obtained p-value is 0.000, which shows the positive relationship between the two measured variables. However, the obtained R-value shows a very strong relationship (0.550) between the experiences of traditional harassment faced by the university students and their academic performance




 

Table 4. Pearson Product Moment between Cyber Harassment and Academic Performance

		CHT	APT
CHT	Pearson Correlation	1	.512**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).

 




Table 4 presents the results of Pearson Product Moment, which was applied to find out the association between cyber-harassment and academic performance of the university students as a result. According to the table, there found a positive association between the measured variables.

However, the obtained R-value shows a strong correlation (0.321) between traditional harassment and substance usage as R-value between 0.5-1 is considered to be strong, between 0.30-0.49 is moderate, while below 0.29 is a weak correlation.




 

Table 5. Pearson Product Moment between Harassment and Academic Performance

		APT	HT
APT	Pearson Correlation	1	.554**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).




Pearson Product Moment test was performed using SPSS (version 26) to find out the association between harassment and academic performance of the university students, and the results are presented in the above table. The obtained p-value is 0.000, which shows the positive relationship between the two measured variables. However, the obtained R-value shows a very strong relationship (0.554) between the experiences of harassment faced by university students and their academic performance.




 

Table 6. Pearson Product Moment between Harassment and Substance Usage

		HT	SUST
HT	Pearson Correlation	1	.334**
	Sig. (2-tailed)		.000
	N	600	600

**. Correlation is significant at the 0.01 level (2-tailed).

 




Table 6 presents the results of Pearson Product Moment, which was applied to find out the association between harassment and substance usage by university students as a result. According to the table, there found a positive association between the measured variables. Results intricate that experiences of harassment lead the students to substance usage. However, the obtained R-value shows a moderate correlation (0.334) between harassment and substance usage.




 

Table 7. One-Way Analysis of Variance by Age (Traditional Harassment):

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	645.901	4	161.475	1.246	.290
Within Groups	77105.564	595	129.589
Total	77751.465	599

 




The above tables are the presentation of the one-way between-groups analysis of variance (Descriptive and ANOVA), which was conducted to explore the effects of age on traditional harassment. Respondents of the study were divided into five different groups according to their age (Group 1: 18-22; Group 2: 23-27; Group 3: 28-32; Group 4: 33-37; Group 5: 38-42). There found no statistically significant difference in the level of traditional harassment faced by the respondents on the basis of their different age groups as the p-value obtained is greater than 0.50.




 

Table 8. One-Way Analysis of Variance by Age (Cyber-Harassment):

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	1281.400	4	320.350	4.033	.003
Within Groups	47266.465	595	79.439
Total	48547.865	599

 




A one-way between-group analysis of variance was conducted to find out the effects of age on cyber-harassment faced by the participants of the study, and the results are presented in the above tables (Descriptive and ANOVA). Respondents of the study were divided into five different groups according to their age (Group 1: 18-22; Group 2: 23-27; Group 3: 28-32; Group 4: 33-37; Group 5: 38-42). There was found a statistically significant difference between five age groups [F(4, 595)=4.0, p=0.003]. Despite the existence of a statistically significant difference, the actual difference in the mean scores between the five groups was very small. However, the effect size calculated manually using the eta squared was 0.03. Moreover, Post-hoc comparisons were made using the Tukey HSD test intricate that the mean score for Group 1 (M=25.99, SD=9.06) was significantly different from Group 3 (M=31.04, SD=8.53) and Group 4 (M=36.33, SD=4.46).

Discussion

The purpose of conducting this study was to find out the instances of traditional harassment and cyber harassment among different university students and to explore the effects of these incidents on the academic performance of the students and substance usage. For this purpose, the Pearson Product moment (PPM) correlation test was applied to the collected data to find out the association between the measured independent variables and dependent variables. For instance, PPM was applied to find the correlation between experiences of harassment and substance usage of such students. However, it was tentatively assumed in H1(a and b), i.e. ‘Cyber harassment positively affects the substance usage’, and ‘Traditional harassment positively affects the substance usage’ that both the variables have a direct positive relationship and on the basis of findings presented in Table 1 (for H1a) and Table 2 (for H1b) it is evident that more the experiences of traditional harassment, cyber-harassment or both, more will be the chances of students indulging in practices of substance usage. Henceforth, both H1a and H1b are evidently approved, which means overall H1 is approved. The findings of this study endorsed the results of Sampasa-Kanyinga (2017); Zych, Baldry, Farrington and Llorenta (2019).

Similarly, the relationship between harassment and academic performance of university students was explored by applying the Pearson product moment correlation. Results have been presented in Table 3, and Table 4 represent this relationship and are evidence supporting the point that there is a strong association between the two measured variables. But according to H2 (a and b), i.e. ‘Cyber harassment negatively affects the academic performance’ and ‘Traditional harassment negatively affects the academic performance’, it was presumed that experiences of harassment, either traditional, cyber or both, will affect the academic performance of the students in a negative way, i.e. if some student experiences harassment he/she will not perform well in exams or assessments tests, but the findings achieved through PPM were totally opposite of it. Thus both the sub-hypotheses were disapproved on the basis of findings which led to disapproval of the overall hypothesis that there is a negative association between harassment and academic performance. One of the reasons may be the self-esteem they have which is developed over the years, maybe the family support or peers influence which is evident from the literature review. However, in this study, these variables were not included, so the possibility of influence from other factors which led the students to perform well academically despite their traumatic experiences was not assessed in this study. That’s why the findings of this study rejected the findings of Gaffney, Farrington & Ttofi (2019).

Lastly, the difference between the experiences of traditional and cyber harassment among university students on the basis of age was analyzed by applying a one-way analysis of variance for the collected data. One-way ANOVA was applied as our gender has more than two categories, i.e. male, female and transgender otherwise, the t-test was suitable for it. After applying ANOVA, results were displayed in Table 7 and 8, and on the basis of values presented in tables mentioned earlier, both the sub-hypotheses for H3 (a and b), i.e. ‘Level of experiences of traditional harassment varies with age’ was disapproved while ‘Level of experiences of cyber harassment varies with age’ was approved and led to the approval of H3 partially as the developed categories were different from the previous categories of age used by already available literature on the topic so the findings can’t endorse or reject anything but contributed to the body of knowledge already available on this topic.

Conclusion

It is evidently proved by the available literature and statistics that harassment, either in its traditional or cyber form, has become one of the severe issues of the present era. It impacts not only the physical but psychological health of the one who faces it. Well, it is either observed that the youngsters who are just at the start of their life do have larger chances of becoming a victim of it; however, there can be a couple of reasons behind it. Therefore, this study is purposefully conducted on university students so that not only pervasiveness of this stigmatic practice could be measured around, but its effects may also be seen, especially on academic performance and substance usage, which may be taken as an outcome of harassment. 

It is concluded by the results that both types of harassment, i.e. traditional and cyber, have significant influence over substance usage. With increasing cases of harassment, usage of substances, i.e. drugs (prescribed or unprescribed), also increases. All those university students who face harassment are inclined towards such stuff. Probably it alters their moods or helps them getting an escape from such tense situations or painful state of mind, which one goes through after being harassed. On the other hand, it is usually assumed that harassment always creates adverse effects on educational/academic performance, and it seems quite natural that one can’t be able to perform one's duties properly when something unusual happens in his/her life. However, this study has come up with some different results which show that harassment doesn’t affect the academic life of the victims; rather, it increases their motivation level to move ahead and perform well in educational tasks. One of the reasons may be the self-esteem they have which is developed over the years, maybe the family support or peers influence which is evident from the literature review. As far as the role of age is concerned, it doesn’t have any significant influence on traditional harassment where both harasser and victim are known to each other or are in front of each other. However, in cyber harassment, age does matter, and it does make sense as well that with the passage of time and age, one gets sensible and comes to learn very well that how to cater to such situations.      

References

• Brody, N., & Vangelisti, A. L. (2016). Bystander intervention in cyberbullying. Communication Monographs, 83(1), 94-119.
• Chen, J. K. (2020). Cyber victimization, social support, and psychological distress among junior high school students in Taiwan and Mainland China. Asia Pacific Journal of Social Work and Development, 30(3), 150-163. https://doi.org/10.1080/02185385.2020.175 5994
• Day, J. K., Fish, J. N., Perez-Brumer, A., Hatzenbuehler, M. L., & Russell, S. T. (2017). Transgender youth substance use disparities: Results from a population-based sample. Journal of Adolescent Health, 61(6), 729-735.
• Felson, M., & Cohen, L. E. (1980). Human ecology and crime: A routine activity approach. Human Ecology, 8(4), 389-406. https://doi.org/10.1007/bf01561001
• Gaffney, H., Ttofi, M. M., & Farrington, D. P. (2019). Evaluating the effectiveness of school- bullying prevention programs: An updated meta-analytical review. Aggression and Violent Behavior, 45, 111-133. https://doi.org/10.1016/j.avb.2018.07.001
• Hinduja, S., & Patchin, J. W. (2019). Connecting adolescent suicide to the severity of bullying and cyberbullying. Journal of school violence, 18(3), 333-346.
• Iranzo, B., Buelga, S., Cava, M. J., & Ortega-Barón, J. (2019). Cyberbullying, psychosocial adjustment, and suicidal ideation in adolescence. Psychosocial Intervention, 28(2), 75- 81.
• Kalia, D., & Aleem, S. (2017). Cyber Victimization among Adolescents: Examining the Role of Routine Activity Theory. Journal of Psychosocial Research, 12(1). https://www.semanticscholar.org/paper/Cyb er-Victimization-among-Adolescents:- Examining-of-Kalia- Aleem/b844a2c215d2994539a70abc92579af4e 9fdaa86
• Kennedy, L. W., & Silverman, R. A. (1990). The elderly victim of homicide: An application of the routine activities approach. Sociological Quarterly, 31(2), 307-319.
• Lee, J. (2017). Traditional Bullying and Cyberbullying in Childhood and Young Adulthood: Prevalence, Relationship, and Psychological Distress Outcomes among Young Adults. http://purl.flvc.org/fsu/fd/FSU_SUMMER2 017_Lee_fsu_0071E_13968.
• Miethe, T. D., & Meier, R. F. (1994). Crime and its social context: Toward an integrated theory of offenders, victims, and situations. Suny Press
• Olweus, D. (1993). Bully/victim problems among schoolchildren: Long-term consequences and an effective intervention program
• Palermiti, A. L., Servidio, R., Bartolo, M. G., & Costabile, A. (2017). Cyberbullying and self- esteem: An Italian study. Computers in Human Behavior, 69, 136-141.
• Reed, E., Salazar, M., Behar, A. I., Agah, N., Silverman, J. G., Minnis, A. M., ... & Raj, A. (2019). Cyber sexual harassment: prevalence and association with substance use, poor mental health, and STI history among sexually active adolescent girls. Journal of adolescence, 75, 53- 62.
• Sampasa-Kanyinga, H. (2017). Co-occurring cyberbullying and school bullying victimization and associations with mental health problems among Canadian middle and high school students. Violence and victims, 32(4), 671-687.
• Song, H., Lynch, M. J., & Cochran, J. K. (2016). A macro-social exploratory analysis of the rate of interstate cyber-victimization. American Journal of Criminal Justice, 41(3), 583-601.
• Thakur, M. B., & Paul, P. (2017). Sexual harassment in academic institutions: A conceptual review. Journal of Psychosocial Research, 12(1), 33.
• Wang, C., La Salle, T., Wu, C., Do, K. A., & Sullivan, K. E. (2018). School climate and parental involvement buffer the risk of peer victimization on suicidal thoughts and behaviors among Asian American middle school students. Asian American journal of psychology, 9(4), 296
• Ybarra, M. L., & Mitchell, K. J. (2004). Youth engaging in online harassment: Associations with caregiver-child relationships, Internet use, and personal characteristics. Journal of adolescence, 27(3), 319-336
• Yubero, S., Navarro, R., Maldonado, M. J., Gutiérrez-Zornoza, M., Elche, M., & Larrañaga, E. (2019). Bullying and psychological distress in a vulnerable group: youth in residential child care. Journal of Child and Family Studies, 28(9), 2618-2629
• Zych, I., Baldry, A. C., Farrington, D. P., & Llorent, V. J. (2019). Are children involved in cyberbullying low on empathy? A systematic review and meta-analysis of research on empathy versus different cyberbullying roles. Aggression and Violent Behavior, 45, 83-97. https://doi.org/10.1016/j.avb.2018.03.004.