Theoretical framework
The positivist theorists argue that criminal and delinquent behaviors are caused by other factors that are beyond the sphere of free will. These factors are varied and can be biological (genetics), sociological (environment), or psychological (personality, learning) in nature. It is believed that psychological theories are positivist because they strive to explain criminal behavior using factors that are beyond an individual’s control. This paper will make use of two positivist theories – differential association theory and social learning theory – to explain cyberbullying.
Differential association theory
Learning theory approaches to the explanation of criminal behavior have been associated with one of the major sociological theories of crime, the differential association theory. The differential association theory is founded on the idea that the current society has incompatible structures of norms and behaviors. Society also has a contradictory description of suitable behavior that causes individuals to engage in crime (Blackburn 1993).
When individuals directly experience this conflict, they are more likely to engage in acts of crime or delinquency through differential association. In differential association, individuals learn criminal and delinquent behaviour by coming into contact with other delinquents/criminals, more often than not in close and personal groups. In short, peer pressure and the attitudes of peers greatly affect the inclination of an individual to engage in crime.
Similarly, associations with individuals who support delinquent/criminal behaviors also influence individuals to engage in such behaviors. This therefore means that people do not necessarily have to associate with criminals for them to engage in criminal activities. The theory of differential association can apply to cyberbullying in several ways. First and foremost, youth who engage in cyber bullying may do so by associating with peers who cyberbully others. Secondly, the act of cyberbullying may be influenced by the lack of strict disciplinarian acts established by parents and schools. The leniency towards cyberbullying may therefore prompt more children and adolescents to engage in the behavior (Blackburn 1993).
Social learning theory
Social learning theory in psychology is normally linked to the work of Albert Bandura and his study on modeling and imitation. Social learning theory asserts that behaviour can be learned cognitively by observing and imitating the behaviors of other people (Blackburn, 1993). People can imagine themselves in related circumstances and incur related outcomes. When the behavior has been learned it may either be reinforced or discouraged according to the results it produces. Bandura supported a number of the vital notions of the operant conditioning theory; reinforcement, punishment, and motivation (Feldman 1993).
He believed that there are three elements of motivation which include external reinforcement, vicarious reinforcement, and self-reinforcement. External reinforcement is likened to Skinner’s notion of reinforcement. Vicarious reinforcement is obtained from watching other people’s behavior is either reinforced or punished. Self-reinforcement denotes individuals’ sense of pride or the meeting of standards in ones’ behavior. The social learning theory postulates that criminal behavior is learned by observing others. The learning occurs in three settings; the family, established subculture, and the social environment.
The reinforcement for criminal behavior can either be internal or external or both. It can also be in form of tangible or social rewards. Tangible rewards refer to outcomes such as material wealth while social reward refers to intangible rewards such as acceptance by peers or increased self-esteem. The reward mechanism, therefore, plays an important role in the criminal career of individuals. Consistent receipt of punishments following a criminal behavior will discourage an individual from engaging in future criminal behaviors while consistent receipt of positive rewards will encourage future criminal behaviors.
Like the differential association theory, the social learning theory can be used to explain the persistence of cyberbullying in schools. Students can learn cyberbullying from their peers. This behavior can be reinforced if the bullies obtain any tangible or intangible rewards from engaging in the act (Feldman 1993).
Past research studies on cyberbullying
In the last decade, technology has become an essential tool in the lives of children and youth. The youths are heavy consumers and users of electronic communication for instance instant messaging, e-mail, and text messaging. They have also become persistent users of communication-related internet sites such as blogs, and social networking sites such as Facebook and hi-5 (Subrahmanyam and Greenfield 2008).
The internet is not only an important source of information but is also a way for people to connect with their friends and families across the globe. Nevertheless, like other social communication environments, the ability to meet and communicate without harm is significantly reduced in internet-based technologies. Cyberbullying has become one illustration of the potential harm of internet-based social environments.
Subrahmanyam and Greenfield (2008) state that cyberbullying is defined as “an individual or a group wilfully using information and communication involving electronic technologies to facilitate deliberate and repeated harassment or threat to another individual or group by sending or posting cruel text and/or graphics using technological means,” (p.119). The effect of cyberbullying particularly on the emotional and psychological state of the victims is so severe that cases of suicide as a result of cyberbullying have been reported in many countries such as the United States.
The problems caused by cyberbullying have attracted the attention of many scholars who have attempted to investigate the reasons why children and youth engage in the activity. Several research studies have found that cyberbullying occurs across the globe and its incidence is increasing on an annual basis. Wolak, Mitchell, and Finkelhor (2007) found that six percent of youth had experienced cyberbullying in form of threats, rumors, and other unpleasant behavior in the previous year. This figure is almost similar to the result of Ybarra (2004) who found that six and a half percent of youth had been cyberbullied in the previous year.
The figure of cyber victims rose to 30% in the year 2006, according to Patchin and Hinduja’s (2006) study. In this study, the researchers found that “almost 30% of the adolescent respondents had been victims of cyberbullying – operationalized as having been ignored, disrespected, called names, threatened, picked on, or made fun of or having had rumors spread by others,” (Patchin and Hinduja 2006, p.162). In the year 2007, a study conducted by Wolak, Mitchell, and Finkelhor (2007) confirmed that the number of young people who had been cyberbullied stood at 43%.
Traditional bullying versus cyberbullying
Although traditional bullying shares some characteristics with cyberbullying, the two differ in several aspects. First, in traditional bullying, the perpetrators are individuals who are well known by their peers. In cyberbullying, on the other hand, perpetrators are hardly known by others because of the anonymity that is offered by the internet. This element of cyberbullying makes it all the more hurtful because victims are left in the dark as to who the actual perpetrators are (Anderson and Sturm 2007).
Second, in traditional bullying, victims usually share certain characteristics that make them prone to bullying. For instance, the majority of victims are overweight, physically weak, have disabilities, and maybe academically challenged. In cyberbullying, on the other hand, anyone is a potential victim because the vice has no limits (Beale and Hall 2007). Third, traditional bullying almost always takes place in the school compound and during the day.
Cyberbullying on the other hand takes place anywhere and any time, as long as people are connected to the internet. The global nature of the internet also makes it easier for individuals to cyberbully a large number of people in minutes or seconds. This is different from traditional bullying in which the act cannot be carried out on a large number of people within a short duration of time (Kowalski and Limber 2007).
Psychological characteristics of bullies and victims
Despite not having distinct physical features, cyberbullies and their victims have different psychological features, according to several research studies. These studies show that cyberbullies are more likely to be highly emotional and to have low self-control. In addition, cyberbullies are more likely to come from homes in which physical punishment is often used and where parental warmth is minimal or lacking.
On the other hand, victims of cyberbullying are more likely to come from stable homes where physical punishment is hardly used and where parental warmth is abundant. Parents of victims also tend to be over-protective of their children. Such children are likely to have negative attitudes towards violence and therefore develop psychological problems such as depression, phobias, and social anxiety when they encounter cyberbullying (Grene 2003). All in all, bullying hurts the physical and psychological health as well as the academic performance of the parties involved (Ybarra 2004).
Whereas the majority of the above-mentioned studies show incidences of cyberbullying, very few of them show the gender aspect of cyberbullying. In the study by Hinduja and Patchin (2006), 32% of boys and more than 36% of girls had been victimized via the internet. In addition, the socio-economic status of the victims and bullies has not been mentioned. Therefore, there exists a literature gap on the socio-economic factors that may contribute to the prevalence of cyberbullying. This research proposal aims to address this literature gap by studying the socio-economic factors that influence children and youth to engage in cyberbullying.
Research questions
The exploration of the socio-economic factors that affect cyberbullying will be guided by the following questions:
- Do cyberbullying experiences differ between male and female students?
- Does cyberbullying differ from one ethnic group to another?
- If cyberbullying differs with ethnicity, what are the factors that explain such disparities?
- Does household income level affect the prevalence of cyberbullying?
- Does family structure (intact or dysfunctional) affect cyberbullying?
Methodology
A qualitative study will be conducted to examine the issues raised above. The justification for conducting a qualitative study rather than a quantitative study lies in the objectives of the study. The study is not interested in finding out how many socio-economic factors influence children and youth to engage in cyberbullying. It is also not interested in finding out the number of children and youth engaging in or victimized by cyberbullying. Instead, the study wants to understand deeply how socioeconomic factors may force children and youth to engage in or become victims of cyberbullying (Crabtree and Miller 1999). The aim of the study is therefore to seek insight into the causal factors of cyberbullying to find the most effective ways of preventing or minimizing the vice.
Participants and sampling techniques
The participants will consist of self-declared former cyberbullies drawn from five middle schools in New York City. The participants will then be selected from four different ethnic communities in New York State: Caucasian, African American, Mexican American, and Chinese American. Participants will also consist of children and youth of both genders, from different household income levels and different family structures. To ensure that all the groups are well represented in the sample, stratified sampling will be used to select the sample. Stratified sampling will group the participants according to the groups mentioned above. From each group, random sampling will then be used to select participants who will make up the final sample.
Data collection techniques
To conduct the study, two major techniques will be used: in-depth interviews and focus group discussions. The in-depth interview will be conducted with the use of a semi-structured questionnaire. The questionnaire will contain both closed-ended and open-ended questions to allow the researcher to gain more information necessary for the study from the informants. The interview will not be conducted in any organized manner. Instead, the researcher will choose to ask questions in an order that he seems suitable to the informant depending on the direction the interview will take and on the responses given by the informants (Banister, Burman, Parker, Taylor, and Tindall 1994).
Focus groups are “an informal assembly of participants whose opinions are requested about a specific topic,” (Crabtree and Miller 1999, p.56). Focus groups as a method of data collection will classify the participants into smaller groups according to their ethnic origin, gender, family structure, and household income level. The researcher will then conduct discussions with each of these groups to enable him to gain a deeper understanding of the factors that affect each of the participating ethnic communities, genders, and households as far as engaging in cyberbullying is concerned.
In-depth interviews and focus groups are relevant to this study in several ways. First, the two methods require that the researcher should establish a healthy relationship with the informants. The informants should be able to trust the researcher while the researcher should have respect towards the informants irrespective of their conflicting beliefs (Coolican 1994). This is because in-depth interviews and focus groups discussions are conducted through a close and personal interaction between the researcher and informants. Second, the two methods allow the researcher to clarify any vague responses given by the informants.
They also enable him to dig deeper and probe further when he feels that the responses given are short or incomplete and that the informant is holding back useful information. The informants also have the opportunity to provide additional information that they feel would be appropriate to the study. This is useful in any qualitative study because its main objective is to understand the thoughts, feelings, experiences, and opinions of the participants. This can only happen through a deep and extensive interaction between the researcher and the informants.
Data analysis approaches
The analysis of the data collected in the study will be conducted using several steps. The transcripts from the interviews and focus group discussions will be analyzed through thematic content analysis using a mixed coding chart. The themes will be derived from the research questions and theoretical framework. In the first phase, data reduction, the transcripts will be read and the text coded sentence by sentence to identify the main themes presented by the informants. In the second phase, data display, the themes identified by the informants will be classified into a conceptually clustered matrix (Miles and Huberman 1994).
The cross-case analysis will then be used to establish any existing relationships between the themes and to identify converging (themes that are commonly identified and shared by the different groups of participants), diverging (themes that are commonly identified by the informants but whose application differ across the different groups of participants), and marginal themes (themes that are sporadically identified by some of the participants).
The final phase will involve drawing conclusions, making inferences, and providing recommendations to the education institutions based on the findings. In this stage, the interrelationships between the converging, diverging, mirror, and marginal themes will further be examined and studied again to identify the major factors that influence children and young adolescents to engage in cyberbullying. Conclusions will then be drawn from these interrelationships and recommendations made appropriately to help educational institutions and parents solve the problem of cyberbullying.
Ethical issues involved in qualitative research
The nature of qualitative research methods is that the researcher must almost always have close interaction with the informants. This can pose several social or psychological problems to the informants. As a result, various ethical principles must be upheld when conducting qualitative studies (Richards and Schartz 2002). These principles include:
- Informed consent – the researcher should provide the potential participants with detailed information concerning the nature of the study, its benefits, potential harm, and the rights of the participants. Based on this information, the participants can choose to participate or withdraw from the study. The consent given by the participants can be in written, verbal, or taped form and it binds the informants to the study.
- Confidentiality – the researcher should not record any personal information of the informants that could damage their reputation or cause them any problem. In this research, confidentiality is important because the kind of activities that the participants engaged in before is criminal and could land them on the wrong side of the law. Information that should be made anonymous includes names, addresses of the location, and sensitive medical information.
- Protection from harm – the researcher should ensure that the benefits of participating in the study far outweigh the risks. Even then, it is the responsibility of the researcher to protect the participants from inevitable harm such as psychological distress that may be caused by a sensitive issue.
- Reciprocity – the researcher should reciprocate the help given by the informants in terms of useful information. This can be done by giving informal feedback and assisting them if they have a problem that is related to and caused by the research process.
- Feedback of findings – it is the responsibility of the researcher to provide the informants with a copy of the study’s findings once the study is completed. The researcher should also recognize the important role played by the informants in the success of the research and should thank them for their participation (Crabtree and Miller 1999).
Politics of research
This research will be conducted using samples of students from three middle schools based in New York. The study, therefore, relies on the schools for access to the samples. As a result, the researchers are likely to encounter several political issues (Maxfield and Babbie 2009). First is the reputation of the schools from which the samples will be collected. The schools would want p to protect their reputation, for instance, by portraying that they have stringent measures against cyberbullying even if this is not the case. Second, the schools would be interested in the protection of the participants from any possible harm.
The researchers would therefore be put to task to explain how the participants would be protected, for instance, from coming into contact with the criminal justice system. Lastly, the schools may be interested in knowing how their participation would serve their interests rather than the interest of the general public.
Reference List
Anderson, T & Sturm, B 2007, ‘Cyber bullying from playground to computer’, Young Adult Library Services, Winter, pp. 24-27.
Banister, P, Burman, E, Parker, I, Taylor, M & Tindall, C 1994, Qualitative methods in Psychology: A research guide, Open University Press, Buckingham, UK.
Beale, A & Hall, R 2007, ‘Cyber bullying: What school administrators (and parents) can do’, The Clearing House, vol. 81, no. 1, pp. 8-12.
Blackburn, R 1993, The psychology of criminal conduct: Theory, research and practice John Wiley & Sons, Toronto.
Coolican, H 1994, Research methods and statistics in Psychology, 2nd edn, Hodder and Stoughton, London.
Crabtree, B & Miller, W 1999, Doing qualitative research, Sage Publications, Thousand Oak.
Feldman, P 1993, The psychology of crime a social science textbook, Cambridge University Press, Cambridge.
Grene, M 2003, ‘Counseling and climate change as treatment modalities for bullying in school’, International Journal for the Advancement of Counselling, vol. 25, no. 4, pp. 293-302.
Hinduja, S & Patchin, J 2008, ‘Cyber bullying: An exploratory analysis of factors related to offending and victimization’, Deviant Behaviour, vol. 29, no. 2, pp. 129-156.
Kowalski, R & Limber, S 2007, ‘Electronic bullying among middle school students’, Journal of Adolescent Health, vol. 41, pp. 22-30.
Miles, M & Huberman, A 1994, Qualitative data analysis: an expanded sourcebook, 2nd edn, Sage Publications, Thousand Oak.
Patchin, J & Hinduja, S 2006, ‘Bullies move beyond the schoolyard: A preliminary look at cyber bullying’, Youth Violence and Juvenile Justice, vol. 4, no. 2, pp. 148-169.
Richards, H & Schartz, L 2002, ‘Ethics of qualitative research: are there special issues for health service research? Family Practice, vol. 19, pp. 135-139.
Subrahmanyam, K & Greenfield, P 2008, ‘Online communication and adolescent relationships’, The Future of Children, vol. 18, no. 1, pp. 119-146.
Wolak, J, Mitchell, K & Finkelhor, D 2007, ‘Does online harassment constitute bullying? An exploration of online harassment by known peers and online-only contacts’, Journal of Adolescent Health, vol. 41, pp. 51-58.
Ybarra, M 2004, ‘Linkages between depressive symptomatology and internet harassment among young regular internet users’, Cyber Psychology & Behaviour, vol. 7, pp. 247-57.