disadvantages of bullying essay

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Cyberbullying: Everything You Need to Know

• Cyberbullying
• How to Respond

Cyberbullying is the act of intentionally and consistently mistreating or harassing someone through the use of electronic devices or other forms of electronic communication (like social media platforms).

Because cyberbullying mainly affects children and adolescents, many brush it off as a part of growing up. However, cyberbullying can have dire mental and emotional consequences if left unaddressed.

This article discusses cyberbullying, its adverse effects, and what can be done about it.

FangXiaNuo / Getty Images

Cyberbullying Statistics and State Laws

The rise of digital communication methods has paved the way for a new type of bullying to form, one that takes place outside of the schoolyard. Cyberbullying follows kids home, making it much more difficult to ignore or cope.

Statistics 

As many as 15% of young people between 12 and 18 have been cyberbullied at some point. However, over 25% of children between 13 and 15 were cyberbullied in one year alone.

About 6.2% of people admitted that they’ve engaged in cyberbullying at some point in the last year. The age at which a person is most likely to cyberbully one of their peers is 13.

Those subject to online bullying are twice as likely to self-harm or attempt suicide . The percentage is much higher in young people who identify as LGBTQ, at 56%.

Cyberbullying by Sex and Sexual Orientation

Cyberbullying statistics differ among various groups, including:

• Girls and boys reported similar numbers when asked if they have been cyberbullied, at 23.7% and 21.9%, respectively.
• LGBTQ adolescents report cyberbullying at higher rates, at 31.7%. Up to 56% of young people who identify as LGBTQ have experienced cyberbullying.
• Transgender teens were the most likely to be cyberbullied, at a significantly high rate of 35.4%.

State Laws 

The laws surrounding cyberbullying vary from state to state. However, all 50 states have developed and implemented specific policies or laws to protect children from being cyberbullied in and out of the classroom.

The laws were put into place so that students who are being cyberbullied at school can have access to support systems, and those who are being cyberbullied at home have a way to report the incidents.

Legal policies or programs developed to help stop cyberbullying include:

• Bullying prevention programs
• Cyberbullying education courses for teachers
• Procedures designed to investigate instances of cyberbullying
• Support systems for children who have been subject to cyberbullying 

Are There Federal Laws Against Cyberbullying?

There are no federal laws or policies that protect people from cyberbullying. However, federal involvement may occur if the bullying overlaps with harassment. Federal law will get involved if the bullying concerns a person’s race, ethnicity, national origin, sex, disability, or religion.

Examples of Cyberbullying 

There are several types of bullying that can occur online, and they all look different.

Harassment can include comments, text messages, or threatening emails designed to make the cyberbullied person feel scared, embarrassed, or ashamed of themselves.

Other forms of harassment include:

• Using group chats as a way to gang up on one person
• Making derogatory comments about a person based on their race, gender, sexual orientation, economic status, or other characteristics
• Posting mean or untrue things on social media sites, such as Twitter, Facebook, or Instagram, as a way to publicly hurt the person experiencing the cyberbullying  

Impersonation

A person may try to pretend to be the person they are cyberbullying to attempt to embarrass, shame, or hurt them publicly. Some examples of this include:

• Hacking into someone’s online profile and changing any part of it, whether it be a photo or their "About Me" portion, to something that is either harmful or inappropriate
• Catfishing, which is when a person creates a fake persona to trick someone into a relationship with them as a joke or for their own personal gain
• Making a fake profile using the screen name of their target to post inappropriate or rude remarks on other people’s pages

Other Examples

Not all forms of cyberbullying are the same, and cyberbullies use other tactics to ensure that their target feels as bad as possible. Some tactics include:

• Taking nude or otherwise degrading photos of a person without their consent
• Sharing or posting nude pictures with a wide audience to embarrass the person they are cyberbullying
• Sharing personal information about a person on a public website that could cause them to feel unsafe
• Physically bullying someone in school and getting someone else to record it so that it can be watched and passed around later
• Circulating rumors about a person

How to Know When a Joke Turns Into Cyberbullying

People may often try to downplay cyberbullying by saying it was just a joke. However, any incident that continues to make a person feel shame, hurt, or blatantly disrespected is not a joke and should be addressed. People who engage in cyberbullying tactics know that they’ve crossed these boundaries, from being playful to being harmful.

Effects and Consequences of Cyberbullying 

Research shows many negative effects of cyberbullying, some of which can lead to severe mental health issues. Cyberbullied people are twice as likely to experience suicidal thoughts, actions, or behaviors and engage in self-harm as those who are not.

Other negative health consequences of cyberbullying are:

• Stomach pain and digestive issues
• Sleep disturbances
• Difficulties with academics
• Violent behaviors
• High levels of stress
• Inability to feel safe
• Feelings of loneliness and isolation
• Feelings of powerlessness and hopelessness

If You’ve Been Cyberbullied 

Being on the receiving end of cyberbullying is hard to cope with. It can feel like you have nowhere to turn and no escape. However, some things can be done to help overcome cyberbullying experiences.

Advice for Preteens and Teenagers

The best thing you can do if you’re being cyberbullied is tell an adult you trust. It may be challenging to start the conversation because you may feel ashamed or embarrassed. However, if it is not addressed, it can get worse.

Other ways you can cope with cyberbullying include:

• Walk away : Walking away online involves ignoring the bullies, stepping back from your computer or phone, and finding something you enjoy doing to distract yourself from the bullying.
• Don’t retaliate : You may want to defend yourself at the time. But engaging with the bullies can make matters worse.
• Keep evidence : Save all copies of the cyberbullying, whether it be posts, texts, or emails, and keep them if the bullying escalates and you need to report them.
• Report : Social media sites take harassment seriously, and reporting them to site administrators may block the bully from using the site.
• Block : You can block your bully from contacting you on social media platforms and through text messages.

In some cases, therapy may be a good option to help cope with the aftermath of cyberbullying.

Advice for Parents

As a parent, watching your child experience cyberbullying can be difficult. To help in the right ways, you can:

• Offer support and comfort : Listening to your child explain what's happening can be helpful. If you've experienced bullying as a child, sharing that experience may provide some perspective on how it can be overcome and that the feelings don't last forever.
• Make sure they know they are not at fault : Whatever the bully uses to target your child can make them feel like something is wrong with them. Offer praise to your child for speaking up and reassure them that it's not their fault.
• Contact the school : Schools have policies to protect children from bullying, but to help, you have to inform school officials.
• Keep records : Ask your child for all the records of the bullying and keep a copy for yourself. This evidence will be helpful to have if the bullying escalates and further action needs to be taken.
• Try to get them help : In many cases, cyberbullying can lead to mental stress and sometimes mental health disorders. Getting your child a therapist gives them a safe place to work through their experience.

In the Workplace 

Although cyberbullying more often affects children and adolescents, it can also happen to adults in the workplace. If you are dealing with cyberbullying at your workplace, you can:

• Let your bully know how what they said affected you and that you expect it to stop.
• Keep copies of any harassment that goes on in the workplace.
• Report your cyberbully to your human resources (HR) department.
• Report your cyberbully to law enforcement if you are being threatened.
• Close off all personal communication pathways with your cyberbully.
• Maintain a professional attitude at work regardless of what is being said or done.
• Seek out support through friends, family, or professional help.

Effective Action Against Cyberbullying

If cyberbullying continues, actions will have to be taken to get it to stop, such as:

• Talking to a school official : Talking to someone at school may be difficult, but once you do, you may be grateful that you have some support. Schools have policies to address cyberbullying.
• Confide in parents or trusted friends : Discuss your experience with your parents or others you trust. Having support on your side will make you feel less alone.
• Report it on social media : Social media sites have strict rules on the types of interactions and content sharing allowed. Report your aggressor to the site to get them banned and eliminate their ability to contact you.
• Block the bully : Phones, computers, and social media platforms contain options to block correspondence from others. Use these blocking tools to help free yourself from cyberbullying.

Help Is Available

If you or someone you know are having suicidal thoughts, dial  988  to contact the  988 Suicide & Crisis Lifeline  and connect with a trained counselor. To find mental health resources in your area, contact the  Substance Abuse and Mental Health Services Administration (SAMHSA) National Helpline  at  800-662-4357  for information.

Cyberbullying occurs over electronic communication methods like cell phones, computers, social media, and other online platforms. While anyone can be subject to cyberbullying, it is most likely to occur between the ages of 12 and 18.

Cyberbullying can be severe and lead to serious health issues, such as new or worsened mental health disorders, sleep issues, or thoughts of suicide or self-harm. There are laws to prevent cyberbullying, so it's essential to report it when it happens. Coping strategies include stepping away from electronics, blocking bullies, and getting.

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By Angelica Bottaro Bottaro has a Bachelor of Science in Psychology and an Advanced Diploma in Journalism. She is based in Canada.

Preventing Bullying: Consequences, Prevention, and Intervention

• Suzanne Le Menestrel National Academies of Sciences, Engineering, and Medicine

Bullying is considered to be a significant public health problem with both short- and long-term physical and social-emotional consequences for youth. A large body of research indicates that youth who have been bullied are at increased risk of subsequent mental, emotional, health, and behavioral problems, especially internalizing problems, such as low self-esteem, depression, anxiety, and loneliness. Given the growing awareness of bullying as a public health problem and the increasing evidence of short- and long-term physical, mental, emotional, and behavioral health and academic consequences of bullying behavior, there have been significant efforts at the practice, program, and policy levels to address bullying behavior. This article summarizes a recent consensus report from the National Academies of Sciences, Engineering, and Medicine, Preventing Bullying Through Science, Policy, and Practice , and what is known about the consequences of bullying behavior and interventions that attempt to prevent and respond to it.

Author Biography

Suzanne le menestrel, national academies of sciences, engineering, and medicine.

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Consequences of Bullying

It is important for parents and people who work with children and adolescents to understand that bullying can have both short- and long-term effects on everyone involved. While most research on bullying has been about children and adolescents who have been bullied, those who bully others are also negatively impacted, as are those who are both bullied and bully others, and even those who are not directly involved but witness bullying.

Children Who Have Been Bullied

Research has found that children and adolescents who have been bullied can experience negative psychological, physical, and academic effects.

Psychological Effects

The psychological effects of bullying include depression, anxiety, low self-esteem, self-harming behavior (especially for girls), alcohol and drug use and dependence, aggression, and involvement in violence or crime (especially for boys). While bullying can lead to mental health problems for any child, those who already have mental health difficulties are even more likely to be bullied and to experience its negative effects.

Cyberbullying – bullying that happens with computers or mobile devices – has also been linked to mental health problems. Compared with peers who were not cyberbullied, children who were cyberbullied report higher levels of depression and thoughts of suicide, as well as greater emotional distress, hostility, and delinquency.

Physical Effects

Bullying and Suicide

Bullying is a risk factor for depression and thinking about suicide. Children who bully others, are bullied, or both bully and are bullied are more likely to think about or attempt suicide than those who are not involved in bullying at all.

The physical effects of bullying can be obvious and immediate, such as being injured from a physical attack. However, the ongoing stress and trauma of being bullied can also lead to physical problems over time. A child who is bullied could develop sleep disorders - such as difficulty falling asleep or staying asleep - stomachaches, headaches, heart palpitations, dizziness, bedwetting, and chronic pain and somatization (i.e., a syndrome of distressful, physical symptoms that cannot be explained by a medical cause).

Being bullied also increases cortisol levels – a stress hormone – in the body, which typically happens after a stressful event. Stress from bullying can impact the immune system and hormones. Imaging studies show that brain activity and functioning can be affected by bullying, which may help explain the behavior of children who have been bullied.

Academic Effects

Research has consistently shown that bullying can have a negative impact on how well children and adolescents do in school. It has a negative impact on both grades and standardized test scores starting as early as kindergarten and continuing through high school.

Children Who Bully and Those Who Witness Bullying

Very little research has been done to understand the effects of bullying on children who bully, and those who witness bullying (e.g., bystanders). More research is needed to understand the consequences of bullying on the individuals who bully others, particularly to understand the differences between those who are generally aggressive and those who bully others.

Studies of children who witness bullying usually focus on their role in the bullying situation (e.g., if they backed up the child who bullied, or defended the victim) and why they did or did not intervene. While studies rarely assess the effects of bullying exposure on the witness, some research has found that bullying witnesses experience anxiety and insecurity based on their own fears of retaliation.

Children Who Bully and Are Also Bullied

Children and adolescents who bully others and who are also bullied are at the greatest risk for negative mental and physical health consequences, compared to those who only bully or are only being bullied. These children and adolescents may experience a combination of psychological problems, a negative perception of themselves and others, poor social skills, conduct problems, and rejection by their peer group.

Compared with non-involved peers, those who have bullied others and have also been bullied have been found to be at increased risk for serious mental illness, be at high risk for thinking about and attempting suicide, and demonstrate heightened aggression.

Exposure to bullying in any manner – by being bullied, bullying others, or witnessing peers being bullied – has long-term, negative effects on children. The School Crime Supplement to the National Crime Victimization Survey found that in 2015, about 21 percent of students ages 12-18 reported being bullied at school during the school year. Given the prevalence of youth exposed to bullying across the nation, it is important to understand the consequences of bullying on children and adolescents, how it relates to other violent behaviors and mental health challenges, in order to effectively address them.

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Source and Research Limitations

The information discussed in this fact sheet is based on the comprehensive review of bullying research presented in the National Academies of Sciences, Engineering, and Medicine’s report entitled Preventing Bullying Through Science, Policy, and Practice .

This report includes the most up to date research on bullying, but it is important to note that this research has several important limitations. Most of the research is cross-sectional, which means it took place at one point in time. This type of research shows us what things are related to each other at that time, but cannot tell us which thing came first or if one of those things caused the other to occur.

Defining school bullying and its implications on education, teachers and learners

Contributing to UNESCO’s work on fostering safe learning environments , which addresses many different forms of violence, the UNESCO Chair on Bullying and Cyberbullying, in collaboration with the World Anti-Bullying Forum (WABF), led an international working group to create a more holistic and inclusive definition of school bullying. Professor James O’Higgins Norman, UNESCO Chair on Bullying and Cyberbullying, shares his insights on this work.

Why revisit the definition of bullying?

Many current anti-bullying programmes in schools are rooted in early definitions characterizing bullying as an “unwanted aggressive behavior that is repeated over time and involves an imbalance of power or strength”. While this was groundbreaking at the time and advanced the work of researchers, policy makers, educators and others, evolving perspectives have deepened our understanding of bullying.

Research shows that progress in reducing school bullying has been slow, with only a 19% decrease in perpetration and a 15% drop in the rate of learners facing bullying. This means we must reassess our understanding and approaches to bullying, especially in our increasingly complex world, where both in-person and online bullying intertwine with personal and societal issues.

How are you revisiting the definition of bullying?

As a UNESCO Chair, my role involves facilitating interdisciplinary research and dialogue, and working towards a more holistic approach to bullying. Our recommendation for a ‘whole-education’ approach to tackle bullying recognizes individual, contextual, and societal dimensions.

With support from UNESCO and the WABF, I facilitated the working group to revisit the definition of bullying, consulting scholars, policymakers and practitioners worldwide. We gathered feedback from a diverse group and have conducted wide consultations. This working group was launched following the recommendations by a Scientific Committee on preventing and addressing school bullying and cyberbullying, convened by UNESCO and the French Ministry of Education, Youth and Sports.

What would a revised definition mean for education policymakers and practitioners, for school communities and learners?

The proposed definition promotes a holistic and inclusion-driven approach to tackling bullying and violence in schools and in online spaces. 

Crafting a more inclusive definition has the potential to break down academic and professional barriers, encouraging cooperation between sectors, and among scholars, policymakers, educators, and learners. It provides a solid foundation to better understand bullying particularly regarding those most marginalized due to appearance, ethnicity, gender, social class, or sexuality, among others. Bullying is a complex issue tied to individual, contextual, and structural factors, making collaboration essential.

Together, we can deepen our understanding and address not only the behavior but also the underlying systems and ideologies supporting bullying.

What is your vision for this improved definition of school bullying?

My vision aligns with United Nations Sustainable Development Goal 4, on education, in that our work on bullying, and all other forms of school violence, is aimed at ensuring an inclusive and equitable quality education and the promotion of lifelong learning opportunities for all. 

What message do you have for teachers and learners?

To teachers and school staff: Do not accept bullying as normal. Create a safe classroom environment by setting clear expectations for kindness and respect, remain vigilant for signs of bullying, stay informed about effective prevention strategies, and promptly address any incidents. Implement a robust anti-bullying policy. Under the idea of a ‘whole-education’ approach, collaborate with colleagues and parents, incorporate empathy and anti-bullying content into the curriculum, and use collaborative learning methods.

To learners: Report bullying, be confident in recognizing and responding to it, and encourage bystander intervention. You have the power to stop bullying.

New definition and what’s next?

The working group presented its proposed revised definition of school bullying at the WABF held in October 2023. The proposed definition reads:

School bullying is a damaging social process that is characterized by an imbalance of power driven by social (societal) and institutional norms. It is often repeated and manifests as unwanted interpersonal behaviour among students or school personnel that causes physical, social, and emotional harm to the targeted individuals or groups, and the wider school community.

This new inclusive definition of school bullying was largely welcomed by delegates at the Forum. The UNESCO Chair and WABF hope that this revised definition will contribute to opening a new chapter in the global conversation on the nature of and responses to bullying and cyberbullying. 

For UNESCO, the new definition of bullying reflects our approach and work to ensure that schools are safe and supportive learning environments. This means that to end all forms of school violence, including bullying, we must understand that these behaviours do not happen in isolation, that there are different drivers of violence, and that a ‘whole-education’ approach is needed. 

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Bullying Essay for Students and Children

500+ words essay on bullying.

Bullying refers to aggressive behavior so as to dominate the other person. It refers to the coercion of power over others so that one individual can dominate others. It is an act that is not one time, instead, it keeps on repeating over frequent intervals.  The person(s) who bullies others can be termed as bullies, who make fun of others due to several reasons. Bullying is a result of someone’s perception of the imbalance of power.

Types of bullying :

There can be various types of bullying, like:

• Physical bullying:  When the bullies try to physically hurt or torture someone, or even touch someone without his/her consent can be termed as physical bullying .
• Verbal bullying:  It is when a person taunts or teases the other person.
• Psychological bullying:  When a person or group of persons gossip about another person or exclude them from being part of the group, can be termed as psychological bullying.
• Cyber bullying:  When bullies make use of social media to insult or hurt someone. They may make comments bad and degrading comments on the person at the public forum and hence make the other person feel embarrassed. Bullies may also post personal information, pictures or videos on social media to deteriorate some one’s public image.

Read Essay on Cyber Bullying

Bullying can happen at any stage of life, such as school bullying, College bullying, Workplace bullying, Public Place bullying, etc. Many times not only the other persons but the family members or parents also unknowingly bully an individual by making constant discouraging remarks. Hence the victim gradually starts losing his/her self-esteem, and may also suffer from psychological disorders.

A UNESCO report says that 32% of students are bullied at schools worldwide. In our country as well, bullying is becoming quite common. Instead, bullying is becoming a major problem worldwide. It has been noted that physical bullying is prevalent amongst boys and psychological bullying is prevalent amongst girls.

Prevention strategies:

In the case of school bullying, parents and teachers can play an important role. They should try and notice the early symptoms of children/students such as behavioral change, lack of self-esteem, concentration deficit, etc. Early recognition of symptoms, prompt action and timely counseling can reduce the after-effects of bullying on the victim.

Get the huge list of more than 500 Essay Topics and Ideas

Anti-bullying laws :

One should be aware of the anti-bullying laws in India. Awareness about such laws may also create discouragement to the act of bullying amongst children and youngsters. Some information about anti-bullying laws is as follows:

• Laws in School: To put a notice on the notice board that if any student is found bullying other students then he/she can be rusticated. A committee should be formed which can have representatives from school, parents, legal, etc.
• Laws in Colleges: The government of India, in order to prevent ragging , has created guideline called “UGC regulations on curbing the menace of ragging in Higher Education Institutions,2009”.
• Cyber Bullying Laws: The victim can file a complaint under the Indian Penal Code .

Conclusion:

It is the duty of the parents to constantly preach their children about not bullying anyone and that it is wrong. Hence, if we, as a society need to grow and develop then we have to collectively work towards discouraging the act of bullying and hence make our children feel secure.

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Health and Medical Blog

Pros and Cons of Cyber Bullying

In today’s world young people have access to the entire world through the use of computers, cell phones, and other electronic devices. The benefits of this have been great, but with the good there has to be the bad. Cyber Bullying is defined as any form of repeated harassment to a person using electronic devices and the internet. It is a growing issue that youth are facing today. Studies have shown that one third of students have faced some form of cyber bullying in their life, that is a startling high amount. While it is hard to imagine any good coming from something so hurtful, could there be pros to go with the cons?

The Pros of Cyberbullying

1. Stand Up For Themselves Cyber bullying often attacks personal traits of an individual, such as their weight, appearance, voice, or values. This can be extremely damaging to a developing child. Cyber bullies often choose this avenue because it can be done from the safety of their home, with no real confrontation. This works both ways, however. Children that are experiencing cyber bullying feel much more empowered to stand up for themselves, because they are also in the comfort of their home.

2. It’s In Writing Social media, texts, and emails are all in writing, and once they are sent they cannot be taken back. This gives hard and undeniable proof that this bullying is occurring, as well as exactly who is involved. It can tremendously help parents and schools to identify who the problem students are and the proper actions to take.

3. From The Bullies Perspective If you are the person who is doing the bullying online, you may feel very confident and courageous when bullying someone from behind a computer. This also often makes people develop an inflated ego and feel “cool”.

The Cons of Cyber Bullying

1. Spreads To Day To Day Life Cyber bullying is very commonly just a side product of real life, face to face bullying that is occurring. This may make the victim feel scared and unsure in there normal days, especially at school or other social situations.

2. Risk of Depression And Suicide An increasing number of young kids are falling into a depressive state, and sadly, committing suicide as a result from this cyber bullying. The abuse is so severe and inescapable that they feel it is their only way out. Young adults and kids are very susceptible to criticism and cruelty because they are still unsure of themselves.

3. Out Of Schools Hands Because cyber bullying doesn’t occur in the school in a literal sense, many schools do not do anything about it. It is not because they don’t care, but the guildelines for discipline and boundaries of when their control stops is unclear when it comes to student’s online lives.

4. It Follows You Traditional bullying, or face to face altercations, doesn’t follow the same rules that cyber bullying does. With traditional bullying the victim can go home and get away from it at some point, they have safety zones and times. However, when it comes to cyber bullying all bets are off. Cell phones and computers are always there, the attacks can happen at any time of the day or night and anywhere. This makes the victims feel completely helpless.

5. Larger Audience Cyber bullying is very much public, and because it is published it has the ability to reach a very broad audience. Furthering the humiliation of the person being harassed.

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Bullying: issues and challenges in prevention and intervention

• Published: 12 August 2023
• Volume 43 , pages 9270–9279, ( 2024 )

Cite this article

• Muhammad Waseem   ORCID: orcid.org/0000-0001-8720-955X 1 , 2 , 3 &
• Amanda B. Nickerson 4  

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Bullying is a public health issue that persists and occurs across several contexts. In this narrative review, we highlight issues and challenges in addressing bullying prevention. Specifically, we discuss issues related to defining, measuring, and screening for bullying. These include discrepancies in the interpretation and measurement of power imbalance, repetition of behavior, and perceptions of the reporter. The contexts of bullying, both within and outside of the school setting (including the online environment), are raised as an important issue relevant for identification and prevention. The role of medical professionals in screening for bullying is also noted. Prevention and intervention approaches are reviewed, and we highlight the need and evidence for social architectural interventions that involve multiple stakeholders, including parents, in these efforts. Areas in need are identified, such as understanding and intervening in cyberbullying, working more specifically with perpetrators as a heterogeneous group, and providing more intensive interventions for the most vulnerable youth who remain at risk despite universal prevention efforts.

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A systematic review and content analysis of bullying and cyber-bullying measurement strategies

Alana m. vivolo-kantor.

a Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, United States

Brandi N. Martell

Kristin m. holland, ruth westby.

b Rollins School of Public Health, Emory University, United States

Bullying has emerged as a behavior with deleterious effects on youth; however, prevalence estimates vary based on measurement strategies employed. We conducted a systematic review and content analysis of bullying measurement strategies to gain a better understanding of each strategy including behavioral content. Multiple online databases (i.e., PsychInfo, MedLine, ERIC) were searched to identify measurement strategies published between 1985 and 2012. Included measurement strategies assessed bullying behaviors, were administered to respondents with ages of 12 to 20, were administered in English, and included psychometric data. Each publication was coded independently by two study team members with a pre-set data extraction form, who subsequently met to discuss discrepancies. Forty-one measures were included in the review. A majority used differing terminology; student self-report as primary reporting method; and included verbal forms of bullying in item content. Eleven measures included a definition of bullying, and 13 used the term “bullying” in the measure. Very few definitions or measures captured components of bullying such as repetition, power imbalance, aggression, and intent to harm. Findings demonstrate general inconsistency in measurement strategies on a range of issues, thus, making comparing prevalence rates between measures difficult.

1. Introduction

Bullying is a form of interpersonal violence that can cause short- and long-term physical, emotional, and social problems among victims, and is, therefore, a serious public health concern ( Copeland, Wolke, Angold, & Costello, 2013 ; Gini & Pozzoli, 2009 ; Nakamoto & Schwartz, 2009 ). However, the magnitude of the problem, the prevalence of bullying behavior, the common antecedents of perpetration, and the consequences of bullying are difficult to interpret because the measurement of bullying remains inconsistent among researchers ( Atik, 2011 ; Furlong, Sharkey, Felix, Tanigawa, & Green, 2010 ). Only recently has the Centers for Disease Control and Prevention (CDC) and the Department of Education (ED) released the first uniform definition of bullying ( Gladden, Vivolo-Kantor, Hamburger, & Lumpkin, 2014 ), however, standardization of bullying measurement 1 is still needed to provide a better understanding of this problem.

Over the past two decades, the concept of bullying has evolved with research. In 1990, Dan Olweus provided a framework for the most widespread contemporary definition of bullying. Specifically, this definition states that bullying includes three key components: intentional aggression, repetition, and a power imbalance ( Olweus, 1993 ). To date, these three components remain a part of the definition of bullying and have been widely used to measure the problem, but they have not been used in a standardized or systematic manner ( Grief & Furlong, 2006 ; Rigby, 2004 ). There has also been much discussion about additional components that may be required for a behavior to be defined as bullying, including the perpetrator’s intent to cause harm and the victim’s report of experiencing harm ( Greene, 2000 ; Smith, del barrio, & Tokunaga, 2013 ; Smith & Thompson, 1991 ).

CDC and ED’s definition of bullying, while similar to previous definitions, introduces some new concepts. Similar to previous definitions, the three main components of unwanted aggressive behavior, observed or perceived power imbalance, and repetition of behaviors are included. However, the definition differs in three ways from other commonly used definitions of bullying. First, the definition requires aggressive behaviors to be unwanted . This helps to exclude rough and tumble play among youth. Second, bullying can involve a single act of aggression if it is perceived to have a high likelihood of being repeated (e.g., may involve threats of future aggression). The intent for this inclusion is to encourage timely intervention at the first sign of these behaviors instead of waiting for multiple incidents of aggression to occur. Third, the current definition excludes teen dating and sibling violence. Other bullying definitions do not distinguish teen and sibling violence from peer violence ( Gladden et al., 2014 ).

Researchers have also modified the scope of bullying by incorporating both direct modes of bullying (e.g., fighting) and indirect modes (e.g., rumor spreading), distinguishing between types (e.g., physical, verbal, and relational), and distinguishing similar and sometimes overlapping constructs, such as peer victimization and peer aggression ( Farrington, 1993 ; Furlong et al., 2010 ; Olweus, 1993 ). Most recently, bullying has been adapted to include “cyber-bullying,” a form of inter-net and electronic harassment ( Tokunaga, 2010 ).

Although research has provided unique perspectives about bullying and improved understandings of the nature of this form of violence, significant inconsistencies still remain with respect to bullying definitions and measurement strategies currently used in studies. These inconsistencies can provide confiicting prevalence estimates and scientific results. A review and meta-analysis of bullying in school-based studies using varying measurement strategies concluded that 53% of students, on average, reported exposure to bullying (as victims, bullies, or bully/victims). However, prevalence ranges drastically for each category; for bullying perpetration, the range was 5% to 44% ( Cook, Williams, Guerra, & Kim, 2010 ). Inconsistent measurement strategies can also increase the difficulty in monitoring the problem through public health surveillance initiatives and evaluating the impact and progress of public health bullying prevention interventions. For example, the Youth Risk Behavior Survey (YRBS) and the School Crime Supplement to National Crime Victimization Survey (NCVS) measure bullying and cyberbullying in drastically different ways. The 2013 YRBS bullying questions starts with “ Bullying is when 1 or more students tease , threaten , spread rumors about , hit , shove , or hurt another student over and over again. It is not bullying when 2 students of about the same strength or power argue or fight or tease each other in a friendly way. During the past 12 months , have you ever been bullied on school property ?” and “ During the past 12 months , have you ever been electronically bullied ? ( Include being bullied through e - mail , chat rooms , instant messaging , Web sites , or texting .)” Using response options of “yes” or “no”, CDC found that 19.6% reported being bullied and 14.8% reported being electronically bullied ( Kann et al., 2014 ). Yet, using the NCVS with a similar age group and time frame, the 2009 results demonstrated larger prevalence rates for school bullying victimization (32%) and smaller prevalence for electronic bullying (4%) ( DeVoe & Murphy, 2011 ). To measure bullying, the NCVS asks youth, “ Now I have some questions about what students do at school that make you feel bad or are hurtful to you. We often refer to this as being bullied. You may include events you told me about already. During this school year , has any student bullied you ? That is , has another student …” followed by a set of seven behavioral questions (i.e., made fun of you, called you names, or insulted you; spread rumors about you; threatened you with harm).

1.1. Goal of the current study

This review identifies various measurement strategies of bullying behaviors among youth and provides suggestions for standardizing measurement for research and surveillance purposes. Specifically, we examined youth bullying measurement strategies to identify variations in data collection methods, terminology used, and definitional components. We provide an overview of reliable measures that identify specific components of bullying (e.g., power imbalance, intention to harm, and repetition) and the content of bullying behaviors (e.g., hitting, kicking, rumor spreading). We also provide an overall assessment of bullying measurement strategies, indicate the usefulness of acknowledged measures, and recognize the next steps to establish a well-constructed measure of bullying behaviors.

2.1. Literature search

A systematic search was conducted for all bullying and cyber-bullying measurement strategies published between 1985 and 2012. First, key search terms were drawn from a review of the literature and included such terms as bully*, violen*, aggress*, victim*, harass*, exclude*, bystand*, measure*, tool*, and survey*. The search terms were used in combination with each other to narrow the search results. For example, the terms “bullying”, “victimization” and “survey” were entered simultaneously to retrieve relevant publications. For a full list of included search terms, please contact the corresponding author of this article.

Using these terms, a search was performed of the following electronic databases: PsychInfo, PsychArticles, MedLine, ERIC, the Psychology and Behavioral Sciences Collection, the Professional Development Collection, SocIndex with Full Text, Expanded Academic Index ASAP, and Science Direct. The abstracts of all relevant articles were screened for inclusion eligibility. When there was sufficient indication that a publication abstract was appropriate for consideration, the publication was retrieved, the full publication was reviewed, and the measure was obtained by contacting authors or copyright holders if it was not available within the publication.

In addition to the search described above, we also included measurement strategies published in the CDC document, “ Measuring Bullying Victimization , Perpetration , and Bystander Experiences: A Compendium of Assessment Tools ” (also known as the Bullying Compendium ) ( Hamburger, Basile, & Vivolo, 2011 ). The Bullying Compendium represents a comprehensive list of bullying measurement strategies used by researchers in the field; however, the Compendium does not provide an in-depth overview of the measures. The current paper, on the other hand, provides a detailed review of constructs measured and definitions used for each bullying measurement strategy, and also identifies advantages and drawbacks of each in an attempt to more consistently guide research efforts.

2.2. Inclusion and exclusion criteria

Measurement strategies included in this study were ones that: (a) assessed bullying behaviors , including physical/psychological bullying and victimization, cyber-bullying/electronic aggression, relational aggression, sexualized and homophobic bullying, and bullying bystander behaviors; (b) was administered to respondents between, but not limited to, age 12 and 20, or administered to parents, teachers, peers, or other individuals who could report on the behaviors of youth within this age range; (c) was developed or revised and examined between 1985 and 2012; and (d) was administered in English. We also reviewed measurement strategies described in published peer-reviewed and non-peer reviewed journals, book chapters, and online sources. Regardless of how the measurement strategy was published, the final inclusion criterion was that (e) the publication included psychometric data. Studies were excluded if they did not meet the abovementioned criteria or the measurement strategy: (a) only assessed beliefs, attitudes, or perceptions; (b) was not a minor adaptation of included measures; (c) did not include psychometric data; (d) was not a scale or index; or (e) explicitly explored workplace bullying. We also excluded measures if we (f) could not retrieve the publication for review after contacting the developer(s).

Minor adaptations were defined as any adaptation that kept intact the response options, time frame, and content of the items. In most cases, minor adaptations included decreasing the number of items. In several situations, measures were shortened to improve reliability and validity. In these situations, both measures were included and reviewed. Also, this review focuses on measures that can be defined as scales or indices. Scales are defined as multiple items that measure only one concept using the same or similar response options, while indices include multiple questions with different response options that may not be correlated with other index items ( Bollen & Lennox, 1991 ; DiIorio, 2006 ; Salazar, DiClemente, & Crosby, 2011 ). We have excluded one-item scales because these typically lack precision, may change over time, and are narrowly defined ( Spector, 1992 ). One-item measures of bullying victimization and perpetration typically involve assessing whether an individual has ever experienced a behavior. While this may be relevant information for assessing bullying prevalence, these measures do not provide a thorough understanding of bullying behaviors.

2.3. Search results

The search began in October, 2012 and concluded in April, 2013. Over 1000 publications were screened, and a total of 164 bullying measures were deemed relevant for abstract screening. Following abstract screening, the publications for 69 measurement strategies were retrieved and reviewed for eligibility. Twenty-eight were subsequently excluded because they failed to meet our inclusion criteria. Forty-one publications met the inclusion criteria and were included in this review. Fig. 1 provides detailed information regarding reasons for publication exclusion.

PRISMA flow of information through the different phases of a systematic review.

2.4. Data extraction and coding process

2.4.1. data extraction form.

A data extraction form was developed to capture all information required to complete this review. The standardized form included 32 questions covering a range of information. The form included two items on publication information: publication type (e.g., journal versus report) and publication year. We collected data on sample size characteristics, including the total number of participants in the sample, the target age range, and the target grade level. The form was also used to collect information about the measurement strategy implementation setting (e.g., school-based survey, clinic-based survey) and location (e.g., domestic vs. international).

The field currently uses an array of terminology and definitions to describe bullying ( Swearer, Siebecker, Johnsen-Frerichs, & Wang, 2010 ). The extraction form captured information about how the authors described bullying in each publication. For example, some publications used the term “peer victimization” or “peer aggression” when describing bullying. Our form also captured information on whether participants were provided a specific definition of bullying and if so, what information the definition encompassed. Because little consensus exists among researchers regarding which components should be included in a bullying definition ( Gladden et al., 2014 ), we noted which of the five most commonly used components, if any, were included (i.e., power imbalance, repetition, intent to harm, victim experiences harm, and intentional aggressive behaviors).

The reliability and validity of each measure were recorded. In situations where the primary publication used for coding referenced a different publication when discussing psychometric data, the study team retrieved and coded that publication only for psychometric data.

We captured data specific to each measurement strategy such as the author-reported type(s) of bullying included in the measure (i.e., relational, verbal, physical, indirect, and/or direct). We also noted the reporter for each strategy (e.g., youth self-report, peer nomination), the number of items in the measure, the response options (e.g., yes/no, Likert scale), the time frame assessed (e.g., past week), whether the measurement strategy specifically included the term “bullying”, how the measure was scored, and if the measure captured victimization, perpetration, or bystander experiences.

Because of potential differences between the manner in which the author defined bullying and the measures administered, we captured data on the components that were measured. For example, if a measure assessed repetition, a description of how repetition was measured (e.g., one incident occurring over a span of time, more than one incident involving the same perpetrator or group of perpetrators) was subsequently recorded. Similarly, we specified how power imbalance was measured (e.g., perpetrator(s) has more physical strength, multiple perpetrators, perpetrator(s) is more popular). In addition, we captured data on the content of behaviors assessed by each measure such as hitting, kicking, throwing objects, destructing property, spreading rumors, name calling, homophobic teasing, and threatening.

2.4.2. Coding process

Prior to coding all publications, all four members of the study team independently coded the same publication. After confirming high levels of agreement across coders and coding form questions using Cohen’s kappa (range per question κ = 0.82–1.00) ( Landis & Koch, 1977 ), each publication was coded independently by two study team members. The two coders assigned to each publication subsequently met to discuss any discrepancies. When two coders did not agree on a code, the other team members were consulted and provided recommendations, so that a consensus was reached among all team members.

2.5. Data analyses

IBM SPSS Statistics 21 was used to conduct analyses focused on characterizing the features of included measurement strategies with frequencies and other descriptive statistics. In several situations, specifically those requiring analysis of responses to open-ended questions from the data extraction form, new variables were created to re-code the data extracted from the measurement strategies.

To best capture pertinent information about the content of bullying behaviors assessed by each measure, a summative, or manifest, content analysis ( Potter & Levine-Donnerstein, 1999 ) was completed, where the appearance of particular content within the items (e.g., hit, kick, or push) was coded and grouped to include all similar contents in each measure. Using the example provided above, all items that included hitting, kicking, or pushing of another youth were combined to form a content area of “physical bullying”. This process was used to determine all relevant bullying behavior contents. A total of 17 behavior content categories were identiied.

3.1. Measurement strategy characteristics

Of the 41 included measurement strategies, most were published in peer-reviewed journal articles (n = 39, 95.1%) between 1988 and 2012, with the majority published after 2003 (n = 27; 65.8%). Measures were administered among samples within the United States (n = 19, 46.3%) and internationally (n = 15, 36.6%), as well as in multiple countries simultaneously (n = 3, 7.3%). The mean sample size was 1089 (SD = 1638; range, 47–8693). Almost all measurement strategies were implemented in schools (n = 38, 92.8%), but several were implemented in other settings such as prisons (n = 1, 2.4%) and by mail (n = 1, 2.4%). One setting (2.4%) was unknown. The included measures were administered among youth between the ages of 3 and 25; the average age range was 10.59–15.73 years. Table 1 provides more information on measure characteristics.

Characteristics of the 41 included measures.

3.1.1. Terminology and types of bullying

The use of varying terminology by authors was captured in this review. The majority described bullying as the behavior(s) assessed by the measure (n = 29, 70.7%); however, a notable proportion used the terms “peer victimization” (n = 14, 34.1%) and “peer aggression” (n = 12, 29.3%) to describe the behaviors they measured. About a third of the strategies used the term bullying either as a precursor to the measure (e.g., “How did you get bullied?” followed by several behavioral items) ( Swearer & Cary, 2003 ) or as an item within the measure (e.g., “I was bullied at school,” [( Hinduja & Patchin, 2010 )]) (n = 13, 31.7%). In most cases, youth self-report of bullying behavior was the primary assessment method (n = 35, 85.4%), followed by peer nomination (n = 9, 22%). Occasionally (n = 4, 9.7%), self-report and peer nomination were used together. In two measures, self-report, peer nomination, and teacher-report were used in conjunction.

The author-reported type(s) of bullying were captured for 38 of the 41 measures (7.3% were unknown). Most often, authors described the inclusion of items assessing verbal forms of bullying (n = 34, 82.9%), followed by direct bullying (n = 30, 73.2), physical bullying (n = 29, 70.7%), relational bullying (n = 22, 53.7%), indirect bullying (n = 17, 41.5%), and cyber-bullying (n = 7, 17.1%). For 29 measures (70.7%), the authors stated that physical and verbal bullying were both included, while no authors said physical, verbal, and relational bullying were all included in the measurement strategy. However, 13 (31.7%) authors stated that physical, verbal, and indirect bullying were measured.

3.1.2. Assessment of behavioral content

The content of the items included in the measures also varied drastically across publications. While we captured the author-stated type of bullying being measured as mentioned earlier (i.e., physical, verbal, relational, cyber, indirect, direct, other), a more in-depth content analysis of the measures’ items was conducted to accurately categorize the behavioral content. Table 2 lists the 17 behavioral content categories developed by analyzing the items in all measures and reports the measures that assessed each construct. Many measures included items on making fun/teasing/embarrassing others (n = 33, 80.5%), physical bullying (n = 32, 78%), specific name calling (n = 30, 73.2%), threatening others (n = 25, 61%), socially excluding others from groups or activities (n = 23, 56.1%), and making rude comments and gestures (n = 22, 53.7%).

Behavior content of the 41 included measures.

3.1.3. Use of definitions and measuring definitional components

Eleven measurement strategies (26.8%) included a definition of bullying. Among those with definitions, less than half (n = 4, 36.4%) captured all five components (i.e., power imbalance, intention to harm, victim experiences harm, repetition, and aggressive behaviors) recommended by the field ( Gladden et al., 2014 ; Olweus, 1993 ) for inclusion in a bullying definition. Three (27.2%) captured four components, and four (36.4%) captured three or less. The components most often included in the definition were power imbalance (n = 9, 81.8%), intention to cause harm (n = 9, 81.8%), aggressive behaviors (n = 8, 72.7%), repetition (n = 7, 63.6%), and victim experiences harm (n = 6, 54.5%).

Because most measures did not include an explicit definition of bullying, we identified which components of the recommended bullying definition were assessed by the measure (e.g., inclusion of items or response options that allowed for a power imbalance to be measured). Regardless of whether a definition was provided, items measuring aggressive behaviors were included most often (n = 39, 95.1%), followed by repetition (n = 32, 78%), intention to harm (n = 26, 63.4%), victim experiences harm (n = 16, 39%), and power imbalance (n = 9, 22%). When segregating the data by those measures with and without a definition, Fisher’s exact test yielded no significant differences at the p = 0.01-level for the definitional components actually measured in the scale or index.

For the 32 measures where repetition was denoted, the study team determined how repetition was measured. In about half of these measures (n = 17, 53.1%), authors used broad frequency response options for each behavioral item such as “How often have you taken things from other students?” with response choices “never”, “sometimes”, and “often” ( Raine et al., 2006 ). In the rest of the measures (n = 15, 46.9%), repetition was assessed using the actual number of times the incident occurred (e.g., “Some kids call each other names such as gay, lesbo, fag, etc. How many times in the last week did you say these things to a friend?” Response options included never, 1 or 2 times, 3 or 4 times, 5 or 6 times, and 7 or more times) ( Poteat & Espelage, 2005 ).

When a power imbalance was denoted in the measurement strategy (n = 9), the same process as was used for repetition was implemented. Most often (n = 5, 55.6%) items included mention of the perpetrators’ physical strength (e.g., “Please think about the main person or leader who did these things to you in the past month. How physically strong is this student?” Response options included “less than me”, “same as me”, and “more than me”) ( Felix, Sharkey, Green, Furlong, & Tanigawa, 2011 ), followed by items describing multiple perpetrators (n = 3, 33.3%) (e.g., “In the past month a group of kids tried to beat me up.” Response options included never, once or twice, three or four times, and five or more times) ( Peters & Bain, 2011 ), perpetrators who were older/in a higher grade (n = 3, 33.3%), perpetrators who were more popular (n = 1, 11.1%), perpetrators who were adults (n = 1, 11.1%), and perpetrators who were smarter (n = 1, 11.1%). Table 3 provides additional information about the measures that included definitions, the components included in the definition, and a detailed breakdown of these components.

Definition characteristics and measured components of included measures.

3.2. Scoring strategies

Scoring strategies for each measure varied by publication. However, in over half of the measures (n = 21, 51.2%), responses were summed to yield a total score for the overall scale/index or subscale. This summed score was then used as a continuous outcome variable where higher scores were predictive of higher levels of perpetration, victimization, or bystander experiences. Eleven measures (26.8%) classified bullying into binary categories by either summing across responses and dichotomizing based on “never” versus “ever” or creating binary categories by using a cut-off score. For example, the Traditional Bullying and Cyber-bullying Scale ( Hinduja & Patchin, 2010 ) creates a summed score for each subscale (e.g., bullying victimization, bullying perpetration, cyber-bullying victimization, and cyber-bullying perpetration) and then dichotomizes each subscale into “never/once or twice” to denote no or low frequency of bullying versus “three or more times” to denote higher frequency of bullying. In another example, the California Bully Victimization Scale ( Felix et al., 2011 ) categorized participants into “bullied victims” by using a cut-off score where youths were classified as bullied victims if they reported victimization of one type of bullying (i.e., teasing) at least 2–3 times a month or more and endorsed at least one type of power imbalance. Scoring for measures that included peer nomination (n = 5, 12.2%) was mostly determined by calculating an individual score for each youth nomination and summing across all categories (i.e., victimization or perpetration). The Participant Role Questionnaire ( Salmivalli & Voeten, 2004 ) computes youths’ peer-evaluated sum scores on each of the five subscales and divides by the number of peer evaluators, which produces a continuous score from 0 (never) to 2 (a lot) for each student on each subscale. Scores range from 0 to 24 for victimization and 0 to 20 for perpetration, with higher scores indicating more experiences as a victim or bully.

3.3. Validity and reliability

All included measurement strategies reported validity and/or reliability statistics. However, not all strategies reported the same types of statistics. Specifically, 13 (31.7%) reported several types of validity tests such as face; construct (e.g., convergent and discriminant); and criterion validity (e.g., concurrent and predictive). For construct validity, scales were compared to other bullying scales such as the Olweus Bully/Victim Questionnaire ( Solberg & Olweus, 2003 ) or The Swearer Bully Survey ( Swearer & Cary, 2003 ); teacher assessments and observations; and other student self-report measures such as prosocial behaviors or other behavioral or attitudinal predictor variables. Other scales, for example the Multidimensional Peer-Victimization Scale ( Mynard & Joseph, 2000 ), compared several bullying-related questions to ensure convergent validity. Youth were first asked to self-report victimization by answering yes or no to the question, “Have you ever been bullied?” and were grouped into “victims” and “non-victims.” Then youths responded to 16 behaviorally-based items that began with, “How often during the last school year has another pupil done these things to you?” Specific items included called me names, punched me, and made other people not talk to me. Comparisons found convergent validity with significant mean differences on self-reports of being bullied between victims and non-victims among all four main factors—physical victimization, verbal victimization, social manipulation, and attacks on property.

Of the 41 measurement strategies, 37 (90.2%) reported Cronbach’s alpha for internal consistency, 11 (26.8%) reported test–retest reliability statistics, and one (2.4%) reported split-half reliability. See Table 3 for details on the reliability of each measure.

3.3.1. Internal consistency

Internal consistency ranged from α = 0.25–0.96 (mean = 0.82) for overall bullying perpetration and α = 0.68–0.97 (mean = 0.84) for overall bullying victimization.

3.3.2. Test–retest reliability

Only one measure reported an overall test–retest (i.e., perpetration and victimization combined) correlation; r = 0.79 when youth ages 10–13 were surveyed two weeks apart. Test–retest correlations for victimization ranged from r = 0.61–0.94 (mean = 0.82) and perpetration ranged from r = 0.76–0.90 (mean = 0.83).

3.3.3. Split-half reliability

One measure reported split-half reliability, where the measure was split into two sections and scores for each section were compared to determine consistency in measurement. These correlations ranged from r = 0.55 to r = 0.82.

4. Discussion

The aim of the current study was to conduct a systematic review and content analysis of bullying measures administered to youth, teachers, and parents in an effort to gain a better understanding of the strategies employed and the specific components of bullying being measured. Findings suggest that there are important discrepancies between bullying measurement strategies, such as the time frame used to assess when bullying occurred, the components included in bullying definitions, and the behavioral content of measures provided to participants. Of the 41 measures included in this review, most were implemented in school settings, and very few measured bullying occurring outside of schools or in homes. Cyber-bullying, which has traditionally been viewed as an issue not addressed by schools, was not assessed by most of the measures included in this study.

The most predominant method used to assess bullying was youth self-report. While self-report has been the most widely used method, many have suggested that challenges exist in using this method as the sole strategy to collect information on an individual’s behavior ( Furlong, Sharkey, Bates, & Smith, 2004 ; Leff, Power, & Goldstein, 2004 ). Because it is important to achieve the most accurate assessment of the frequency and magnitude of these behaviors, multiple methods should be considered. For instance, prevalence estimates may increase as the awareness of what constitutes bullying increases, thus self-report alone may not be sensitive enough to detect real changes in the rate of bullying. In addition, the field knows very little about the accuracy of self-report bullying measurement. Only a handful of studies have introduced peer nomination, school records, or parent report to supplement information gleaned from youth self-report ( Cornell & Brockenbrough, 2004 ; Leff et al., 2011 ), and only four measures in this review used multiple reporters to assess bullying. In fact, research by Cornell and Brockenbrough (2004) found very low agreement among student self-report, peer nomination, and teacher nomination of students as victims of bullying in a rural sample of middle school youth. Interestingly, they found better agreement between peer nomination and teacher nomination at identifying both bullying perpetrators and victims. Because this research raises concern about the sole use of student self-report measurement methods, future research should aim to implement multiple-source reporting to assess bullying behaviors with a national sample of youth.

Regardless of reporting method, almost all of the measures in this review captured both victimization and perpetration of bullying. With increasing evidence that youth are often both victims and perpetrators, it is important to continue to capture both behaviors in measurement. These individuals, also called “bully/victims,” report negative outcomes as much as, if not more than, individuals who are only victims or only perpetrators ( Haynie et al., 2001 ; Nansel, Craig, Overpeck, Saluja, & Ruan, 2004 ; Veenstra et al., 2005 ). In this review, few measures included items to better understand bystanding or witnessing behaviors even though there is mounting evidence that bystanders or witnesses also experience similar deleterious effects of bullying ( Nishina & Juvonen, 2005 ; Rivers, Poteat, Noret, & Ashurst, 2009 ). Without capturing victimization, perpetration, and bystanding behavior measurement, it could be more difficult to target interventions for those most at risk.

The field of bullying is in desperate need of uniform terminology and definitions to describe these behaviors ( Swearer et al., 2010 ; Vivolo, Holt, & Massetti, 2011 ). In this review, authors used several terms to discuss bullying behaviors, including peer victimization and peer aggression. The use of inconsistent terminology is problematic for several reasons. First, specific to peer victimization and peer aggression, the term “peer” denotes someone of equal status, age, or grade. However, one of the key constructs in bullying definitions, as mentioned earlier, is the presence of a power differential or imbalance in the relationship between the victim and the perpetrator. Thus, this terminology is in direct conflict with the construct of bullying.

Second, there is a growing literature that distinguishes aggression, fighting, and even legally-defined harassment, from bullying ( Crick & Dodge, 1996 ). Many researchers have developed subscales that measure fighting separate from bullying. For example, analyses of the Illinois Bully Scale ( Espelage & Holt, 2001 ; Espelage, Low, Rao, Hong, & Little, 2013 ) have demonstrated using confirmatory factor analysis that the items capturing physical fighting result in a subscale different from bullying, which included behaviors such as teasing other students, upsetting other students for the fun of it, excluding others from their group of friends, helping to harass other students, and threatening to hit or hurt another student. It is possible that these forms of aggression and violence differ by perceived reasoning and decision processes. Research by Crick and Dodge (1996) interpreted the differences between children who use proactive (i.e., a deliberate behavior to obtain a desired goal) and reactive (i.e., a response driven by anger, frustration, or provocation) aggression. Additionally, there is some evidence that interventions that target physical fighting and other forms of aggression or youth violence are unsuccessful in preventing bullying behaviors ( Espelage, Low, Polanin, & Brown, 2013 ; Taub, 2002 ; Van Schoiack-Edstrom, Frey, & Beland, 2002 ), and some bullying prevention programs are not effective at preventing violence and aggression ( Ferguson, San Miguel, Kilburn, & Sanchez, 2007 ). This illustrates the need to address bullying as a distinct construct that should be examined separately from physical fighting and aggression that is neither repeated, nor involves a power imbalance.

Further, this review uncovered 13 measures that included the term bullying in their strategy and 11 that included a bullying definition. Using the term bullying without providing additional guidance for youth in the form of a definition or list of behaviors may be problematic, as research is mixed on how youth perceive this term. Smith, Cowie, Olafsson, and Liefooghe (2002) found that terms like “bullying” and “picking on” clustered together while terms such as “harassment” and “intimidation” fell into a separate cluster; thus, these terms are not always synonymous with bullying. Using the term bullying in measurement may also impact prevalence. Results from Kert, Codding, Tryon, and Shiyko (2010) show that youth reported significantly less bullying behavior when the word “bully” was provided in a measure than youth not provided a measure with the term included. Another problem with using the term “bullying” in measurement is the fact that recent research suggests that youths may not perceive bullying as researchers do. Land (2003) presented several terms to students (i.e., teasing, bullying, and sexual harassment) and asked them to provide examples of what constituted these terms. The author found that a key component of bullying (e.g., repetition) was not included in students’ examples. Similarly, research from Vaillancourt et al. (2008) revealed discrepancies with respect to youths not including power imbalance and intentionality in a definition of bullying.

Skepticism around using a researcher-developed definition without explicit examples of bullying behaviors has increased over time. Vaillancourt et al. (2008) found that students who were given a definition of bullying in measurement reported less victimization than students who were not provided a definition. This finding has important implications for establishing accurate prevalence rates of bullying. In the current review, the components most often included in the definitions of bullying that prefaced bullying measures were power imbalance, intention to cause harm, and aggressive behaviors, and only four measures included all five components of bullying as recognized by experts in the field. The exclusion of specific components of bullying behaviors from measures of bullying calls into question the validity of the construct being measured.

The vast majority of publications included in this review did not provide a definition in their measurement strategy. Without a presented definition it remains unclear what the author’s a priori definition of bullying included. The current review provides a thorough examination of how measurement strategies with and without explicit definitions integrate the definitional components of bullying and can be used as a guide for bullying researchers in their plans for measuring bullying-related behaviors. Because bullying has been used as a catch-all phrase to encompass a broad category of behaviors (i.e., physical, verbal, relational), Cornell, Sheras, and Cole (2006) have asked “whether all these forms of bullying are psychologically equivalent.” For example, several definitions include multiple behaviors such as hitting, teasing, and spreading rumors; however, incorporating these behaviors in the same definition may fail to capture the nuances associated with each type of behavior.

The time frames used for reporting also vary drastically based on measurement strategy. In fact, most of the measures included in the review did not provide a specified time range, which presents problems in terms of both comparing bullying rates within the sample of interest and between multiple samples. Among those that did provide a time frame, there were variations in the time frames assessed (e.g., nine used the time frame “past 30 days”, four used “past 7 days/week”, two used “current school year”). Although these variations in reporting periods may seem slight, the differences can result in great disparities in prevalence estimates, particularly depending on the time of year when measures are administered. For example, measures administered in September with the time frame “past 30 days” may have students reporting on behaviors that occurred over the summer; a similar measure administered in February would likely yield different results, given that school is in session in the month of January and therefore the opportunity for bullying perpetration/victimization is theoretically higher. Further, four measurement strategies instructed youths to indicate the frequency with which behaviors occurred with respect to other time frames, such as “recently”. Estimating prevalence rates using such broad terms can be problematic since individuals may interpret the meanings of such terms differently. Overall, the differences in reporting time frames make comparing prevalence rates between samples difficult, if not impossible.

Almost all of the included measures provided Likert-type response options, less than half used binary response options (e.g., yes/no, true/false) or open-ended questions, and two used multiple choice responses to assess bullying behaviors. The variation in response options likely impacts not only overall prevalence rates, but also the kind of information being reported. For instance, responses to open-ended questions may garner more or less detail about bullying behaviors, depending on the extent to which the respondent elaborates. Again, based on the various response options used in different measurement strategies, comparing prevalence rates of bullying overall, or even specific components of bullying behavior, becomes nearly impossible, as there is no clear way to draw parallels between behaviors that occur, for instance, “frequently” as judged by a 5-point Likert-type response option to those that have occurred at least once as judged by a “yes” response to a binary item.

Finally, in terms of scoring the measures that assess bullying behaviors, it is difficult to synthesize results across measures. Most often, measures were summed to yield a total score and then characterized as continuous. Eleven measures created binary categories by either summing across responses and dichotomizing based on “never” versus “ever” or creating binary categories by using a cut-off score. Five used peer nomination strategies by which youths identified peers as victims, bullies, and/or bully/victims. The characterization of bullying in a sample greatly depends on how measures are scored and on how bullies and victims are identified. Thus, scoring techniques are critical in establishing accurate estimates of bullying rates.

In addition to the variability in establishing solid prevalence estimates based on the criteria described earlier, most bullying measurement strategies used in the field lack sufficient psychometric properties, including reliability and validity. These characteristics are fundamental to accurately assessing bullying prevalence. In this review, almost all studies reported moderate to high reliability for their measures, indicating that they consistently yielded similar findings, but most did not assess the validity of the measure, thus leaving the question of whether the surveys accurately measured what they aimed to measure unanswered. Those that did assess validity mostly reported low convergent, discriminant, concurrent, and predictive validity, suggesting that these measures did not clearly assess the intended construct(s). While it is important for measures to be reliable so that researchers can be sure that they are consistently measuring their construct of interest, reliability does not imply validity. It is critical that researchers aiming to assess bullying behaviors are accurately measuring those behaviors, not only in terms readily interpreted by the researchers themselves, but also in terms that recognize the differing perspectives of the youths being surveyed. Thus, in future implementation of measurement strategies, researchers should determine both the reliability and validity of their measures.

4.1. Research limitations

There are several limitations of this review. One particular limitation is that several measures were excluded due to developer non-response to repeated emails for additional information. It is possible that the measures not included based on this factor may be different from the ones included, thus affecting our results. Second, the publications with enough information to describe the measurement strategy tended not to include prevalence data, and therefore we were unable to analyze the data on prevalence by measurement strategy. Next steps should determine how to capture best the relevant prevalence or incidence data to make comparisons across measurement strategies. Lastly, very few measures meeting our inclusion criteria included cyber-bullying items or were dedicated solely to measuring cyber-bullying behavior. A systematic review of cyber-bullying measurement conducted by Berne et al. (2013) included only measures that assessed web-based or electronic bullying behaviors. The authors found that very few cyber-bullying measures stated that their aim was to measure bullying, nor were most measures assessed for reliability and validity. Additional research is needed to better integrate cyber-bullying measures with traditional bullying measurement. Despite these limitations, the results of this study still provide important information about the measures currently being used to assess bullying behaviors, including the measurement strategies employed and the behavioral content assessed by the measures.

4.2. Conclusion

There is much inconsistency in the manner in which bullying is measured by researchers. These inconsistencies range from differences in terminology and temporal referent period to differences in definitional components and actual behaviors measured by the surveys. While these inconsistencies may seem minor, they most likely explain the wide variation in bullying prevalence rates obtained by researchers in the field. Our results further highlight the need for a consistent definition of bullying, which has major implications for the measurement of the construct and the prevention of its occurrence. Future research should focus on integrating a honed definition of bullying into the development of new or improved measurement strategies so that bullying can be more accurately and precisely assessed.

Acknowledgments

The authors would like to thank Dr. Laura Salazar for contributing feedback on drafts of the manuscript.

1 The term “measurement strategy” is used in this article to encompass the methods used to assess bullying such as reporter type, time frame, and content of behaviors. When the term “measure” is used, we are specifically describing the items and response options that comprise each scale or index.

Financial disclosure

The authors have no financial relationships relevant to this article to disclose.

Conflict of interest

The authors have no conflicts of interest to disclose.

All authors certify that the abovementioned manuscript represents valid work and not been submitted for publication elsewhere. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Funding source

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Home — Essay Samples — Social Issues — Bullying — Bullying In Schools: Causes, Effects, And Solutions

Bullying in Schools: Causes, Effects, and Solutions

• Categories: Bullying Youth Violence

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Words: 1534 |

Published: Dec 16, 2021

Words: 1534 | Pages: 3 | 8 min read

Works Cited

• Bradshaw, C. P., Sawyer, A. L., & O'Brennan, L. M. (2007). Bullying and peer victimization at school: Perceptual differences between students and school staff. School Psychology Review, 36(3), 361-382.
• Espelage, D. L., & Swearer, S. M. (2003). Research on school bullying and victimization: What have we learned and where do we go from here?. School Psychology Review, 32(3), 365-383.
• Hinduja, S., & Patchin, J. W. (2018). Cyberbullying fact sheet: Identification, prevention, and response. Cyberbullying Research Center.
• National Bullying Prevention Center. (2021). Resources. https://www.pacer.org/bullying/resources/
• National Center for Education Statistics. (2022). Student reports of bullying and cyberbullying: Results from the 2020–21 School Crime Supplement to the National Crime Victimization Survey. US Department of Education.
• Olweus, D. (2013). School bullying: Development and some important challenges. Annual Review of Clinical Psychology, 9, 751-780.
• Patchin, J. W., & Hinduja, S. (2020). School climate 2.0: Preventing cyberbullying and sexting one classroom at a time. Corwin Press.
• StopBullying.gov. (2021). Prevent bullying. https://www.stopbullying.gov/prevention/index.html
• Thompson, F., Smith, P. K., & Rigby, K. (2022). Addressing bullying in schools: Theory and practice. Routledge.
• Ttofi, M. M., & Farrington, D. P. (2011). Effectiveness of school-based programs to reduce bullying: A systematic and meta-analytic review. Journal of Experimental Criminology, 7(1), 27-56.

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Anti-bullying programs in schools may do more harm than good.

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Bullying can exact a huge emotional and mental toll on the victims (Pic: Getty Creative)

Anti-bullying programs in schools may be doing more harm than good.

Programs that enlist fellow students to intervene or help support the victim can lead to an increase in bullying and make it worse for the victims, according to a new study.

Peer involvement is a popular feature of anti-bullying programs at many schools, prompted by the belief that they can prove more effective than teacher-led interventions alone.

This has seen many schools train students as playground buddies, given the job of trying to solve problems between children without the need for adult involvement.

Previous research has shown that the actions of bystanders, such as laughing or joining in, can intensify bullying, while the majority of playground incidents have been found to stop within 10 seconds of a peer intervention.

But there is little evidence that it was the peer interventions themselves that caused the bullying to stop, and no indication that training peers to intervene would have the same effect as spontaneous interventions based on feelings of empathy and injustice, according to the researcher behind the new study.

Instead, she identified that training peers to get involved in a bullying incident could increase both the severity of victimization and the level of distress among victims.

Victims can feel disempowered if peers intervene to protect them, the presence of trained anti-bullying students can actually reinforce or provoke bullying, and interventions can erode wider peer support for the victim, the study found.

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‘Many school bullying prevention programs encourage and train peer bystanders (helpers) to get actively involved in assisting with possible instances of bullying,’ said Karyn L. Healy, research officer from QIMR Berghofer Medical Research Institute and the University of Queensland, Brisbane, author of the study.

‘Although this approach is very common and well-intentioned, there is no evidence that it helps victims. Encouraging peers to actively defend victims of bullying may actually produce adverse outcomes for victims.’

Involving other students can make an incident more public, which can damage the victim’s social status, while if peers step in then it stops the victim from dealing with it themselves, making them look weak in the eyes of the bully, Healy said.

Students trained in intervention strategies may feel it gives them higher status or may enjoy the feeling of belonging, potentially leading them to misuse their power and intervene where it was not necessary, she added.

The apparent success of anti-bullying programs involving peers may be due to other elements of the strategies, such as staff training and interventions, parent newsletters or lessons incorporating anti-bullying messages, according to the study, published today in Child Development Perspectives, the journal of the Society for Research in Child Development.

Evaluation of anti-bullying programs can also often be based entirely on whether bullying incidents have fallen, and does not always take into account the overall impact on the victim, Healy said.

Instead, schools should focus on strategies that examine the outcomes for victims, as well as on the bullying incidents themselves.

Approaches are likely to be more effective if they support victims to stand up for themselves, are motivated by genuine empathy, rather than a desire to help, and do not provoke bullies or increase the visibility of victimization, Healy added.

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Anti-Bullying Programs: Do they Help or Hurt?

Lucy Lawrence

EL Haynes PCS

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We all know those signs: the ones about reporting bullying and speaking out-the signs in every school hallway. Those signs that, like most kids, you never give a second glance. Do those signs and other more assertive anti-bullying programs actually help reduce bullying? According to research, they don’t have much of an impact at all. In fact, bullying and anti-bullying efforts have almost synonymous results because both have negative effects on people’s futures.

As bullied children grow older, their social and emotional lives tend to be less content than people who were not bullied. Bullied children tend to become less mentally stable when they get older, compared to their non-bullied counterparts. This could mean that kids who were bullied end up less happy when they get older, or it could even mean that being bullied as a child could increase the chance of someone getting mentally sick when they’re older. A study of roughly 18,000 kids in Europe tracked how bullying, or the lack thereof, affected them later in life. “The researchers found that people who were bullied either occasionally or frequently continued to suffer higher levels of psychological distress decades after the bullying occurred.”(Kaplan, paragraph 6). This evidence shows that anyone who is bullied, whether it’s often or not, ends up suffering from it years later. As a result, bullying affects people’s brains and makes them less psychologically healthy in the future.

Bullying also causes people to become more anti-social. “Adults who were bullied as kids were more socially isolated too. At age 50, bullying victims are less likely to be living with a spouse or a partner; less likely to have spent time with friends recently; less likely to have friends or family to lean on if they got sick.” (Kaplan, paragraph 8). This shows that people who are bullied end up less mentally stable, that they don’t have many friends, and that they isolate themselves. People who were bullied, overall, end up with a much sadder life than those who weren’t bullied. It’s important that we recognize the significance of bullying and the effect it has on the victim’s mental health, even if the amount of bullying is small, it will still change someone’s life, be it in a small way or a life altering way.

Anti-bullying programs are not as distinguished and effective as they could be, and sometimes have the opposite effect they were intending. In fact, anti-bullying programs can lead to children getting bullied more often. For example, in an article from USA Today by Amanda Oglesby, it talks about how teens experience bullying in schools with anti-bullying programs compared to those in schools without programs. “In the study of 7,000 students ages 12 to 18 who completed a survey in the 2005-06 school year, researchers found that a higher percentage of students who attended schools with anti-bullying programs had reported experiencing bullying than in schools without programs.” (Oglesby, paragraph 4). The fact that more students are bullied in those schools with the program is proof that anti-bullying programs don’t work, according to those who know best: the students.

In the same article, the author elaborates on why the anti-bullying programs don’t work. “…bullies may simply choose not to practice prevention techniques, or perhaps, learned more effective bullying techniques through the programs.” (Oglesby, paragraph 6). This shows that anti-bullying programs aren’t only defective due to the fact they don’t do much to prevent bullies, but also because they are helping bullies become better at being bullies. So even if anti-bullying programs were intended to be helpful, they end up hurting more than doing good.

Some believe that anti-bullying programs are at least making kids more aware of bullying, and that helps to slow bullies from harming other students, but that doesn’t necessarily mean it’s true. In one article, the author makes the claim that children in communities with the anti-bullying programs are more likely to report bullying than children without that resource. “Students who are aware of bullying because of programs report it more often than children who know little about it.” (Oglesby, paragraph 6). Children reporting bullying is a start, but all that’s saying is that students are reporting bullying. It isn’t saying anything about how adults then react to said report. Adults and administrators could just ignore these kids who are reporting all this bullying. The people who have the power could not be doing anything, which could be a major factor in the statistics. The adults who have the power to change the situation are not doing everything necessary to solve the problem.

Another recent study shows that the results of anti-bullying programs show little progress. “…investigations into harassment, intimidation or bullying happened in New Jersey schools in the 2012-2013 school year…that number decreased by nearly 5,000 from the prior year- a decrease of 19%…” (Oglesby, paragraph 9). Even though the number of bullying investigations has gone down by 5,000, or 19%, is 19% really a significant difference, considering the time and money put into these anti-bullying programs? For these reasons, anti-bullying programs may help kids report more bullying, but it doesn’t really help with how administrators and teachers respond to said bullying. And, the actual results show that they don’t help as much as was intended.

Bullying is a huge problem, and it changes children’s lives forever, but the methods that are being used to combat bullying today aren’t working. In some cases, these anti-bullying programs are even making bullying worse. At some schools, the teachers monitor kids more carefully, checking in and watching in the hallways. This may be a very invasive option, but it really helps more than any poster or bullying awareness assembly. We need to find an anti-bullying program that works, holding both the students and teachers accountable of making the school a better place.

Works Cited

Kaplan, Karen, “Victims of Bullying Live With the Consequences for decades, study says,” LA Times, April 2014.

Oglesby, Amanda, “Researchers Unsure of Success of Anti-Bullying Programs,” Asbury Park USA Today 20 Mar. 2014, News sec. Web

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Benefits to Bullying

Just because it's mean doesn't make it maladaptive..

Posted November 29, 2015 | Reviewed by Ekua Hagan

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When it comes to assessing hypotheses of evolutionary function, there is a troublesome pair of intuitions which frequently trip many people up.

The first of these is commonly called the naturalistic fallacy, though it also goes by the name of an appeal to nature: the idea that because something is natural, it ought to be good. As a typical argument using this line might go, because having sex is natural, we ought to — morally and socially — approve of it. The corresponding intuition to this is known as the moralistic fallacy: If something is wrong, then it’s not natural (or, alternatively, if something is good, it is natural ). An argument using this type of reasoning might (and has, more or less) gone, because rape is morally wrong, it cannot be a natural behavior. In both cases, "natural" is a bit of a wiggle word but, in general, it seems to refer to whether or not a species possesses some biological tendency to engage in the behavior in question.

Put another way, "natural" refers to whether a species possesses an adaptation(s) that functions so as to bring about a particular outcome. Extending these examples a little further, we might come up with the arguments that, because humans possess cognitive mechanisms which motivate sexual behavior, sex must be a moral good; however, because rape is a moral wrong, the human must not contain any adaptations that were selected for because they promoted such behavior.

This type of thinking is, of course, fallacious, as per the namesakes of the two fallacies. It’s quite easy to think of many moral wrong which might increase one’s reproductive fitness (and thus select for adaptations that produce them), just as it is easy to think of morally-virtuous behaviors that could lower one’s fitness: infanticide is certainly among the things people would consider morally wrong, and yet there is often an adaptive logic to be found in the behavior; conversely, while the ideal of universal altruism is praised by many as morally virtuous, altruistic behavior is often limited to contexts in which it will later be reciprocated or channeled towards close kin. As such, it’s probably for the best to avoid tethering one’s system of moral approval to natural-ness, or vice versa; you end up in some weird places philosophically if you do.

Now, this type of thinking is not limited to any particular group of people: Scientists and laypeople alike can make use of these naturalistic and moralistic intuitions (intentionally or not), leading to cases where hypotheses of function are violently rejected for even considering that certain condemned behaviors might be the result of an adaptation for generating them, or other cases where weak adaptive arguments are made in the service of making other behaviors with which the arguer approves seem more natural and, accordingly, more morally acceptable.

With that in mind, we can turn to the matter of bullying : aggression enacted by more powerful individuals against weaker ones, typically peaking in frequency during adolescence . Bullying is a candidate behavior that might fall prey to the former fallacies because, well, it tends to generate many consequences people find unpleasant: having their lunch money taken, being hit, being verbally mocked, having slanderous rumors about them being spread, or other such nastiness. As bullying generates such proximately negative consequences for its victims, I suspect that many people would balk at the prospect that bullying might reflect a class of natural, adaptive behaviors, resulting in the bully gaining greater access to resources and reputation; in other words, doing evolutionarily useful things. Now that’s not to say that if you were to start bullying people you would suddenly find your lot in life improving, largely because bullying others tends to carry consequences; many people will not sit idly by and suffer the costs of your bullying; they will defend themselves. In order for bullying to be effective, then, the bully needs to possess certain traits that minimize, withstand, or remove the consequences of this retaliation, such as a greater physical formidability than their victim, a stronger social circle willing to protect them, or other means of backing up their aggression.

Accordingly, only those in certain conditions and possessing particular traits are capable of effectively bullying others (inflicting costs without suffering them in turn). Provided that is the case, those who engaged in bullying behaviors more often might be expected to achieve correspondingly greater reproductive success, as the same traits that make bullying an effective strategy also make the bully an attractive mating prospect. It’s probably worse to select a mate unable to defend themselves from aggression, relative to one able and willing to do so; not only would your mate (and perhaps you) be exploited more regularly, but such traits may well be passed onto your children in turn, leaving them open for exploitation as well. Conversely, the bully able to exploit others can likely can access to more plentiful resources, protect you from exploitation, and pass such useful traits along to their children. That bullying might have an adaptive basis was the hypothesis examined in a recent paper by Volk et al (2015). As noted in their introduction, previous data on the subject is consistent with the possibility that bullies are actually in relatively better condition than their victims, with bullies displaying comparable or better mental and physical health, as well as improved social and leadership skills, setting the stage for the prospect of greater mating success (as all of those traits are valuable in the mating arena). Findings like those run counter to some others suggestions floating around the wider culture that people bully others precisely because they lack social skills, intelligence , or are unhappy with themselves. While I understand that no one is particularly keen to paint a flattering picture of people they don’t like and their motives for engaging in behavior they seek to condemn, it’s important to not lose sight of reality while you try reduce the behavior and condemn its perpetrators.

Volk et al (2015) examined the mating success of bullies by correlating people’s self-reports of their bullying behavior with their reports of dating and sexual behavior across two samples: 334 younger adolescents (11-18 years old) and 143 college freshman, all drawn from Canada. Both groups answered questions concerning how often they engaged in, and were a victim of, bullying behaviors, whether they have had sex and, if they had, how many partners they’ve had, whether they have dated and, if so, how many people they’ve dated, as well as how likable and attractive they found themselves to be. Self-reports are obviously not the ideal measures of such things, but at times they can be the best available option.

Focusing on the bullying results, Volk et al (2015) reported a positive relationship between bullying and engaging in dating and sexual relationships in both samples: controlling for age, sex, reported victimization, attractiveness , and likability, bullying not only emerged a positive predictor as to whether the adolescent had dated or had sex at all (about 1.3 to 2 times more likely), but also correlated with the number of sexual and, sometimes, dating partners; those who bullied people more frequently tended to have a greater number of sexual partners, though this effect was modest (bs ranging from 0.2 to 0.26). By contrast, being a victim of bullying did not consistently or appreciably affect the number of sexual partners one had (while victimization was positively correlated with participant’s number of dating partners, it was not correlated with their number of sexual partners. This might reflect the possibility that those who seek to date frequently might be viewed as competitors by other same-sex individuals and bullied in order to prevent such behavior from taking place, though that much is only speculation).

While this data is by no means conclusive, it does present the possibility that bullying is not indicative of someone who is poor shape physically, mentally, or socially; quite the opposite, in fact. Indeed, that is probably why bullying often appears to be so one-sided: those being victimized are not doing more to fight back because they are aware of how well that would turn out for them. Understanding this relationship between bullying and sexual success might prove rather important for anyone looking to reduce the prevalence of bullying. After all, if bullying is providing access to desirable social resources – including sexual partners – it will be hard to shift the cost/benefit analysis away from bullying being the more attractive option barring some introduction of more attractive alternatives for achieving that goal. If, for instance, bullying serves a cue that potential mates might use for assessing underlying characteristics that make the bully more attractive to others, finding new, less harmful ways of signaling those traits (and getting bullies to use those instead) could represent a viable anti-bully technique.

As these relationships are merely correlational, however, there are other ways of interpreting them. It could be possible, for example, that the relationship between bullying and sexual success is accounted for by those who bully being more coercive towards their sexual partners as well as their victims, achieving a greater number of sexual partners, but not in the healthiest fashion. This interpretation would be somewhat complicated by the lack of sex differences between men and women in the current data, however, as it seems unlikely that women who bully are also more likely to coerce their male partners into sex they don’t really want. The only sex difference reported involved the relationship between bullying and dating, with the older sample of women who bullied people more often having a greater number of dating relationships (r = 0.5), relative to men (r = 0.13), as well as a difference in the younger sample with respect to desire for dating relationships (female r = 0.28, male r = 0.03). It is possible, then, that men and women might bully others, at least at times, to obtain different goals , which ought to be expected when the interests of each sex diverge. Understanding those adaptive goals should prove key for effectively reducing bullying; at least I feel that understanding would be more profitable than positing that bullies are mean because they wish to make others as miserable as they are, crave attention , or other such implausible evolutionary functions.

Volk, A., Dane, A., Marini, Z., & Vaillancourt, T., (2015). Adolescent bullying, dating, and mating: Testing an evolutionary hypothesis. Evolutionary Psychology , DOI: 10.1177/1474704915613909

Jesse Marczyk, Ph.D. , studies evolutionary psychology and writes the blog Pop Psychology.

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• Why people have fallen out of love with dating apps

Tinder and Bumble are struggling as singles refuse to pay up

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W hen Tinder , a mobile dating app, launched on college campuses in America in 2012, it quickly became a hit. Although online dating had been around since Match.com, a website for lonely hearts, launched in 1995, it had long struggled to shed an image of desperation. But Tinder, by letting users sift through photos of countless potential dates with a simple swipe, made it easy and fun.

Soon Tinder and its rivals had transformed courtship. A report published last year by the Pew Research Centre found that 30% of American adults had used an online dating service, including more than half of those aged between 18 and 29. One in five couples of that age had met through such a service. Usage surged during the pandemic, as lonely locked-down singles sought out partners. The market capitalisation of Bumble, a rival to Tinder, surged to $13bn on its first day of trading in February 2021. Later that year the value of Match Group, which owns Tinder, Hinge and scores of other dating services, reached nearly $50bn. Today roughly 350m people around the world have a dating app on their phone, up from 250m in 2018, according to Business of Apps, a research firm. In June Tokyo’s government even said it would launch a matchmaking app of its own to pair up singles in the city.

Yet lately online dating has lost its spark. The apps were downloaded 237m times globally last year, down from 287m in 2020. According to Sensor Tower, another research firm, the number of people who use them at least once a month has dwindled from 154m in 2021 to 137m in the second quarter of this year (see chart 1). On August 7th Bumble reported revenue growth of just 3%, year on year, in the quarter from April to June, and lowered its forecast for the full year to 1-2%. Its shares plunged by a third in after-hours trading. On July 30th Match Group reported that its revenue for the same quarter grew by only 4%. Both companies’ market values have cratered since Bumble’s listing (see chart 2). That reflects users’ increasing disillusionment with dating apps, decreasing willingness to pay for them—and growing interest in offline alternatives.

Start with the disillusionment. Apps that once felt fun have, for many, become wellsprings of frustration. The network effects that initially propelled services such as Tinder, in which a widening choice of partners lured in ever more users, have now made them exasperating. Users grumble about spending hours sorting through tens of thousands of profiles. Half of women surveyed by Pew said they felt overwhelmed by the number of messages they received. It doesn’t help that 84% of Tinder users are men. So are 61% of those on Bumble, which is targeted at women. Many users also fret about scams.

Younger adults are growing especially weary of the apps. One survey commissioned last year by Axios, a news site, found that only a fifth of American college students were using them at least once a month. “It’s not fun, it’s so superficial and it’s also just like really exhausting,” laments one youthful influencer on TikTok, a short-video app. “I’m kind of over it,” sums up Wunmi Williams, a 27-year-old who, after years of swiping and matching, has been unable to find a partner through a dating app. In a sign of growing despair, the Marriage Pact, an annual event in which participants are matched with a “backup” spouse should their future romantic endeavours fail, has spread to 88 college campuses across America.

All this helps explain why dating-app developers are struggling to convince users to part with cash—the second reason for their lacklustre performance. In an effort to boost margins, dating apps have been peddling paid upgrades to supplement their lowly ad revenues. Hinge has a separate feed with popular profiles it thinks you might like, but demands that you hand over $3.99 for a “rose” before you can chat with them. Tinder’s paid plans range from $17.99 a month (which gives you unlimited swipes and lets you change your location) to a hefty $499 a month (which lets you see the most popular profiles on the app and message users you haven’t matched with).

Got the ick

Online dating may no longer look desperate, but users seem to worry that paying for it might. The share of people who are willing to spend money on dating apps has been falling. Tinder’s paid users have declined for seven consecutive quarters. Men are more likely to cough up, which may be worsening the feeling common among women of being bombarded by messages on the apps.

Perhaps the biggest threat to the future of dating apps, though, is the growing share of singles looking offline for love. Last year some began wearing an aqua-coloured ring, made by a startup called Pear, to show their openness to being wooed. Thursday, a company that organises in-person events for singles, has expanded its service to roughly 30 cities, from Stockholm to Sydney. Its app works only on Thursday, when the events are held.

The romance is not confined to bars. Running clubs have become a place for athletic types to meet. Cooking classes, too, have become a place to look for partners, says Julia Hartz, the boss of Eventbrite, a ticketing platform. Attendance at its singles events rose 42% between 2022 and 2023. “You are bonding with someone, you’re having an experience, even if they’re not the love of your life,” says Casey Lewis, a blogger on youth culture, of such events.

Dating apps are looking for ways to lure users back. Some are hoping to spice things up with artificial intelligence ( AI ). Whitney Wolfe Herd, Bumble’s founder, recently mused that the future of courtship could involve one person’s AI bot going on “dates” with another’s. One new app, Volar, has begun offering just that.

In time, society might be willing to leave matchmaking to machines—but it is hard to imagine the strategy paying off just yet. A more fruitful approach for dating apps may instead be to focus on narrower markets. Grindr, an app for gay men, continues to grow quickly. So does Feeld, which targets the polyamorous. In the past few years Match Group has launched apps targeted at gay men (Archer), single parents (Stir), ethnic minorities ( BLK , Chispa) and snobs (The League). Revenue from this portfolio of brands grew by 17%, year on year, in the second quarter of 2024.

In addition to offering a smaller pool of partners, such apps also serve as a community for like-minded people. Grindr, for example, acts as a travel guide for tourists looking for gay bars and a hub for information on HIV . The company says its average user sends 50 messages a day, about the same as for WhatsApp, a messaging service. Its success in that regard might explain why Lidiane Jones, the chief executive of Bumble, has said she wants her firm to be known as a “connections company, rather than a dating company”. Pulling off such a rebrand may prove tricky. But love has never been an easy business. ■

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This article appeared in the Business section of the print edition under the headline “Swiped out”

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