15 Bystander Effect Examples

The bystander effect refers to an emergency situation in which the people witnessing the emergency do not offer help. It is a social phenomenon caused by group dynamics, groupthink, and deindividuation.

This phenomenon was first researched by social psychologists Darley and Latané in 1968 after a widely publicized event of the bystander effect that took place in New York City.

Even though most people would like to think that they would help an innocent person in an emergency, it turns out that there are numerous factors that decrease the likelihood of helping.

As research by Darley and Latané over several years has delineated, the presences of other witnesses create a diffusion of responsibility.  

Diffusion of responsibility refers to the fact that the more people that are present, the less responsibility each one feels.

“When there are several observers present, however, the pressures to intervene do not focus on any one of the observers; instead the responsibility for [bystander] intervention is shared among all the onlookers and is not unique to any one. As a result, no one helps” (Darley & Latané, 1968, p. 378).

In addition, failure to interpret the situation as an emergency can also be affected by the reactions of others. If no one seems to be panicked, then each person misinterprets the matter as not constituting an emergency. This is referred to as pluralistic ignorance.

Bystander Effect Examples

• The restaurant emergency: A person in a crowded restaurant begins to cough loudly, but other patrons continue dining and do not help.
• The injured pedestrian: An individual is lying motionless on the side of a busy road. As many cars pass by, no one stops to see if the individual is in need of assistance.
• The distressed swimmer: On a crowded beach, an older gentleman struggles to reach the shore and falls down as he struggles to overcome waves that keep knocking him down.
• The gym emergency: A man at the gym is doing a bench press but is unable to lift the bar high enough to rest on the pegs. Other members of the gym fail to take action because no one is really sure if he wants help or not.
• The thief in daylight: A man is running down the street with a cell phone in his hand while being chased by another man. People on the street are unsure of what is happening, so no one takes action.
• The panicked police: A group of police officers are all huddled outside the classroom where a lone individual is threatening to shoot. The officers seem to be “frozen” and are looking to their leader for instructions on what to do.
• The swimming pool panic: A youngster in a public pool is flailing their arms about and yelling. But, everyone around him fails to act because lots of kids are yelling and splashing water.
• The physical altercation: Three friends walk past a man and woman having a loud argument, pushing and shoving one another. None of the friends seems to notice that a physical altercation is happening right in front of them.
• The homeless man: As an office worker turns the corner on their way to work one winter morning, they notice a homeless person with no shoes gesturing for help. Everyone simply keeps walking, and no one offers any assistance.
• The crying child: A child in a shopping mall is crying loudly while standing alone in the middle of the lobby. Busy shoppers keep walking as everyone assumes the child is just upset with their mother.    

Case Studies of the Bystander Effect  

1. The Kitty Genovese Case  

Late at night on March, 13^th, 1964, a 28-year-old woman was brutally attacked in an alley just steps from her apartment door in New York City. Although she screamed for help numerous times, none of the 38 people that heard her cries for help attempted to save her. One call was made to the police, but it was dismissed as a “domestic dispute.”

The case soon caught the attention of the national media and sparked outrage and condemnation of the residents that failed to act.

Many scholars, politicians, and community leaders throughout the country responded with blame and accusations of what happens when people live in large cities; they become callous and uncaring human beings.

This was the case that then sparked the research of Darley and Latané. Over the subsequent decades, a large number of scientific studies were conducted in an attempt to understand how people can fail to act in emergency situations.

The results were less about finger-pointing and more about identifying diffusion of responsibility (i.e. social loafing) and pluralistic ignorance as two key factors that explain how and why people often fail to take action in similar circumstances.

2. Bystander Intervention: The First Study

Latané and Darley (1968) conducted the first scientific study on the bystander effect.

Their methodology was straightforward. Over 60 college students at New York University participated in a study on “personal problems in college.” Each participant was taken to a small room individually where they would discuss the issue via an intercom system.

The small rooms were situated along a narrow corridor, so it was clear that several participants would be involved in the discussion simultaneously.

As one “participant” spoke they mentioned their difficulties adjusting to college life and a medical condition they had which sometimes resulted in seizures. This script was pre-recorded and included an incident where the “participant” began to show significant physical distress, and eventually ceased communicating.

The results revealed that:

“The number of bystanders that the subject perceived to be present had a major effect on the likelihood with which she would report the emergency (Table 1). Eighty-five percent of the subjects who thought they alone knew of the victim’s plight reported the seizure before the victim was cut off, only 31% of those who thought four other bystanders were present did so” (p. 379).

This indicates that the more “witnesses” to an emergency, the less likely a person will take action. Thus, supporting the concept of diffusion of responsibility.

This study needed to be followed up with a debriefing from the researchers in order to clarify the study’s purpose and meet research ethics standards.

3. Cyberbystander Intervention and Cyberbullying  

According to the Pew Research Center (2011), over 90% of teenagers 12-19 years old access the Internet daily. Based on statistics by the Cyberbullying Research Center, in 2021, “23.7% of girls and 21.9% of boys between the ages of 13 and 17 report being cyberbullied.”

While bystanders are individuals that do not intervene in emergency situations, cyberbystanders do this in the virtual world (Dillon & Bushman, 2015). To examine online cyberbystanding, the researchers had 221 university students participate in a study regarding online research surveys.

A chat window was visible on the computer monitor as participants filled out the survey. At key moments, the chat window revealed remarks by one of the “other participants” that acted confused regarding the procedures. Their remarks were met with increasingly hostile responses from another fictitious participant.

The results revealed that:

“Of the 221 cyberbystanders, only 10.4% (n = 23) directly intervened compared to 88.24% (n = 198) of cyberbystanders who did not directly intervene” (p. 148).

Only one participant reported the cyberbullying incident to the on-site researcher, at one point, opening the laboratory door and refusing to continue participating.

4. The Bystander Intervention Model 

Latané and Darley (1970) developed a 5-stage model that explains when and if a bystander will intervene.

• Step 1 is that the situation must be noticed. If the bystander fails to see what is happening, then no intervention will occur.
• Step 2 is that the bystander must accurately interpret the situation as an emergency. This is in part affected by the reactions of other people also witnessing the situation.

If others do not seem to be acting as if the matter is an emergency, then the situation will not be interpreted correctly (i.e., pluralistic ignorance).

If they identify the situation as an emergency, then they may move to Step 3 and feel a personal sense of responsibility. However, as the number of witnesses increases, the sense of personal responsibility decreases (i.e., diffusion of responsibility)

If the bystander feels responsible, then they must determine whether or not they have the skills to provide adequate help (Step 4). That will lead to a final, conscious decision to provide help, or not (Step 5).

A graphic which depicts the model can be seen here.

5. Research on Teacher Bystander Intervention

There are three forms of traditional bullying: physical, verbal, and relational. Physical bullying involves direct physical harm; verbal bullying involves taunts and insults; and relational bullying involves damaging a person’s reputation. In each of these scenarios, teachers can play an important role as bystanders with the authority to intervene.

Eldridge and Jenkins (2020) examined the role of teacher empathy in each step of the Bystander Intervention Model (Latané & Darley, 1970).

There were 150 teachers that participated in an email survey which included a measure of the Bystander Intervention Model and affective empathy.

“The current study found that teachers report higher scores on each step of the bystander intervention model for traditional bullying than cyber bullying” (p. 6).

“…affective empathy was positively related to noticing both traditional bullying and cyber bullying” (p. 7). However, “There was not a significant association between affective empathy and interpreting cyber bullying as an emergency” (p. 8)

“Teachers with greater affective empathy reported a higher likelihood of accepting responsibility for intervening in events of both traditional bullying and cyber bullying” (p. 8).

Finally, while teachers with high levels of empathy were more likely to know what to do with traditional bullying, this was not the case with cyberbullying.

Conclusion

The bystander effect is when witnesses to an emergency situation fail to intervene. This can be due to several factors, which are described in the Bystander Intervention Model.

There is a 5-step process of decision-making that must occur before an individual will intervene or not. Often, the decision is affected by an interpretation of the situation as being an actual emergency. If so, then the number of other witnesses present, reduces the sense of personal responsibility that each one feels.

If a person does feel responsible, then there must be an analysis of one’s ability to help. If a person does not have the skills to intervene successfully, an attempt is less likely.

The Internet era has led to a substantially larger number of intervention scenarios that occur as instances of cyberbullying become increasingly prevalent in society.

Most of us like to think that we would help another person in obvious distress, but, that might not be the case.

References

Darley, J. M., & Latané´, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 8, 377–383.

Dillon, K., & Bushman, B. (2015). Unresponsive or un-noticed?: Cyberbystander intervention in an experimental cyberbullying context. Computers in Human Behavior, 45, 144-150. http://doi.org/10.1016/j.chb.2014.12.009

Eldridge, M., & Jenkins, L. (2020). The Bystander Intervention Model: Teacher intervention in traditional and cyber bullying. International Journal of Bullying Prevention, 2(3), 1-11. https://doi.org/10.1007/s42380-019-00033-7

Hortensius, Ruud, & De Gelder, Beatrice. (2018). From Empathy to Apathy: The Bystander Effect Revisited. Current Directions in Psychological Science, 27(4), 249-256.

Latané, B., & Darley, J. M. (1968). Group inhibition of bystander intervention in emergencies. Journal of Personality and Social Psychology, 10, 215–221. http://dx.doi.org/10.1037/h0026570

Latané, B., & Darley, J. (1970). The unresponsive bystander: Why doesn’t he help. NY: Appleton-Century-Crofts.

Lea, M., & Spears, R. (1991). Computer-mediated communication, de-individuation and group decision-making. International Journal of Man-Machine Studies, 34, 283–301.

Pew Research Center (2011). Internet & American Life Project 2011: Teen/Parent.
Survey, April 19 – July 14, 2011. http://www.pewinternet.org/Trend-Data-(Teens)/Online-Activites-Total.aspx

Pew Research Center (October, 2014). Online harassment. http://www.pewinternet.
org/2014/10/22/online-harassment/