The Bystander Effect

The research into the phenomenon of the “bystander effect” was kicked off by an unfortunate case of the murder of Kitty Genovese in 1964. According to the “ The New York Times”, the murder, which took over 40 minutes to happen, was witnessed by 38 people who did not report the crime or try to intervene in any way. When going into the analysis of this effect, both Darley and Latané came up with a theory of the diffusion of responsibility/ accountability which takes effect in the large groups. This effect was shown by their study involving the students of the Columbia state university where the smoke was pumped into the testing room and the time taken for the incident to be reported was recorded. What was found, that when the students were presented

Such possible effects can be divided into 5 categories, the: noticing of the emergency (or acknowledgment of an emergency), interpretation, degree of responsibility (which the helper will have to undertake by interfering), form of assistance (or how can they help) and finally the implementation of the actions, which might lead to the helping outcome. Although these are considered to be the main affecting factors, they also rely on several conditions. If we take the second stage, the interpretation, we can find the different factors that determine if the overall outcome is going to be helping or abstaining from help. One of the main factors is social influence, the effect of this was demonstrated in the same “smoke” study. When presented with the emergency the subjects, after seeing that others payed no attention to the smoke entering the room, in five out of eight groups involved chose to completely ignore the potentially dangerous situation and not report it, even when the smoke got to the point where it impaired their vision and caused some coughing. Other groups, although the smoke was reported, the subjects took very long time to break this effect of “pluralistic ignorance” and take action and responsibility into their own

In reality the data showed the polar opposite. Then the question arose, “Why are we more likely to help in more dangerous situations?” First, these results showed the high chance of positive response when the situation was clearly perceived as dangerous, unlike in the situations where the possibility of dangers is ambiguous. For example, if the participant is presented with a woman running away from the man screaming “Why are you following me”, the participant will intervene much more frequently in both, bystander and non-bystander states. But if the participant sees a woman running away from a man shouting “Why did I marry you?” then the chance of intervention drops drastically. Even though the woman in both cases might be running away from a potential attacker, the reason for the difference in response comes from the perception of danger. In the former example the danger is clear and therefor the bystanders become aroused quicker, leading to the positive helping response, unlike in the latter example where the danger is not as clear, causing the “bystander effect” where the woman is not helped. Secondly, when presented with the situation where danger is clear, the cost of non-intervention rises (Fischer et al., 2011) which again leads to increased arousal and higher