by Paul Seager
Latane and Darley concluded that the presence of others inhibits people from responding to an emergency situation, especially if they seem to be unconcerned by the unfolding events. These types of experiments (see also Latane and Rodin’s (1969) ‘Lady in Distress’ study) can perhaps start to give us an insight into bystander apathy.
Overall, the model has an intuitive feel to it, and can account for both emergency and non-emergency situations; there is also some good evidence to support it. However, it is perhaps a little far-fetched to believe that there is any conscious attempt by an individual to address the five questions before deciding to intervene. Additionally, the model is a little too linear, and also doesn’t take into account the emotional reactions of the individual who is contemplating offering help. Nevertheless, it provides a good first step in understanding the cognitive processes that may be involved in determining whether or not an individual will offer help in an emergency situation.
The bystander-calculus model
Another model, which attempts to address the shortcomings of the cognitive model, is the bystander-calculus model (Piliavin et al., 1981). This suggests that bystanders, who perceive a person in trouble and in need of assistance, work through three stages:
1 Physiological arousal: when exposed to a potential emergency situation, an individual experiences a change in their physiology (e.g. their heart rate). Initially, there is a decrease in physiological signs (an orienting response) as they try to figure out what is happening. Then, as they prepare to act (or not), their physiological signs increase (a defence reaction). In general, the greater the arousal, the more likely it is that the individual will act.
2 Labelling the arousal: exactly how the individual will act depends on how they label their arousal. The arousal does not trigger a specific emotion, instead it is left to the individual to decide whether they are feeling personal distress (they are more likely to leave the scene without helping) or empathic concern (they are more likely to intervene with helping behaviour).
3 Evaluating the consequences (via a reward-cost matrix): however, before intervention is assured, the costs and benefits are weighed to decide if, and what type of, helping will be offered (see Spotlight below).
This model has the advantage of considering the emotions of the potential helper, but still has a slightly mechanical feel to it.
Spotlight: Weighing the costs of intervening
According to stage 3 of Piliavin et al.’s bystander-calculus model, an individual will weigh up the costs of helping (high/low) and the costs of not helping (high/low) before making a decision to intervene or not. This is illustrated in the table below:
Only one situation dictates automatic helping. All of the others may depend on personality characteristics, time and other factors. The predictions are general, and do not appear to account for the most extreme situations.
Other theories have also been used to explain helping behaviour. For example, social exchange theory suggests that whether or not an individual helps is based on self-interest. Rewards and costs are weighed (albeit implicitly rather than consciously), and only if the latter outweigh the former will help be offered. Rewards and costs will vary from individual to individual, for example the costs of jumping into a river to save a drowning person will be prohibitively high to a non-swimmer but negligible to an Olympic-class swimmer; a normally helpful person will be unlikely to help if they find themselves under unbearable time pressures. This theory, popular in the area of interpersonal attraction (see Chapter 5), bears a resemblance to stage 3 of the bystander-intervention model, but has been criticized by some as being inappropriate for the discussion of prosocial behaviour as it certainly doesn’t allow for the existence of altruism.
Other theories have concentrated more on the impact of where the emergency takes place. For instance, Milgram’s ‘urban overload hypothesis’ proposes that the location of an incident can determine whether or not helping behaviour will be offered. Initial findings suggested that more help was given in rural areas as opposed to urban areas. For example, one study conducted in Australia suggested that a man limping down a street, who then falls over and reveals a bandaged but bleeding shin, was helped approximately 50 per cent of the time in a small town, but only 15 per cent of the time in a city. This finding was repeated for a number of different types of helping behaviour (e.g. helping a lost child or giving directions to a stranger) in a number of different countries (though not all – see Case study below).
Milgram put forward his theory which suggested that people living in cities are continually being bombarded with stimulation and that they keep to themselves in order to avoid being overloaded by it. Consequently they are unlikely to help as much as those living in less stimulating environments (such as towns or villages), although a slight modification to the theory suggests that it is the population density which affects helping rather than its actual size: the greater the density, the less likely help will be offered.
Case study: Cultural differences in helping behaviour
Levine (2001) reports on the amount of help given in different cities throughout the world. In one situation, a supposedly blind man (actually a confederate) was about to make his way out on to a busy road at a pedestrian crossing. In Rio (Brazil), 100 per cent of the time he was offered help before putting his life at risk. However, he fared less well in other cities: passers-by in New York (USA) and Rome (Italy) only helped about 75 per cent of the time, and those in Shanghai (China) only helped a little better than 60 per cent of the time. Overall, using a composite score of helping in three different types of situation, Rio and San Jose (Costa Rica) rated as the top two most helpful places in the world, with New York and Kuala Lampur (Malaysia) ranking as the bottom two (22nd and 23rd).
Finally, the ‘empathy-altruism model’ proposes a slightly more upbeat explanation for helping behaviour. Proposed by Batson (1991), this model suggests that if we can put ourselves into the metaphorical shoes of a person who is in need of help, and experience what they might be feeling, then we are more likely to help. In short, if we can feel empathy for the person in need, then we will exhibit altruistic behaviour. However, the model goes on to suggest that if we don’t feel empathy for the person, then we may still help but only if it is in our self-interest to do so (i.e. the rewards outweigh the costs). This theory has its merits in that it suggests that altruism can exist, however it is very difficult to determine the exact nature of the motives underlying some potentially very complex behaviour: that is to say, do people experiencing empathy help purely out of concern for the person in need or do they do it to alleviate their own growing personal distress?
Most of the previous explanations are situational in nature and don’t consider the core attributes of the individual who is proposing to help. This potentially crucial factor should not be ignored.
Individual differences in helping behaviour
It is generally agreed that any type of behaviour, prosocial or otherwise, is a product of both the situation in which an individual finds themselves and the individual’s personal characteristics. To this end, a number of researchers have attempted to determine whether or not there are personality traits linked to helping behaviour. Early research found no personality variables that reliably predicted helping behaviour, although positive relationships were found between helping and:
• the belief that one’s fate lies within one’s control;
• mature moral judgement;
• the need for social approval;
• the tendency to take responsibility for the welfare of others.
More recent research reported by Bierhoff (2002), using retrospective interviews with rescuers of Jews during the Second World War, suggested that helpers score more highly on personality characteristics such as social responsibility and internal locus of control, that they placed much more emphasis on an adherence to ethical rules, and they attached much more importance to personal responsibility. Other research has also shown that
individuals scoring highly in characteristics such as empathy and agreeableness are more likely to help compared to low scorers. There is also the possibility that unlikely traits, such as Machiavellianism, will, under a specific set of circumstances, lead to more prosocial behaviour.
As well as personality, gender has also been found to mediate helping behaviour. Certainly within western cultures, help offered tends to coincide with cultural norms for genders. The male role is seen to be a more heroic and chivalrous one, and consequently men are seen to help in more heroic and chivalrous ways compared to women. For instance, 91 per cent of individuals who received the Carnegie medal (awarded to individuals in America for risking their lives to save a stranger) were men; though this could of course be due more to physical attributes than to gender. The norm for females is one that places more emphasis on nurturing and caring, and typical helping interventions by women are likely to involve longer term commitment and nurturance, usually directed towards friends rather than strangers; they are much more likely to do volunteer work in communities than men.
‘… research on prosocial behaviour yields patterns of gender specialization that are well known in daily life. Although it is incorrect to claim that there is a more helpful sex, a persistent pattern emerges of female emotionally supportive and sensitive behaviour, especially in close relationships, and male agentic behaviour, often directed to strangers and to the support of social collectives.’
(Alice Eagly, 2009, p. 653)
A final personal characteristic that might affect prosocial behaviour is mood. There can be no doubting that being in a good mood makes us more likely to help others, and there is much research to back this notion (the ‘feel good, do good’ effect). A good mood, induced in a variety of ways such as performing well on a test, receiving a gift or simply thinking happy thoughts, has led to an increase in helping behaviours, such as contributing money to charity or donating blood.
Being in a bad mood, however, does not necessarily lead to a decrease in helping behaviour. Feeling guilty, for example, has been found to lead to an increase in prosocial behaviour. A field study found that churchgoers were more likely to donate money to charity before attending Confession than after! More controlled experiments, whereby guilt was induced by leading the participant to believe that they had broken a passer-by’s camera (they were asked by the passer-by to take a picture and given their camera), found that when there was an opportunity to help a person in distress at a later juncture, guilty participants were more likely to intervene than participants who had not been subjected to the guilt manipulation.
Applying the research
Given the assumption that the world would be a better place if we were all more helpful people, some thought has been given as to how we might put the theories underlying prosocial behaviour into practice. For example, could we increase the likelihood of people donating blood or reporting shoplifting activity?
There is some evidence that just listening to a lecture on this subject can help to increase prosocial behaviour. During the break in one of my lectures on this topic, a student told me that they had just been out to buy a snack and had been given too much change; instead of keeping it as they would have done normally, they returned the surplus to the cashier (I didn’t know whether to be proud or shocked). A more controlled example of this effect was found when students were randomly assigned to listen to a lecture either on Latane and Darley’s bystander intervention research, or on an unrelated topic. Two weeks later, the students participated in what they believed to be a sociology study. As they were being led to a room by an experimenter, they passed a student lying slumped against a wall. The experimenter didn’t appear to be concerned and just carried on walking. Results found that 43 per cent of students who had listened to the prosocial lecture previously stopped to check on the student compared to 25 per cent who hadn’t. It would appear that simply knowing something about factors affecting prosocial behaviour (in this case, pluralistic ignorance) may increase helping behaviour.
Similarly, many of the other ideas that have been encountered in this chapter can also be used to increase helping behaviour. Imagine that you own a shop and find that you are prone to shoplifters stealing your stock. Using Latane and Darley’s cognitive theory, you decide to put up a number of signs telling your customers what constitutes shoplifting and how they can report it if they see it: this would help to overcome any ambiguity that might be felt by witnesses to a shoplifting event (and if you offered a reward, even better). Likewise, imagine that you wish to increase blood donation, and you are recruiting on a University campus or on the high street. Using the learning approach (specifically Bandura’s social learning theory), you might have confederates modelling the behaviour that you want others to emulate – namely, you would have your stooges pretend to sign up to donate blood, with the theory being that if people see others signing up to help, then they too will be more likely to sign up.
Summary
Prosocial behaviour is a complex topic – just defining what is and is not helpful or prosocial can be tricky – and researchers certainly have a number of hurdles to jump through to understand this type of behaviour fully. Nevertheless, a number of theories have been advanced to try to explain if, and when, people will help when the situation requires it. Whether or not such behaviour is learned or innate is also a matter for debate, as is the exact contribution made by the situation and the person’s individual characteristics. However, there can be no doubting that the applications of this research are of great importance to society as a whole.
Food for thought
Imagine you are the co-ordinator for a local conservation organization and you realize that the band of volunteers is diminishing. How would you use the information in this chapter to recruit more helpers? Or, as the chief constable of a regional police force, how would you use the information to orchestrate a campaign to help achieve local community safety by getting people to report suspicious activity in their area?
Dig deeper
Bierhoff, H. (2002) Prosocial Behaviour. Psychology Press.
Eagly, A. H. (2009) ‘The His and Hers of Prosocial Behavior: An Examination of the Social Psychology of Gender’. American Psychologist, 64(8), 644–658.
Fischer, P., Greitemeyer, T., Pollozek, F. & Frey, D. (2006) ‘The Unresponsive Bystander: Are Bystanders More Responsive in Dangerous Emergencies?’ European Journal of Social Psychology, 36, 267–278.
Manning, R., Levine, M. & Collins, A. (2007) ‘The Kitty Genovese murder and the social psychology of helping: the parable of the 38 witnesses’. American Psychologist, 62, 555–562.
Fact-check
1 A shop assistant helps a customer to choose which television to buy. According to Bierhoff, this is referred to as:
a Helping behaviour
b Prosocial behaviour
c Altruistic behaviour
d None of the above
2 Which of the following is not a dimension on which helping behaviour should be studied?
a Planned vs. spontaneous
b Direct vs. indirect
c Serious vs. non-serious
d None of them are valid dimensions for study
e They are all valid dimensions for study
3 According to Burnstein’s study looking at a biological explanation for helping, which of the following is not true?
a In a non-emergency situation, people will help the elderly as a priority
b In an emergency situation, people will help children above all others
c In a non-emergency situation, there is no differentiation between helping relatives and non-relatives
d In an emergency situation, priority will be given to helping those who are related to the helper
4 John helps Jack because he has been helped by him in the past. This behaviour can be explained by:
a The norm of social responsibility
b The norm of equity
c The norm of reciprocity
d
The norm of fair return
5 According to the learning approach, we learn to help by seeing people we like and respect helping others. This is referred to as:
a Giving instruction
b Taking instruction
c Reinforcement
d Modelling
6 Which of the following is not a stage in Latane & Darley’s cognitive model of helping behaviour?
a Notice the event
b Interpret the event as an emergency
c Diffusion of responsibility
d Know the appropriate form of assistance
7 The ‘smoke filled room experiment’ provides evidence for which concept highlighted in Latane & Darley’s cognitive model?
a Diffusion of responsibility
b Cognitive dissonance
c Physiological arousal
d Pluralistic ignorance
8 According to Piliavin et al.’s Bystander-Calculus model of helping behaviour, which of the following four sets of circumstances will lead to direct helping?
a Lost cost of helping and high cost of not helping
b High cost of helping and high cost of not helping
c High cost of helping and low cost of not helping
d Low cost of not helping and low cost of helping
9 Levine (2001) surveyed a number of international cities with regards to their helping behaviour. Which country’s city ranked lowest?
