Social Psychology

by Paul Seager

  Defining and studying prosocial behaviour

  Generally, there seem to be three types of behaviour aimed at helping others, though the definitions do seem to vary from source to source. According to Bierhoff (2002), these three types of behaviour are defined as:

  • Helping behaviour: This is characterized as an intentional act which is carried out to benefit an individual. This covers all forms of interpersonal support and it is not necessarily voluntary. For example, an assistant in a shop can help a customer, but they do this because they are paid to do so, not necessarily because they choose to do so. This form of behaviour can also be antisocial: for example, an individual can help another person in order to make them look incompetent.

  • Prosocial behaviour: This type of behaviour is purely voluntary and is valued positively by society (and therefore may be culturally determined). It has positive consequences, contributes to the physical and/or psychological well-being of an individual, and is not motivated by professional obligation.

  • Altruism: There is some debate about whether pure altruism actually exists as this type of behaviour puts the emphasis on the needs of another without any consideration of benefit to the helper. This would be exemplified by the parable of the Good Samaritan, or perhaps by the act of heroism by an individual at an underground station outlined above. However, it is difficult to define such an action as purely altruistic as it may have been carried out in order to alleviate anticipated personal distress.

  ‘… the broad range of actions intended to benefit one or more people other than oneself – behaviors such as helping, comforting, sharing and cooperation’… Altruism is motivation to increase another person’s welfare … Prosocial behaviour need not be motivated by altruism; altruistic motivation need not produce prosocial behaviour.

  (C. Daniel Batson, 1998, p. 282)

  One of the challenges faced by researchers is to capture and understand the diversity of prosocial behaviour. For example, there are many different dimensions to helping, and these can include:

  • Planned vs. spontaneous

  • Serious vs. non-serious

  • Direct vs. indirect

  Planned helping might include a regular monthly donation from your wages to a charity, whereas spontaneous helping could include giving directions to a motorist who stopped you in the street whilst you were out walking. Helping in a serious situation could include going to the aid of victims of a car crash, whereas non-serious intervention might be characterized by helping to pick up dropped groceries from a basket. Direct helping would be exemplified by assisting in an immediate fashion, such as rushing over to a person who has collapsed in the street, whereas indirect helping would, in such a situation, be characterized by calling the emergency services. A good theory should be able to explain why we help in all of these different types of situation.

  Similarly, a question has also been raised regarding how often prosocial behaviour actually occurs in daily life and whether simple lab experiments (of which social psychologists are very fond) can actually capture the richness and diversity of the helpfulness of individuals. For example, helping behaviour can actually increase over time, and if an experiment only looks to capture whether an individual helps within a given time frame (e.g. a ten-minute experiment), then it might not capture delayed helping. Likewise, the amount of helping is rarely measured – it is normally only captured in a yes/no format without any contextualization. For example, a child or adult who donates to a charity collection is said to have shown some form of prosocial behaviour, but the helping might be viewed differently if the donation represents either a substantial, or negligible, amount of their individual wealth.

  For a complete understanding of how and why individuals help (or not), researchers must attempt to capture the full gamut of behaviours.

  Approaches to explain why people help

  There are two broad approaches to explaining prosocial behaviour: the biological approach (nature) and the learning approach (nurture). The former suggests that we are predisposed to help (it’s in our genes) whereas the latter suggests that we are taught whether, and how, we should help.

  According to the biological approach, genes that further our chances of survival should be passed on, and those that don’t should disappear. The survival of our genetic lineage is all important, and this has implications for the field of prosocial behaviour. If the biological approach is to play a major role in explaining why people do or don’t help, there should be evidence to suggest that individuals only help others when it promotes (or at least doesn’t adversely harm) their gene survival. There is some evidence to suggest this is the case. For instance, Burnstein and colleagues administered a questionnaire asking people about their likely helping behaviour towards family and strangers, in emergency (e.g. a house fire) and non-emergency (e.g. helping with the shopping) situations. They found that whilst there was a broad range of helping in non-emergency situations which didn’t seem to discriminate between those who were genetically related and those who weren’t, when it came to a life-or-death emergency situation, helping was prioritized towards genetic relatives.

  Key idea: Biological approach to helping behaviour

  The assumption than an individual is genetically predisposed to help others (nature).

  A further study, which capitalized on a real-life situation where there was a fire at a holiday resort hotel, found a similar occurrence. Survivors were interviewed about their behaviour when they found out that the building was on fire. Those who reported re-entering the burning hotel said that they went in search of family members, and not friends or strangers. This supports the idea that helping is intended to promote gene survival.

  However, whilst there is some evidence to support this broad explanation for why people help, the biological explanation for helping behaviour is quite a limited one. Firstly, the evidence used to support it tends to be based on hypothetical questionnaires or anecdotal evidence which is subject to biases, such as social desirability. Secondly, according to this perspective, altruistic behaviour should have disappeared (effectively been bred out of the species) as it serves no purpose if the goal is to promote gene survival. It cannot readily explain why people sacrifice their own lives for those of strangers.

  A more plausible approach to explaining helping behaviour is offered by the learning approach. Individuals help others because they learn that it is the right thing to do. They learn it from those that they trust (e.g. parents) or those that they like and respect. Similarly, there are rules (norms) of civilized society which help to explain when, and whether, we should help another: evidence suggests we learn these norms early on in life.

  Key idea: Learning approach to helping behaviour

  The assumption that an individual learns how, and when, to help others from various sources (nurture).

  The norm of reciprocity (and we come across this very powerful norm many times in social psychology) suggests that there is the assumption that if we help others, then, if we need their aid in the future, there is an increased likelihood that they will help us. This would explain helping behaviour given to a stranger with whom it is possible that we will interact in the future.

  The norm of equity suggests that we should give benefits (help) roughly in proportion to those benefits that we receive from others. We quickly learn that if somebody only gives back a fraction of what they receive, then we should be guarded about what we give them in the future. This norm is important in regards to interpersonal relationships (see Chapter 5).

  The norm of social responsibility claims that we should simply help other people because they need it, and because it is the right thing to do. This would explain why we give to charities where there is no expectation that we will get anything back.

  Norms are a useful explanation for why we might help others. However, they are not without their problems. For example, they are good as explanatory tools (e.g. John gave money to a homeless person because they needed it) but not
as predictive tools (e.g. we can’t use them to tell us when (or if) John will give money to a homeless person). They can also be a little circular in their explanatory power (e.g. John gives money to a homeless person. Why? Because of the norm of social responsibility. How do we know the norm of social responsibility exists? Because people like John give money to homeless people). Finally, as explanatory tools they can contradict one another: the norm of social responsibility predicts that John will give money to a homeless person, but the norm of reciprocity predicts that he won’t (as he can’t reasonably expect that person to help him in the future).

  Broadly speaking, the learning approach says that we will help others because we learn that it is the right thing to do, and there are a number of ways that this happens:

  • Giving instructions: children are told to be helpful by their parents.

  • Reinforcement: rewarded behaviour is more likely to be repeated, therefore if we are rewarded for helping, we are more likely to do it in the future.

  • Modelling: we see other people helping (usually those who we like or respect, but not always), and therefore we are more likely to help ourselves.

  Evidence suggests that modelling, based on Bandura’s social learning theory, is a very powerful tool to increase learning. Studies show that children watching television programmes with prosocial content are more likely to engage in helping behaviour than children who don’t. Modelling has also been found to be effective with adults too (see Case study below). Numerous pieces of research have shown that if an individual sees others behaving helpfully, whether on TV, in computer games, or in pictures, then they are more likely to be helpful themselves. Interestingly, we’ll come across social learning theory again in Chapter 9, when we look at explanations for why people behave aggressively.

  Key idea: Social learning theory

  Bandura’s theory that suggests we learn behaviour from appropriate ‘models’, such as parents or respected others.

  Case study: The helpful motorist

  Bryan and Test (1967) carried out a simple piece of research. Motorists passed a car with a flat tyre and a woman standing by it. In one condition, the woman was alone and in the other she was still standing by the car but another motorist had stopped and was giving her help. Further down the road, the motorist encountered (coincidentally!) another car with a flat tyre. Results of the study found that those motorists exposed to prosocial behaviour (as modelled by the motorist who had stopped to help) were 50 per cent more likely to stop and help than those who had not been so exposed.

  The search for explanations for why people help or don’t help stemmed from the Kitty Genovese incident reported in the New York newspapers in 1964. Kitty was a 28-year-old bar manager who was fatally stabbed as she returned home from her job in the early hours of one morning. As she walked from her car to her apartment, a man grabbed her and she screamed. Lights went on in the nearby apartments, the man stabbed her, she screamed and slumped to the ground. It seemed that the lights drove off her attacker but no help was forthcoming. According to media reports, her assailant returned twice more to attack her and still no help came. When someone finally did call the police, she was dead. The headlines were unkind to the 38 people who reportedly heard her cry for help but did nothing: the incident was labelled as ‘bystander apathy’ and spawned a whole strand of research to try to explain it (though subsequent reports of this incident suggest this version of events might not be entirely accurate – see Manning et al., 2007).

  The cognitive model of helping behaviour

  Latane and Darley (1968) proposed a cognitive model to explain why people do, or do not, help in an emergency situation (such as the Kitty Genovese incident). They suggested that there were five questions that needed to be answered before an individual would decide to help. At each stage, if the answer was ‘no’, then no help would be forthcoming: only five positive responses would lead to helping behaviour. The stages are:

  1 NOTICE THE EVENT

  Failure to notice an emergency situation will obviously result in no help being given. To test which factors might be important in explaining whether or not a situation might be noticed, Darley and Batson (1973) conducted a study using students at a theological seminary. Half of the students were asked to think about the parable of the Good Samaritan (helping oriented), and half were asked to think about professional problems facing the priesthood (task oriented). Students were then told that they had to report to another building to give a presentation on their topic, but they were told that either: (i) they had plenty of time to do so (no time pressure); (ii) they had just enough time to do so; or (iii) they were running late (maximum time pressure). En route to the building, it was arranged so that the students would pass someone (a confederate) slumped in an alleyway, head down and eyes closed, coughing and groaning.

  The researchers were interested to see who would stop and who would carry on. The obvious expectation was that those who were preparing to talk about the parable of the Good Samaritan would be most likely to stop to help. However, this was not the case. It transpired that the best predictor of helping behaviour was the amount of time pressure the participants were under: those with plenty of time to spare were more likely to stop than the others. Those in the maximum time pressure situation seemed not even to notice the confederate. Therefore, time pressure, rather than frame of mind, seems to be a good indicator of whether or not we will even notice an emergency situation.

  2 INTERPRET THE EVENT AS AN EMERGENCY

  Assuming that the incident is noticed, it must be interpreted as an emergency. Whilst there are times when a situation is a clear-cut emergency, there are many more times where a situation is ambiguous: for example, is the person slumped on the pavement simply drunk or are they seriously ill; is that steam coming out of the vent or smoke from a fire? In an ambiguous situation, we have a tendency to look to others to help us define it; if they appear not to be concerned, then we are more likely to conclude that the situation is a non-emergency. This is referred to as pluralistic ignorance. If, however, a person is on their own, they are much more likely to double-check as they have no frame of reference. This conclusion has been supported by the findings from many experiments.

  Key idea: Pluralistic ignorance

  The phenomenon whereby bystanders assume that nothing is wrong in an emergency situation because no one else appears to be concerned.

  3 ASSUME RESPONSIBILITY

  Having decided that the situation is one that warrants some form of helping behaviour, the individual must decide whether or not it is their responsibility to intervene. Again, it seems that the more people there are present, the less likely the individual is to help. This is referred to as diffusion of responsibility; the sense of responsibility felt by any one individual will decrease as the number of witnesses increases.

  This rule can be mitigated by a number of factors. For example, an individual’s sense of competence: if they feel that they are uniquely qualified to help, e.g. they are a medical doctor and they witness an accident where someone is injured, then they are more likely to help. Similarly, if the individual notices that other witnesses appear to be more qualified to help, e.g. they are dressed in nurses’ uniforms, they will be less likely to help. Finally, more recent research suggests that, whilst the probability of receiving help decreases as the number of bystanders increases, this effect may only be found for non-dangerous emergencies: where the emergency is severe, help is likely to be received regardless of more than one bystander being present (Fischer et al., 2006).

  Key idea: Diffusion of responsibility

  The more witnesses there are to an emergency situation, the less likely any one individual will be to offer help.

  4 KNOW THE APPROPRIATE FORM OF ASSISTANCE

  Having accepted responsibility for helping, if the individual does not know the appropriate form of assistance to give, then they are unlikely to intervene directly. Thus if they feel that a person who has collapsed on a hot day is
in need of CPR, but they don’t know how to administer it, then they are less likely to help; but if they feel that the person has heatstroke, and can be helped by being given a drink, then they may feel more able to do this, and therefore they will intervene.

  5 IMPLEMENT THE DECISION TO HELP

  The final stage requires actual intervention. It may be that the previous four stages have been passed successfully, but there are still barriers to intervention. For example, it could be an inherently dangerous situation and to help might risk their own lives, or they may simply feel afraid of appearing foolish if they do the wrong thing.

  Case study: The smoke-filled room experiment

  Latane and Darley (1970) asked individuals to volunteer to fill in a questionnaire measuring ‘attitudes to urban life’. When they reported for the study, the participants were taken to a room to complete the survey. They were either alone in the room, with two other strangers or with two confederates. After a short time, smoke was pumped into the room, and the reactions of the participants observed.

  When they were alone, within two minutes, 50 per cent had left the room to seek help; after six minutes, 75 per cent had left the room. When they were with two other strangers, after two minutes, only 12 per cent had left the room, and after six minutes the figure had only increased to 36 per cent. When they were in the room with two stooges, who had been instructed to pretend that nothing was amiss, only 10 per cent eventually left the room to seek help, despite at one point the smoke being so dense that it was unlikely they could clearly see the questionnaire!