Human Relationships

Bystanderism

Bystanderism is the phenomenon of a person or people not intervening despite awareness of another person's needs
3 main reasons:

Diffusion of Responsibility

• Individuals feel less personal responsibility to help when others are present.

• Leads to lower likelihood of helping in emergencies.

• Related to the bystander effect: people are less likely to intervene when others are passive.

Evaluation Apprehension

• Bystanders fear being judged if they misinterpret the situation.

• Fear of social disapproval or embarrassment prevents action, especially when others might seem more knowledgeable.

Pluralistic Ignorance

• People look to others to judge if a situation is an emergency.

• If no one else acts, individuals assume help is not needed.
  

Bystanderism → evaluation

• Strengths:

  • These theories are well-supported by research (e.g., Darley and Latané’s experiments) showing how the presence of others reduces helping behavior.

  • They offer clear cognitive and social explanations for why people sometimes fail to act in emergencies.

  • The theories can be applied in real-world settings, like designing interventions to encourage helping behavior (e.g., public awareness campaigns).

• Limitations:

  • They may oversimplify complex emergencies — sometimes people do act even when others are present, depending on personal values or training.

  • Cultural differences are not always considered: collectivist cultures may show different patterns of helping behavior.

  • Situational factors (like perceived danger, relationship to the victim, or the clarity of the emergency) also strongly affect helping, which these models might not fully explain.

Bystanderism → Piliavin et al. (1969)

Aim:

• To investigate diffusion of responsibility and test the arousal-cost-reward model of helping behavior.

Procedure:

• Field experiment on a New York subway with 4,450 passengers.

• Confederate (victim) collapsed either appearing drunk or ill (with a cane).

• Observers recorded helping behavior and other reactions.

• IVs: type of victim (drunk/ill), race of victim (black/white), and timing of model help (early/late).

Results:

• Cane (ill) victim helped spontaneously 62/65 times; drunk victim only 19/38 times.

• Helping was more likely and quicker for ill victims.

• Same-race helping observed more in drunk condition.

• 90% of helpers were male.

• More than one person helped in 60% of spontaneous help trials.

Conclusion:

• Diffusion of responsibility was not strongly observed when escape was difficult (confined subway).

• Arousal-cost-reward model better explains behavior: helping reduces personal discomfort (arousal) rather than being purely altruistic.

Bystanderism → Piliavin et al. (1969) → Evaluation

G (Generalisability):

• Large and diverse sample (over 4,400 passengers), but only from New York City — urban, Western setting limits cross-cultural generalisability.

R (Reliability):

• High ecological validity (real-life subway setting), but less control over extraneous variables makes replicability lower than in lab settings.

A (Applications):

• Useful for understanding real-world helping behavior, especially in emergencies where escape is not easy (e.g., public transport, crowded events).

V (Validity):

• Strong ecological validity (naturalistic environment).

• However, observer bias is possible, and participants were unaware they were being studied (no informed consent).

E (Ethics):

• Ethical concerns: no informed consent, deception (staged collapse), possible psychological distress for passengers.

Bystanderism → Latane and Darley (1968)

Aim:

• To investigate whether the presence of others affects an individual’s likelihood of reporting an emergency (testing diffusion of responsibility and pluralistic ignorance).

Method:

• Participants were asked to fill out a questionnaire either alone, with two passive confederates, or with two other real participants.

• While completing the questionnaire, smoke was pumped into the room through a vent to simulate an emergency.

• Researchers measured how long it took participants to notice the smoke and whether they reported it.

Results:

• 75% of participants who were alone reported the smoke within 6 minutes.

• When with two passive confederates (who ignored the smoke), only 10% reported the smoke.

• When with two other real participants (naive), about 38% reported the smoke.

Conclusion:

• People are much less likely to react to a potential emergency when others are present — particularly if others are not reacting.

• Supports concepts of diffusion of responsibility and pluralistic ignorance.

Bystanderism → Latane and Darley (1968) → evaluation

G (Generalisability):

• Mostly college students → limited age range, may not represent wider population.

R (Reliability):

• Lab experiment → high control over variables → easily replicable for consistent results.

A (Applications):

• Explains the bystander effect in real-life emergencies; important for emergency response training.

V (Validity):

• High internal validity (well-controlled setting), but low ecological validity → artificial situation (smoke in a study room isn't the same as a real emergency).

E (Ethics):

• Mild deception (participants didn't know smoke was staged), but minimal harm; participants were debriefed afterward.

Biological explanations → Reciprocal altruism

Altruism:

• The purest form of helping behavior.

• Helping another person purely out of empathy, with no expectation of benefit or reward.

• There is no obligation or anticipated reciprocation.

Reciprocal Altruism:

• Helping others with the expectation that they will help you in the future.

• Helping is more likely between individuals who have close relationships, expect future interactions, and believe help will be returned.

• Evolutionarily beneficial as it increases survival and reproductive success.

Supporting Research:

• The Prisoner’s Dilemma:

  • A situation where two individuals must decide whether to cooperate or betray each other.

  • Mutual cooperation leads to the best outcome for both, demonstrating the value of trust and reciprocal help.

Biological explanations → Reciprocal altruism → Evaluation

Strengths:

• Evolutionary Support: Explains why prosocial behavior persists even when it is costly — it improves long-term survival and reproduction.

• Research Support: Experiments like the Prisoner’s Dilemma show that humans often cooperate when future interaction is expected.

• Cross-cultural Evidence: Reciprocal helping behavior is found across many cultures, suggesting it is a universal human tendency.

Limitations:

• Hard to Measure Motivation: It’s difficult to prove whether helping is genuinely for future benefit or partly driven by empathy.

• Doesn’t Explain One-off Altruism: Cases where people help strangers they will never meet again (e.g., anonymous donations, heroic acts) aren't easily explained by reciprocal altruism.

• Overemphasis on Self-Interest: Some argue it portrays humans as too calculating, ignoring genuine selfless altruism.

Biological explanations → Reciprocal altruism → Axelrod & Hamilton (1981)

Aim:
To investigate the theory of reciprocal altruism using the prisoner's dilemma.

Procedure:

• Two participants played a computer-based version of the prisoner's dilemma game multiple times.

• Each had two options: “confess” or “stay silent.”

• The best outcome for both was if they both stayed silent, but if either betrayed the other, they could get a better outcome individually.

• In repeating the game, players had the opportunity to adjust their strategies based on their partner’s previous decisions (learning the patterns of cooperation or betrayal).

Results:

• Players tended to "stay silent" during the first round to see how their partner would act.

• If both stayed silent, they continued cooperating in subsequent rounds using a “tit for tat” strategy (reciprocating cooperation or betrayal).

Conclusion:
The study provides evidence for reciprocal altruism, showing that repeated interactions can build trust and cooperation between participants.

Biological explanations → Reciprocal altruism → Axelrod & Hamilton (1981) → evaluation

Generalizability:
The study may not fully represent real-life interactions as it uses a controlled computer-based game with a limited sample of participants, typically university students.

Reliability:
The study is reliable due to its standardized procedure and the consistent use of the “tit for tat” strategy, which suggests repeatable results.

Applicability:
The findings apply to real-world situations requiring trust and cooperation, like negotiations or collaborations. However, real-world complexity may not be fully captured.

Validity:
The study has good internal validity with a clear hypothesis and consistent measurements. External validity is limited as real-world interactions are more complex.

Ethics:
The study is ethically sound, as participants were likely informed and consented. Psychological pressure or stress was minimal in the controlled environment.

Biological explanations → Kin Selection theory

This theory, suggests that altruistic behavior is driven by genetic relatedness. The more closely related individuals are, the more likely they are to help each other, as it increases the chances of their shared genes surviving. According to Dawkins' Selfish Gene Theory (1976), altruism isn't purely selfless but rather a strategy for the survival of genes. Organisms, including humans, aim to maximize their inclusive fitness, meaning they try to pass on their genes not only through their own offspring but also by helping close relatives. This explains behaviors like parents sacrificing themselves to protect their children, as it ensures the continuation of shared genetic material.

Biological explanations → Kin Selection theory →Evaluation

Strengths

• Supporting evidence: Studies like Madsen (2007) show people are more altruistic toward closer genetic relatives, supporting the theory.

• Evolutionary basis: Explains why self-sacrificing behaviours make sense biologically — helping relatives still promotes the survival of shared genes.

Limitations

• Reductionist: Focuses only on genetic relatedness and ignores social, emotional, or cultural reasons for helping others.

• Cannot explain altruism toward strangers: Many people help non-relatives (e.g., through charity), which kin selection alone can't fully explain.

• Cultural variation: In some cultures (e.g., Zulu samples in Madsen’s study), kin distinctions weren't as clear, suggesting environment and norms also matter.

Biological explanations → Kin Selection theory → Madsen (2007)

Aim:

• To test whether willingness to invest altruistically declines as genetic relatedness declines.

• To see if this pattern is consistent across different cultures (comparing British and Zulu participants).

Procedure:

• 11 males and 13 females under 40 from London squatted against a wall for as long as possible to earn a reward for different recipients (varying in genetic relatedness: self, sibling, grandparent, cousin, charity).

• Three experiments: Oxford students, London students (including best friends/charity), and Zulu participants (using food hampers instead of money).

Results:

• Participants held the painful position longest for themselves, then siblings, and least for cousins and charity.

• Zulu participants helped close family but did not clearly distinguish between cousins and closer relatives.

Conclusion:

• Altruistic behavior increases with genetic relatedness.

• Kinship-based altruism appears to be a universal, cross-cultural human tendency.

Biological explanations → Kin Selection theory → Madsen (2007) → Evaluation

• Generalisability: Cross-cultural (British and Zulu participants) increases generalisability, but small sample sizes limit it.

• Reliability: Standardised procedure (wall squat task) — results are replicable.

• Application: Supports evolutionary theories of kin selection and altruism in real-world family behaviors.

• Validity: Low ecological validity — wall-squatting isn't a natural real-life helping behavior.

• Ethics: No major ethical concerns; participants could stop anytime, but physical discomfort was involved.

Cognitive explanation → Negative state relief model

• it considers the extent to which personal discomfort at the sight of another’s distress motivates altruistic acts (akin to egoistic helping in the EAH)

• when someone witnesses another in need of help they experience a negative mood, for example: sadness or guilt

• The NSRM assumes that if an individual feels empathy for someone in need then they are likely to experience sadness or guilt about it:

  • this negative mood may then prompt the individual to offer help in order to improve their own mood

  • the model is directed towards the egoistic motivation of making oneself feel better rather than simply helping the person in need

• According to the NSRM there are two ways to alleviate the unpleasant symptoms experienced when in the presence of someone in need:

1. walk away

2. stay and help

Cognitive explanation →Negative state relief model → Evaluaiton

Strengths

• Evidence supports egoistic motivation: Research shows that helping behaviour often increases when people are in a bad mood, supporting the idea that helping can improve mood.

• Explains why people sometimes help strangers: Unlike kin selection, NSRM explains why we may help people we are not related to — to feel better ourselves.

Limitations

• Reductionist: Reduces complex prosocial behaviour to just mood regulation, ignoring genuine empathy or moral principles.

• Not always consistent: Sometimes, people in a bad mood do not help, or helping can worsen mood if the help is costly or unsuccessful.

• Cultural bias: Based mostly on Western, individualistic samples — may not generalise well across cultures where community-focused helping is more valued.

Cognitive explanation → Negative state relief model → Regan et al (1972)

Aim:

• To investigate whether reducing negative feelings (like guilt) motivates prosocial behaviour.

Method:

• Female participants were asked by a male confederate to take his photograph.

• Two conditions:

  • Guilt condition: The confederate implied the participant broke the camera.

  • No-guilt condition: The confederate reassured the participant it wasn’t their fault.

• Later, the confederate dropped sweets, and researchers observed whether participants helped.

Results:

• 55% helped in the guilt condition.

• Only 15% helped in the no-guilt condition.

Conclusion:

• Participants were more likely to help when they felt guilty, supporting the idea that prosocial behaviour can be motivated by a desire to relieve negative emotions.

Cognitive explanation → Negative state relief model → Regan et al (1972) → Evaluation

G (Generalisability):

• The study only used female participants, so results may not generalise across genders or different cultures.

R (Reliability):

• The procedure was fairly controlled (same setup with the camera and sweets), suggesting good reliability and potential for replication.

A (Applicability):

• Findings help explain how emotions like guilt can drive everyday helping behaviours (e.g., in workplaces or social interactions).

V (Validity):

• High ecological validity: the scenario (taking a photo, dropping sweets) mimics real-life social interactions.

• However, participants might have guessed the aim (demand characteristics).

E (Ethics):

• Mild deception was used (participants falsely believed they broke the camera), which could cause short-term distress.

Cognitive explanation → Empathy based altruism

• Psychological theories of altruism focus on cognitive and social processes that influence helping behaviour.

• These theories suggest that specific states of mind (e.g., empathy, egoism, negative mood) affect the amount of help given.

• Batson's Empathy-Altruism Hypothesis (1981):

  • Suggests that not all altruistic acts are purely selfless.

  • Egoistic motivations (e.g., wanting to relieve personal discomfort or gain praise) can also drive helping behaviour.

• Batson aimed to distinguish between:

  • Prosocial behaviour based on empathy (genuine concern for others)

  • Prosocial behaviour based on egoism (helping for personal benefit)

Cognitive explanation →Empathy based altruism → evaluation

Strengths

• Well-supported by research showing empathy increases helping even when there’s no personal gain.

• Explains genuine altruism, not just selfish motives.

Limitations

• Hard to separate empathy from egoism—people may help to feel better.

• Relies on lab studies, which may lack real-world accuracy.

• Ignores cultural and social factors that also influence helping behavior.

Cognitive explanation → Empathy based altruism → Batson et al (1981)

Aim:

• To investigate participants' motives to help when they had the opportunity to escape, based on the empathy-altruism theory.

Procedure:

• Participants believed they were working with another student, 'Elaine', to study how stress affects performance.

• They were assigned the role of observer and watched Elaine via CCTV as she performed a memory task.

• During the task, Elaine was given electric shocks at random intervals. Participants were then offered the chance to swap places with her.

• Independent variables:

  • Empathy level:

    • High empathy: Elaine’s questionnaire responses were similar to the participant’s.

    • Low empathy: Elaine’s responses were different.

  • Ease of escape:

    • Easy escape: Participants could leave after 2 trials.

    • Difficult escape: Participants had to stay for all 10 trials.

Results:

• High empathy condition: Most participants agreed to swap places, whether escape was easy or difficult.

• Low empathy condition: Most participants chose to leave when escape was easy; some agreed to swap in the difficult escape condition.

Conclusion:

• High empathy led to altruistic helping (help regardless of personal cost).

• Low empathy with difficult escape led to egoistic helping (help to reduce personal distress).

Cognitive explanation → Empathy based altruism → Batson et al (1981) → Evaluation

• Generalizability:

  • Limited; participants were mostly university students from the USA — may not represent wider populations or different cultures.

• Reliability:

  • High; standardized procedure (same setup, tasks, and conditions) allows replication.

• Application:

  • Useful for understanding real-world prosocial behavior, especially how empathy can drive helping actions.

• Validity:

  • Strong internal validity due to tight control of variables; however, artificial lab setting may reduce ecological validity.

• Ethics:

  • Ethical concerns; participants were deceived (believing shocks were real), and the study involved emotional distress.

Sociocultural explanation → Social cognitive explication

• Social Cognitive Theory suggests that people learn prosocial behaviour through observational learning and role models—especially during childhood.

• Samuel Oliner (1992) studied rescuers of Jews during the Holocaust and found that they often held strong values of compassion, justice, and responsibility.

• These values were likely learned from parents and caregivers, supporting the idea that prosocial behaviour is influenced by socialisation and modeling, rather than purely personality or biology.

Sociocultural explanation → Social cognitive explication → evaluation

Strengths:

• Emphasizes learning through observation and role models, especially during childhood.

• Supported by research (e.g., Oliner, 1992 – Holocaust rescuers learned values from parents).

• Explains how values like compassion and responsibility are passed on through socialization.

• Useful in educational and community settings to encourage prosocial behavior.

Limitations:

• May overlook biological or personality factors (e.g., innate empathy, genetics).

• Doesn't fully explain spontaneous prosocial behavior without prior observation.

• Oliner’s study has limited generalizability – based on a unique sample.

• Hard to experimentally test or replicate observational learning in real-world contexts.

Sociocultural explanation → Social cognitive explication → Park and Shin (2017)

Aim:
To investigate the influence of social cognitive theory on prosocial behavior by manipulating peer influence.

Method and Procedure:

• Participants: 125 South Korean university students.

• Independent Variables:

  1. Direct peer influence: Confederate's prosocial behavior (signing a petition or donating money) vs. neutral behavior.

  2. Indirect peer influence: Participants reading either prosocial or neutral messages before the experiment

  3. Dependent Variable: Whether participants signed a petition or donated money to a charity.

• Participants were provided with additional money to encourage donations.

• Confederate Behavior:

  • Neutral condition: The confederates did not donate or sign the petition.

  • Prosocial condition: The confederates modeled prosocial behavior by donating and signing.

• Participants were observed to see if they mimicked the confederates' actions.Results:

• Participants were strongly influenced by confederates who modeled prosocial behavior, signing the petition and donating money.

• Indirect influence through reading prosocial messages had minimal impact.

Conclusion:
Direct peer influence through modeling prosocial behavior was effective in encouraging prosocial actions, while indirect influence via messages had little effect. This supports the role of observational learning in prosocial behavior.

Sociocultural explanation →Social cognitive explication → Park and Shin (2017) → Evaluation

G - Generalizability:
Limited to South Korean university students; findings may not apply to other cultures or age groups.

R - Reliability:
High reliability due to controlled procedure, consistent measurement of prosocial behavior, and replication potential.

A - Applications:
Useful for promoting prosocial behaviors in various contexts like education or charity campaigns.

V - Validity:

• Internal Validity: Strong, with controlled variables and clear manipulation of peer influence.

• External Validity: Limited due to artificial setting and potential demand characteristics.

E - Ethical Considerations:
Ethical concerns are minimal, though the use of confederates may raise deception issues. No mention of debriefing.

Sociocultural explanation → Culture and prosocial behaviour

• Definition of Culture: Culture includes social behavior, norms, beliefs, customs, and institutions within human societies.

• Cooperation & Evolution:

  • Tomasello et al. (2012) theorized that human cooperation evolved from small-scale foraging societies, leading to shared cultural norms for collaboration.

  • This suggests that altruism may have evolutionary origins and that prosocial behavior is rooted in cooperative cultural norms.

• Cross-Cultural Prosocial Behavior:

  • If cultural norms influence helping behavior, then differences in prosocial actions should appear in cross-cultural studies.

  • However, since cooperation evolved similarly across cultures, prosocial behavior may also be largely similar worldwide.

Sociocultural explanation → Culture and prosocial behaviour →evaluation

• Cultural relevance: This explanation recognizes the role of culture in shaping norms of helping and cooperation, aligning with sociocultural theory’s emphasis on environment and social context in influencing behaviour.

• Cross-cultural support: Research like Whiting & Whiting (1975) and Oliner & Oliner (1992) supports the idea that prosocial behaviour varies with cultural values and upbringing, strengthening this perspective.

• Evolutionary-cultural link: Tomasello et al. (2012) effectively bridges evolutionary and sociocultural explanations by proposing that cooperative behaviour evolved in small-scale societies and was then passed on through cultural norms.

• Limited explanation of individual differences: This theory may not fully explain why individuals within the same culture behave differently—biological or cognitive factors could also play key roles.

• Difficult to isolate cultural effects: Prosocial behaviour likely results from a mix of sociocultural, biological, and cognitive influences, making it hard to determine the specific impact of culture alone.

Sociocultural explanation → Culture and prosocial behaviour → Whiting and whiting (1975)

Aim:
To compare prosocial behaviour across six cultures based on child-rearing practices.

Method:

• Naturalistic observation of children aged 3–11 in USA, Mexico, India, Japan, the Philippines, and Kenya.

• Daily observations in homes and communities.

• Focused on prosocial behaviours like food preparation, childcare, and household chores.

Results:

• Kenyan children showed the most prosocial behaviour (traditional, collectivist society).

• Mexico and the Philippines also ranked high in family involvement.

• USA showed the least prosocial behaviour and more egocentrism; American children often helped only when rewarded.

Conclusion:
Cultural values (e.g., collectivism vs. individualism) influence prosocial behaviour, especially through child-rearing practices and social norms taught in the home.

Sociocultural explanation → Culture and prosocial behaviour → Whiting and whiting (1975) → Evaluation

• G – Generalisability:

  • Cross-cultural sample across six countries increases generalisability,

  • but results may not apply to all cultures or subcultures within each country.

• R – Reliability:

  • Naturalistic observation increases ecological validity,

  • But observational methods may lack standardisation and consistency across locations.

• A – Application:

  • Useful for understanding how cultural norms and parenting shape prosocial behaviour—especially relevant for education and parenting practices.

• V – Validity:

• High ecological validity due to real-life observation,

• but observer bias or cultural misunderstandings may affect internal validity.

• E – Ethics:

• Non-invasive observation means low ethical risk,

• however, informed consent and privacy concerns might arise, especially with children.

Promoting Prosocial Behavior

One effective way to promote prosocial behaviour is through early socialisation and education. Research suggests that childhood is the optimal time to teach prosocial norms due to the brain's plasticity. If children are socialised to view helping others as a social expectation, it can reduce the bystander effect and increase helping behaviour. Bandura’s Social Cognitive Theory supports this idea, showing that individuals learn behaviours through observation and reinforcement. Therefore, modelling prosocial behaviour—both in person and through media—can encourage children to adopt similar actions. Reinforcement, both positive (rewarding prosocial acts) and negative (discouraging antisocial acts), further strengthens this learning process, helping to develop lasting prosocial habits.

Promoting Prosocial Behavior → Park and Shin (2017)

full study then:

Park and Shin (2017) found that Korean children who watched prosocial media (where characters helped others) were more likely to show prosocial behaviour themselves. This supports Bandura’s Social Cognitive Theory, which says people can learn by watching others. If children see helping behaviour being shown and rewarded in the media, they may copy it. This shows that prosocial media can be used to teach children to help others. Since children are still developing, this kind of learning is especially effective when they are young. It shows how media and role models can be used to promote prosocial behaviour in society.

Promoting Prosocial Behavior → Batson et al (1981)

Study first then:

Batson et al. (1981) found that when people felt high empathy toward someone in distress, they were more likely to help—even when they had the chance to leave and avoid the situation. This supports the empathy-altruism hypothesis, which says that people help others not for personal gain, but because they care. This suggests that promoting empathy, especially through education and socialisation, could increase prosocial behaviour. If young people are taught to understand and care about others' feelings, they may become more willing to help in real-life situations.