define contact hypothesis

Allport’s Intergroup Contact Hypothesis: Its History and Influence

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Contact hypothesis was proposed by Gordon Allport (1897-1967) and states that social contact between social groups is sufficient to reduce intergroup prejudice.

However, empirical evidence suggests that this is only in certain circumstances.

Key Takeaways:

The contact hypothesis fundamentally rests on the idea that ingroups who have more interactions with a certain outgroup tend to develop more positive perceptions and fewer negative perceptions of that outgroup.
Theorists have long been interested in intergroup conflict . However, Robin Williams and Gordon Allport proposed a number of conditions for ameliorating intergroup conflict that has formed the basis of empirical research for several decades.
Allport suggests four “positive factors” leading to better intergroup relations; however, recent research suggests that these factors can facilitate but are not necessary for reducing intergroup prejudice.
Although originally studied in the context of race and ethnic relations, the contact hypothesis has applicability between ingroup-outgroup relations across religion, age, sexuality, disease status, economic circumstances, and so on.

Contact Hypothesis

The Contact Hypothesis is a psychological theory that suggests that direct contact between members of different social or cultural groups can reduce prejudice, improve intergroup relations, and promote mutual understanding.

According to this hypothesis, interpersonal contact can lead to positive attitudes, decreased stereotypes, and increased acceptance between individuals from different groups under certain conditions.

The Contact Hypothesis was first proposed by Gordon W. Allport in 1954 and has since been supported by numerous studies in the field of social psychology. T

The contact theory suggests that contact between groups is more likely to be effective in reducing prejudice and improving relations if it meets specific criteria:

1. Equal Status Between Groups

Members of the contact situation should not have an unequal, hierarchical relationship (e.g., teacher/student, employer/employee).

Both groups perceive the other to be of equal status in the situation (Cohen, 1982; Riordan and Ruggiero, 1980; Pettigrew and Tropp, 2005).

Although some scholars emphasize that groups should be of equal status both prior to (Brewer and Kramer, 1985) and during (Foster and Finchilescu, 1986) a contact situation, research demonstrated that equal status could promote positive intergroup attitudes even when the groups initially differ in status (Patchen, 1982; Schofield and Rich-Fulcher, 2001).

2. Common Goals

Members must rely on each other to achieve their shared desired goal. To have effective contact, typically, groups need to be making an active effort toward a goal that the groups share.

For example, a national football team (Chu and Griffey, 1985; Patchen, 1982) could draw from many people of different races and ethnic origins — people from different groups — in working together and replying to each other to achieve their shared goals of winning. This tends to lead to Allport’s third characteristic of intergroup contact; intergroup cooperation (Pettigrew and Tropp, 2005).

3. Intergroup Cooperation

Members should work together in a non-competitive environment.

According to Allport (1954), the attainment of these common goals must be based on cooperation over competition. For example, in Sheriff et al. ‘s (1961) Robbers’ Cave field study , researchers devised barriers to common goals, such as a planned picnic that could only be resolved with cooperation between both groups.

This intergroup cooperation encourages positive relations between the groups. Another instance of intergroup cooperation has been studied in schools (e.g., Brewer and Miller, 1984; Johnson, Johnson, and Maruyama, 1984; Schofield, 1986).

For example, Elliot Aronson developed a “jigsaw” approach such that students from diverse backgrounds work toward common goals, fostering positive relationships among children worldwide (Aronson, 2002).

4. The Support of Authorities, Law, or Custom

The support of authorities, law, and customs also tend to lead to more positive intergroup contact effects because authorities can establish norms of acceptance and guidelines for how group members should interact with each other.

There should not be official laws enforcing segregation. This importance has been demonstrated in such wide-ranging circumstances as the military (Landis, Hope, and Day, 1983), business (Morrison and Herlihy, 1992), and religion (Parker, 1968).

Legislation, such as the civil-rights acts in American society, can also be instrumental in establishing anti-prejudicial norms (Pettigrew and Tropp, 2005).

5. Positive Contact Norms

The belief in positive contact norms refers to the understanding that positive interactions between individuals from different groups are the norm and valued by society.

When individuals perceive that positive contact is socially accepted and encouraged, it can increase the effectiveness of intergroup contact.

6. Personal Accountability

A belief in personal accountability for one’s actions and attitudes is important for effective intergroup contact.

Taking responsibility for one’s biases, stereotypes, and prejudices and actively working towards changing them, can contribute to positive intergroup relationships.

7. Empathy and Perspective-Taking

The belief in the importance of empathy and perspective-taking can enhance intergroup contact.

When individuals try to understand and empathize with the experiences and perspectives of members from other groups, it can lead to greater mutual understanding and positive relationships.

Why Does Contact Reduce Prejudice?

Brewer and Miller (1996) and Brewer and Brown (1998) suggest that these conditions can be viewed as an application of dissonance theory (Festinger, 1957).

Specifically, when individuals with negative attitudes toward specific groups find themselves in situations in which they engage in positive social interactions with members of those groups, their behavior is inconsistent with their attitudes.

This dissonance, it is theorized, may result in a change of attitude to justify the new behavior if the situation is structured so as to satisfy the above four conditions.

In contrast, Forbes (1997) asserts that most social scientists implicitly assume that increased interracial/ethnic contact reduces tension between groups by giving each information about the other.

Those who write, adopt, participate in or evaluate prejudice reduction programs are likely to have explicit or implicit informal theories about how prejudice reduction programs work.

Examples of Contact Hypothesis

Homelessness.

Historically, in contact hypothesis research, racial and ethnic minorities have been the out-group of choice; however, the hypothesis can extend to out-groups created by a number of factors. One such alienating situation is homelessness.

Like many out-groups, homeless people are more visible than they once were because of their growth in number as well as extensive media and policy coverage.

This has elicited a large amount of stigmatization and associations between homelessness and poor physical and mental health, substance abuse, and criminality, and ethnographic studies have revealed that homeless people are regularly degraded, avoided, or treated as non-persons by passersby (Anderson, Snow, and Cress, 1994).

Lee, Farrell, and Link (2004) used data from a national survey of public attitudes toward homeless people to evaluate the applicability of the contact hypothesis to relationships between homeless and housed people, even in the absence of Allport’s four positive factors.

The researchers found that even taking selection and social desirability biases into account, general exposure to homeless people tended to affect public attitudes toward homeless people favorably (Lee, Farrell, and Link, 2004).

Contact Between Age Groups

In the 1980s, there was a trend of pervasive age segregation in American society, with children and adults tending to pursue their own separate and independent lives (Caspi, 1984).

This had consequences such as a lack of transmission of work skills and culture, poor preparation for parenthood, and generally inaccurate stereotypes and unfavorable attitudes toward other age groups.

Caspi (1984) assessed the effects of cross-age contact on the attitudes of children toward older adults by comparing children attending an age-integrated preschool to children attending a traditional preschool.

Those in the age-integrated preschool (having daily contact with older adults) tended to hold positive attitudes toward older adults, while those without such contact tended to hold vague or indifferent attitudes.

In addition, children placed in the age-integrated preschool show better differentiation between adult age groups than those not in that preschool.

These findings were among the first to suggest that Allport’s contact hypothesis held relevance in intergroup contact beyond race relations (Caspi, 1984).

Contact Between Religious Groups in Indonesia and the Philippines

Following a resurgence of religion-related conflict and religiously motivated intolerance and violence and the 1999-2002 outbreak of sectarian violence in Ambon, Indonesia, between Christians and Muslims, researchers have become motivated to find ways to reduce acts of religiously motivated intolerance.

Kanas, Scheepers, and Sterkens (2015) examined the relationship between interreligious contact and negative attitudes toward religious out-groups by conducting surveys of Christian and Muslim students in Indonesia and the Philippines.

They attempted to answer the following questions (Kanas, Sccheeepers, and Sterkens, 2015):

Does positive interreligious contact reduce, while negative interreligious contact induces negative attitudes towards the religious out-group?
Does the perception of group threat provide a valid mechanism for both the positive and negative effects of interreligious contact?
Does positive interreligious contact reduce negative out-group attitudes when intergroup relations are tense and both groups experience extreme conflict and violence?

The researchers focused on four ethnically and religiously diverse regions of Indonesia and the Philippines: Maluku and Yogyakarta, the Autonomous Region in Muslim Mindanao, and Metro Manila, with Maluku and the Autonomous Region in Muslim Mindanao having more substantial religious conflicts than the other two regions.

Kanas, Scheepers, and Sterkens found that even accounting for the effects of self-selection, interreligious friendships reduced negative attitudes toward the religious out-group, while casual interreligious contact tended to increase negative out-group attitudes.

In regions experiencing more interreligious violence, there was no effect on interreligious friendships but a further deterioration in effect between casual interreligious contact and negative out-group attitudes.

Kanas, Scheepers, and Sterrkens believed that this effect could be explained by perceived group threat.

Evaluating the Contact Hypothesis

Allport’s testable formulation of the Contact Hypothesis has spawned research using a wide range of approaches, such as field studies, laboratory experiments, surveys, and archival research.

Pettigrew and Tropp (2005) conducted a 5-year meta-analysis on 515 studies (a method where researchers gather data from every possible study and statistically pool results to examine overall patterns) to uncover the overall effects of intergroup contact on prejudice and assess the specific factors that Allport identified as important for successful intergroup contact.

These studies ranged from the 1940s to the year 2000 and represented responses from 250,493 individuals across 38 countries.

The researchers found that, in general, greater levels of intergroup contact were associated with lower levels of prejudice and that more rigorous research studies actually revealed stronger relationships between contact and lowered prejudice (Pettigrew and Tropp, 2005).

The meta-analysis showed that the positive effects of contact on group relations vary dramatically between the nature of the groups, such as age, sexual orientation, disability, and mental illness, with the largest contact effects emerging for contact between heterosexuals and non-heterosexuals.

The smallest contact effects happened between those with and without mental and physical disabilities (Pettigrew and Tropp, 2005).

Although meta-analyses, such as Pettigrew and Tropp’s (2005) show that there is a strong association between intergroup contact and decreased prejudice, whether or not Allport’s four conditions hold is more widely contested.

Some researchers have suggested that the inverse relationship between contact and prejudice still persists in situations that do not match Allport’s key conditions, albeit not as strong as when they are present (Pettigrew and Tropp, 2005).

Gordon Allport taught sociology as a young man in Turkey (Nicholson, 2003) but emphasized proximal and immediate causes and disregarded larger-level, societal causes of intergroup effects.

As a result, both Allport and Williams (1947) doubted whether contact in itself reduced intergroup prejudice and thus attempted to specify a set of “positive conditions” where intergroup contact did.

Researchers have criticized Allport’s “positive factors” approach because it invites the addition of different situational conditions thought to be crucial that actually are not.

As a result, a number of researchers have proposed a host of additional conditions needed to achieve positive contact outcomes (e.g., Foster and Finchilescu, 1986) to the extent that it is unlikely that any contact situation would actually meet all of the conditions specified by the body of contact hypothesis researchers (Pettigrew and Tropp, 2005).

Researchers have also criticized Allport for not specifying the processes involved in intergroup contact’s effects or how these apply to other situations, the entire outgroup, or outgroups not involved in the contact (Pettigrew, 1998).

For example, Allport’s contact conditions leave open the question of whether contact with one group could lead to less prejudicial opinions of other outgroups.

All in all, Allport’s hypothesis neither reveals the processes behind the factors leading to the intergroup contact effect nor its effects on outgroups not involved in contact (Pettigrew, 1998).

Theorists have since pivoted their stance on the intergroup contact hypothesis to believing that intergroup contact generally diminishes prejudice but that a large number of facilitating factors can increase or decrease the magnitude of the effect.

In fact, according to newer theoretical approaches, there are negative factors that can even subvert the way that contact normally reduces prejudice (Pettigrew and Tropp, 2005).

For example, groups that tend to feel anxiety and threat toward others tend to have less decreased prejudice when put in contact with other groups (Blair, Park, and Bachelor, 2003; Stephan et al., 2002).

Indeed, more recent research into the contact hypothesis has suggested that the underlying mechanism of the phenomenon is not increased knowledge about the out-group in itself but empathy with the out-group and a reduction in intergroup threat and anxiety (Pettigrew and Tropp, 2008; Kanas, Scheepers, and Sterkens, 2015).

Social Darwinists such as William Graham Sumner (1906) believed that intergroup contact almost inevitably leads to conflict. Sumner believed that because most groups believed themselves to be superior, intergroup hostility and conflict were natural and inevitable outcomes of contact.

Perspectives such as those in Jackson (1983) and Levine and Campbell (1972) make similar predictions. In the twentieth century, perspectives began to diversify.

While some theorists believed that contact between in groups, such as between races, bred “suspicion, fear, resentment, disturbance, and at times open conflict” (Baker, 1934), others, such as Lett (1945), believed that interracial contact led to “mutual understanding and regard.”

Nonetheless, these early investigations were speculative rather than empirical (Pettigrew and Tropp, 2005). The emerging field of social psychology emphasized theories of intergroup contact.

The University of Alabama researchers Sims and Patrick (1936) were among the first to conduct a study on intergroup contact but found, discouragingly, that the anti-black attitudes of northern white students increased when immersed in the then all-white University of Alabama.

Aligning more with the later work of Allport, Brophy (1946) studied race relations between blacks and whites in the nearly-desegregated Merchant Marine. The researchers found that the more voyages that white seamen took with black seamen, the more positive their racial attitudes became.

In a similar direction, white police in Philadelphia with black colleagues showed fewer objections to working with black partners, having black people join previously all-white police districts, and taking orders from qualified black police officers (Kephart, 1957; Pettigrew and Tropp, 2005).

Following these studies, Cornell University sociologist Robin Williams Jr. offered 102 propositions on intergroup relations that constituted an initial formulation of intergroup contact theory.

These propositions generally stressed that intergroup contact reduces prejudice when (Williams, 1947):

The two groups share similar statuses, interests, and tasks;
the situation fosters personal, intimate intergroup contact;
participants do not fit stereotypical conceptions of their group members;
the activities cut across group lines.

Stouffer et al. offered the first extensive field study of the effects of intergroup contact (1949).

Stouffer et al. demonstrated that white soldiers who fought alongside black soldiers in the 1944-1945 Battle of the Bulge tended to have far more positive attitudes toward their black colleagues (Pettigrew and Tropp, 2005), regardless of status or place of origin.

Researchers such as Deutsch and Collins (1951); Wilner, Walkley, and Cook (1955); and Works (1961) supported mounting evidence that contact diminished racial prejudice among both blacks and whites through their studies of racially desegregated housing projects.

Allport, G. W. (1955). The nature of prejudice. In: JSTOR.

Anderson, L., Snow, D. A., & Cress, D. (1994). Negotiating the public realm: Stigma management and collective action among the homeless. Research in Community Sociology, 1(1), 121-143.

Aronson, E. (2002). Building empathy, compassion, and achievement in the jigsaw classroom. In Improving academic achievement (pp. 209-225): Elsevier.

Baker, P. E. (1934). Negro-white adjustment in America. Journal of Negro Education, 194-204.

Blair, I. V., Park, B., & Bachelor, J. (2003). Understanding Intergroup Anxiety: Are Some People More Anxious than Others? Group Processes & Intergroup Relations, 6(2), 151-169. doi:10.1177/1368430203006002002

Brewer, M. B., & Kramer, R. M. (1985). The psychology of intergroup attitudes and behavior. Annual review of psychology, 36(1), 219-243.

Brophy, I. N. (1945). The luxury of anti-Negro prejudice. Public opinion quarterly, 9(4), 456-466.

Caspi, A. (1984). Contact Hypothesis and Inter-Age Attitudes: A Field Study of Cross-Age Contact. Social Psychology Quarterly, 47(1), 74-80. doi:10.2307/3033890

Chu, D., & Griffey, D. (1985). The contact theory of racial integration: The case of sport. Sociology of Sport Journal, 2(4), 323-333.

Cohen, E. G. (1982). Expectation states and interracial interaction in school settings. Annual review of sociology, 8(1), 209-235.

Deutsch, M., & Collins, M. E. (1951). Interracial housing: A psychological evaluation of a social experiment: U of Minnesota Press.

Foster, D., & Finchilescu, G. (1986). Contact in a”non-contact”society: The case of South Africa.

Jackson, J. W. (1993). Contact theory of intergroup hostility: A review and evaluation of the theoretical and empirical literature. International Journal of Group Tensions, 23(1), 43-65.

Jackson, P. (1985). Social geography: race and racism. Progress in Human Geography, 9(1), 99-108.

Johnson, D., Johnson, R., & Maruyama, G. (1984). Goal Interdependence and Interpersonal-personal Attraction in Heterogeneous Classrooms: a meta analysis, chapter in Miller N & Brewer MB Groups in Contact: The Psychology of Desegregation. In: New York: Academic Press.

Kanas, A., Scheepers, P., & Sterkens, C. (2015). Interreligious Contact, Perceived Group Threat, and Perceived Discrimination:Predicting Negative Attitudes among Religious Minorities and Majorities in Indonesia. Social Psychology Quarterly, 78(2), 102-126. doi:10.1177/0190272514564790

Kephart, W. M. (2018). Racial factors and urban law enforcement: University of Pennsylvania Press.

Kramer, B. M. (1950). Residential contact as a determinant of attitudes toward Negroes. Harvard University.

Lee, B. A., Farrell, C. R., & Link, B. G. (2004). Revisiting the Contact Hypothesis: The Case of Public Exposure to Homelessness. American Sociological Review, 69(1), 40-63. doi:10.1177/000312240406900104

Lee, F. F. (1956). Human Relations in Interracial Housing: A Study of the Contact Hypothesis. In: JSTOR.

Lett, H. A. (1945). Techniques for achieving interracial cooperation. Harvard Educational Review, 15(1), 62-71.

LeVine, R. A., & Campbell, D. T. (1972). Ethnocentrism: Theories of conflict, ethnic attitudes, and group behavior.

MacKenzie, B. K. (1948). The importance of contact in determining attitudes toward Negroes. The Journal of Abnormal and Social Psychology, 43(4), 417.

Morrison, E. W., & Herlihy, J. M. (1992). Becoming the best place to work: Managing diversity at American Express Travel related services. Diversity in the Workplace, 203-226.

Nicholson, I. A. M. (2003). Inventing personality: Gordon Allport and the science of selfhood. Washington, DC, US: American Psychological Association.

Parker, J. H. (1968). The Interaction of Negroes and Whites in an Integrated Church Setting. Social Forces, 46(3), 359-366. doi:10.2307/2574883

Pettigrew, T. F. (1998). INTERGROUP CONTACT THEORY. Annual review of psychology, 49(1), 65-85. doi:10.1146/annurev.psych.49.1.65

Pettigrew, T. F., & Tropp, L. R. (2005). Allport’s intergroup contact hypothesis: Its history and influence. On the nature of prejudice: Fifty years after Allport, 262-277.

Riordan, C., & Ruggiero, J. (1980). Producing equal-status interracial interaction: A replication. Social Psychology Quarterly, 131-136. Schofield, J. W. (1986). Black-White contact in desegregated schools.

Schofield, J. W., & Eurich-Fulcer, R. (2004). When and How School Desegregation Improves Intergroup Relations.

Sims, V. M., & Patrick, J. R. (1936). Attitude toward the Negro of northern and southern college students. The Journal of Social Psychology, 7(2), 192-204.

Stephan, W. G., Boniecki, K. A., Ybarra, O., Bettencourt, A., Ervin, K. S., Jackson, L. A., . . . Renfro, C. L. (2002). The Role of Threats in the Racial Attitudes of Blacks and Whites. Personality and Social Psychology Bulletin, 28(9), 1242-1254. doi:10.1177/01461672022812009

Stouffer, S. A., Suchman, E. A., DeVinney, L. C., Star, S. A., & Williams Jr, R. M. (1949). The american soldier: Adjustment during army life.(studies in social psychology in world war ii), vol. 1.

Sumner, W. G. (1906). Folkways: The Sociological Importance of Usages. Manners, Customs, Mores, and Morals, Ginn & Co., New York, NY.

Williams Jr, R. M. (1947). The reduction of intergroup tensions: a survey of research on problems of ethnic, racial, and religious group relations. Social Science Research Council Bulletin.

Works, E. (1961). The prejudice-interaction hypothesis from the point of view of the Negro minority group. American Journal of Sociology, 67(1), 47-52.

Further Information

Dovidio, J. F., Love, A., Schellhaas, F. M., & Hewstone, M. (2017). Reducing intergroup bias through intergroup contact: Twenty years of progress and future directions. Group Processes & Intergroup Relations, 20(5), 606-620.

Pettigrew, T. F., Tropp, L. R., Wagner, U., & Christ, O. (2011). Recent advances in intergroup contact theory. International journal of intercultural relations, 35(3), 271-280.

Pettigrew, T. F., & Tropp, L. R. (2006). A meta-analytic test of intergroup contact theory. Journal of personality and social psychology, 90(5), 751.

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What Is the Contact Hypothesis in Psychology?

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Archaeology
Ph.D., Psychology, University of California - Santa Barbara
B.A., Psychology and Peace & Conflict Studies, University of California - Berkeley

The contact hypothesis is a theory in psychology which suggests that prejudice and conflict between groups can be reduced if members of the groups interact with each other.

Key Takeaways: Contact Hypothesis

The contact hypothesis suggests that interpersonal contact between groups can reduce prejudice.
According to Gordon Allport, who first proposed the theory, four conditions are necessary to reduce prejudice: equal status, common goals, cooperation, and institutional support.
While the contact hypothesis has been studied most often in the context of racial prejudice, researchers have found that contact was able to reduce prejudice against members of a variety of marginalized groups.

Historical Background

The contact hypothesis was developed in the middle of the 20th century by researchers who were interested in understanding how conflict and prejudice could be reduced. Studies in the 1940s and 1950s , for example, found that contact with members of other groups was related to lower levels of prejudice. In one study from 1951 , researchers looked at how living in segregated or desegregated housing units was related to prejudice and found that, in New York (where housing was desegregated), white study participants reported lower prejudice than white participants in Newark (where housing was still segregated).

One of the key early theorists studying the contact hypothesis was Harvard psychologist Gordon Allport , who published the influential book The Nature of Prejudice in 1954. In his book, Allport reviewed previous research on intergroup contact and prejudice. He found that contact reduced prejudice in some instances, but it wasn’t a panacea—there were also cases where intergroup contact made prejudice and conflict worse. In order to account for this, Allport sought to figure out when contact worked to reduce prejudice successfully, and he developed four conditions that have been studied by later researchers.

Allport’s Four Conditions

According to Allport, contact between groups is most likely to reduce prejudice if the following four conditions are met:

The members of the two groups have equal status. Allport believed that contact in which members of one group are treated as subordinate wouldn’t reduce prejudice—and could actually make things worse.
The members of the two groups have common goals.
The members of the two groups work cooperatively. Allport wrote , “Only the type of contact that leads people to do things together is likely to result in changed attitudes.”
There is institutional support for the contact (for example, if group leaders or other authority figures support the contact between groups).

Evaluating the Contact Hypothesis

In the years since Allport published his original study, researchers have sought to test out empirically whether contact with other groups can reduce prejudice. In a 2006 paper, Thomas Pettigrew and Linda Tropp conducted a meta-analysis: they reviewed the results of over 500 previous studies—with approximately 250,000 research participants—and found support for the contact hypothesis. Moreover, they found that these results were not due to self-selection (i.e. people who were less prejudiced choosing to have contact with other groups, and people who were more prejudiced choosing to avoid contact), because contact had a beneficial effect even when participants hadn’t chosen whether or not to have contact with members of other groups.

While the contact hypothesis has been studied most often in the context of racial prejudice, the researchers found that contact was able to reduce prejudice against members of a variety of marginalized groups. For example, contact was able to reduce prejudice based on sexual orientation and prejudice against people with disabilities. The researchers also found that contact with members of one group not only reduced prejudice towards that particular group, but reduced prejudice towards members of other groups as well.

What about Allport’s four conditions? The researchers found a larger effect on prejudice reduction when at least one of Allport’s conditions was met. However, even in studies that didn’t meet Allport’s conditions, prejudice was still reduced—suggesting that Allport’s conditions may improve relationships between groups, but they aren’t strictly necessary.

Why Does Contact Reduce Prejudice?

Researchers have suggested that contact between groups can reduce prejudice because it reduces feelings of anxiety (people may be anxious about interacting with members of a group they have had little contact with). Contact may also reduce prejudice because it increases empathy and helps people to see things from the other group’s perspective. According to psychologist Thomas Pettigrew and his colleagues , contact with another group allows people “to sense how outgroup members feel and view the world.”

Psychologist John Dovidio and his colleagues suggested that contact may reduce prejudice because it changes how we categorize others. One effect of contact can be decategorization , which involves seeing someone as an individual, rather than as only a member of their group. Another outcome of contact can be recategorization , in which people no longer see someone as part of a group that they’re in conflict with, but rather as a member of a larger, shared group.

Another reason why contact is beneficial is because it fosters the formation of friendships across group lines.

Limitations and New Research Directions

Researchers have acknowledged that intergroup contact can backfire , especially if the situation is stressful, negative, or threatening, and the group members did not choose to have contact with the other group. In his 2019 book The Power of Human , psychology researcher Adam Waytz suggested that power dynamics may complicate intergroup contact situations, and that attempts to reconcile groups that are in conflict need to consider whether there is a power imbalance between the groups. For example, he suggested that, in situations where there is a power imbalance, interactions between group members may be more likely to be productive if the less powerful group is given the opportunity to express what their experiences have been, and if the more powerful group is encouraged to practice empathy and seeing things from the less powerful group’s perspective.

Can Contact Promote Allyship?

One especially promising possibility is that contact between groups might encourage more powerful majority group members to work as allies —that is, to work to end oppression and systematic injustices. For example, Dovidio and his colleagues suggested that “contact also provides a potentially powerful opportunity for majority-group members to foster political solidarity with the minority group.” Similarly, Tropp—one of the co-authors of the meta-analysis on contact and prejudice— tells New York Magazine’s The Cut that “there’s also the potential for contact to change the future behavior of historically advantaged groups to benefit the disadvantaged.”

While contact between groups isn’t a panacea, it’s a powerful tool to reduce conflict and prejudice—and it may even encourage members of more powerful groups to become allies who advocate for the rights of members of marginalized groups.

Sources and Additional Reading:

Allport, G. W. The Nature of Prejudice . Oxford, England: Addison-Wesley, 1954. https://psycnet.apa.org/record/1954-07324-000
Dovidio, John F., et al. “Reducing Intergroup Bias Through Intergroup Contact: Twenty Years of Progress and Future Directions.” Group Processes & Intergroup Relations , vol. 20, no. 5, 2017, pp. 606-620. https://doi.org/10.1177/1368430217712052
Pettigrew, Thomas F., et al. “Recent Advances in Intergroup Contact Theory.” International Journal of Intercultural Relations , vol. 35 no. 3, 2011, pp. 271-280. https://doi.org/10.1016/j.ijintrel.2011.03.001
Pettigrew, Thomas F., and Linda R. Tropp. “A Meta-Analytic Test of Intergroup Contact Theory.” Journal of Personality and Social Psychology , vol. 90, no. 5, 2006, pp. 751-783. http://dx.doi.org/10.1037/0022-3514.90.5.751
Singal, Jesse. “The Contact Hypothesis Offers Hope for the World.” New York Magazine: The Cut , 10 Feb. 2017. https://www.thecut.com/2017/02/the-contact-hypothesis-offers-hope-for-the-world.html
Waytz, Adam. The Power of Human: How Our Shared Humanity Can Help Us Create a Better World . W.W. Norton, 2019.
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magazine issue 2 2013 / Issue 17

Justice seems not to be for all: exploring the scope of justice.

written by Aline Lima-Nunes, Cicero Roberto Pereira & Isabel Correia

That human touch that means so much: Exploring the tactile dimension of social life

written by Mandy Tjew A Sin & Sander Koole

Intergroup Contact Theory: Past, Present, and Future

written by Jim A. C. Everett
edited by Diana Onu

In the midst of racial segregation in the U.S.A and the ‘Jim Crow Laws’, Gordon Allport (1954) proposed one of the most important social psychological events of the 20th century, suggesting that contact between members of different groups (under certain conditions) can work to reduce prejudice and intergroup conflict . Indeed, the idea that contact between members of different groups can help to reduce prejudice and improve social relations is one that is enshrined in policy-making all over the globe. UNESCO, for example, asserts that contact between members of different groups is key to improving social relations. Furthermore, explicit policy-driven moves for greater contact have played an important role in improving social relations between races in the U.S.A, in improving relationships between Protestants and Catholics in Northern Ireland, and encouraging a more inclusive society in post-Apartheid South Africa. In the present world, it is this recognition of the benefits of contact that drives modern school exchanges and cross-group buddy schemes. In the years since Allport’s initial intergroup contact hypothesis , much research has been devoted to expanding and exploring his contact hypothesis . In this article I will review some of the vast literature on the role of contact in reducing prejudice , looking at its success, mediating factors, recent theoretical extensions of the hypothesis and directions for future research. Contact is of utmost importance in reducing prejudice and promoting a more tolerant and integrated society and as such is a prime example of the real life applications that psychology can offer the world.

The Contact Hypothesis

The intergroup contact hypothesis was first proposed by Allport (1954), who suggested that positive effects of intergroup contact occur in contact situations characterized by four key conditions: equal status, intergroup cooperation , common goals, and support by social and institutional authorities (See Table 1). According to Allport, it is essential that the contact situation exhibits these factors to some degree. Indeed, these factors do appear to be important in reducing prejudice , as exemplified by the unique importance of cross-group friendships in reducing prejudice (Pettigrew, 1998). Most friends have equal status, work together to achieve shared goals, and friendship is usually absent from strict societal and institutional limitation that can particularly limit romantic relationships (e.g. laws against intermarriage) and working relationships (e.g. segregation laws, or differential statuses).

Since Allport first formulated his contact hypothesis , much work has confirmed the importance of contact in reducing prejudice . Crucially, positive contact experiences have been shown to reduce self-reported prejudice (the most common way of assessing intergroup attitudes) towards Black neighbors, the elderly, gay men, and the disabled - to name just a few (Works, 1961; Caspi, 1984; Vonofako, Hewstone, & Voci, 2007; Yuker & Hurley, 1987). Most interestingly, though, in a wide-scale meta-analysis (i.e., a statistical analysis of a number of published studies), it has been found that while contact under Allport’s conditions is especially effective at reducing prejudice , even unstructured contact reduces prejudice (Pettigrew & Tropp, 2006). What this means is that Allport’s proposed conditions should be best be seen as of a facilitating, rather than an essential, nature. This is important as it serves to show the importance of the contact hypothesis : even in situations which are not marked by Allport’s optimal conditions, levels of contact and prejudice have a negative correlation with an effect size comparable to those of the inverse relationship between condom use and sexually transmitted HIV and the relationship between passive smoking and the incidence of lung cancer at work (Al-Ramiah & Hewstone, 2011). Contact between groups, even in sub-optimal conditions, is strongly associated with reduced prejudice .

Importantly, contact does not just influence explicit self-report measures of prejudice , but also reduces prejudice as measured in a number of different ways. Explicit measures (e.g. ‘How much do you like gay men?’) are limited in that there can be a self-report bias: people often answer in a way that shows them in a good light. As such, research has examined the effects of contact on implicit measures: measures that involve investigating core psychological constructs in ways that bypass people’s willingness and ability to report their feelings and beliefs. Implicit measures have been shown to be a good complement to traditional explicit measures - particularly when there may be a strong chance of a self-report bias. In computer reaction time tasks, contact has been shown to reduce implicit associations between the participant’s own in-group and the concept ‘good’, and between an outgroup (a group the participant is not a member of) and the concept ‘bad’ (Aberson and Haag, 2007). Furthermore, positive contact is associated with reduced physiological threat responses to outgroup members (Blascovich et al., 2001), and reduced differences in the way that faces are processed in the brain, implying that contact helps to increase perceptions of similarity (Walker et al., 2008). Contact, then, has a real and tangible effect on reducing prejudice – both at the explicit and implicit level. Indeed, the role of contact in reducing prejudice is now so well documented that it justifies being referred to as intergroup contact theory (Hewstone & Swart, 2011).

How does it work?

Multiple mechanisms have been proposed to explain just how contact reduces prejudice . In particular, “four processes of change” have been proposed: learning about the out-group , changing behavior, generating affective ties, and in-group reappraisal (Pettigrew, 1998). Contact can, and does, work through both cognitive (i.e. learning about the out-group , or reappraising how one thinks about one’s own in-group ), behavioural (changing one’s behavior to open oneself to potential positive contact experiences), and affective (generating affective ties and friendships, and reducing negative emotions) means. A particularly important mediating mechanism (i.e. the mechanisms or processes by which contact achieves its effect) is that of emotions, or affect, with evidence suggesting that contact works to reduce prejudice by diminishing negative affect (anxiety / threat) and inducing positive affect such as empathy (Tausch and Hewstone, 2010). In another meta-analysis , Pettigrew and Tropp (2008) supported this by looking specifically at mediating mechanisms in contact and found that contact situations which promote positive affect and reduce negative affect are most likely to succeed in conflict reduction. Contact situations are likely to be effective at improving intergroup relations insofar as they induce positive affect, and ineffective insofar as they induce negative affect such as anxiety or threat. If we feel comfortable and not anxious, the contact situation will be much more successful.

Generalizing the effect

An important issue that I have not yet addressed, however, is how these positive experiences after contact can be extended and generalized to other members of the outgroup . While contact may reduce an individual’s prejudice towards (for example) their Muslim colleague, its practical use is strongly limited if it doesn’t also diminish prejudice towards other Muslims. Contact with each and every member of an outgroup – let alone of all out-groups to which prejudice is directed – is clearly unfeasible and so a crucial question in intergroup contact research is how the positive effect can be generalized.

A number of approaches have been developed to explain how the positive effect of contact, including making group saliency low so that people focus on individual characteristics and not group-level attributes (Brewer & Miller, 1984), making group saliency high so that the effect is best generalized to others (Johnston & Hewstone, 1992), and making an overarching common ingroup identity salient (Gaertner, Dovidio, Anastasio, Bachman, & Rust, 1993). Each of these approaches have both advantages and disadvantages, and in particular each individual approach may be most effective at different stages of an extended contact situation. To deal with this issue Pettigrew (1998) proposed a three stage model to take place over time to optimize successful contact and generalization. First is the decategorization stage (as in Brewer & Miller, 1984), where participants’ personal (and not group) identities should be emphasized to reduce anxiety and promote interpersonal liking. Secondly, the individuals’ social categories should be made salient to achieve generalization of positive affect to the outgroup as a whole (as in Johnston & Hewstone, 1992). Finally, there is the recategorization stage, where participants’ group identities are replaced with a more superordinate group: changing group identities from ‘Us vs. Them’ to a more inclusive ‘We’ (as in Gaertner et al., 1993). This stage model could provide an effective method of generalizing the positive effects of intergroup contact.

Theoretical Extensions

Even with such work on generalization, however, it may still be unrealistic to expect that group members will have sufficient opportunities to engage in positive contact with outgroup members: sometimes positive contact between group members is incredibly difficult, if not impossible. For example, at the height of the Northern Ireland conflict, positive contact between Protestants and Catholics was nigh on impossible. As such, recent work on the role of intergroup contact in reducing prejudice has moved away from the idea that contact must necessarily include direct (face-to-face) contact between group members and instead includes the notion that indirect contact (e.g. imagined contact, or knowledge of contact among others) may also have a beneficial effect.

A first example of this approach comes from Wright, Aron, McLaughlin-Volpe, and Ropp’s (1997) extended contact hypothesis . Wright et al. propose that mere knowledge that an ingroup member has a close relationship with an outgroup member can improve outgroup attitudes, and indeed this has been supported by a series of experimental and correlational studies. For example, Shiappa, Gregg, & Hewes, (2005) have offered evidence suggesting that just watching TV shows that portrayed intergroup contact was associated with lower levels of prejudice . A second example of an indirect approach to contact comes from Crisp and Turner’s (2009) imagined contact hypothesis , which suggests that actual experiences may not be necessary to improve intergroup attitudes, and that simply imagining contact with outgroup members could improve outgroup attitudes. Indeed, this has been supported in a number of studies at both an explicit and implicit level: British Muslims (Husnu & Crisp, 2010), the elderly (Abrams, Crisp, & Marques 2008), and gay men (Turner, Crisp, & Lambert, 2007).

These more recent extensions of the contact hypothesis have offered important suggestions on how to most effectively generalize the benefits of the contact situation and make use of findings from work on mediating mechanisms. It seems that direct face-to-face contact is always not necessary, and that positive outcomes can be achieved by positive presentation of intergroup-friendships in the media and even simply by imagining interacting with an outgroup member.

Issues and Directions for Future Research

Contact, then, has important positive effects on improved intergroup relations. It does have its critics, however. Notably, Dixon, Durrheim, & Tredoux (2005) argue that while contact has been important in showing how we can promote a more tolerant society, the existing literature has an unfortunate absence of work on how intergroup contact can affect societal change: changes in outgroup attitudes from contact do not necessarily accompany changes in the ideological beliefs that sustain group inequality. For example, Jackson and Crane (1986) demonstrated that positive contact with Black individuals improved Whites’ affective reactions towards Blacks but did not change their attitudes towards policy in combating inequality in housing, jobs and education. Furthermore, contact may also have the unintended effect of weakening minority members’ motivations to engage in collective action aimed at reducing the intergroup inequalities. For example, Dixon, Durrheim, & Tredoux (2007) found that the more contact Black South Africans had with White South Africans, the less they supported policies aimed at reducing racial inequalities. Positive contact may have the unintended effect of misleading members of disadvantaged groups into believing inequality will be addressed, thus leaving the status differentials intact. As such, a fruitful direction for future research would be to investigate under what conditions contact could lead to more positive intergroup relations without diminishing legitimate protest aimed at reducing inequality. One promising suggestion is to emphasize commonalities between groups while also addressing unjust group inequalities during the contact situation. Such a contact situation could result in prejudice reduction without losing sight of group inequality (Saguy, Tausch, Dovidio, & Pratto, 2009).

A second concern with contact research is that while contact has shown to be effective for more prejudiced individuals, there can be problems with getting a more prejudiced individual into the contact situation in the first place. Crisp and Turner’s imagined contact hypothesis seems to be a good first step in tackling this problem (Crisp & Turner, 2013), though it remains to be seen if, and how, such imagined contact among prejudiced individuals can translate to direct contact. Greater work on individual differences in the efficacy of contact would provide an interesting contribution to existing work.

Conclusions

Contact, then, has been shown to be of utmost importance in reduction of prejudice and promotion of more positive intergroup attitudes. Such research has important implications for policy work. Work on contact highlights the importance of institutional support and advocation of more positive intergroup relations, the importance of equal status between groups, the importance of cooperation between groups and the importance of positive media presentations of intergroup friendships - to name just a few. As Hewstone and Swart (2011) argue,

“Theory-driven social psychology does matter, not just in the laboratory, but also in the school, the neighborhood, and the society at large” (Hewstone & Swart, 2011. p.380).

Aberson, C. L., & Haag, S. C. (2007). Contact, perspective taking, and anxiety as predictors of stereotype endorsement, explicit attitudes, and implicit attitudes. Group Processes and Intergroup Relations, 10 , 179–201.
Abrams, D. and Crisp, R.J. & Marques, S., (2008). Threat inoculation: Experienced and Imagined intergenerational contact prevent stereotype threat effects on older peoples math performance. Psychology and Aging, 23 (4), 934-939.
Al Ramiah, A., & Hewstone, M. (2011). Intergroup difference and harmony: The role of intergroup contact. In P. Singh, P. Bain, C-H. Leong, G. Misra, and Y. Ohtsubo. (Eds.), Individual, group and cultural processes in changing societies. Progress in Asian Social Psychology (Series 8), pp. 3-22. Delhi: University Press.
Allport, G. W. (1954). The nature of prejudice . Cambridge/Reading, MA: Addison-Wesley.
Aronson, E., & Patnoe, S. (1997). The jigsaw classroom: Building cooperation in the classroom (Vol. 978, p. 0673993830). New York: Longman.
Blascovich, J., Mendes, W. B., Hunter, S. B., Lickel, B., & Kowai-Bell, N. (2001). Perceiver threat in social interactions with stigmatized others. Journal of Personality and Social Psychology, 80, 253–267.
Brewer, M. B., & Kramer, R. M. (1985). The psychology of intergroup attitudes and behavior. Annual review of psychology, 36 (1), 219-243.
Brewer, M. B., & Miller, N. (Eds.). (1984). Groups in contact: The psychology of desegregation. Academic Press.
Caspi, A. (1984). Contact hypothesis and inter-age attitudes: A field study of cross-age contact. Social Psychology Quarterly, 74-80.
Chu, D., & Griffey, D. (1985). The contact theory of racial integration: The case of sport. Sociology of Sport Journal, 2 (4), 323-333.
Cohen, E. G., & Lotan, R. A. (1995). Producing equal-status interaction in the heterogeneous classroom. American Educational Research Journal, 32 (1), 99-120.
Crisp, R. J., & Turner, R. N. (2009). Can imagined interactions produce positive perceptions? Reducing prejudice through simulated social contact. American Psychologist, 64, 231–240.
Crisp, R. J., & Turner, R. N. (2013). Imagined intergroup contact: Refinements, debates and clarifications. In G. Hodson & M. Hewstone (Eds.), Advances in intergroup contact. New York, NY: Psychology Press.
Dixon, J., Durrheim, K., & Tredoux, C. (2005). Beyond the optimal contact strategy: A reality check for the contact hypothesis . American Psychologist, 60, 697–711.
Dixon, J., Durrheim, K., & Tredoux, C. (2007). Intergroup contact and attitudes toward the principle and practice of racial equality. Psychological Science, 18, 867–872.
Gaertner, S. L., Dovidio, J. F., Anastasio, P. A., Bachman, B. A., & Rust, M. C. (1993). The common ingroup identity model: Recategorization and the reduction of intergroup bias. European Review of Social Psychology, 4 (1), 1-26.
Hewstone, M., & Swart, H. (2011). Fifty-odd years of inter-group contact: From hypothesis to integrated theory. British Journal of Social Psychology, 50 (3), 374-386.
Husnu, S. & Crisp, R. J. (2010). Elaboration enhances the imagined contact effect. Journal of Experimental Social Psychology, 46, 943-950
Jackman, M.R., & Crane, M. (1986). “Some of my best friends are black...”: interracial friendship and whites’ racial attitudes. Public Opinion Quarterly 50, pp. 459–86
Johnston, L., & Hewstone, M. (1992). Cognitive models of stereotype change: 3. Subtyping and the perceived typicality of disconfirming group members. Journal of Experimental Social Psychology, 28 (4), 360-386.
Landis D., Hope R.O., & Day H.R. (1984). Training for desegregation in the military. In N. Miller & M. B. Brewer 1984, Groups in Contact: The Psychology of Desegregation, pp. 257–78. Orlando, FL: Academic Press.
Miller, N., & Brewer M. B., eds. (1984). Groups in Contact: The Psychology of Desegregation. Orlando, FL: Academic Press.
Pettigrew, T. F. (1998). Intergroup contact theory. Annual review of psychology, 49 (1), 65-85.
Pettigrew, T. F., & Tropp, L. R. (2006). A meta- analytic test of intergroup contact theory. Journal of Personality and Social Psychology, 90 (5), 751.
Pettigrew, T. F., & Tropp, L. R. (2008). How does intergroup contact reduce prejudice ? Meta- analytic tests of three mediators. European Journal of Social Psychology, 38 (6), 922-934.
Saguy, T., Tausch, N., Dovidio, J. F., & Pratto, F. (2009). The irony of harmony: Intergroup contact can produce false expectations for equality. Psychological Science, 20 , 114–121.
Schiappa, E., Gregg, P. B., & Hewes, D. E. (2006). Can One TV Show Make a Difference? Will & Grace and the Parasocial Contact Hypothesis . Journal of Homosexuality, 51 (4), 15-37.
Tausch, N., & Hewstone, M. (2010). Intergroup contact and prejudice . In J. F. Dovidio, M. Hewstone, P. Glick, & V. M. Esses (Eds.), The Sage handbook of prejudice , stereotyping, and discrimination (pp. 544–560). Newburg Park, CA: Sage.
Turner, R. N., Crisp, R. J., & Lambert, E. (2007). Imagining intergroup contact can improve intergroup attitudes. Group Processes and Intergroup Relations, 10 , 427-441.
Vonofakou, C., Hewstone, M., & Voci, A. (2007). Contact with outgroup friends as a predictor of meta-attitudinal strength and accessibility of attitudes towards gay men. Journal of Personality and Social Psychology, 92 , 804–820.
Works, E. (1961).The prejudice -interaction hypothesis from the point of view of the Negro minority group. American Journal of Sociology. 67 : 47–52
Wright, S. C., Aron, A., McLaughlin-Volpe, T., & Ropp, S. A. (1997). The extended contact effect: Knowledge of cross-group friendships and prejudice . Journal of Personality and Social Psychology, 73 , 73–90.
Yuker, H. E., & Hurley, M. K. (1987). Contact with and attitudes toward persons with disabilities: The measurement of intergroup contact. Rehabilitation Psychology, 32 (3), 145.

From the editors

Everett (2013) presents an excellent overview of the research on Intergroup Contact Theory and how psychologists have used it to understand prejudice and conflict. As the article notes, friendship between members of different groups is one form of contact that helps dissolve inter-group conflict. Friendships are beneficial because of “self-expansion,” which is a fundamental motivational process that drives people to grow and integrate new things into their lives (Aron, Norman, & Aron, 1998). When an individual learns something or experiences something for the first time, his/her mind literally grows. When friendships are very intimate, people include aspects of their friends in their own self-concept (Aron, Aron, Tudor, & Nelson, 1991).

For example, if Scott (an American) becomes friends with Dan (a Russian), Scott might grow to appreciate Russian culture, because of their intimacy. Even the word “Russian” is now part of Scott’s own self-concept through this friendship, and Scott will have more positive feelings and attitudes toward Russians as a group. The same process happens for all kinds of other groups based race/ethnicity, religion, sexual orientation, etc.

Importantly, self-expansion and intimacy through friendship do not work like magic; psychologists can’t wave a wand and make them appear. Nor does it happen through superficial small talk (e.g., “how about this crazy weather?”). Intimacy develops through deep communication: sustained, reciprocal, escalating conversations in which two friends come to know each other in a meaningful way. A Christian person might say, “I have a Jewish co-worker” (while talking about a casual acquaintance) or a Caucasian person might say, “I give money to an organization that helps starving people in Africa” or a straight person might say, “I support same-sex marriage equality because I know someone who is gay.” All of that is good, but it’s not as effective at reducing inter-group conflict as a true friendship with someone in those other groups; superficial contact has a small effect on racism, anti-Semitism, or homophobia. A recent meta-analysis (Davies, Tropp, Aron, Pettigrew, & Wright, 2011) revealed that spending lots of time with cross-group friends and having lots of in-depth communication with those friends were the two strongest predictors of change in positive attitudes and prejudice reduction.

At In-Mind, we work in a transnational team and we think this is enriching. What about you? Have you found friendships, or even working relations, across social groups? Did this lead you to have more open or positive attitudes? Or, do you have other experiences?

article author(s)

Jim A. C. Everett

Jim Everett studied for his undergraduate at the University of Oxford, gaining a First Class degree in Psychology, Philosophy, and Physiology. He completed... more

article keywords

discrimination
intergroup contact hypothesis

article glossary

intergroup conflict
recognition
Intergroup Contact Hypothesis
contact hypothesis
cooperation
meta-analysis
stereotypes
stereotype threat
field study

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Contact Hypothesis theory explained

Contact Hypothesis Theory: this article explains the Contact Hypothesis Theory in a practical way. Next to what it is, this article also highlights the intergroup contact and prejudice, stereotypes and discrimination, the conditions and contact hypothesis examples. After reading you will understand the basics of this psychology theory. Enjoy reading!

What is the Contact Hypothesis?

The contact hypothesis is a psychology theory suggesting that prejudice and conflict between groups can be reduced by allowing members of those groups to interact with one another. This notion is also called intra-group contact. Prejudice and conflict usually arise between majority and minority group members.

The background to the contact hypothesis

Social psychologist Gordon Allport is credited with conducting the first studies on intergroup contact.

Allport is also known for this research in the field of personalities . After the Second World War, social scientists and policymakers concentrated mainly on interracial contact. Allport brought these studies together in his study of intergroup contact.

In 1954, Allport published his first hypothesis concerning intergroup contact in the journal of personality and social psychology. The main premise of his article stated that intergroup contact was one of the most effective ways to reduce prejudice between groups.

Allport claimed that contact management and interpersonal contact could produce positive effects against with stereotyping, prejudice and discrimination, leading to better and more worthwhile interaction between two or more groups.

Over the years since Allport’s original article, the hypothesis has been expanded by social scientists and used for research into reducing prejudice relating to racism, disability, women and LGBTQ + people.

Empirical and meta analytical research into intergroup contact is still ongoing today.

Intergroup contact and prejudice, stereotypes and discrimination

The term “prejudice” is used to refer to a preconceived, negative view of another person, based on perceived qualities such as political affiliation, skin colour, faith, gender, disability, religion, sexuality, language, height, education, and more.

Prejudice can also refer to an unfounded belief, or to pigeonhole people or groups. Gordon Allport, the originator of the contact hypothesis, defined prejudice as a feeling, positive or negative, prior to actual experience, that is not based on fact.

Stereotypes, as defined in the contact hypothesis, are generalisations about groups of people. Stereotypes are often based on sexual orientation, religion, race, or age. Stereotypes can be positive, but are usually negative. Either way, a stereotype is a generalisation that does not take into account differences at the individual level.

Prejudice and stereotypes concern biased views regarding others, but discrimination consists of targeted action against individuals or groups based on race, religion, gender or other identifying features. Discrimination takes many forms, from pay gaps and glass ceilings to unfair housing policies.

In recent years, more and more new legislation and regulations have been introduced, designed to tackle discrimination and prejudice reduction in, for example, the workplace. It is not however possible to eliminate discrimination through legislation. Discrimination is a complex issue relating to the justice, education and political systems in a society.

Conditions for intergroup contact to reduce prejudice

Gordon Allport claimed that prejudice and conflict between groups can be reduced by having equal status contact between groups in pursuit of common goals. This effect is even greater when contact is officially sanctioned.

This can be achieved through legislation, but also through local customs and practice. In other words, there are four conditions under which prejudice can be reduced. These are:

Equal status

Both groups taking part in the contact situations must play equal roles in the relationship. The members of each group should have similar backgrounds, qualities and other features. Differences in academic background, prosperity or experience should be kept to a minimum.

Common goals

Both groups should seek to serve a higher purpose through the relationship and working together. This is a goal which can only be achieved when the two groups join forces and work together on common initiatives.

Working together

Both groups should work together to achieve their common goals, rather than in competition.

Support from the authorities through legislation

Both groups should recognise a single authority, to support contact and collaborative interaction between groups. This contact should be helpful, considerate, and foster the right attitude towards one another.

Examples of the contact hypothesis

The effect of greater contact between members of disparate groups has been the basis of many policy decisions advocating racial integration in settings such as schools, housing, workplaces and the military.

The contact hypothesis in the desegregation of education

An example of this is a 1954 landmark court decision by the US Supreme Court. The decision brought about the desegregation of schools. In this ruling, the contact hypothesis was used to demonstrate that this would increase self-esteem among racial minorities and respect between groups in general.

Studies into the implications of this decision in subsequent years did not always yield positive results. There have been studies showing that prejudice was actually reinforced and that self-esteem did not improve among minorities. The reason for this has already been set out above.

Contact between groups in schools, for example, was not always equal, nor did it take place with social supervision. These are two essential requirements or conditions for improving relationships between disparate groups.

The contact hypothesis in developing education strategies

The contact hypothesis has also proved invaluable in developing cooperative education strategies. The best known of these is the jigsaw classroom technique. This technique involves creating a particular classroom setting where students from various racial backgrounds are brought together in pursuit of a common goal.

In practice this means that students are placed in study groups of 6. The lesson is split into six elements, and each student is assigned one part of those six. That means that each student actually represents one piece in that jigsaw.

For the lesson to succeed, students need to trust one another based on their knowledge. This increases interdependence within the group, which is necessary for improving relationships between people.

Reducing prejudice

Besides it being very important to know how prejudice arises, studies on prejudice also focus on the potential to reduce prejudice. One technique widely believed to be highly effective is training people to become more empathetic towards members of other groups.

Putting yourself in someone else’s shoes makes it easier to think about what you would do in a similar situation.

Other techniques and methods used to reduce prejudice are:

Contact with members of other groups
Making others aware of the inconsistencies in their beliefs and values
Legislation and regulations which promote fair and equal treatment of people in minority groups
Creating public support and awareness

Implication of prejudice and discrimination in the workplace

Discrimination and prejudice can lead to wellbeing issues and substantial financial loss to the organisation, along with a sharp fall in employee and company morale. According to the American Psychological Association, 61% of adults face prejudice or discrimination at some time.

For some this happens at work; others face it as part of everyday life in society. Most people are aware of the negative effects this can have on employees, but discrimination and prejudice going unchecked can also have serious consequences.

Firstly, treating people unfairly can contribute to increased stress levels. This in turn leads to more wellbeing issues for those who are personally harmed or attacked. When someone is constantly worrying about discrimination or religion, he or she is forced to think about that thing all day long. Too much stress reduces sleep quality and suppresses appetite. When this becomes the norm for someone, they are going to feel chronically ill or down.

Prejudice also has a negative effect on the company in general. Companies may even suffer financial loss as a consequence. Employees who feel ill or down because of social issues are more likely to resign. The company then incurs substantial costs training new people.

Another obvious negative outcome for organisations is employees who hate management if they feel they are not being treated fairly. This negative attitude from employees has an effect on individual employee performance and ultimately also on the performance of the organisation as a whole.

The contact hypothesis in summary

The contact hypothesis, of which the intergroup contact theory is a part, is a theory from sociology and psychology which suggests that problems such as discrimination and prejudice can be drastically reduced by having more contact with people from different social groups. This notion is also called intergroup contact. Prejudice and conflict usually arise between majority and minority group members.

The social psychologist credited for his contributions in this field is Gordon Allport. Allport brought together several studies of interracial contact after the Second World War and developed the intergroup contact theory from those. His hypothesis was published in 1954. In the decades which followed, the theory was widely used in initiatives to tackle these social problems.

Prejudice is often a negative evaluation of others based on qualities such as political affiliation, age, skin colour, height, gender or other identifying features. Stereotyping resembles prejudice, but is in fact making generalisations about groups of people.

This social failing is also based on religion, gender or other identifying features which say nothing about the group as a whole. Discrimination goes a step further than prejudice and stereotypes. Discrimination is about actually treating people in a negative way based on particular identifying features such as race or education.

Gordon Allport developed four requirements or conditions necessary for reducing prejudice through increased intergroup contact. The first is that both groups should have an equal status. The members of each group should have similar backgrounds, qualities or social status.

Differences in academic background, prosperity or experience should be kept to a minimum. The second is to have common goals. The groups should not be brought together without some purpose. As mentioned too in the example above in the jigsaw classroom section, dependence on one another is stimulating, which is a prerequisite for social equality and improved relationships. This is linked to the third condition: working together.

Now it is your turn

What do you think? Are you familiar with the explanation of the contact hypothesis? Have you ever faced prejudice or discrimination? Have you ever experienced the positive effects of contact? Had you ever heard of this theory before? Do you think eliminating discrimination and prejudice is possible? What is your view on opportunity of outcome vs opportunity of equality? Do you have any other advice or additional comments?

Share your experience and knowledge in the comments box below.

More information

Amir, Y. (1969). Contact hypothesis in ethnic relations . Psychological bulletin, 71(5), 319.
Brewer, M. B., & Miller, N. (1984). Beyond the contact hypothesis: Theoretical . Groups in contact: The psychology of desegregation, 281.
Paluck, E. L., Green, S. A., & Green, D. P. (2019). The contact hypothesis re-evaluated . Behavioural Public Policy, 3(2), 129-158.
Pettigrew, T. F., & Tropp, L. R. (2005). Allport’s intergroup contact hypothesis: Its history and influence . On the nature of prejudice: Fifty years after Allport, 262-277.

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Original publication date: 05/25/2021 | Last update: 08/21/2023

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Ben Janse is a young professional working at ToolsHero as Content Manager. He is also an International Business student at Rotterdam Business School where he focusses on analyzing and developing management models. Thanks to his theoretical and practical knowledge, he knows how to distinguish main- and side issues and to make the essence of each article clearly visible.

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contact hypothesis

Quick reference.

The proposition by the US psychologist Gordon W(illard) Allport (1897–1967) that sheer social contact between social groups is sufficient to reduce intergroup prejudice. Empirical evidence suggests that this is so only in certain circumstances.

From: contact hypothesis in A Dictionary of Psychology »

Subjects: Science and technology — Psychology

ORIGINAL RESEARCH article

From contact to enact: reducing prejudice toward physical disability using engagement strategies.

$\r\nKristian Moltke Martiny,,*$

1 Center for Subjectivity Research, Faculty of Humanities, University of Copenhagen, Copenhagen, Denmark
2 Stages of Science, Copenhagen, Denmark
3 Enactlab, Copenhagen, Denmark
4 Medical Museion, Department of Public Health, University of Copenhagen, Copenhagen, Denmark

The contact hypothesis has dominated work on prejudice reduction and is often described as one of the most successful theories within social psychology. The hypothesis has nevertheless been criticized for not being applicable in real life situations due to unobtainable conditions for direct contact. Several indirect contact suggestions have been developed to solve this “application challenge.” Here, we suggest a hybrid strategy of both direct and indirect contact. Based on the second-person method developed in social psychology and cognition, we suggest working with an engagement strategy as a hybrid hypothesis. We expand on this suggestion through an engagement-based intervention, where we implement the strategy in a theater performance and investigate the effects on prejudicial attitudes toward people with physical disabilities. Based on the results we reformulate our initial engagement strategy into the Enact (Engagement, Nuancing, and Attitude formation) hypothesis. To deal with the application challenge, this hybrid hypothesis posits two necessary conditions for prejudice reduction. Interventions should: (1) work with engagement to reduce prejudice, and (2) focus on the second-order level of attitudes formation. Here the aim of the prejudice reduction is not attitude correction, but instead the nuancing of attitudes.

Introduction

The contact hypothesis, or intergroup contact theory, is described as one of the most tested, and yet one of the most controversial theories within work on prejudice ( Brown, 1988 ). Since it was formalized by Williams (1947) and Allport (1954) , it has been one of the dominant frameworks within work on prejudice reduction. Allport originally defined prejudice as a feeling, favorable or unfavorable, toward a person or thing, that is not based on actual experience (ibid). In a more recent definition, prejudice is described as the negative evaluation of a group or its members based on group membership ( Crandall et al., 2002 ). The basic assumption in the contact hypothesis is that direct contact – under appropriate conditions – will provide opportunity for actual experience and reduce prejudice and negative evaluations between in- and out-groups and their members.

The contact hypothesis still enjoys immense research attention, and a variety of studies provide solid empirical confirmation that contact does in fact reduce prejudice ( Pettigrew and Tropp, 2006 ; Page-Gould et al., 2008 ; Binder et al., 2009 ; Vezzali et al., 2010 ; Davies et al., 2011 ; Swart et al., 2011 ; Mickus and Bowen, 2017 ; Paluck et al., 2018 ; De Coninck et al., 2020 ). In order to control the quality of the contact and avoid the risk of counterproductive contact (e.g., strengthening stereotypes), the contact hypothesis operates with a set of structural conditions. Since Allport (1954) original formulation of four basic conditions (equal status, common goals, intergroup cooperation, and support of authorities, law or customs), the list of conditions has expanded throughout the years.

Already by 1997, Wright et al. compared the contact hypothesis to a grocery list solution. Following Pettigrew’s (1998) argument that researchers have overburdened the hypothesis with too many conditions, Dixon et al. (2005) collected a list of 13 conditions based on the available literature and highlighted the narrow academic focus that the theory has attracted. They re-named it the “optimal contact strategy” and pointed out that in aiming to avoid backlash, the contact hypothesis has become an idealist aim of optimizing conditions rather than application. This aim, along with the fact that contact in everyday life is not always possible or may even be resisted because of the prejudice it is aimed at reducing ( Vezzali et al., 2014 ), has put the contact hypothesis in danger of becoming untranslatable to any real-life situations. Further, Paluck et al. (2018) point out that only a minority of studies succeed in ensuring just the four conditions originally given by Allport.

A range of suggestions already exist for modifying and/or extending the contact hypothesis to make it more applicable in real-life situations, addressing what can be called the “application challenge.” Some of the most influential suggestions share a strategy of moving toward forms of indirect contact through either acquaintance, media, technology or imagination, as seen in the Extended ( Wright et al., 1997 ), the Vicarious ( Gómez and Huici, 2008 ) the Para-social ( Horton and Wohl, 1956 ; Schiappa et al., 2005 ), the Imagined ( Crisp and Turner, 2009 ) or the Electronic or E-contact ( Amichai-Hamburger and McKenna, 2006 ; White et al., 2015 ) contact hypothesis. These indirect approaches have been widely published on, and all have shown evidence of positive effect ( Gómez and Huici, 2008 ; Davies et al., 2011 ; Lemmer and Wagner, 2015 ; Zhou et al., 2019 ).

The main challenge that these proposals try to solve by way of indirectness, is how to negotiate real-world applicability while avoiding the risk of a counterproductive effect of contact. Many of them share the strategy of minimizing intergroup anxiety, i.e., anticipated negative reactions or consequences of an intergroup encounter ( Stephan and Stephan, 1985 , 2001 ). A reduction in intergroup anxiety is known to be a significant factor in increasing the effect of contact as means to reduce prejudice ( Stephan and Stephan, 1985 ; Dijker, 1987 ; Islam and Hewstone, 1993 ; Stephan et al., 2002 ; Voci and Hewstone, 2003 ; Paolini et al., 2004 ; Brown and Hewstone, 2005 ). It is suggested that the mechanism behind such effect is that intergroup anxiety creates a disengagement with the other person. As a consequence, this makes individuals rely more heavily on pre-existing stereotypes, causing them to jump to stereotypical conclusions, and making them pay less attention to counter-stereotypical behavior ( Wilder and Shapiro, 1989 ; Wilder, 1993 ).

In the following, we propose to deal with the “application challenge” in a hybrid way that includes and combines aspects of both direct and indirect contact strategies. We aim to see if it is possible to maintain aspects of the embodied contact from the direct contact hypothesis, while at the same time use the indirect strategy to minimize intergroup anxiety and counteract the development of disengagement. We develop this hybrid strategy by drawing on the second-person method in cognitive science and its focus on engagement.

A Second-Person Method: Engagement Strategy

Within the past 20 years currents in social psychology and cognitive science have turned their attention toward an understanding of cognition as embodied, enacted, emotive, extended and embedded ( Varela et al., 2000 ; Gallagher, 2005 ; Chemero, 2009 ; Rowlands, 2010 ; Stewart et al., 2010 ; Ward and Stapleton, 2012 ; Colombetti, 2014 ). This trend is especially prominent in the Interactive Turn ( de Jaegher et al., 2010 ) in social cognition, which suggests using a second-person methodology when exploring social cognitive phenomena ( Thompson, 2001 ). This turn emphasizes the importance of both engagement and reciprocal embodied interaction (e.g., de Bruin et al., 2012 ; Schilbach et al., 2013 ; Satne and Roepstorff, 2015 ), the overall idea being that these features of social psychology and cognition are necessary to consider when researching social phenomena such as prejudice reduction or attitude change.

Satne and Roepstorff (2015) define engagement as involving two aspects: (1) an experiential aspect, and (2) a normative aspect. The first aspect illustrates that there is an inherent experiential trait in entering into relations of engagement with others, which can occur in many different relations such as: bodily interactions (e.g., dancing), collaborations (e.g., moving a couch together) or a shared experience (e.g., watching a movie together). The experiential trait is an affective, emotional, and reciprocal we-experience. However, as the second aspect emphasizes, such experience and feeling of the other has a normative trait. The experience is one in which I commit to the other as a person, and vice versa. The relation of engagement is thus structured through a mutual and personal commitment. That is: bodily interaction, collaboration and shared experience can drive mutual commitment and engagement.

Within the contact hypothesis literature, we find a similar notion in Tropp and Barlow (2018) . They argue that contact in the contact hypothesis is effective if and when it encourages what they call “psychological investment.” Such investment is connected to notions of empathy, personal relevance, and humanization. Similar trends can be found in Vezzali et al. (2010) regarding the role of contact in increased empathy and reduced anxiety, and in Capozza et al. (2014) regarding contact and humanness attribution.

Focusing on the positive trait of creating engagement rather than on the negative trait of reducing intergroup-anxiety, we integrate lessons from the second-person methodology, in order to design an intervention which allows us to examine the effect of such engagement strategy on prejudice reduction.

Engagement Through Theater Performance

In line with other earlier sociocultural psychologists and sociologists the work of Ulric Neisser criticizes research in social psychology for being over-academic and inapplicable in real-life. Neisser suggests that social scientists could benefit from collaborating with professionals from the world of theater, since the expertise of such professions consists of manipulating social impressions ( Neisser, 1980 ). We follow this suggestion and turn to theater in order to design an engagement-based intervention.

Research in theater and performance studies suggests that we can understand theater performance in a way that is very much in line with a second-person methodology. Specifically, it focuses on three notions to understand theater performance: (1) embodiment, (2) engagement, and (3) transformation (e.g., Zarrilli, 2004 ; McConachie and Hart, 2006 ; Cook, 2007 ; McConachie, 2007 , 2008 ; Blair, 2008 ; Di Benedetto, 2010 ; Nicholson, 2011 ; Shaughnessy, 2012 ).

The notion of “embodiment” in theater and performance studies is used as a way of understanding the “affective” impacts that the performance has on the audience ( Thompson, 2009 ; Nicholson, 2011 ), where the audience experiences “being kinesthetically moved” ( Fenemore, 2003 ). This “moving” of the audience is due to the felt, embodied experience of the live performance, of being in a shared space and of being haptically affected. Such embodiment leads to an empathic engagement ( Shaughnessy, 2012 ). The notion of “engagement” is therefore already implied in the notion of embodiment, and is used to emphasize that, in theater performance, the distinctions between creator/performer/perceiver are blurred, as performers and audience are in a shared, participatory, and immersed dialogue ( Shepherd, 2006 ; Shaughnessy, 2012 ). These elements strongly suggest that theater can provide the engagement we aim at in our intervention. Depending on the type of theater performance one can operate with different degrees of embodied engagement, ranging from direct bodily interactions and collaboration between performers and audience to more indirect, sedentary behavior of the audience, as they watch the performers. In the latter case, the theater performance, should, however, still be seen as an embodied, shared and participatory dialogue between performer and audience, as audience and performers still share the same space and are haptically moved and affected by each-other.

The idea and notion of “transformation” is understood by perceiving theater as an encounter with the social community ( Taylor, 2003 ) or as a public and social event ( Thompson and Schechner, 2004 ). The participatory, engaging performance is then used to “effect” social change through its embodied “affect” ( Nicholson, 2005 ; Thompson, 2009 ), whereby the audience members become “active producers,” rather than consumers, and are transformed with the production of the performance.

Thus, theater affords embodied engagement, both experientially and normatively, and it has the potential to transform social notions, and hence, be the foundation for possible prejudice reduction through attitude change. That is, the format of a performance as well as the engagement “on stage” (i.e., between performers) may act as mediators, much like the indirect strategies, without losing embodiment. Additionally, theater, like many of the indirect strategies, also has the advantage that large numbers of audience can be involved. Theater therefore seems to be a good fit for developing an engagement-based intervention of hybrid contact.

Changing Attitudes Toward People With Physical Disability

To develop and investigate the possible effects of an engagement-based intervention we focus on the reduction of prejudice toward people with physical disability. Physical disability is a constructive attitude object to work with in an intervention study, since group salience is often immediately present in the encounter, particularly when the disability is visible.

The feelings that people without disability immediately experience toward people with physical disability are typically that of discomfort and fear ( Krahé and Altwasser, 2006 ; Coleman et al., 2015 ). These feelings arise because people without physical disability are irrationally concerned with “catching” the disability ( Park et al., 2003 ) and they perceive people with disability as being unpredictable, incompetent, weak, dependent on others and lacking strength and endurance ( Louvet, 2007 ; Rohmer and Louvet, 2009 , 2012 ; Novak et al., 2011 ; Martiny, 2015 ).

These stereotypical attitudes toward people with physical disability lead to a range of reactions including: bodily objectification and “intersubjective oppression” in everyday face-to-face interactions ( Toro, 2020 ), discrimination and marginalization in the labor marked ( Louvet, 2007 ; Grue, 2016 ) and in healthcare settings ( Toriello et al., 2007 ; Sterkenburg and Vacaru, 2018 ) and challenges in forming social relations such as friendships, which has been related to the fact that people without disability also express sadness and pity toward people with disability ( Harper, 1999 ; Lightfoot et al., 1999 ; Weiserbs and Gottlieb, 2000 ; Green, 2003 , 2007 ).

The overall aim of the study is to see if an engagement-based intervention can change such prejudicial attitudes toward people with physical disability.

Method: Changing Attitudes With an Engagement-Based Theater Intervention

The experimental setup was developed around a theater intervention. The study design consisted of tests pre- and post-intervention (quantitative questionnaire, IAT test and qualitative interview) monitoring during intervention (interactive questionnaire), as well as tests of a population control-group (quantitative questionnaire). We outline the experimental setup in more detail in the section “Experimental Instruments: Mixing Methods” (see also Figure 1 ).

Figure 1. The figure shows the study design with the different test-methods used before (QQ, IAT), during (interactQ) and after (QQ, IAT, phenQI) the performance and the different test-groups that was involved.

We aimed to create embodied, engaged contact between in-group (i.e., audience) and out-group (i.e., people with physical disability, present on stage), and to test the effect of such contact on attitudes toward people with disability. Our hypothesis was that engagement during the theater performance would reduce prejudice by changing the negative attitudes of participants to more positive attitudes toward people with physical disabilities. The intervention therefore operates with an engagement condition, and the experimental variables measured were the level of engagement during the performance and the change in attitudes toward physical disability before and after the performance.

The Theater Intervention: Direct and Indirect Contact

The theater performance was set up as a 1 h and 45 min autobiographical stage performance about a 28-year-old man, JN, who lives with quadriplegic cerebral palsy (CP) and has a speech impediment, thus displaying group salience both visibly and audibly at first encounter. The performance would provide embodied engagement with JN (an out-group member) on stage, but was designed with a seated audience, that is, there was no bodily interaction between JN and audience. Instead, and in-group member (i.e., a person without physical disability) interacted with JN on stage, adding a mediated indirect contact to the embodied engagement already present in theater performance.

The performance was developed in close collaboration and conversation between the research group, the theater group, and JN, in order to obtain an accurate image of life with CP. To present a complex life with CP, the performance was divided into four parts. The first, serving as a general introduction to “the person JN,” and the following three dealing with sensitive issues related to life with physical disabilities, i.e., (1) introduction, (2) employment, (3) finding a partner, and (4) parenthood. The autobiographical format was chosen as a way of articulating, exploring, and interrogating a person, identity, and subject through embodied and engaged theatrical strategies. To emphasize both group salience and personalization (see Miller, 2002 ) documentation material from JN’s “real life” was used in the performance to illustrate the difference between JN’s own perspective and that of science and society. For example, in part 1, JN described the experience of living with congenital brain damage while, in the same part, audio/visual documentation presented a neurologist describing JN’s brain damage based on an MRI scan of JN’s brain. As another example, in part 2, JN’s personal medical journal and his diagnosis were presented and compared to medical and diagnostic demographic statistics of CP in the Danish society (taken from Michelsen, 2006 ). In the same part, the audience was presented with recordings of JN’s real-life phone conversations for job-interviews, while being informed about statistics of employment, also of people with CP in the Danish society.

JN was the main performer, but he was joined on stage by a non-CP actor (KF), who guided the audience through JN’s life. This was done for practical reasons: to support JN in performing the theater performance, and to help the audience understand JN. The relation between JN and KF was used explicitly to stress their difference (in- and out-group salience), the complexities of this difference (personalization), and as an indirect contact strategy to provide a way for the audience to interact vicariously with JN.

The scenography was minimally designed (see Picture 1 ) and the lightning, sound, and music were designed to support and enhance the connection between JN and the audience – forming specific moods and helping the varying “real-life” locations appear present during the performance.

The intervention was carried out in two versions, a pilot followed by a larger experiment-set. We conducted the pilot-experiment with a single theater performance and approximately 1,100 people in the audience 1 . The actual experiment was conducted during 17 theater performances, held over the course of a month, with approximately 2,600 people in the audience in total.

Picture 1. Shows the stage and scenography, where the main prop is an 11 m × 2.5 m projection wall used for an interactive questionnaire (described in section “Experimental Instruments: Mixing Methods”). Other props included three small stools, one leather stool with a connected small table, and two bar stools.

Participants

The intervention and experimental design were tested and adjusted during the pilot-experiment and was then used in the experiment to test different groups of the total audience sample ( n = 2,604). Everyone in the audience was given the interactive questionnaire during the performance, but out of the total audience sample, a pre-group (group 1, n = 193) that was about to see the performance, and a post-group (group 2, n = 191) that had just seen the performance, was given the quantitative questionnaire. A control-group (control, n = 505) of Danish citizens (age 18–60) that did not see the performance, where also given the quantitative questionnaire. A pre-group (group A, n = 70) and post-group (group B, n = 100) were given the IAT tests before and after the performance, respectively. A focus-group of Danish citizens (focus group, n = 30; 15 women, 15 men, age 22–59) was given the quantitative questionnaire and the IAT test after the performance, and we also conducted qualitative interviews (phenQI) after the performance.

The audience was informed at the beginning of the performance that the performance was part of an experiment and that they would be given an interactive questionnaire during the performance. They were free not to answer, if they did not wish to participate in the study. Written informed consent was obtained from all individual participants that took part in measurements before and after the performance 2 .

The pre-group (group 1 and group A in Figure 1 ) and post-group (group 2 and group B in Figure 1 ) were recruited by random selection from the audience in attendance at the theater across the 17 shows, i.e., people who had come to the performance by own initiative. The test-selected groups were recruited by research and theater staff asking audience members in the theater lobby before the performance and coming out after the performance if they wanted to participate in the research. Random selection was approximated by asking whoever passed once a conversation with one audience member ended. To ensure that changes were not due to increased acquaintance with the questionnaire, none of the individuals in the pre-group and post-group were identical. The quantitative questionnaire was filled out for pre- and post-group at a restricted research test-area close to the theater stage, the same was the case for the IAT test.

To be able to balance biased selection in recruiting at the theater, we recruited a focus-group, as well as a control-group, outside the group who came to the theater on own accord. The focus-group was recruited 2 weeks in advance of the specific performance they were going to see, which was either a performance in the beginning ( n = 10), middle ( n = 10) or end ( n = 10) of the playing period. They were recruited randomly by the research group by selecting people between the ages of 18 and 60 who were walking past the Royal Theater (i.e., on a central square in the capital). Participants were recruited through the following process: after being informed that they would be participating in a research project by accepting two free tickets to a theater show, those who still chose to participate were formally invited into the experiment over an e-mail a few days after in-person recruitment, giving them details of time and place. They were not informed of the kind of research project and topic, but only told that they were going to see a theater performance and would have to do tests after. Out of 70 persons recruited (i.e., who agreed and were sent an e-mail), 30 persons came to the performance. The control-group, who did not see the performance, was recruited randomly online by the research assisting organization Enalyzer, selected based on the same criteria as the focus group and aiming for a balanced distribution in age and gender. We will discuss the participant selection further in the strengths and limitations section.

Experimental Instruments: Mixing Methods

Previous research on attitudes toward physical disability emphasize the methodological challenge of relying on explicit, self-reported attitude measures, such as the challenge of potential bias through social desirability – where participants answer in a way, they believe is the most socially appropriate ( Antonak and Livneh, 2000 ; Wilson and Scior, 2014 ). For the experiment we therefore used a mixed-method approach consisting of both explicit (self-reporting) quantitative and qualitative methods, as well as implicit (behavioral) measures.

We specifically used a quantitative questionnaire (QQ) pre- and post-intervention; Implicit Association Test (IAT) pre- and post-intervention; an interactive questionnaire (interactQ) during the intervention; and phenomenological qualitative interviews (phenQI) post-intervention. An overview of all of the study design and the following details can be found in Figure 1 .

The mixed method used is phenomenologically framed, which means there is certain credence given to the qualitative method of the data generation and analysis. This is not to downplay the quantitative method, but rather to give it a specific purpose; the purpose being to accompany the qualitative method in gaining different (complementary or divergent) perspectives on the same phenomenon of prejudice toward people with disability 3 .

Quantitative Questionnaire (QQ)

The first explicit method used is a 7-point Likert Scale quantitative questionnaire (QQ), to acquire self-reports on attitudes toward people with physical disability. This questionnaire included a set of introductory questions to gather biographical information regarding the participants age, gender/sex, employment, education, and whether they themselves live with a physical disability or have a family member, friend or colleague who lives with physical disability.

In addition to the biographical questions, the questionnaire contained 26 items. Quantitative questionnaires on physical disability used in large-scale, national surveys on the British and Danish perception and attitude toward people with physical disability ( Olsen, 2000 ; Staniland, 2011 ) already exist. So the questionnaire items was developed by selecting the questions from the previous questionnaires that made sense in relation to both the themes of the theater performance (e.g., employment, relationship and parenthood) and two standardized parameters of prejudice toward physical disability ( Coleman et al., 2015 ): (1) incompetence, that is, the perceived level of competence or lack of competence of a person with physical disability, often in specific tasks; and (2) social distance, that is, the level of intimacy a person is willing to have with another person, e.g., recognize, live near and associate with them ( Toriello et al., 2007 ; Ouellette-Kuntz et al., 2010 ). Measuring the amount of social distance through the degree of (un)comfortable experience in having relations with people with physical disability will signalize prejudice ( Abrams et al., 1990 ). After selection, the questions were related specifically to CP, making them more specific toward a particular disability than the previous quantitative questionnaires.

The 26 items were randomly mixed between items relating to incompetence and social distance regarding people with CP. Questions of incompetence were framed in relation to work, politics, taking care of children and being independent. Examples of questions (translated from Danish) are: “How productive do you consider a person with CP to be in a work context?”, “How would you feel about a person with CP having a child?”, and “How would you feel if a person with CP took up an important political position in your municipality?”. Questions of social distance were framed in relation to being a friend, partner, or colleague to a person with CP, sitting next to them in public transport, and associating with them in different social settings. Examples of these questions are: “How would you feel about being friends with a person with CP?”, “How would you feel about being served in a store by a person with CP?”, “How would you feel about having a person with CP as a colleague?”. Most questions (all questions on social distance and several of the questions on incompetence) were answered on a scale going from 1 (very uncomfortable) to 7 (very comfortable). The remaining questions of incompetence were answered by (dis)agreeing with posed statements, on a scale going from 1 (strongly disagree) to 7 (strongly agree), or on a scale of productivity going from 1 (very unproductive) to 7 (very productive). Questions were posed so that it varied whether agree/disagree would indicate negative attitudes toward people with disability, so that participants would not score positive or negative as an effect of placing themselves on the same point of the scale.

Implicit Association Test (IAT)

The first implicit measurement was the standardized Implicit Association Test (IAT) for measuring implicit attitudes toward physical disability ( Greenwald and Banaji, 1995 ; Greenwald et al., 1998 , 2003 ). The test is a latency-based method that indirectly measures strengths of associations between, in our case, people with and without disability and attributes of either pleasant (good) or unpleasant (bad) valence. The IAT test divides results into a (1) slight, (2) moderate or (3) strong automatic preference for abled people compared to disabled people ; (4) a little to no automatic preference between abled and disabled people ; a (5) slight, (6) moderate or (7) strong automatic preference for disabled people compared to abled people , and (8) too many errors to determine a result.

The IAT test can be taken online on the topic of physical disability, and the test was used to explicate the audience’s implicit attitudes before and after the intervention. For controls, we relied on accumulated statistical material from regular use of the IAT test. The test was taken at a restricted research test-area close to the theater stage.

Interactive Questionnaire (interactQ)

The second implicit measurement was the interactive questionnaire (interactQ), which was developed as a proxy-measure of the audiences’ level of engagement throughout the performance and their behavior in forming their attitude toward physical disability in general and JN specifically. This was done by measuring the consistency in time to answer the question, the number of audience-members who answered, and whether they made answer-revisions.

The interactQ was made up of 18 questions structured within four questioning-sections to coordinate with the four parts of the theater performance. The questions were framed in a way to make the audience reflect on the experiences of living with physical disability and particularly on JN’s experiences. The first section of questions related to the audience’s understanding of physical disability in general, such as “To what degree are you able to familiarize yourself with living with a physical disability?”. The questions in section 2–4 were designed based on concrete theatrical scenes and situations that the audience experienced and shared with JN. The aim was for the audience to reflect on the shared experience, by asking them to either: (1) relate themselves to JN, e.g., “Where would you place your quality of life relative to JN?” or (2) try to answer from JN’s perspective, e.g., “Where do you believe that JN would place his quality of life relative to yours?”.

For each question, the theater performance paused, and the question was announced by a speaker and posed for a time-period of 12 s on the projection wall on the stage (see Picture 1 ). The answers were submitted using a mobile answering-device placed in the participants’ seats. For technical reasons, i.e., the button function of the device, these questions were answered on a 10-point Likert scale. As the aim of this questionnaire was not the given answers, but the measure of time and behavior of audience in answering, we used different scale labels that corresponded with the performance, ranging from 1 (to the lowest degree) to 10 (to the highest degree), 1 (much worse) to 10 (much better), and 1 (much lower) to 10 (much higher). There was no neutral answer (e.g., I don’t know), and no medium point on the scale, making it necessary for the audience to form their attitude in relation to the specific question. Within the 12 s, participants could revise their answer as many times as they wanted.

When the audience answered, their answers were shown anonymously in real-time below the question on the projection wall on stage (see Picture 1 ). This aspect, as well as the option to change one’s answer as many times as one wanted, was made clear to the audience at the beginning of the performance. It was not announced that we would be measuring the time it took for the audience members to answer and whether they changed their answers during the time-period.

Phenomenological Qualitative Interview (phenQI)

The second explicit method used was semi-structured qualitative interviews, conducted phenomenologically (phenQI) with the focus-group. The interviews were used to understand the quality of the contact with JN.

The focus-group filled out the QQ and took an IAT test after the performance. After each performance, an email was sent to the 30 participants, respectively, asking them if they wanted to participate in a follow-up interview. 15 out of the 30 (5 from each sub-group) agreed to participate, and the follow-up phenQI were conducted 1 week after the performance that they watched. The interviews lasted around 1–11/2 h.

The phenQI used a specific type of interview based on philosophical phenomenology with its own specific second-person questioning and analysis techniques ( Høffding and Martiny, 2016 ; Martiny, 2017 ; Zahavi and Martiny, 2019 ). The method is developed particularly to gain insight into second-person experiences. The method employs open “how” questions to draw the attention of the interviewees to detailed pre-reflective aspects of their experience. In our case, the focus was on how the audience experienced JN on the stage, specifically in relation to their experience of being in direct and indirect contact with him, their perception of him and the potential change in their perception during the performance. We also asked about their experience of the theater performance in general and their thoughts on their individual QQ, IAT and interactQ test results.

Analysis: Phenomenological Framing and Triangulation

In mixed method research, one can mix the methods at different stages, e.g., in the data generation, analysis or interpretation. In this study the methods are mixed in the interpretation of the data by using the phenomenologically based second-person theory and understanding of engagement (presented in section “A Second-Person Method: Engagement Strategy”) to combine the quantitative and qualitative datasets into one account of prejudice reduction.

This means that the quantitative and qualitative data were generated and analyzed separately. The quantitative analysis concerned statistical comparison of the data before, during, and after the performance. In relation to the QQ the analysis focused on pre/post differences within the individual questions, mapping the concrete aspects and situations within which attitudes on incompetence and social distance changed. A series of Kruskal-Wallis H tests were conducted to determine differences in attitude toward people with physical disability based on a ranking of the responses to the individual questions – with a higher rank indicating a more positive attitude. We did not look at single index or attempt to create factors across the 26 items.

For the data of the IAT test an independent-samples Mann-Whitney U -test was conducted in SPSS based on ranking of the results to test for pre-IAT to post-IAT differences. The data of the interactQ was analyzed descriptively, as the technical equipment did not allow data gathering that fulfilled statistical assumptions of independence.

The qualitative data of the phenQI, i.e., the recorded interviews, were transcribed ad verbatim and through multiple rounds of labeling, categorization and repeated listening the data was coded and structured in order to identify experiential categories. The analysis was conducted in accordance with phenomenological methods of descriptive analysis (see Gallagher and Zahavi, 2008 , chapter 2), and the strategy of “phenomenological consistency” was employed in order to validate the descriptions ( Høffding and Martiny, 2016 ; Martiny et al., 2021 ).

After the separate qualitative and quantitative analyses were completed, they were triangulated and mixed into one interpretation (see Discussion). This was done by first providing tentative interpretations of the separate analyses regarding the level of engagement, change in attitudes and possible prejudice reduction toward physical disability that occurred because of the intervention. These tentative interpretations and answers to the research questions were then compared and combined with each other and integrated into one meta-interpretation that also explained the contrast and differences between the tentative interpretations and answers 4 .

Table 1 presents the results of the biographical questions in the QQ for both test selected audience groups (group 1, 2, A, B, and focus-group) and control group, seen in relation to theater audience in Denmark and general population.

Table 1. Biographical information: The table shows biographical data for test selected audience groups and control group, as well as data on average theater audience in Denmark and general population.

Figure 2 presents a selected sample of the questions in the QQ that showed significant results 5 . Out of the 26 QQ questions, 8 questions (renamed as questions Q1-Q8) showed significant differences ( P < 0.05) between various groups regarding concrete attitude changes to physical disability. When compared to the control-group, the post-QQ participants’ attitudes are more positive in their evaluations of questions on social distance (e.g., about having a relationship with people with CP) and on competence (e.g., their ability to become parents and care for a child). For the questions Q3, Q4, Q5, and Q6 the post-intervention group (group 2) differ significantly from the control-group.

Figure 2. Quantitative questionnaire (QQ). The table shows, from left to right: the question posed, the total sample size, the X 2 values obtained and the degrees of freedom, the asymptotic significance levels based on the X 2 values, a graphing of the mean ranks for the control, pre-QQ and post-QQ groups and identical letters denote no significant difference between mean ranks and non-identical letters denote a significant difference between mean ranks. Total sample sizes differ between 689 and 849 respondents due to both missing answers to the questions and difference in responses of “Do not know,” which were excluded in the statistical analysis.

For these questions, post-intervention replies had the highest mean rank in terms of positive attitudes toward people with CP, the pre-QQ group (group 1) had the medium mean rank and the control-group had the lowest mean rank. For questions Q3 and Q4 no other differences were significant. For question Q5 the control-group scored significantly lower than both pre- and post-intervention group (group 1 and 2). For question Q6 all three groups scored significantly different in terms of attitudes toward people with CP where control group had the lowest, pre-group medium and post-group the highest mean rank (group 1). For the questions Q1, Q2, Q7 and Q8 the pre-QQ group (group 1) differ significantly from the control-group, but no other differences were significant. This concerns social distance in relation to being friends with people with CP, and competence in regard to employment, i.e., working with people with CP. For these questions, group 1 has the highest mean rank in terms of positive attitudes toward people with CP, the control-group had the lowest mean rank, with post-intervention group (group 2) scoring in-between, not being significantly different from either of the two other groups.

Figure 3 shows the results of the IAT test of the pre-IAT (group A) and post-IAT (group B), ranging from “no automatic preference for abled or disabled people” to a “strong preference for abled people over disabled 6 .” The data was ranked with a higher rank, representing a stronger preference for abled people over disabled people. The test showed no significant changes at the implicit attitude level between pre- and post-group ( P = 0.273).

Figure 3. Implicit Association Test (IAT). The figure shows the distribution of results on the IAT for the pre-IAT ( n = 70) and the post-IAT ( n = 100) group.

Figure 4 shows the implicit measures of engagement from the interactQ with number of responses (4a), the response times (4b) and number of answer-revisions made (4c). The figure shows that out of the total audience sample ( n = 2,604), there was an average of 2,312 answer-responses across all questions of the interactQ, with a slight drop in responses at the very end. The audience used an average of 4.73 s in mean response time with a maximum difference being on average 0.68 s. quicker (4.04 s) for question 1.4 and 0.97 s. slower (5.70 s) for question 4.3. In average 5.02% of the audience (116 people) revised their answers, with a maximum of 7.68% (178 people) for question 1.3 and a minimum of 3.53% (82 people) for question 4.3.

Figure 4. Interactive questionnaire (interactQ): The graph shows: (A) the combined amount of responses for each question, (B) the mean response time in seconds to answer the questions, where the Y -axis represents the response time in seconds and the X -axis represents the 16 questions, and (C) the percentage of audience members who made one or more revisions of their answers to the questions, where the Y -axis represents the percentage of the audience who made one or more revisions and the X -axis represents the 16 questions. For technical reasons we only differentiated between whether audience members made any number of revisions and if they did not. Two questions (3.1 and 4.1) were removed from the analysis as the majority of responses for these were lost due to technical issues.

Table 2 presents the descriptive data given by the focus-group in the phenQI and the analytical categories. Here a selection of quotes illustrates the 29 tags used in the qualitative data analysis, 9 themes developed from these, as well as three overall categories (intervention, nuancing and reflective effect and attitude formation). The interviews show that participants experienced an awkward and biased first encounter with JN, which they describe as instinctive and relate to being prejudicial (quote 1A). They describe their initial attitudes as objectifying toward JN, as well as based on false beliefs about what it means to be physically disabled and how this affects JN, e.g., that he has a low IQ.

Table 2. Phenomenological qualitative interviews (phenQI) a .

However, they also show that the participants (re-)form attitudes toward JN during the intervention in an attentive and reflective way, increasing awareness of their own attitudes (quote 3G, 3H). Participants mention the performance as a source of new and factual knowledge about people with physical disability (i.e., out-group). It is a gateway into a deeper understanding of the person (in this case JN) behind the category “physical disability” and of the degree of complexity involved in belonging to this group (i.e., personalization). Noticeably, some interviewees particularly mention a difference in receiving this information and knowledge about physical disability within theater, as compared to other media (quote 1C).

Interviewees indicated that the social and immediate nature of the theater situation influenced the attitude formation through a sense of belonging here and now to a shared space (quote 1H). They further mention that being directly addressed and experiencing the explication (some particularly mention the interactQ) make them become aware of their own prejudice and beliefs about people with physical disability and the variety of attitudes it is possible to hold (quote 2G). Participants also describe that this self-reflectivity made them feel embarrassed and uncomfortable (quote 3C). Yet it also made them normalize and humanize the person with physical disability, to the point of personal self-identification (quote 3D). Participants described that such identification elicited a further self-reflection process – making them reflect on how they typically form attitudes, what kind of categorizations they typically use to form attitudes, and how they should evaluate themselves in such processes of attitude formations in the future (quote 3I).

In this section we discuss the results. The results indicate that we achieved the engagement aimed for in the experimental setup, and we note that there were significant differences between groups in the QQ. However, the difference is not unequally one of moving toward more positive attitudes. Further, there was no change in implicit attitude measure (IAT). We draw on the results from the phenQI to make sense of these findings, and suggest first that we obtained a nuancing effect, still countering stereotypical views on people with disability, and that this effect occurred primarily as an effect of second-order attitude formation (i.e., increased awareness on own formation of and reasons for forming attitudes). To capture these findings, we propose an Enact framework as an alternative to the more established contact theories. We end with some critical remarks on strengths and limitations of our methodological setup.

Engagement and Attitude Change

Firstly, we wished to make sure that the performance succeeded in creating engagement – as defined by both experiential and normative aspects. The phenQI interview show that the encounter is characterized by the interviewees’ initial awkward, uncomfortable, and reserved, objectifying and prejudicial attitudes toward JN. These results replicate existing research on attitudes toward people with physical disability, as described above: the immediate feelings that people without disability experience are that of discomfort and fear, based on the objectification and perception of people with disability as incompetent. Such attitudes are associated with intergroup anxiety and known to decrease engagement.

However, the interviewees describe that as the performance progresses, they acquire a situated, intimate, and bodily understanding of JN, i.e., him as individual, rather than as an abstract disabled body or object; they commit to him, and he commits to them by being right there in flesh and blood, in their face, and telling his personal story. PhenQI thus affirms that the performance succeeded in giving the focus-group a situated, bodily and emotional understanding of living with a physical disability, as well as a normative commitment between audience and JN, despite initial awkwardness. In other words, members of the audience – sampled through the interviewees – experienced a second-person engagement with JN. Interviewees also indicate that the embodied and shared space of the theater is an important element of this engagement, supporting the claims of the second-person methodology made in the introduction.

Additionally, Figure 4 shows that in answering the interactQ, a high number of audience members were consistently active during the performance. With a few exceptions, and with a minor drop toward the very last part of the performance, their responses, their response time, and the amount of audience members who made answer revisions were consistent throughout the performance. This indicates that the audience’s commitment and active interaction with the questionnaire was intact during the performance, which are both signs of engagement and would not have been expected, if engagement had been absent.

Based on these results, we conclude that the performance kept the audience committed and engaged with JN in the intervention. In addition, the results of the phenQI indicate that the engagement has an effect on the audience’s attitude toward JN and physical disability. This is corroborated by the results of the QQ, which show a change of attitudes between pre-QQ (group 1) and post-QQ (group 2), when compared to the control group. This signals a reduction in prejudice regarding the specific aspects and situations of social distance and incompetence. Although this could be explained by selection bias, we see a significant tendency for improved attitudes between pre and post, indicating an effect of the intervention, nonetheless.

Re-defining Prejudice Reduction: The Nuance and Self-Reflection Effect

To our surprise, the QQ results also show some effects of a decrease in positive attitudes, which could signal increase in prejudice, i.e., post-QQ participants are less positive than the pre-QQ participants – although not significantly. Initially we considered this a problematic outcome, since we expected that a reduction in prejudice toward people with physical disability would be a change from negative to more positive attitudes when it comes to competence and social distance. However, the reports of the phenQI indicate that through the engagement of the performance, the interviewees start to experience and understand the complexity and individuality of living with physical disability. Their attitudes and understanding of disability therefore become increasingly nuanced and less stereotypical.

Research shows that the prejudice that exists toward people with disability can be characterized as “paternalistic prejudice,” where both positive and negative stereotypes are mixed into the prejudice. This means that people without disability perceive people with disability as incompetent, they fear, objectify, and pity them, while at the same time showing compassion, sympathy, and even tenderness toward them ( Fiske et al., 2002 ; Coleman et al., 2015 ). A nuanced experience and understanding of JN and people with physical disability, would therefore reduce prejudice by reducing negative attitudes of e.g., incompetence and social distancing, while at the same time reducing positive, stereotypical attitudes that leads to pitiful compassion and sympathy toward people with disability.

Our proposal is thus to see prejudice reduction as a nuancing of attitudes rather than mere change in positivity, or in other cases, mere negativity. This conception of prejudice reduction is especially relevant in the case of physical disability and other groups where paternalistic prejudice is dominant. We thus propose that when reporting prejudice reduction, one might aim at measuring a nuancing effect, rather than a positive/negative improvement. However, this proposal and the connection between prejudice, nuanced attitudes, and measures should be investigated further.

In the phenQI the participants also emphasize their relation to the rest of the audience (in-group relation). Answering the interactQ, they are forced to form their attitudes about physical disability and JN, and their evaluations are shown in real-time on stage, making it visible to JN and contextualized in relation to the replies of others. This means that they see how their individual evaluations correspond to the majority or minority of the audience group. Such comparison gives the participants additional reflections and perspectives on their own attitudes in a social setting. This is for instance, seen in reports of feeling embarrassed about their reply, which most prominently happened when interviewees realize that their answers were stereotypical and not supported factually or were part of the minority of answers from the audience.

The interactQ which was developed to implicitly measure indicators of engagement thus turned out to be a key feature mentioned in the self-reported prejudice reduction, for the attitude explication and social contextualization that it provided. The focus-group interviewees report that the nuancing effect of engagement with the out-group member, and the social effect of the real-time interactQ, make them self-reflectively aware of their own prejudice, and stereotypical beliefs about people with physical disability. They become self-reflective about the act of forming their attitude, which means reflecting on why a possible dissonance (e.g., embarrassment) occurs. This self-reflection enables them to answer the questions of why they hold the attitudes they do, rather than merely causing them to correct their attitudes.

The prejudice reduction we see can therefore be explained as reduction on an explicit and conscious level, rather than implicit level. It concerns increased engagement with the attitude object (i.e., people with physical disability), which creates a nuancing and self-reflective effect. This may explain the lack of significance in the IAT test results. The effect of the intervention would not show up on a binary (good-bad) IAT test, since such tests target “automatic” and “implicit” associations that operate at a lower (un)conscious level of attitudes. Whether the engagement-based strategy for prejudice reduction can have effects on the implicit level would require further research.

Given this discussion we expand our initial proposal of reducing prejudice through an engagement-strategy with two further points: nuance and attitude formation. We formulate this in the Enact (Engagement, Nuancing, and Attitude formation) hypothesis, which posits that interventions working with an engagement condition can reduce prejudice through a nuancing effect and by working with a second condition focusing on the formation of attitudes. This also means that we redefine the aim of prejudice reduction, which should not be thought of as changing either positive or negative attitudes and stereotypes, but as a nuancing of attitudes and stereotypes.

Enact vs. Contact

The risk of backfire effects (e.g., intergroup anxiety, disengagement, and reinforced prejudice) is particularly known in attempts of attitude correction ( Campo and Cameron, 2006 ; Nyhan and Reifler, 2010 ). In the Enact hypothesis, we aim to avoid the risk of backfire effects, not by adding conditions to the list of direct contact or by removing the direct embodied contact, described in the introduction as strategies used by current versions of contact theory, but by distinguishing attitude correction from prejudice reduction . As we saw with the results, attitudes may go both ways at once, so to speak. Reducing prejudice or stereotypes, as we see it, is therefore not a question of improving categories, but of de-reification ( Berger and Pullberg, 1965 ). That is, de-reifying orthodox frameworks for knowing and relating, or as formulated by Allport “a differentiated category is the opposite of a stereotype” ( Allport, 1954 ).

Even without the attempt to correct the audiences’ attitudes, we saw in the results from the phenQI that the audiences experienced embarrassment in their engagement with JN. As described above, these negative emotional experiences of discomfort are usually to be avoided in direct and indirect contact approaches, as they are related with intergroup anxiety and pose a risk of disengagement and stereotype strengthening. In our intervention, however, the interviewees do not focus on ways of realigning cognitive content and escape embarrassment, but rather on how they reflected on the embarrassment. As shown in Figure 4 , only few participants (in average 5.02%) revised their answer during the performance. We take this as an indication that the audience took their time to consider their answer and stuck to it, even if they would be embarrassed by it. Dealing with intergroup anxiety through self-reflection is a possible explanation for why the reports of initial embarrassment in the encounter did not lead to disengagement, as could have been expected.

To emphasize this effect of self-reflection, we draw attention to the second-order level of attitudes, namely the act of attitude formation, rather than the first-order level of attitudes, i.e., the content of the specific attitudes. In contrast to the direct and indirect contact approaches, results indicate that the intervention did not primarily correct or change attitudes at the first-order level. Instead, the participants became aware of the second-order act, i.e., aware of how and why they (re)form their attitudes when they engage with the attitude object (e.g., JN and physical disability).

This means that in the Enact hypothesis the aim is for people to self-validate their own attitude formation, rather than to increase informational content about the attitude object. Recent persuasion research has defined self-validation as a parameter associated with high credibility to the attitude source, and as a parameter which generates both personal relevance and self-confidence in the attitude formation ( Briñol et al., 2009 ). With an attitude formation based on a nuancing process, the changes will originate from the participants themselves – not from external factors – meaning that they will entail self-validation, which provides a certain strength to the attitude (re)formation.

This may also address the issue of long-term exposure as seen in some contact interventions, i.e., the assertion by Pettigrew (1998) that content-related attitude change often demands repeated and frequent direct or indirect contact. We suggest that this may not be the case in second-order attitude change. Since the engagement strategy effects changes on the structural level of forming attitudes, there might not be a necessity for the same degree of repeated direct or indirect contact. Interviewees did mention that they returned to the experience in the theatre in the days after the performance when they encountered other people with physical disability at workplaces or in public spaces. However, we did not measure for such long-term changes (see strengths and limitations section).

How does the Enact hypothesis relate to the direct and indirect contact hypothesis and does it solve the application challenge? To deal with the application challenge the Enact hypothesis operates in a hybrid way that includes and combines aspects of both direct and indirect contact strategies. The Enact hypothesis is thus a version of contact theory, working with contact in terms of engagement 7 .

To deal with the application challenge, the Enact hypothesis posits two necessary conditions for prejudice reduction: (1) engagement, and (2) explicit reflection of the attitude (re)formations. However, drawing on theater as the intervention for contact implicitly controls further factors of the contact. In the use of theater, the settings, customs, and norms of the theater regulate the contact, as they structure the engagement between the in- and out-groups, e.g., the audience voluntarily agrees to see this performance, and it is legitimated by an institution. Theater was chosen because it operates with shared, embodied participation between in- and out-group, but placing JN on stage further effects this interaction to the end that the out-group is granted higher status (audience is listening to JN’s experience). This means that depending on which intervention one uses additional factors and structures may help in structuring the contact 8 . It nevertheless shows that using theater as an intervention is one way to create engagement, nuance and reflection, and thereby to reduce prejudice in a real-life setting.

Finally, the phenQI results highlight that the current social media, information, and technological landscapes are determined by potential disengagement. Thus, the use of those strategies in solving the applicability challenge (particularly for their benefit of vast scalability) comes with a risk of disengagement, and from that with a risk of reinforcement of stereotypes, as outlined in the introduction. Since engagement is a necessary condition for reduction of prejudice in the Enact hypothesis, one must be aware when choosing and designing the intervention medium that engagement is possible and ensured, and preferably monitored by indirect and direct measures.

Strengths and Limitations

We conceive of this study as an initial exploratory phase of developing a hybrid strategy for prejudice reduction. We therefore maintain that there are good indicators that the Enact hypothesis has something to offer, and that further investigation and development is warranted. Here, we explicate a few of the method-implications for the strength of the results.

In terms of evaluating selection bias, we draw on statistical material from general population as well as theater audiences. Of the seven groups involved in the study (see Figure 1 ) we have biographical information on the four pre- and post-groups of the audience (group 1 + 2 + A + B), as well as on the focus-group. Those can be compared to data about the general population, as well as data on the average theater audience in Denmark (see Table 1 ). We do not have data on the general audience group (included in the interactQI), and only limited data on the control-group, showing a slight variation in gender and age to the general population (see Table 1 ). It should be noted that the test-selected groups (group 1 + 2 + A + B) and main part of the general audience group were self-selected by buying tickets for the performance, i.e., knowing the title and general topic of the performance. The focus-group was on the other hand randomly recruited and invited to the performance. Although they had to agree to go to the theater they were not informed of the title nor of the topic of the performance.

In the focus-group we see a predominance of women compared to men, mirroring the distribution for the average theater audience 9 . However, in the test-selected groups, the ratio is reversed with a dominance of male participants. Both groups, focus- and test-selected, show a younger average age than the median age for average theater audience and they also show higher levels of education than both the average Danish population and average theater audience. The latter might be explained by the lower average age, as the level of education is higher among younger generations ( Nørtoft, 2014 ). Further, the performance took place in traditional theatrical institutions tied to higher social class. The participants might therefore had been different had we used community theater settings or street performance. The age difference may indicate that our intervention performance has attracted a slightly different crowd than usual theater that attracts on average an older population.

There are two things to note from this. First, there is some selection bias (whether self-selection or recruitment bias). We have tried to balance this by also drawing on a control-group, and by recruiting groups from two different settings: the audience and a randomly recruited focus-group in the city center. Some selection bias is likely to be shared by these groups, e.g., an interest in theater 10 , but other elements will vary. Second, levels of education might be a particularly important factor in the outcomes of our study, and further studies should be carried out to test the Enact-interventions in more diverse, cultural settings.

On average, 10–15% of the Danish population has a disability. The focus-group participants have a lower percentage, whereas the test-selected groups place themselves in the high end of the spectrum (14.7%). There is no data available on disabilities in theater audiences. Approximately half of both groups know someone with a physical disability. We do not have a specification of the closeness of the relations, and there is no data available for this number in the general population, nor in general theater audiences. However, assuming that these numbers are indicative of the general audience, this means that even if there was self-selection of audience members – risked by the general audience knowing the topic in advance – approximately half of the audience did not have prior acquaintance with someone with physical disability, and thus, at least self-selection of in-group or in-group familiars did not occupy the entire test group.

As for possible transfer between different target out-groups (i.e., race, gender, sexuality or other groups subject to prejudice) we see no theoretical limitations for the transferability of the Enact hypothesis. However, Paluck et al. (2018) finds evidence that contact seems to be particularly effective for prejudice reduction in the case of physical disability. This may also apply to our hypothesis, and the tendencies we have shown may not be as present in other target groups.

An unanswered question in relation to our results is whether it generates long-lasting effects of prejudice reduction. It would be interesting for future experiments using the Enact hypothesis to do cross-sectional and longitudinal follow-up studies of individual participants, to see if immediate attitude change could become long-term and potentially change the behavior toward people with physical disability or other out-groups. In this experiment we did not conduct such studies, but we conducted interviews 4 months after the pilot-experiment, which indicated behavioral changes in relation to the participant’s openness when meeting people with physical differences in their daily life.

One thing to consider in new Enact-interventions is an attentiveness to unexpected ethical challenges due to the effect and manipulative skill of the theater performance, namely the transformative effect that lies in engagement. In one case, a focus-group participant was clearly upset after the performance and told a member of the research group that they found the intervention very uncomfortable and did not feel they had properly agreed to having their attitudes and beliefs challenged. However, as it might affect results in multiple ways – e.g., creating selection bias and priming test participants – to fully inform participants beforehand, an ethical dilemma arises. Although such strong discomfort should not be inflicted on test participants against their will, we suggest that the best responsible handling of this is through a proper off-boarding process. In our case, we made sure that research and theater personnel were present and clearly visible when the audience exited the performance. If any audience member wished or felt a need to discuss the performance, they were able to make contact and research or theater members would listen, answer questions, and make sure that no one left the location feeling distressed.

In this paper, it has been our aim to deal with the application challenge of the contact hypothesis, by using a hybrid strategy of both direct and indirect contact. Based on second-person methodology, we developed an engagement strategy for prejudice reduction. We implemented the strategy in a theater performance and investigated the effects on prejudicial attitudes toward people with physical disabilities. From the case study results we reformulated our initial engagement strategy to an Enact (Engagement, Nuancing, and Attitude formation) hypothesis. This hypothesis deals with the application challenge by positing two necessary conditions for prejudice reduction. Interventions should: (1) work with engagement to reduce prejudice, and (2) work on the second-order level of forming attitudes. However, working with such a strategy, means that the goal of the prejudice reduction should not be thought of as attitude correction. Instead, the aim for reducing prejudice should be to nuance attitudes. We see good indications for further development and investigation of the Enact hypothesis.

Data Availability Statement

The original contributions presented in the study are included in the article. Additional data can be found at the Open Science Framework webpage: https://osf.io/n32zu/ .

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author Contributions

KM: conceptualization, methodology, investigation, supervision, project administration, and writing – original draft. HS-F: conceptualization, methodology, and writing – original draft. AJe: software, formal analysis, data curation, and visualization. AJu: methodology and formal analysis. DN: investigation and formal analysis. TC: resources, project administration, and funding. All authors contributed to the article and approved the submitted version.

This research as well as parts of the theater performance was funded by the Elsass Foundation.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

Conducting phenomenological mixed-method research is a collaborative effort, so we want to thank TC and his theater team for their incredible work in developing and conducting the study on prejudice toward people with physical disability. In relation to this, thanks should also be given to the graduate students who helped in gathering data, namely, Sofie B. Jørgensen, Kenni Antonsen, Kristoffer F. Dalsgård, and Line M. Møller.

^ The pilot-experiment and its results are discussed in Martiny (2015) .
^ The authors assert that all measurement procedures contributing to this work comply with the ethical standards of the relevant Danish committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Ethics approval is not obtained for this experiment because, according to the Danish ethics committee law §2, no. 1, only health scientific research that includes biological material and clinical trials needs approval, whereas questionnaires, qualitative interviews and non-health scientific intervention studies, do not need approval.
^ See Martiny et al. (2021) for at further description and discussion of the phenomenologically based mixed-method design.
^ For further description of how to conduct mixed-method triangulation with a phenomenological frame see Martiny et al. (2021) .
^ The data and results that were not included in Figure 2 , along with additional material (e.g. the questionnaires used), can be found at the Open Science Framework webpage: https://osf.io/n32zu/ .
^ The scale also includes slight, moderate, and strong preference for disabled , but as no participant achieved this result, these preferences are not included in the ranked data.
^ Thanks to reviewer 1 for clarifying this relation between the Enact and Contact hypothesis.
^ Thanks to reviewer 1 for clarifying that the Enact hypothesis does not only work with two conditions, but depending on the intervention it works with, additional factors and structures can be added.
^ It should be noted that the focus-group consists of a relatively small number of people, skewing the biographical statistics by 3.33% for each participant.
^ It could be argued that such a self-selected group may be more easily engaged than an average population. We do not deny this. Our intervention test focused on whether there would be an effect, given engagement was present. Underlying reasons for the engagement are thus interesting, but not directly relevant.

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Keywords : contact hypothesis, second-person cognitive science, prejudice reduction, attitude change, physical disability

Citation: Martiny KM, Scott-Fordsmand H, Jensen AR, Juhl A, Nielsen DE and Corneliussen T (2022) From Contact to Enact: Reducing Prejudice Toward Physical Disability Using Engagement Strategies. Front. Psychol. 12:602779. doi: 10.3389/fpsyg.2021.602779

Received: 04 September 2020; Accepted: 27 September 2021; Published: 12 January 2022.

Reviewed by:

Copyright © 2022 Martiny, Scott-Fordsmand, Jensen, Juhl, Nielsen and Corneliussen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Kristian Moltke Martiny, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Intergroup Contact Theory

First Online: 02 July 2019

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Oliver Christ 3 &
Mathias Kauff 3

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Bringing members of different social groups into contact is thought to be as one of the most promising approaches for improving intergroup relations. Indeed, a plethora of studies has shown that this intergroup contact is an effective means not only to reduce mutual prejudice but also to increase trust and forgiveness. In this chapter, we will first review evidence for the effectiveness of intergroup contact and introduce different forms of intergroup contact – direct (i.e., face-to-face contact) as well as more indirect forms of contact (i.e., extended, vicarious, and imagined contact). We will then discuss moderators (e.g., types of in- and outgroup categorization) and mediators (e.g., intergroup anxiety and empathy) of contact effects as well as potential unintended effects of intergroup contact. Finally, we will summarize research on the effectiveness of intergroup contact interventions and give two examples of such interventions that have been implemented in the context of conflictual intergroup relations (i.e., Israeli-Palestinian conflict and Hutu-Tutsi conflict in Rwanda).

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Christ, O., Kauff, M. (2019). Intergroup Contact Theory. In: Sassenberg, K., Vliek, M.L.W. (eds) Social Psychology in Action. Springer, Cham. https://doi.org/10.1007/978-3-030-13788-5_10

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Open access
Published: 16 May 2024

Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics

Adriana Manna ORCID: orcid.org/0009-0005-8195-861X 1 ,
Júlia Koltai ORCID: orcid.org/0000-0002-8676-7303 2 , 3 &
Márton Karsai ORCID: orcid.org/0000-0001-5382-8950 1 , 4

Nature Communications volume 15 , Article number: 4137 ( 2024 ) Cite this article

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Computational models
Epidemiology
Infectious diseases
Interdisciplinary studies

Individuals’ socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies.

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Introduction.

Individuals’ socio-demographic and economic characteristics are among the most significant factors that shape the dynamics of epidemic spreading processes. They not only influence the epidemic outcome in the hosting population but largely determine the course and severity of the disease for those who got infected 1 . There is a widespread agreement that pandemics disproportionately affect certain population groups rather than others 2 , 3 , 4 , 5 , 6 , 7 . Health-related inequalities in the burden of an epidemic partly arise from differences in the level of exposure to viruses and bacteria. These are associated with differences in social interactions, mobility patterns and work-related conditions, which are aggravated by disparities in the ability to be compliant with non-pharmaceutical interventions (NPIs), such as self-isolation, home-office and avoiding crowded places 8 , 9 , 10 , 11 , 12 , 13 . At the same time, inequalities in the severity and fatality of a disease can be accounted for by the heterogeneity in preexisting individual health conditions, protection attitudes and access to medical care, which are themselves related to socio-demographic and economic factors 14 , 15 .

Although it is widely recognised that socio-economic inequalities play a crucial role in the transmission dynamics of diseases, traditional mathematical approaches have often overlooked these factors. Indeed, the state-of-the-art framework of modelling infectious diseases incorporates stratification of the population according to age groups 16 while discarding other potential relevant heterogeneities between groups of individuals belonging to different socio-economic strata. They commonly ignore the mechanisms through which these heterogeneities come into play, both directly and indirectly, in the different phases of an epidemic process. In traditional epidemiological models, contact patterns are usually represented in the aggregate form of an age contact matrix ( C i j ), which encodes information on the average number of contacts that individuals of different age groups have with each other 17 , 18 , 19 , 20 , 21 , 22 . Moreover, not only the description of contact patterns is limited to an age structure, but also other epidemiological-relevant factors, such as vaccination uptake, infection fatality rates 23 or susceptibility 24 , are usually described only by considering differences between age groups. While age is unarguably one of the most important determinants of these characters, the current literature falls short of understanding the role of other social, demographic, and economic factors in shaping human behaviour that are relevant to the epidemic’s spreading. In recent years, researchers have advocated including social aspects in infectious disease modelling, arguing that the epidemic modelling community lacks a deep understanding of the mechanisms through which the socio-economic divide translates into heterogeneities in the spread of infectious diseases 25 , 26 , 27 , 28 .

With this in mind, we aim to shed light on these mechanisms to address the following interrogatives: which are the most important individual characters and corresponding subgroups of the population that differentiate the most their epidemic-relevant behaviours, and how do these differences translate into epidemiological outcomes? We address these questions by analysing a large survey dataset coming from the MASZK study carried out in Hungary during the COVID-19 pandemic 29 , 30 . This data collects information on individuals’ face-to-face interaction patterns in different contexts and other epidemiological-related behavioural patterns and opinions such as travel habits, vaccination uptake, or mask-wearing. The MASZK study consists of 26 cross-sectional representative surveys conducted monthly between 2020/04 and 2022/06 (for more details on the data, see Section 1 of SI and MM). By considering the course of the pandemic in the country, we aggregate the data in six periods covering four epidemic waves (Ws) and two interim periods (IPs), as demonstrated in Fig. 1 a.

a Left axis : number of new daily COVID-19 cases in Hungary from 2020/04 to 2022/07. Right axis : average number of daily contacts from 2020/04 to 2022/06, excluding household contacts. The values are shown as the median and interquartile range (IQR) of 1000 bootstrapped samples. The white and grey areas delimit the periods that have been aggregated in the analysis: two interim periods (IPs) (white areas) and four epidemic waves (W) (grey dashed areas). b Box-plot (outliers, minimum, lower quartile, median, upper quartile and maximum) of the maximum confidence level at which the effect of the different categories of the variable on the total number of contacts becomes significantly different. The dispersion of the box plot refers to the variation of this value over different age groups. Results are shown for education level, employment situation, income level (which is present from the 2nd W, since this information was missing in the first few data collections), gender, settlement, chronic disease, acute disease, and smoking behaviour. The higher this value is, the more the variable influences people’s number of contacts given their age. The horizontal dotted line is placed at 95% and it represents the confidence level at which the AME is considered to be statistically significant. Sample sizes are indicated in Section 1.2. of SI.

Throughout this study, we are mainly interested in the dynamics and most influential determinants of social contacts that were recorded in the data as reported proxy interactions between pairs of individuals who spent at least 15 min within 2 m of each other on a given day. Outside of home, we distinguish between two contexts where social interactions may evolve. We differentiate between work contacts that emerge at the workplace (or at school) of respondents (or their minors) and community contacts that they evolved elsewhere than home or work. Meanwhile, we do not take into account household contacts in our study as we assume they do not change significantly during the different phases of the pandemic. Through the analysis of contact patterns, our aim is to show existing significant differences among subgroups of different socio-demographic characters, when accounting for the effect of age. Particularly, we demonstrate that dimensions such as employment situation and education level play a crucial role in determining contact numbers and vaccination uptake during a pandemic. Additionally, by proposing a new data-driven mathematical framework which explicitly considers further social dimensions other than age, we analyse the impact of such differences in terms of epidemic outcomes. Finally, by focusing on the Hungarian COVID-19 pandemic scenario, we reveal the unequal impact of the pandemic in terms of individuals belonging to different socio-economic statuses, where we differentiate individuals by their employment situation and income level. Note that although all the models have been completed on each pandemic period, for the demonstration of our findings, we exclusively show results about the 4th wave in the main text. We chose this period to demonstrate our results because NPIs were not significantly changing, while the vaccination rate had saturated already during the 4th wave; this way, neither of these effects could bias the observed behaviours. We report our findings concerning other periods in the SI .

The main determinants of human contact patterns

Human contact patterns represent the routes of infectious disease spreading by shaping the underlying transmission chain among susceptible individuals. During the COVID-19 pandemic, many aspects of human behaviour have experienced drastic interruptions in most countries worldwide. This was largely due to the implementation of non-pharmaceutical interventions (NPIs) that were installed to mitigate the spreading and other effects of the pandemic. They aimed at controlling the number of contacts, as well as influencing individual attitudes, to change the ways humans meet and interact with each other 24 , 31 , 32 . Their effects are evident in Fig. 1 a, where the average number of daily contacts in Hungary is shown. This value increases during interim periods (IPs) when the numbers of daily infection cases are low and decreases during the epidemic waves (Ws) when infection risk is high, this way sensitively reflecting the adaptive behaviour of people throughout the pandemic.

Although at the aggregate level, these patterns are clear, there are non-trivial disparities at the level of individuals that may result in diverse contact patterns for given subgroups of the population. To explore these effects, in our statistical analysis, we focus on several socio-economic dimensions that, interacting with age, may significantly affect the number of contacts that individuals have. We consider various socio-demographic variables such as individuals’ education, employment, income, gender, settlement type, actual chronic or acute disease or smoking habits (for more details and definitions, see MM and Section 1.1 of SI). As a first observation, in Fig. 1 b, we show the distribution of the maximum confidence level of the effects of these variables on the number of contacts in interaction with age during each period (for definition see MM). In these distributions, a higher value indicates higher certainty that a given variable has an effect, i.e., its effect is significantly different from zero at a smaller type I error probability 33 , given the age of individuals. Based on these results, employment, education and income level were found to be the three most important dimensions in determining the number of contacts. This observation stands if we consider the overall number of contacts including both work and community relationships, and it is true as well if we only consider community contacts (with results shown in Section 2.1. of the SI along with all the robustness checks).

To further investigate the ways individuals of different characters adapt their number of contacts to the actual epidemiological situation, in Fig. 2 we show the average number of contacts over time decoupled by education level (Fig. 2 a, c) and employment situation (Fig. 2 b, d) for adult individuals older than 15 years old (for the corresponding plots related to income and settlement see Section 4.1 of SI, while for the plot decoupled by age groups see Section 4.2 of the SI). Results in panel (a) suggest that high and mid-high-educated individuals have consistently higher number of contacts in the community layer throughout the observed period. In addition, the pattern of the average number of contacts of these groups suggests that they were probably able to better adapt to the epidemiological situation and NPIs by decreasing their contacts number during epidemic waves and increasing again during interim periods. Conversely, individuals with mid-low and low education levels exhibit a lower and relatively stable number of contacts over time. Workplace contact dynamics suggest that only highly educated individuals (high and mid-high) were able to adapt to the epidemiological situation, while seemingly, those with lower education levels had less flexibility to adjust during different pandemic periods. Interestingly, mid-low educated individuals reported a higher number of workplace contacts, particularly during the second wave (2nd W) and the second interim period (2nd IP), attributable to their predominant vocational degree status and involvement in on-site interactive work. These patterns are confirmed when examining the relative number of contacts over time, as elaborated in Section 4.1.1 of the SI.

a and b Average number of contacts in the community layer a by different education levels and b employment situation. c and d Average number of contacts at workplace c by different education levels and d for employed people. All curves have been smoothed over the observation periods for better visualisation. e–h Decoupled age contact matrices by education level for the 4th epidemic wave. i and j Decoupled age contact matrices by employment situation for the 4th wave. These figures depict contact numbers only for the adult population [15+), while matrices containing children are shown in Section 4.3.2 of the SI. All the values are shown as the median and IQR of 1000 bootstrapped samples.

When we group people by their employment situation, it makes sense to compare groups in the community layer. From Fig. 2 b it is clear that employed people maintain more contacts even outside of their workplace as compared to not-employed individuals, which is a clear sign of behavioural differences between these two groups. Meanwhile, employed individuals follow somewhat similar contact dynamics as highly educated people (see Fig. 2 d), signalling some correlation between these two groups.

From an epidemic modelling perspective, the most convenient way to code interaction patterns between different groups is via contact matrices that quantify the average number of interactions between population strata. Contact matrices allow models to depart from the homogeneous mixing assumption, i.e. taking all individuals to meet with the same probability. Instead, they allow the introduction of non-homogeneous mixing patterns between different groups, while keeping the model computationally more feasible as compared to contact network-based simulations. Conventionally, epidemic models incorporate C i , j age contact matrices that code the average number of contacts between people from different age groups (for formal definition, see MM). Nevertheless, age contact matrices could be further stratified by other socio-demographic characters that influence the contact numbers of individuals. In Fig. 2 e–j, we show the age contact matrices decoupled by education level and employment situation ( C d i , j ) for the 4th epidemic wave for the adult population (see MM for more details and Section 4.3.2 of SI for the corresponding matrices including children). These matrices have been computed by considering community , work and household contacts together. The emerging large differences between these matrices demonstrate clearly that beyond age, the identified variables, i.e. education and employment status, induce significant differences in the contact patterns of individuals. Although these variables may not be independent of the age of people, the observed distinct patterns suggest more complex mechanisms controlling contact patterns among subgroups that cannot be explained by age alone.

Beyond age stratification

We demonstrate that social inequalities significantly influence human contact patterns, thereby shaping the network of proxy social interactions. This is critically important for the propagation of diseases as it determines the transmission chain of an infection spreading among a susceptible population. Consequently, incorporating the contact pattern differences among individuals of different socio-economic backgrounds into epidemiological models is crucial. This could help to understand the unequal spread and uneven burden that an epidemic could impose on the different socio-demographic groups of a society. To this end, we propose a simple mathematical framework based on the extension of a conventional age-structured SEIR compartmental model 34 , 35 , which we call the extended SEIR model. The conventional SEIR model assumes that each individual in a population is in one of the mutually exclusive states of Susceptible (S), Exposed (E), Infected (I) or Recovered (R). Transitions of an individual between these states are controlled by rates ( ${\rm {S}}{\longrightarrow}^{\lambda }{\rm {E}}$ , ${\rm {E}}{\longrightarrow}^{\varepsilon }{\rm {I}}$ , ${\rm {I}}{\longrightarrow}^{\mu }{\rm {R}}$ ) with the λ rate influenced by the frequencies of interactions between age groups coded in a C i , j age-contact matrix. The proposed extended model incorporates ${C}_{\bar{d},i,j}$ age contact matrices instead, that are decoupled along important socio-demographic dimensions $\bar{d}$ to model epidemic spreading in different subgroups of the population (see MM and Section 6 of the SI for further details).

Particularly, we analyse the impact of decoupled age-contact matrices along four dimensions: employment situation, education level, settlement, and income level (for exact definitions and possible variable values, see MM). Taking the decoupled contact matrices as input, we simulate the spread of infectious disease among an entirely susceptible population using both the conventional SEIR and the extended SEIR models. Having fixed the epidemiological parameters such as the transmission rates and seeding strategy, other input parameters like the population distributions and contact matrices have been estimated from data, as we explain in Section 7 of the SI in more detail.

The proposed model allows us to investigate how differences in contact patterns along diverse social groups translate into an unequal burden of the epidemic. To quantify these differences in the epidemic outcome, we measure the attack rate defined as the population-wise normalised fraction of individuals who contracted the infection from a given group. To follow the distribution of the people along the investigated dimensions, we show the survey population fractions in the different age groups in Fig. 3 a–d. Meanwhile, in Fig. 3 e–h, we depict the attack rates calculated using the extended SEIR models for different age and socio-demographic groups (and as reference only for age—see grey solid lines). Results are shown for the cases when we decouple each age group along the four dimensions analysed. As anticipated by the statistical analysis, employment and education produce the largest differences between groups in terms of attack rate by age. Interestingly, the group of employed people happened to be the most infected group in all age groups, while mid and high-educated individuals are more infected among those who are 45–60 years old. When decoupling age contact matrices by settlement and income, although differences appear smaller between groups, high-income individuals and the ones living in the capital are more infected, particularly elderly ones with age 60+. These modelling results suggest the interesting overall conclusion that employed and wealthier group of the population, as well as those living in the capital report a higher attack rate, thus they are typically the most infected group relative to their population size.

a–d Survey population distribution by age and employment situation ( a ), education level ( b ), settlement ( c ) and income ( d ). e–h Attack rate by age and employment situation ( e ), education level ( f ), settlement ( g ) and income ( h ) as predicted by the extended SEIR (i.e. calculated with both age and the given socio-economic variable stratification). The grey lines represent the attack rate by age calculated only with age stratification as predicted by classical SEIR with C i , j (solid lines) and extended SEIR with C d i , j (dotted lines). i Difference in the attack rate by age as predicted by the classical ( M w / C i , j ) and the extended ( M w / C d i , j ) model when different, the dimensions are considered. Results are shown for the 4th wave. Epidemiological parameters: μ = 0.4, ϵ = 0.25, and R 0 = 2.5. Simulations start with I 0 = 5 initial infectious seeds. Results are sown as the median and IQR computed over 1000 simulations.

These results also demonstrate that the extended SEIR model is able to capture differences introduced by the considered socio-demographic variable and, in this way, to model the epidemic impact on the different groups of the population. These differences are also visible at the population level. In Fig. 3 i, we show the differences between the attack rates predicted by the conventional and the extended SEIR models for each age group and overall, too. It is evident from these results that models using contacts only stratified by age may overestimate (negative difference) the size of the epidemic in different age groups or in the whole population. For example, our simulations based on data from the 4th wave demonstrate that the conventional SEIR model could predict higher attack rates for each age group with respect to the extended SEIR , which considers differences in contact numbers along the employment situation or the education level. (See Section 7.1 of SI for the corresponding figures for the other periods and the relatively sensitive analysis). It is important to highlight that the uneven age distribution within the different subgroups sometimes reduces or annul the effect of the difference in the contact patterns when we are computing aggregate quantities at the population level. This explains why, even if there is a significant difference in contact patterns, the difference in the overall attack rates only spans a small range between the two models.

Vaccination uptake and contact number differences

Beyond the crucial role played by the network of face-to-face interactions, individual vaccination uptake may also substantially affect epidemiological outcomes by decreasing morbidity and mortality. By applying the same pipeline of statistical analysis as we explained above, we identify the dimensions along which individuals made different decisions in terms of vaccination, given their age. In this case, the interaction with age is particularly important given that the COVID-19 immunisation strategy implemented in Hungary followed an age-stratified outreach by prioritising elderly individuals 36 , 37 . Despite the prioritisation of specific groups, such as medical personnel, in the initial months of the vaccination campaign, we regard the associated impact as negligible for the purposes of this study. Interestingly, the statistical analysis in this case indicates income as the most important dimension along which individuals made different vaccination decisions (see Section 2.2 of SI for the results of the statistical analysis). Figure 4 a–d shows the percentage of vaccinated individuals by age and the investigated dimensions during the 4th wave of the pandemic. Although by the 4th epidemic wave the vaccination saturated in Hungary, the effects of the age-dependent vaccination policy are clearly visible. More strikingly, we find that higher socio-economic groups of the population were more likely to get vaccinated against the COVID-19 virus. This observation is valid for all age groups and periods considered in the analysis (see Section 5 of SI for the corresponding figures for the other periods).

a–d Fraction of individuals vaccinated with at least one dose against COVID-19 during the 4th wave, decoupled by age and a employment situation, b education level, c settlement, and d income. Panels e–h show the averted attack rates (difference between the attack rate in the non-vaccination scenario with respect to the vaccination one) by e age and employment situation, f education level, g settlement, and h income as predicted by extended SEIR . The model takes into account different rates of vaccination uptake by subgroups of the given variable compared to the non-vaccination scenario. Epidemiological parameters: μ = 0.4, ϵ = 0.25, and R 0 = 2.5. Simulations start with I 0 = 5 initial infectious seeds. Results are sown as the median and IQR computed over 1000 simulations.

To consider these observations, we model the vaccination uptake in the extendend SEIR framework. More precisely, we define the probability of getting vaccinated (i.e. immune or recovered from the point of the infection) to be dependent, in this case, on both the age and the subgroup of the population considered. Using this extended SEIR model, we are able to compare the effects of vaccination uptake, while keeping fixed the structure of contacts. Figure 4 e–h shows the averted attack rate due to vaccination with respect to the non-vaccination scenario. We consider the probability of getting vaccinated along the four different investigated dimensions separately. In all of these scenarios, the gain in averted infection is strongly dependent on the subgroup membership. As expected, the groups with higher vaccination uptake are the ones, which reduce their attack rate the most in the vaccination scenario. However, this pattern is not linear. For example, among individuals aged 60+, although the not-employed people report a higher vaccination uptake, they are the ones that gain less in terms of averted infections. This is because these individuals, having a low number of contacts, are already protected from exposure to the virus; thus, they gain less from vaccination (see Section 7.2 of SI for the corresponding figures for the other periods and the relative sensitive analysis).

Stratified modelling of the Hungarian scenario

To provide an example of how the proposed mathematical framework can be applied to a real case scenario, we model the 4th COVID-19 wave in Hungary between 09/2021 and 01/2022. As the statistical analysis showed that employment and income are the most important dimensions along which, respectively, contact patterns and vaccination uptake change the most, here we divide the population into subgroups by considering simultaneously these two additional dimensions other than age. In addition, we introduce a new compartment D to our SEIR model, which represents a dead state that infected individuals may enter with a transmission rate ${\rm {I}}{\longrightarrow}^{\mu {\rm {IFR}}}{\rm {D}}$ .

To simulate the SEIRD for the 4th COVID-19 wave in Hungary, we calibrate our model using the Approximate Bayesian Computation (ABC) method 38 , 39 on the total number of daily deaths from 09/2021 to 01/2022 40 . Details about the fitting method and calibrated results are summarised in Section 8 of the SI.

The results of the simulated model are presented in Fig. 5 , which shows the daily fraction of newly infected (panels (a)−(c)) and new dead (panels (d)−(f)) cases for different employment, income, and age groups. As expected, these curves suggest that the group of employed people experienced the infection at a higher rate as compared to those not employed. At the same time, in terms of socio-economic status and age, more affluent and younger people got infected more during the simulated epidemic wave. On the other hand, strikingly the contrary trend is suggested in terms of mortality rates. From the simulations, we find that although not-employed, low-income and older individuals appeared with the lowest infection rates, they evolved with the highest mortality rate as compared to other groups.

Results from the simulated model for the 4th wave in Hungary. The figure shows the median and the IQR over 1000 runs. a–c Fraction of newly infected by a employment situation, b income level, and c age group. d–f Fraction of new deaths by d employment situation, f income level, and g age groups. g Attack rate by age, employment situation and income level. h Mortality rate by age, employment situation and education level. For more details about the parameters of the numerical simulations, see SI .

Considering that the COVID-19 fatality rate of infected individuals (IFR) depends on their age, this observation can be largely attributed to the fact that not-employed and low-income individuals are also the oldest ones in the population. To explicitly separate the effect of age when it comes to analysing the burden of the epidemic, we examine the attack rates and mortality rates by age groups separately in each of the subgroups of the population stratified by income level and employment status (Fig. 5 g, h).

As we have shown in the analysis above, these results confirm an overall decreasing infection rate by age and that not-employed individuals experience the lowest attack rate in each age group. The further stratification of not-employed individuals by income level reveals a clear pattern, with high-income people exhibiting a higher infection rate compared to mid-income and low-income individuals. In contrast, the infection pattern among income levels of employed individuals is age-dependent. For young employed individuals in the age group 15–30, high and mid-income individuals register a higher share of infections, while among those older than 30, low-income individuals exhibit a higher infection rate compared to mid and high-income individuals. An exception is represented by the age group 60–70, for which the most infected group is still the high income.

In terms of mortality, as expected, we find an increasing trend by age; otherwise, we can conclude a similar pattern as for the attack rate. Particularly, the mortality rate by age group shows that employed people die at a higher rate. While in terms of income, other than the group aged 15–30 and 60–70, the lower-income people suffered more deaths, according to our simulations. The extreme decrease in mortality rate for the employed high-income group is due to data sparsity in the survey data, recording only a few data points in this category (see Section 1.2. of SI).

Several factors may determine how an infection would turn out for a given person. Some of them are coded genetically or determined by physiological conditions, but many of them are environmental and correlate with one’s socio-demographic characteristics. In any society, people show uneven patterns along numerous social, demographic, and economic characteristics, like age, income or employment status. These characteristics not only induce medical disparities between people (as in immunity, overall health conditions, or chronic diseases) but naturally translate to differences in adaption capacities and other behavioural patterns, allowing certain groups to be more exposed to infection. The simultaneous actions of all these factors lead to observable inequalities in terms of epidemic burden between different groups at the population level.

This study highlights the significant impact that social determinants have on human behaviours that are relevant to epidemic transmission. Specifically, exploiting the data of the MASZK study 29 , 30 , we show that contact patterns and vaccination uptake are influenced by socio-economic factors. Our findings suggest that contact patterns are shaped by social factors not only in their absolute values but also in the extent to which they vary in response to extraordinary events, such as lockdown or curfew interventions. Specifically, our statistical analysis shows that socio-economic factors such as employment situation and education level played a significant role in determining contact numbers and vaccination uptake during the COVID-19 pandemic in Hungary. Additionally, in contrast to studies reporting a negative correlation between poverty and the number of contacts 41 , we find that people with higher socio-economic status tend to have a higher number of contacts and are the ones that change the most their number of interactions with respect to the epidemiological situation. Contrarily, people with lower socio-economic status maintain a lower number of contacts over time with smaller oscillations. Although we cannot establish a causal connection as a possible and plausible explanation these results suggest that people from higher socio-economic groups, such as those with higher education, income, and employment status, were able to better adapt to the epidemiological situation and NPIs and were more likely to get vaccinated.

We propose a mathematical framework that extends the well-known age-stratified approach to model infectious diseases by explicitly accounting for differences in contact patterns and vaccination uptake for specific subgroups of the population. This method allows us to better understand the mechanisms underlying the emergence of inequalities in epidemiological outcomes. Results demonstrate that traditional epidemiological models, that only consider age, could overlook crucial heterogeneities along other social and demographic aspects that may impact the spreading of an epidemic. Through simulated epidemic processes, we show that significant differences in terms of attack rates arise from differences in contact patterns. By neglecting differences in vaccination uptake and the effects of vaccination campaigns among subgroups in modelling, we would miss important determinants which significantly influence the outcome of an epidemic.

By simulating a pandemic period in Hungary, we reveal the unequal health-related impact of the COVID-19 pandemic among individuals belonging to different socio-economic groups. Although the higher number of contacts translates into higher attack rates for wealthier and employed individuals, the age structure and the vaccination decision of such groups translate into lower mortality rates for these individuals, while disadvantaged groups are the ones suffering higher mortality. These results are in line with the empirical findings of refs. 42 , 43 for the 2nd and 3rd COVID-19 waves in Hungary. In those studies, the authors find that individuals living in more deprecated areas are associated with a lower risk of being ascertained as a confirmed COVID-19 case and a higher risk of death. Additionally, during the 3rd wave, those were associated as well with lower vaccination uptake. However, we recognise as a limitation of our work that, owing to data gaps, the initialisation of population distributions within compartments and socio-demographic groups for the calibrated model is done only proportionally the population distribution. Indeed, the assumption of a homogeneous initial condition is improbable precisely because of the different contact patterns, exposure risks, and vaccination uptake among different age and socio-economic groups (see Section 8 of SI for further detail).

Due to the limitation of the survey collection methodology, contact patterns of individuals can be differentiated only by the characteristics of participants. Indeed, the only information we know about the contacted peers is their age, while their other characteristics remain unknown. Thus, our extended SEIR model can only account for age-contact matrices that are decoupled along other social dimensions of the participants (ego). In other words, although our model incorporates additional social dimensions, given the subgroup the ego belongs to, it still only considers the average number of contacts stratified by the age group of the contacted (alter). In order to introduce a generalised contact matrix 44 stratified along multiple socio-demographic dimensions of the contactee, we would need information about such dimensions. Such information can be collected via detailed contact diaries 30 , which are based on the reports of the respondents about peers and commonly suffer from recall bias and other limitations 45 , 46 . Moreover, we acknowledge the interplay between vaccination and contacts in mutually shaping each other, yet we have opted not to delve deeper into these mechanisms in the current work as they may fall beyond the scope of our study.

By shedding light on the complex interplay between social, demographic and economic factors and disease transmission dynamics, our findings underline the need for a new mathematical framework for epidemic modelling that accounts for multidimensional inequalities. This would help us to better understand the socially stratified consequences of an epidemic and highlight non-negligible inequalities between different socio-demographic groups. Additionally, incorporating social factors into epidemiological models will provide a valuable tool to design and evaluate targeted NPIs to cope more efficiently with the spread of an infectious disease.

Data description

The data used in this study comes from the MASZK survey 29 , 30 , a large data collection effort on social mixing patterns made during the COVID-19 pandemic. It was carried out in Hungary from April 2020 to July 2022 on a monthly basis. The data was collected via cross-sectional anonymous representative phone surveys using the Computer Assisted Telephone Interviewing (CATI) methodology and involved a 1000 large nationally representative sample each month. During the data collection, participants were not asked for information that could be used for their re-identification. The phone survey data collection was carried out after informed consent from the respondent at the beginning of each interview. Any information about children was obtained by asking questions from their parents or legal guardians after consent. Survey data was not collected from any under-age subject. The data collection fully complied with the actual European and Hungarian privacy data regulations and was approved by the Hungarian National Authority for Data Protection and Freedom of Information 47 and also by the Health Science Council Scientific and Research Ethics Committee (resolution number IV/3073-1/2021/EKU).

The primary goal of the data collection effort was to follow how people changed their social contact patterns during the different intervention periods of the pandemic. Relevant to this study, the questionnaires recorded information about the proxy social contacts , defined as interactions where the respondent and a peer stayed within 2 m for more than 15 min 48 , at least one of them not wearing a mask. Approximate contact numbers were recorded between the respondents and their peers from different age groups of 0–4, 5–14, 15–29, 30–44, 45–59, 60–69, 70–79, and 80+. Of which we aggregate the last two groups in 70+. Contacts number data about underage children were collected by asking legal guardians to estimate daily contact patterns.

Beyond information on contacts before and during the pandemic, the MASZK dataset provided us with an extensive set of information on socio-demographic characteristics (gender, education level, etc.), health conditions (chronic and acute illness, etc.), financial and working situation (income, employment status, home office, etc.), and attitude towards COVID-19 related measures and recommendations (attitude towards vaccination, mask-wearing, etc.) of the participants. In order to study different stages of the pandemic, we consider six epidemiological periods, including three epidemic waves (Ws) and three interim periods (IPs) (see Fig. 1 a).

On the collected data, a multi-step, proportionally stratified, probabilistic sampling procedure was elaborated and implemented by the survey research company using a database that contained both landline and mobile phone numbers. The survey response rate was 49%, which is notably higher than the average response rate (between 15% and 20%) of telephone surveys in Hungary. The sample is representative of the Hungarian population aged 18 or older by gender, age, education and domicile. To correct sampling biases, we used individual weighting to decrease the difference between population and sample distribution of social-demographic variables. The weights were calculated by the survey research company responsible for the data collection. For the calculation of the weights, raking was used 49 , which relies on iterative proportional fitting 50 . More details about the weighting procedure can be found in Section 1.3 of SI. After data collection, only the anonymised and hashed data were shared with people involved in the project after signing non-disclosure agreements.

Sociodemographic dimensions

The sociodemographic dimensions that we analyse are the following: (i) education level , which can have four possible levels: low, mid-low, mid-high and high; (ii) employment situation , which can be either employed or not-employed, including students and retirees individuals; (iii) perceived income (called simply income through the manuscript) can have three possible levels: low, mid and high; (iv) gender refers to the biological gender and can be either female or male; (v) settlement , which refers to the area where individuals live and can be either capital, rural or urban; (vi) chronic disease is a Boolean dimension indicating if an individual is affected by any chronic disease; (vii) acute disease is a Boolean dimension indicating if an individual is affected by any acute disease, and (viii) smoking is a Boolean dimension indicating if an individual is a smoker or not. A detailed explanation of these variables is provided in Section 1.1 of the SI.

Data prepossessing

All the analyses on the number of contacts have been performed after having deleted the outliers at the 98% percentile with respect to the period of interest. All the results presented in this work have been computed by accounting for each participant according to its representative weight, as detailed in Section 1.3 of SI. In addition, to assess the uncertainty of the estimation of contacts and contact matrices, we employ the bootstrapping sampling technique, as described in Section 3 of SI.

Statistical analysis

In order to build an epidemiological model that explicitly takes into account social inequalities, we need to identify which are the main dimensions that interact with age and affect contact patterns the most. To identify these dimensions, we model the expected number of contacts of respondent i using a negative binomial regression 18 , 51 as defined in Eq. ( 1 ):

where age_group i is the age class of i ; X i is the variable of interest (e.g., education, income, etc.), age_group i ${*}$ X i is the interaction term of the age group and the variable of interest, and ϵ i is the error term. Given μ i , we define ${\lambda }_{i}=\exp ({\mu }_{i})$ to be the expected number of contacts for respondent i . Then we model the reported number of contacts for respondent i , y i , as

where ϕ ∈ [1, ∞ ) is a shape parameter that is inversely related to over-dispersion: the higher ϕ is estimated to be, the closest y i ’s distribution is to a Poisson distribution with rate parameter λ i .

We build model ( 1 ) for each variable of interest ( X ). Particularly, the interaction term between age_group i and the variable of interest allows us to examine whether there are differences in the effect of X i on the number of contacts in the different age groups. To be able to provide a meaningful description of the interactions, we analyse the average marginal effect (AME) 52 , 53 , 54 of X i on the number of contacts for different age groups, defined as

Working with categorical variables (e.g., education level or employment situation), we can calculate different AMEs for all categories of the categorical variables in each age_group. It means, that, for example, for the interaction of the settlement type (with three categories, out of which one is a reference category) and age (with five categories) on the number of contacts, we have 2 × 5 = 10 different AME values: one for each settlement category by each age category. However, as we would like to know the overall effect of the interaction with the given variable, settlement, we have to aggregate these values into one measure. Therefore, we developed the following strategy. For each age group, we examined all the AMEs related to the category of the variable analysed (e.g., all AMEs related to the categories of the settlement type). In each case, we calculated the confidence level 55 at which the confidence interval belonging to the AME of a given category reaches zero. The higher this calculated confidence level is, the more certain we can be that the given variable category has an effect on the number of contacts in the given age group. Equivalently, the estimated effect is significantly different from zero at a smaller type I error probability. Out of these confidence levels, we consider the maximum confidence level for each age group as that denotes the highest confidence level at which the AME of the given variable (e.g., settlement type) reaches zero, i.e. the smallest type I error probability 33 at which the estimated effect is significant. Finally, to summarise the results across age groups, we look at its distribution. By following this procedure for each of the variables of interest in the different waves of the pandemic, we are able to rank the variables according to their importance in driving differences in contact patterns additionally to age, in different periods of the COVID-19 pandemic. The pipeline of these analyses is illustrated in Fig. 6 .

Pipeline of the statistical analysis to compute the distribution of the max confidence level over age groups for each of the variables analysed. The figure is made considering as an illustrative example of the variable employment .

Following the same methodology, we investigate the dimensions that, in interaction with age, affect the most the probability of getting vaccinated against COVID-19. In this case, we model this probability using a logistic regression model instead of a negative binomial, as the dependent variable was binary and not a count one (see Section 2.2 of SI for further details). Although the data were aggregated to obtain NPIs-homogeneous periods, minor variations in restrictions persist within certain intervals (see SI Fig. 3 ). Thus, acknowledging the importance of NPIs in shaping human contact during the COVID-19 pandemic, we tested the validity of our results when considering this effect. Additionally, we account for the interplay of vaccination behaviour and contacts, which can be significant in dynamic situations when vaccination strategies are implemented during an epidemic crisis 56 . Specifically, we have included two additional control variables in the statistical model ( 1 ): (i) the Oxford Stringency Index, a composite measure quantifying the government’s response strictness to the pandemic, and (ii) a dummy variable indicating individual vaccination status (vax i ). The results of these robustness analyses are presented in Section 2.1.2 of the SI, along with further robustness analysis where we control for all the other available individual features. Additionally, we investigate the effects of NPIs on vaccination uptake, with results presented in Section 2.2.1 of the SI. All the results of the robustness analysis align with those discussed earlier and lead to the same qualitative conclusions.

Decoupled contact matrices

Conventionally, to compute age-contact matrices C i j we divide a population into subgroups according to their age and calculate the average number of contacts that individuals in age class i have with individuals in age class j 30 . Here, instead, we further stratify individuals from each age class i according to various dimensions, like employment status, settlement or education level.

In detail, we decouple the conventional age contact matrix C i j into D number of matrices, one for each of the subgroups of the dimension that we want to take into account. More precisely, let $\bar{d}$ be the subgroup of the dimension considered and let $\bar{d} \in 1,\ldots,D$ . We can write

where $C{T}_{\bar{d}i,j}$ is the total number of contacts that individuals of age class i and belonging to subgroup $\bar{d}$ have with individuals in age class j , regardless of the subgroup to which the contacted individuals belong; and ${N}_{\bar{d}i}$ is the total number of individuals in age class i and subgroup $\bar{d}$ .

For example, to differentiate between employed and not-employed individuals, we compute two age contact matrices: C employed, i , j and C not-employed, i , j . All these matrices have been corrected for symmetrization as explained in Section 4.3.1 of SI. This framework can be extended to any number of dimensions considered simultaneously, in this case, the length of the $\bar{d}$ vector will correspond to the number of combinations of the levels of the dimensions considered. Note that the available data lack information on the subgroup membership of contacts, recording only the demographic details of survey respondents. Consequently, we opted to decouple the age contact matrices solely along the dimension of the respondent.

The epidemiological model

In order to investigate the effect of the decoupled contact matrices on the dynamic of infectious disease transmission, we propose a simple mathematical framework as an extension of the conventional age-structured SEIRD compartmental model 34 , 35 .

The conventional SEIRD model is defined as a population where individuals are assigned to five compartments based on their actual state: susceptible (S), exposed (E), infected (I), recovered (R) and dead (D). The model further defines the transition rates of individuals from one compartment to another by incorporating for each age class a given force of infection, which includes the average number of contacts with all the other age classes. The model proposed here extends this definition by taking into account not only the age structure of the contacts in the population but also their differences along a set of other dimensions $\bar{d}$ , such as education level, income level and employment situation.

The model can be described by a set of ordinary coupled differential equations as presented in Eq. ( 5 ):

Here i indicates the age group of the ego, j indicates the age group of the peer, $\bar{d}$ represents a vector of dimensions to which the ego belongs, β is the probability of transmission given a contact, ϵ is the rate at which individuals become infectious, μ is the recovery rate, IFR is the infection fatality rate, and ${C}_{\bar{d}}$ is the age contact matrix corresponding to dimensions $\bar{d}$ .

In this system of equations system, we rely on the concept of the force of infection, which is defined as

Further, we rely on the definition of the infection fatality rate (IFR i ), which is defined as the fraction of infected individuals that died. In order to account for the variability of contacts in our data, for each simulation that we run we use a static decoupled contact matrix that we compute from a bootstrapped sample of our data. See Section 7 of SI for the details on the implementation of the numerical simulations.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The MASZK survey data cannot be shared openly due to privacy regulations, but they may be available upon request to the corresponding author ([email protected]) after the signature of non-disclosure agreements with the data owner. A sample of data, including contact matrices stratified by age, has been published at https://github.com/adrianamanna/epi_social_inequalities . Data on the Oxford Stringency Index are available at: https://ourworldindata.org/metrics-explained-covid19-stringency-index . Data on the number of vaccinated individuals are available at: https://www.statista.com/statistics/1196109/hungary-number-of-people-vaccinated-against-covid-19/ . Data on the total number of deaths in Hungary during the 4th wave are available at: https://kimittud.hu/request/koronavirus_elhunytakra_es_gyogy?nocache=incoming-28514&fbclid=IwAR14PP0DyWIEzIix6mGwNkjHHJmyi8PZLl141vfXeRUzmghjjOqcCBuHx_M#incoming-28514 .

Code availability

We made available a simplified code to (i) derive the decoupled age contact matrix, and (ii) to simulate a S E I R model with these matrices together with their visualisation. The code and a sample data set are available at https://github.com/adrianamanna/epi_social_inequalities and https://zenodo.org/doi/10.5281/zenodo.10980134 57 .

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Acknowledgements

The authors gratefully thank Alessandro Vespignani, Jessica Davis, Eszter Bokányi, Alessia Melegaro and Filippo Trentini for useful discussions. A.M. and M.K. were supported by the Accelnet-Multinet NSF grant. J.K. and M.K. acknowledge funding from the National Laboratory for Health Security (RRF-2.3.1-21-2022-00006). M.K. acknowledges support from the ANR project DATAREDUX (ANR-19-CE46-0008); the SoBigData++ H2020-871042; the EMOMAP CIVICA projects.

Open access funding provided by HUN-REN Alfréd Rényi Institute of Mathematics.

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Adriana Manna & Márton Karsai

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Department of Social Research Methodology, Faculty of Social Sciences, Eötvös Loránd University, Pázmány Péter sétány 1/A, Budapest, 1117, Hungary

National Laboratory for Health Security, HUN-REN Rényi Institute of Mathematics, Reáltanoda utca 13-15, Budapest, 1053, Hungary

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A.M. performed the numerical simulations and data analysis. A.M., J.K. developed the statistical analysis. A.M., M.K. developed the epidemiological model. All authors wrote the first draft of the manuscript. All authors designed the study, interpreted the results, edited and approved the manuscript.

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Manna, A., Koltai, J. & Karsai, M. Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics. Nat Commun 15 , 4137 (2024). https://doi.org/10.1038/s41467-024-48332-y

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Allport’s Intergroup Contact Hypothesis: Its History and Influence

Key Takeaways:

Contact Hypothesis

1. Equal Status Between Groups

2. Common Goals

3. Intergroup Cooperation

4. The Support of Authorities, Law, or Custom

5. Positive Contact Norms

6. Personal Accountability

7. Empathy and Perspective-Taking

Why Does Contact Reduce Prejudice?

Examples of Contact Hypothesis

Contact Between Age Groups

Contact Between Religious Groups in Indonesia and the Philippines

Evaluating the Contact Hypothesis

Further Information

What Is the Contact Hypothesis in Psychology?

Key Takeaways: Contact Hypothesis

Historical Background

Allport’s Four Conditions

Evaluating the Contact Hypothesis

Why Does Contact Reduce Prejudice?

Limitations and New Research Directions

Can Contact Promote Allyship?

Sources and Additional Reading:

magazine issue 2 2013 / Issue 17

That human touch that means so much: Exploring the tactile dimension of social life

Intergroup Contact Theory: Past, Present, and Future

The Contact Hypothesis

How does it work?

Generalizing the effect

Theoretical Extensions

Issues and Directions for Future Research

Conclusions

From the editors

article author(s)

Jim A. C. Everett

article keywords

article glossary

Contact Hypothesis theory explained

What is the Contact Hypothesis?

The background to the contact hypothesis

Intergroup contact and prejudice, stereotypes and discrimination

Conditions for intergroup contact to reduce prejudice

Equal status

Common goals

Working together

Support from the authorities through legislation

Examples of the contact hypothesis

The contact hypothesis in the desegregation of education

The contact hypothesis in developing education strategies

Reducing prejudice

Other techniques and methods used to reduce prejudice are:

Implication of prejudice and discrimination in the workplace

The contact hypothesis in summary

Now it is your turn

More information

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