One common method used to study the effects of culture on behaviour is the correlational study. This method involves measuring the strength of a relationship between two or more co-variables. In correlational studies on the effects of culture on behaviour, one variable is related to culture (e.g. cultural dimensions) and the other is related to behaviour (e.g. conformity, mate preference or helping others). The results might show a positive correlation (which means as one variable increases, so does the other) or a negative correlation (as one variable increases, the other decreases).
Unlike experimental studies that investigate the effects of an independent variable on a dependent variable, a correlational study doesn’t have IVs and DVs because we don’t know the direction of the relationship. There are also not enough controls put in place, so effects of extraneous variables aren’t controlled and may be influencing the relationship. This is a major limitation that will be explained later.
How are correlational studies conducted?
Correlational studies on culture and behaviour must first gather data on the co-variables in the study. In psychological studies one co-variable is nearly always a measure of behaviour or cognitive process. Cultural factors studied in correlational studies are often related to cultural dimensions. For example, a culture’s score on the individualism/collectivism scale could be a co-variable. Questionnaires are commonly used to gather the data needed to calculate the correlation.
Why are correlational studies conducted?
One major reason correlation studies are conducted is because they allow researchers to study variables that are naturally occuring in large populations. However, unlike natural or quasi-experiments, there is no identifiable “treatment” because either there are too many possible extraneous variables and/or the variable is an innate personal quality (like cultural background) and so this isn’t considered an independent variable. We can also conduct correlational studies to see if a relationship does exist, and from these findings experimental studies can then be designed to explore the relationship further.
What are some examples?
- Evolution and culture in mate preferenceBuss (1989): This study gathered data over 10,000 participants in order to study cross-cultural similarities and differences in mate preference across cultures. The results showed that there was a correlation between cultural values (individualism/collectivism) and mate preference. For example, males from collectivist cultures placed a higher preference on domestic skills and chastity, whereas females from collectivist cultures placed more emphasis on social status and ambition. (Read more here).
- The importance of love in marriage – Levine et al. (1995): This study found correlations between 11 different cultures and the importance placed on love in a marriage. When asked if they would marry someone who had everything they desired, participants from the collectivist cultures of India, Pakistan and Thailand were more likely to say yes, even if they were not in love with that person (when compared to people from the USA, UK and Australia. The results also showed a positive correlation between cultures that placed more emphasis on love (individualistic cultures) and divorce rates.
- Helping others – Levine et al. (2001): This study gathered data from 23 cities around the world. One co-variable was the rate of helping, which was measured by things like how many people would help a blind person cross the street, post a dropped envelope or pick up someone’s dropped pen. Other co-variables were GPD (gross domestic product – a measure of a country’s wealth), life pace (measured by how fast people walk) and individualism/collectivism. The results showed a strong negative correlation between GDP and helping others, as well as a negative correlation between life pace and help. There was a correlation between individualism/collectivism and helping (i.e. collectivist cultures were more likely to help), but this correlation was weak. This is a good example of the benefits of using a correlational method because the strength of relationships between variables can be compared.
What are the limitations?
- Correlation does not mean causation: this is the fundamental limitation of using correlational studies. Just because two variables are related, it doesn’t mean that one is causing the other. For example, we might want to conclude that having lots of wealth (high GDP) causes people to not want to help others as they become greedy and selfish. But could it be that not helping others was what caused their wealth? When we’re not sure which direction the relationship is working as in this example, we call this bidirectional ambiguity.
- Too many extraneous variables: another way to explain limitations of correlational studies is to not only show how A could influence B, but also how B could influence A (i.e. explain bidirectional ambiguity), but also how C could be influencing A or B. For example, in studies comparing individualistic and collectivist cultures like Levine’s on the importance of love, we could conclude that variable A (cultural values of ind/coll) is affecting B (how important love is), but could religious beliefs (variable C) be a factor? USA, UK and Australia are Western, predominantly Christian countries, compared with Muslim, Hindu and Buddhism for Pakistan, India and Thailand, respectively.
Exam Tip: Technically speaking, the IB could ask about the use of research methods on “cultural origins of behaviour and cognition” or “cultural influences on individual attitudes, identity and behaviours.” My advice is to keep it simple and make sure you can explain how correlational studies are used to study the effects of culture on behaviour.