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Imagine a team of researchers who want to find out if an increase in flu cases eight years ago was due to age or a specific event and what effect those cases had on the current population. They cannot do an experiment where a variable is manipulated because the event has already happened. Instead, they want to observe the information that has already occurred, describe it, and make inferences about the data. They can essentially take a point in time and analyse the information collected then and make observations based on that data.
In our example, public health records would have observed increasing flu cases and affecting the age group. Researchers can infer what happened and conclude that age group. They can then also see if the result of that increase affected that group years later and if that result correlates with anything. This is cross-sectional research.
Cross-sectional research in psychology is a non-experimental, observational research design. It is usually used to describe, for example, the characteristics of a population or subgroup of people at a particular point in time. Or for descriptive purposes. Cross-sectional research is not usually a method used when the researcher wants to draw analytical or causal conclusions from the research.
Researching the past, Flaticon
Cross-sectional research is a type of research often used in psychology.
Cross-sectional research is a study that measures the relationship between variables by collecting data at a specific point in time in the target population. A typical cross-sectional study examines individuals who have or have not been exposed to a factor. The research seeks to determine the differences between those who have been exposed to a factor and those who have not.
There is a lot of cross-sectional research being done regarding disease and public health.
In psychology, cross-sectional research is usually conducted to:
The target population is the subgroup of people to whom the research findings are to be generalised.
Characteristics of a person, Flaticon
When conducting cross-sectional studies, the participants usually:
It is important to note that the cross-sectional study is a non-experimental research method. It relies on observations. Rather than manipulating variables, experimenters observe naturally occurring phenomena.There are three types of cross-sectional studies used in research.
Descriptive cross-sectional research is a type of research designed to measure characteristics or describe disease prevalence in the target population.
An example of a descriptive cross-sectional study is a study examining the prevalence of developmental disabilities in boys in the UK.
In analytical cross-sectional research, researchers examine whether there is a relationship between two factors at a given time within the target population.
An example of an analytic cross-sectional study is an investigation of the side effects of interventions in men at various stages of cancer, and have been receiving cancer treatment for three months.
Serial cross-sectional research is when multiple cross-sectional studies are conducted on different populations/participants at different time points. Each time data are collected, different participants are included in the study.
The fact that different participants are used each time is important. If the same participants are used, it is a longitudinal study and not a cross-sectional study.
An example of a serial cross-sectional study is measuring the prevalence rate of mental illness at different time points.
This research is useful because it reveals there may be an increase in risk factors in today’s society that increase the incidence of mental illness or that awareness of mental health has now increased. Researchers can determine this trend exists using cross-sectional studies, but they cannot conclude the cause.
Let’s discuss the cross-sectional research advantages and disadvantages.
The cross-sectional research advantages are:
The nature of cross-sectional studies allows researchers to compare different populations or factors at a given point in time.
This is beneficial because it allows researchers to identify naturally occurring differences/similarities and relationships between variables and subgroups of people.
Cross-sectional studies can be conducted relatively quickly.
Cross-sectional research is a relatively inexpensive research method.
Cross-sectional studies are often used as a preliminary part of an investigation to determine what should be studied later. Follow-up studies may include longitudinal studies or other experimental designs. The purpose is to determine what direction future empirical research might take.
Cross-sectional research has many practical applications in psychology. For example, it can be used to estimate the prevalence of certain mental illnesses. This is important because it raises the awareness of public health services that changes, such as the support offered, need to be improved.
Huang et al. (2019) found that prevalence rates of mental illness in China increased in 2013 compared with 1982.
The disadvantages of cross-sectional research are:
Cross-sectional research is not conducted in a controlled setting with a standardised procedure (due to the nature of the experimental research method). Therefore, it is difficult for researchers to prevent confounding variables from influencing the factors studied. This reduces the validity of the study.
Because of the cross-sectional research design, researchers cannot draw causal conclusions. Researchers cannot infer cause and effect from this research design because it does not consider how changes over time affect the data (it focuses on the present).
According to Wang and Cheng (2020), cross-sectional research requires a large, heterogeneous sample. This increases the risk of sampling bias. If the sample does not meet these requirements, it is unlikely that the results will be generalisable. According to the researchers, sample bias can occur in clinical research when a larger number of individuals come from backgrounds that are more susceptible to developing the disease.
The period and population the researchers selected for the study may not be truly representative.
The following research scenarios show cross-sectional research study examples that can be conducted in psychology.
Clinical psychology, e.g., research examining the prevalence of diabetes in the South Asian community.Developmental psychology, e.g., research to investigate the prevalence of symptoms listed in the DSM-5 (the manual used by clinicians to diagnose people with mental illness) in children diagnosed with autism spectrum disorder in the UK.Social psychology, e.g., investigating factors that may contribute to educational failure in school children.
The purpose of typically using cross-sectional research designs in psychology is to: measure the current prevalence rates of mental illnesses in specific populations describe characteristics of the target population.
Examples of cross-sectional research that may be used in different domains of psychology are:
Serial cross-sectional research collects cross-sectional data at several different time points. In this research method, each time data is collected from different participants. In longitudinal research, data is collected at different time points from the same participants.
Cross-sectional research is a study that measures the relationship between variables by collecting data at a given time in the target population.
Cross-sectional research in research methods is a non-experimental, observational research design. It is usually used to describe things such as the characteristics of a population or a sub-group of people or for descriptive purposes. Cross-sectional research is not typically a method used when the researcher aims to provide analytical or causal inferences from the research.
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