Definition/How it is conducted: A longitudinal study is where participants are observed on multiple occasions, spanning over longer periods of time – it could be months or even years of this repeated testing. With every repeated observation, the same variables are measured to see how they may change as a result of time passing.
Purpose/Benefits: Longitudinal studies are often used to measure development throughout the lifespan, however they can also focus on the progression of certain illnesses or addictions to understand the effectiveness of certain treatments.
Example: Researchers are interested in seeing how alcohol use changes over the lifespan. They may use a longitudinal method where participants are asked questions regarding their alcohol consumption over a long period of time. For example, they may ask participants “How often do you drink alcohol?” once a year over a span of twenty years. This will allow them to collect data throughout one’s life to see how alcohol usage increases or decreases with age.
Benefits/Limitations: Longitudinal studies allow researchers to examine how certain effects on participants change over time. However, longitudinal studies have a larger time commitment needed of researchers and participants than other types of research. Because of this, longitudinal studies may have frequent attrition. Also, due to these repeated measures, longitudinal studies are usually more costly than other methods of research.
Cross Sectional Study
Definition/How it is conducted: Cross-sectional studies measure many participants, from many different age groups, at one-time interval to compare the differences between the demographics.
Purpose/Benefits: Cross-sectional studies help researchers compare differences between certain age groups very quickly. This method is also cheaper than longitudinal studies.
Example: Researchers want to see how cigarette usage changes depending on age. At one time point, they can ask thousands of participants across a range of ages about how often they smoke cigarettes. This will allow them to see the different smoking patterns associated with different age groups.
Benefits/Limitations: As many participants from varying demographics are measured within a short period of time, this allows cross-sectional research to be completed quite quickly. Additionally, because of its shorter time period, cross-sectional designs are usually more cost-efficient than longitudinal designs. However, a limitation of cross-sectional designs is known as a cohort effect. This may harm cross-sectional research as a difference that is assumed to be due to lifespan development may be actually due to those differences in living associated with different groups.
When a participant leaves the study before the experiment ends. This is commonly the case in lengthy types of research, such as longitudinal studies, because of the large time commitment associated with them.
Statistical data of the population. This commonly includes age, income, and education level.
The differences in groups of certain participants that are not present within other groups. For instance, an older age group may have lived through wartime whereas a younger age group would have not experienced this.
A condition or characteristic that can be changed or measured. Examples may include the presence/absence of a certain treatment, the decrease of a participant’s number of relapses, or the participant’s heart rate.