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Sequential designs are developmental research designs that include elements of both cross-sectional and longitudinal studies; they are configured in ways to address confounds between age, cohort, and time of measurement. Sequential designs were developed in response to concerns that researchers had regarding conventional cross-sectional and longitudinal developmental designs. Although they originated in the developmental study of aging, sequential designs can be used across developmental periods in life-span human development research. This entry begins by discussing the challenges to developmental research inherent in the conventional cross-sectional and longitudinal designs. Next, the entry explores the way in which sequential designs are conceptualized. Finally, the entry describes the three sequential designs: cross sequential, time sequential, and cohort sequential. One of the problems inherent in developmental ...
 Study design depends greatly on the nature of the research question. In other words, knowing what kind of information the study should collect is a first step in determining how the study will be carried out (also known as the methodology). Let’s say we want to investigate the relationship between daily walking and cholesterol levels in the body. One of the first things we’d have to determine is the type of study that will tell us the most about that relationship. Do we want to compare cholesterol levels among different populations of walkers and non-walkers at the same point in time? Or, do we want to measure cholesterol levels in a single population of daily walkers over an extended period of time? The first approach is typical of a cross-sectional study. The second requires a longitudinal study. To make our choice, we need to know more about the benefits and purpose of each study type. Cross-sectional studyBoth the cross-sectional and the longitudinal studies are observational studies. This means that researchers record information about their subjects without manipulating the study environment. In our study, we would simply measure the cholesterol levels of daily walkers and non-walkers along with any other characteristics that might be of interest to us. We would not influence non-walkers to take up that activity, or advise daily walkers to modify their behaviour. In short, we’d try not to interfere. The defining feature of a cross-sectional study is that it can compare different population groups at a single point in time. Think of it in terms of taking a snapshot. Findings are drawn from whatever fits into the frame. To return to our example, we might choose to measure cholesterol levels in daily walkers across two age groups, over 40 and under 40, and compare these to cholesterol levels among non-walkers in the same age groups. We might even create subgroups for gender. However, we would not consider past or future cholesterol levels, for these would fall outside the frame. We would look only at cholesterol levels at one point in time. The benefit of a cross-sectional study design is that it allows researchers to compare many different variables at the same time. We could, for example, look at age, gender, income and educational level in relation to walking and cholesterol levels, with little or no additional cost. However, cross-sectional studies may not provide definite information about cause-and-effect relationships. This is because such studies offer a snapshot of a single moment in time; they do not consider what happens before or after the snapshot is taken. Therefore, we can’t know for sure if our daily walkers had low cholesterol levels before taking up their exercise regimes, or if the behaviour of daily walking helped to reduce cholesterol levels that previously were high. Longitudinal studyA longitudinal study, like a cross-sectional one, is observational. So, once again, researchers do not interfere with their subjects. However, in a longitudinal study, researchers conduct several observations of the same subjects over a period of time, sometimes lasting many years. The benefit of a longitudinal study is that researchers are able to detect developments or changes in the characteristics of the target population at both the group and the individual level. The key here is that longitudinal studies extend beyond a single moment in time. As a result, they can establish sequences of events. To return to our example, we might choose to look at the change in cholesterol levels among women over 40 who walk daily for a period of 20 years. The longitudinal study design would account for cholesterol levels at the onset of a walking regime and as the walking behaviour continued over time. Therefore, a longitudinal study is more likely to suggest cause-and-effect relationships than a cross-sectional study by virtue of its scope. In general, the research should drive the design. But sometimes, the progression of the research helps determine which design is most appropriate. Cross-sectional studies can be done more quickly than longitudinal studies. That’s why researchers might start with a cross-sectional study to first establish whether there are links or associations between certain variables. Then they would set up a longitudinal study to study cause and effect. Source: At Work, Issue 81, Summer 2015: Institute for Work & Health, Toronto This column updates a previous column describing the same term, originally published in 2009.
Cross-sectional study is defined as an observational study where data is collected as a whole to study a population at a single point in time to examine the relationship between variables of interest. Longitudinal study, like the cross-sectional study, is also an observational study, in which data is gathered from the same sample repeatedly over an extended period of time. Longitudinal study can last from a few years to even decades depending on what kind of information needs to be obtained. Cross-sectional and longitudinal study both are types of observational study, where the participants are observed in their natural environment. There are no alteration or changes in the environment in which the participants exist. Despite this marked similarity, there are distinctive differences between both these forms of study. Let us analyze the differences between cross-sectional study and longitudinal study.
ConclusionIt is true, study design greatly depends on the nature of research questions. Whenever a researcher decides to collect data by deploying surveys to his/her participants, what matters the most are the survey questions that are placed tactfully, so as to gather meaningful insights. In other words, to know what kind of information a study should be able to collect is the first step in determining how to carry out the rest of the study. What steps need to be included and what can be given a pass. Continuing from the example above, a researcher wants to establish a relation between the variables, “jogging” and “cholesterol” in this case, one of the first things that a researcher would need to establish in this kind of study is, to tell the most about the relationship. A few questions to ask would be, whether to compare cholesterol levels among different populations of joggers, non-joggers at the same point in time? Or to measure cholesterol levels in a single population of daily joggers over an extended period of time? The first approach typically requires a cross-sectional study and the second approach requires a longitudinal study. |
What research method includes elements of both longitudinal and cross-sectional research designs?
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