Longitudinal research refers to any study that collects the same sample of data from the same group of people at different points in time. While time-consuming and potentially costly in terms of resources and effort, a longitudinal study has enormous utility in understanding complex phenomena that might change as time passes.
In this article, we will explore the nature and importance of longitudinal studies to allow you to decide whether your research inquiry warrants a longitudinal inquiry or if a cross-sectional study is more appropriate.
To understand a longitudinal study, let's start with a simple survey as an example. Determining the popularity of a particular product or service at a specific point in time can simply be a matter of collecting and analyzing survey responses from a certain number of people within a population. The qualitative and quantitative data collected from these surveys can tell you what people think at the moment those surveys were conducted. This is what is known as a cross-sectional study.
Now imagine the product that you're trying to assess is seasonal like a brand of ice cream or hot chocolate. What's popular in summer may not be popular in winter, and trends come and go as competing products enter the market. In this context, the one survey that was conducted is merely a snapshot of a moving phenomenon at a single point in time.
In a longitudinal study design, that same survey will be distributed to the same group of people at different time intervals (e.g., twice a year or once a month) to allow researchers to see if there are any changes. Perhaps there is an ice cream that is as popular in the winter as it is in the summer, which may be worth identifying to expand profitability. A longitudinal study would thus be useful to explore this question.
Longitudinal research isn't conducted simply for the sake of being able to say research was conducted over a extended period of time. A longitudinal analysis collects data at different points in time to observe changes in the characteristics of the object of inquiry. Ultimately, collecting data for a longitudinal study can help identify cause-and-effect relationships that cannot otherwise be perceived in discrete or cross-sectional studies.
Longitudinal studies are found in many research fields where time is an important factor. Let's look at examples in three different research areas.
Classroom research is often longitudinal because of the acknowledgment that successful learning takes place over time and not merely in a single class session. Such studies take place over several classes, perhaps over a semester or an entire academic year. A researcher might observe the same group of students as they progress academically or, conversely, identify any significant decline in learning outcomes to determine how changes in teaching and learning over time might affect student development.
Medical research often relies on longitudinal studies to determine the effectiveness and risk factors involved with drugs, treatments, or other medical remedies. Consider a dietary supplement that is purported to help people lose weight. Perhaps, in the beginning, people who take this supplement actually do lose weight. But what happens later on? Do they keep the weight off, gain it back or, even worse, gain even more weight in the long term? A longitudinal study can help researchers determine if that supplement produces sustainable results or is merely a quick fix that has negative side effects later on.
Product life cycles and market trends can take extended periods of time to manifest. In the meantime, competing products might enter the market and consequently affect customer loyalty and product image. If a cross-sectional study captures a snapshot of opinions in the marketplace, then think of a longitudinal study as several snapshots spread out over time to allow researchers to observe changes in market behavior and their underlying causes as time passes.
Cross-sectional studies are discrete studies that capture data within a particular context at a particular point in time. These kinds of studies are more appropriate for research inquiries that don't examine some form of development or evolution, such as concepts or phenomena that are generally static or unchanging over extended periods of time.
To determine which type of study would be more appropriate for your research inquiry, it's important to identify the object of inquiry that is being studied. Ask yourself the following questions when planning your study:
If you said yes to all of these questions, a longitudinal study would be suited to addressing your research questions. Otherwise, cross-sectional studies may be more appropriate for your research.
A longitudinal study can provide many benefits potentially relevant to the research question you are looking to address. Here are three different advantages you might consider.
In many cases, research rigor is served by collecting abundant data. Research approaches like thematic analysis and content analysis benefit from a large set of data that helps you identify the most frequently occurring phenomena within a research context. Large data sets collected through longitudinal studies can be useful for separating abundance from anecdotes.
Analyzing patterns often implies exploring how things interact sequentially or over time, which is best captured with longitudinal data. Think about, for example, how sports competitions and political elections take place over a year or even multiple years. Construction of ships and buildings can be a long and protracted process. Doctoral students can spend four or more years before earning their degree. A simple cross-sectional study in such contexts may not gather sufficient data captured over a period of time long enough to observe sequences of related events.
Certain relationships between different phenomena can only be observed longitudinally. The famous marshmallow test that asserted connections between behaviors in childhood and later life outcomes spawned decades of longitudinal study. Even if your research is much simpler, your research question might involve the observation of distant but related phenomena that only a longitudinal study can capture.
There are two types of longitudinal studies to choose from, primarily depending on what you are looking to examine. Keep in mind that longitudinal study design, no matter what type of study you might pursue, is a matter of sustaining a research inquiry over time to capture the necessary data. It's important that your decision-making process is both transparent and intentional for the sake of research rigor.
A cohort study examines a group of people that share a common trait. This trait could be a similar age group, a common level of education, or a shared experience.
An example of a cohort study is one that looks to identify factors related to successful aging found in lifestyles among people of middle age. Such a study could observe a group of people, all of whom are similar in age, to identify a common range of lifestyles and activities that are applicable for others of the same age group.
The difference between a cohort study and a panel study is that panel studies collect data from within a general population, rather than a specific set of particular individuals with a common characteristic. The goal of a panel study is to examine a representative sample of a larger population rather than a specific subset of people.
A longitudinal survey that adopts a panel study model, for example, would randomly sample a population and send out questionnaires to the same sample of people over time. Such a survey could look at changes in everyday habits regarding spending or work-life balance and how they might be influenced by environmental or economic shifts from one period of time to the next.
Planning a prospective or future research study that is longitudinal requires careful attention to detail prior to conducting the study. By itself, a longitudinal study can be considered a repeated sequence of the same discrete study across different periods of time.
However, ensuring that multiple iterations of the same study are conducted repeatedly and rigorously is the challenge in longitudinal studies. With that in mind, let's look at some of the different research methods that might be employed in longitudinal research.
Action research and ethnographies rely on longitudinal observations to provide sufficient depth to the cultural practices and interactions that are under study. In anthropological and sociological research, some phenomena are so complex or dynamic that they can only be observed longitudinally.
Organizational research, for example, employs longitudinal research to identify how people in the workplace or other similar settings interact with each other. This kind of research is useful for understanding how rapport is established and whether productivity increases as a result.
A longitudinal survey can address research questions that deal with opinions and perspectives that may change over time. Unlike a cross-sectional survey from a particular point in time, longitudinal surveys are administered repeatedly to the same group of people to collect data on changes or developments.
A personal wellness study, for example, might examine how healthy habits (or the lack thereof) affect health by asking respondents questions about their daily routine. By comparing their routines over time with information such as blood pressure, weight, and waist size, survey data on lifestyle routines can allow researchers to identify what habits can cause the greatest improvement in individual health.
Various experimental studies, especially in medical research, can be longitudinal in nature. A longitudinal experiment usually collects data from a control group and an experimental group to observe the effects of a certain treatment on the same participants over a period of time.
This type of research is commonly employed to examine the effects of medical treatments on outcomes such as cardiovascular disease or diabetes. The requirements for governmental approval are incredibly stringent and call for rigorous data collection that establishes causality.
Needless to say, longitudinal studies tend to be time-consuming. The most obvious drawback of longitudinal studies is that they take up a significant portion of researchers' time and effort.
However, there are other disadvantages of longitudinal studies, particularly the likelihood of participant attrition. In other words, the more lengthy the study, the more likely it is that participants may drop out of the study. This is especially true when working with vulnerable or marginalized populations such as migrant workers or homeless people, populations that may not always be easy to contact for collecting data.
Over the course of time, the research context that a researcher studies may change with the appearance of new technologies, trends, or other developments that may not have been anticipated. While confounding influences are possible in any study, they are likely to be more abundant in studies on a longitudinal scale. As a result, it's important for the researcher to try to account for these influences when analyzing the data. It could even be worthwhile to examine how the appearance of that phenomenon or concept impacted a relevant outcome of interest in your area.