Longitudinal Study: Approaches and Definition

A longitudinal study is a kind of observational research in which variables are examined over a long period. This research can take a few months or even decades to complete. Researchers make multiple observations on the same group of participants over a long period.

Longitudinal studies, unlike cross-sectional studies, endure longer than a given moment of time, allowing researchers to identify cause and effect links between variables. Many scientific studies, such as medical research, are longitudinal, meaning that researchers keep track of the same participants over time.

What is the duration of a longitudinal study?

A longitudinal study has the advantage of allowing researchers to detect changes in a specific population at both the collective and individual levels. The important thing to remember is that longitudinal studies go beyond a particular point in time. As a result, they can develop recurring patterns.

It can take anywhere from two or three weeks to years, if not decades, to finish research. When a systematic study lasts for a long time, the researcher is most likely conducting longitudinal research of the sample group. It takes longer to finish longitudinal research.

Cross-sectional vs longitudinal studies

Longitudinal studies, as previously said, monitor changes over time. Cross-sectional studies, on the other hand, capture a 'snapshot' of how a particular population (or a subgroup) behaves at a certain point in time. Cross-sectional research collects data at a single point in time, whereas longitudinal research collects data over a longer period of time.

In contrast to longitudinal studies, where study variables can evolve over time, a cross-sectional study looks at a single event with all variables remaining constant. A longitudinal study may be used to give an update on a cross-sectional study and dig further into the correlation between the variables. Here are some main differences between the two types of research:

• Time-frame.
  It takes longer to finish longitudinal research. Academics can spend years recording relationships between different variables in some circumstances. This is not the case in cross-sectional investigations. Instead, the scientist gathers data in a brief period of time and draws appropriate conclusions from it. While cross-sectional research provides a picture of the study environment, longitudinal studies are more suited to situations in which you need to analyze a problem over time.
• Sample Information.
  Longitudinal studies follow the same sample group through time, whereas cross-sectional studies use multiple study samples.
• Funds.
  Longitudinal studies are more expensive than cross-sectional studies since they cover a longer period of time.

How to conduct a longitudinal research

Before doing a longitudinal study, a researcher needs to understand where the information will come from. You can use secondary sources, which have previously been recorded by someone else if you like. If the sources are reliable, such as official data, you will be fine. If you opt to acquire your own data, it will be primary information collected from your own study. You can conduct either a retrospective or prospective longitudinal study.

Longitudinal retrospective studies

This type of research gathers information on past events. For instance, you may look at the educational achievement of girls between 1970 and 2010.

Longitudinal prospective studies

These studies gather information on a specific population and monitor it in real-time to follow events or factors that occur throughout the study period. For example, you could decide to study the development of a local immigrant community every year for the following couple of years.

Longitudinal study: pros and cons

Longitudinal studies, like any other way of conducting research, have some drawbacks and benefits. When preparing to adopt this methodology, keep the following in mind:

Pros✔️
✔️ It offers good reliability levels. For a long-term study to be effective, rules and regulations must be set from the start, dictating the direction that researchers must take. The research's ultimate objective must also be stated from the initial stage, with outlined measures in place to ensure that the data being collected is accurate. Example You are researching the weight-loss effects of daily exercise. If you asked your participants to recall how many minutes a day they exercised at any point in the past, they might struggle. These characteristics can be tracked in real-time in longitudinal research, allowing for high validity levels.
✔️ It is highly effective in researching developmental patterns. As previously indicated, these studies are usually applied in psychology to investigate developmental patterns across life lengths. This is because longitudinal studies follow the same people throughout time, making the variations found in a group less likely to be the consequence of a shift or difference in culture between generations. Example You decide to investigate the effects of a specific fitness program on physical performance. Natural talent's impact on performance should be minimized if you choose a longitudinal study because it will not vary over time.
✔️ Accurate information. Because longitudinal research allows scientists to study participants in real-time, the information gathered is accurate. This provides the study with promising and valid outcomes. Example A cross-sectional study on the relationship between physical starvation and binge eating might find that eating less is associated with a lower risk of binge eating and wrongly conclude that binge eating stimulates physical starvation when it is the other way around. However, a longitudinal study would be able to conclude that food restriction naturally leads to binging and emotional overeating.
Cons❌
❌ Unpredictable outcomes. Because the researchers intend to study the same participants throughout time, dropout rates are likely to be high, making the previously gathered data irrelevant. Example Participants in your study on the relationship between food deprivation and binge eating cycles who are not seeing much progress may become frustrated and hence drop out, making the gathered data less relevant.
❌ Longitudinal research is time-consuming and expensive. It necessitates a significant amount of time and effort on the side of the researcher. Example Because the negative impacts of poor mental health accumulate over decades, you must wait several years to observe any findings in the study investigating the relationship between loneliness, depression, and mortality among elders.