Observational studies can assist statisticians, scientists, psychologists, business market analysts, and other professionals to gain knowledge on natural behaviors or phenomena.
While conducting research, one has to ensure that the right study design has been undertaken because the results have to be valid and relevant. But first, exactly what is an observational study?
In this article, we will aim at defining observational studies, provide some examples, differentiate between types and briefly discuss some key differences between observational and experimental studies, pros and cons, and real-life use cases.
What’s An Observational Study? Definition and Purpose
Observational research is a kind of research design whereby the researchers simply observe events and variables as they occur and what participants do, minimally or not at all. On the other hand, in observational study, the investigator does not interfere but only ‘‘observes’’ and evaluates the degree of association between an exposure and disease variable.
This is different from an experimental study that has the researchers controlling the exposure of the treatment, intervention, etc
These studies are normally preferred in disciplines such as epidemiology, social science, and public health to find out mere coincidences and tendencies of the variables in consideration rather than causal. Observational studies prove most helpful in conditions where it is impossible, or it becomes ethically wrong, to conduct experiments.
Types of Observational Studies
Observational studies can be categorized into several types, each with its own unique characteristics and applications:
1. Case Control Observational Study
In case control studies, researchers select people with an existing health problem, at least one condition ‘case’, and other similar persons without the problem, referred to as ‘control’. This kind of research is useful to develop a hypothesis if such has to be investigated.
This kind of study is useful to develop a hypothesis that can be used for further research.
For example, analyzing lung cancer patients (cases) against non-lung-cancer patients (controls) to establish past history of exposure to smoking.
2. Longitudinal Observational Study
They focus on the same population for a long- time; hence, they are able to make comparisons and identify evolutions. Some of these can be short, such as observing the participants several times during one hour. These time intervals could also have larger intervals; for instance, the time spans could be measured in terms of months or years.
For instance, scientists may employ longitudinal studies to monitor physical growth of babies and children.
3. Cohort Observational Study
This type of observational study is commonly applied for the purpose of explaining cause-and-effect relationships. A cohort observational study examines causes, frequency and outcome, for instance. It is a means of grouping or categorizing people in certain respects; for instance, a birth cohort would refer to individuals who were born during a certain time. Subjects are assigned to groups through exposure and incidence of outcomes are compared in the cohort. Investigators can make use of what happens to the members of the cohort that has been exposed to some variable to determine what happens to the members of the same group that has not been exposed.
For instance, the use of a group of smokers and a group of non-smokers to assess frequency of lung cancer within a decade.
4. Cross Sectional Observational Study
While cross sectional observational study does not necessarily aim at relationships between causes and effects or vice versa, they do examine prevalence issues. Here, you would focus on information about a specific group at a single time. They would just describe the characteristics of something that is in the population, which they have no control over by changing it. This type of study is helpful to generate a hypothesis that can then be researched.
For instance, a scientist conducting a cross-sectional study can examine how often members of a specific demographic, for example, an age bracket, develop a certain illness.
5. Naturalistic observation
Naturalistic observation is where the behavior of humans or animals is observed by researchers in the environment where the behavior occurs. Thus, naturalistic observation is a kind of field study in which data is gathered outside a laboratory or clinical environment.
In naturalistic observation, the researchers want the participants to not notice that they are being observed so that they can behave naturally. A large number of zoologists, or specialists in the behaviors of animals, adopt a naturalistic approach to their work.
6. Participant observation
Particularly, participant observation is the observation of behaviors in their natural context, similar to naturalistic observation. However, while using participant observation, researchers assume an active role in the course of conducting the study. Participant observation is selected by researchers when data of a given type can only be obtained by becoming or assuming parts of the natural setting. For instance, when a scientist is researching behaviors in a rehabilitation facility, they would let themselves be admitted in the facility as patients.
What Are Examples Of Observational Studies?
Observational studies can be of many types and relate to a number of fields and factors. A researcher conducting observational studies might observe one or more factors related to:
- Wildlife and their habitat
- Consumption of products and services provided by a particular company
- Natural disasters: tornadoes, hurricanes or tsunamis.
- Humans using technology
- Actions and conduct of individuals in a given environment, for instance, a cafeteria or a church.
- A specific disease, for instance, cancer, that possibly has afflicted a human being
- Extraterrestrial objects, e.g. stars, planets and other celestial bodies
- People who are grouped, for instance, by their gender or nationality
Pros of Observational Study Design
1. Cost-effective
As compared to experimental study, observational study is less costly. They are not as complex as other measures that involve establishment of controlled environments or interventions that can be expensive.
They do not entail establishment of controlled environments or interventions, which may be expensive to mount. They can often work with the data that is already available or gather the data without having to interfere with any individual in the process.
This cost-effectiveness enables researchers to recruit more participants into the study besides having longer study periods, hence improving the overall validity of the study. They also make research cheaper to institutions with limited funding, thus equalizing research.
2. Real-world insights
In observational research, variables are recorded in their natural setting, and this makes the research data realistic. This approach is particularly useful in such areas as ecology, sociology, and epidemiology, where the interactions are real. It enables researchers to observe phenomena that were not initially of interest and develop hypotheses on the basis of such observations; it also provides high external validity of results. Although the source provides a lot of information that can be useful for researchers, they need to be careful with confounding factors since the conditions are not controlled.
3. Long-term observations
These studies have the best capabilities of tracking long-term trends and impacts. They can observe subjects or phenomena with a high degree of continuity for extended periods—sometimes for tens of years. Thus capture changes and results that short-term experiments might overlook, which is useful in such fields as epidemiology or environmental sciences. It means that long-term observations can give a better insight into slow processes and consequences that may occur after some time.
4. Large sample sizes
Also, observational studies usually allow for a significantly larger number of subjects than experimental studies do. This leads to a larger sample size, which raises statistical power and increases the credibility and external validity of the results. Larger samples are more likely to be accurate and provide less sampling error as compared to samples with a smaller number of people. It also permits for additional explanations, such as comparability of subgroups or identification of outstanding instances or minute outcomes that could be overlooked in less large-scale investigations.
Limitations of Observational Studies
1. Lack of control
The goal of observational research is to look at the variables, but it cannot control any of them and has no control environment. This lack of control is dangerous because it makes it almost impossible to have a control group, compare it to other groups and thus have an easy way of separating the effects of specific factors. These statistical approaches are used to control confounding factors and though they may not be infallible, researchers and analysts are forced to use them.
2. Confounding variables
The problem of confounding factors is most acute with observational studies where extraneous factors that are related to both the independent and dependent variables exist. They can be challenging to discern and manage, particularly with large-scale, diverse research studies. Despite the fact that statistical techniques can be used to deal with measured confounding factors, there can be other confounding factors which are unknown or unmeasured, which can influence the results and lead to the drawing of the wrong conclusions.
3. Correlation vs. causation
However, observational studies possess some of the most important drawbacks, one of which is the inability to prove causality conclusively. These studies can describe correlations between variables but do not allow to conclude that one variable causes another one. This limitation may result in wrong conclusions, especially when the findings are being presented in media or to the public. It is therefore imperative that researchers do not over interpret their findings and ensure they explain to the audience that the results are correlational.
4. Selection bias
There is always a tendency of bias in the selection of participants or the ability of the participants to select themselves in observational studies. This type of sampling can lead to a sample that is not really representative of the population under study. For instance, people participating in a health survey may be healthier than the average population, thus giving a biased outcome.
Also, some population types might not be included or could be underrepresented in a study, which might reduce the external validity of the conclusions. Selection bias is a major concern in all research and therefore, researchers need to be very cautious and avoid or minimize this bias in their studies.
A comparison between observational studies and experimental studies
Another type of scientific works is experimental works. Here are the similarities and differences between observational studies and experimental studies:
1. Influencing results
These are studies that are done in a controlled manner with the view of influencing the results that are obtained in scientific research. In experimental research, scientists manipulate factors and processes in order to study the impact of their actions. For example, in medical research, experimental designs are applied to ascertain the effectiveness of new therapy to patients with a certain illness. One group of participants is given the treatment, while the other is given a placebo or fake treatment.
The study then evaluates whether there is a statistically significant difference between the treatment and control group in the management of the medical condition.
2. Finding participants
In observational and experimental research, the researchers employ random sampling techniques to identify participants. These methods entail making a choice of a sub-sample of a population in such a way that the sub-sample represents the whole. For example, researchers may employ random sampling in an attempt to investigate particular behaviors in children.
3. Costs
The observational research studies are usually cheaper than the experimental ones. More controls or manipulations lead to more expenses. Observational studies can be conducted over a longer period of time since they are cheaper to conduct. Annual data collection is less burdensome to scientists than repeating an experiment annually is to the participants.
Conclusion
It is therefore important for anyone involved in research, particularly in areas where experimental research may not be possible, to understand what an observational study is. Observational research is an effective method of studying events and processes in their natural context. This article aims to familiarize the reader with what an observational study is so that observational studies can be carried out in a way that enables valuable insights into actual reality to be gained.
