Observational Vs. Experimental Studies: Differences, Similarities & Uses

Observational and experimental clinical studies significantly contribute to the advancement of medical knowledge. The vital insights researchers gain enable scientists to develop effective new treatments and therapies that can save lives, and improve patient care.

However, these two types of studies are very different in terms of their design, their purpose, and the insights they provide. We examine them in-depth to discover more about the intricacies of these important scientific approaches, and outline how you can get involved.

What is an observational study?

During an observational study, researchers observe a sample group of people and collect data from them, without interfering in any way. Instead, they allow the natural course of events to unfold while extracting relevant information.

This type of study is frequently used to determine the potential risks and benefits of a treatment or intervention.

The different types of observational studies

There are three main types of observational studies, namely cohort studies, case-control studies, and cross-sectional studies.

Cohort studies

Cohort studies assess a group of people over a certain period of time, and are often used to study the effects of a behavior or treatment on the group as a whole.

These types of studies can be prospective, retrospective, or both. For example, in cancer research, a team might observe patients who don’t have cancer over a number of years to see who develops cancer, and who doesn’t. They can then look back on their observations to determine whether those who developed the disease had anything in common.

Although a cohort study can be effective at assessing risk factors, they are generally time consuming and expensive to run. As such, they’re usually reserved for theories that can’t be tested using a different method.

Case-control studies

During a case-control study, a group of people with a disease or condition (the case group) is compared with a group of people who do not have the disease or condition (the control group).

Case-control studies are often used to determine the cause of a disease or condition. For example, the risk of people with diabetes developing cardiovascular disease, against the risk for those without diabetes.

Cross-sectional studies

Cross-sectional studies – otherwise known as descriptive research studies – gather data from a cross-section of the population over a specific period of time, usually through surveys and/or interviews.

These types of studies might be used to assess the prevalence of a disease or condition, such as depression, anxiety or other mental health disorders for example. However, they cannot determine the cause.

How are participants assigned in an observational study?

Rather than being assigned to a study, researchers observe and collect information about individuals or groups as they go about their daily lives.

A sample of the general population is usually selected, either entirely at random, or based on certain characteristics, such as age, gender or social status. Variables of interest – which might include demographics, lifestyle factors, medical history, or outcomes – are then recorded without any interference or manipulation.

The benefits of an observational study

Observational studies are an important tool for understanding diseases, treatments, and outcomes for patients, and they have many benefits.

• Real-world insights: Subjects are observed in their natural environment, which validates the findings, and means they’re applicable to the wider population.
• Ethical considerations: Observational studies offer an ethical method of gathering data when an experimental study might be unethical – for example, studying the effects of smoking.
• Long-term and rare insights: Because these studies can be undertaken over long periods of time, and they involve a large number of participants, they’re ideal for examining long-term and rare outcomes of treatments or interventions.
• Assessment of practical effectiveness: Observational studies include a broad range of patients outside a controlled setting, providing insights into a treatment's effectiveness in real clinical practice
• Trend analysis: Researchers can analyze changes and trends over long periods of time to improve their understanding of how a disease progresses, and the effectiveness of treatments.
• Treatment comparisons: Different medications and interventions can be compared in real-world settings, which helps guide clinical decision-making.

The challenges of an observational study

Although observational studies are incredibly valuable for gathering real-world data, they also present several challenges.

• Confounding variables: Researchers are unable to control all the confounding variables – factors such as diet, levels of physical activity, smoking status etc. that influence the outcome of a study, but aren’t accounted for. This can lead to incorrect conclusions.
• Selection bias: Participants in these types of studies are not randomized. As such, if the sample is unlikely to fully represent the population being studied, and the results may not be accurate.
• Measurement bias: If participants don’t provide accurate information, the measurements aren’t precise, or reporting errors occur, then unreliable conclusions could be made.
• Recall bias: Study participants may find it difficult to recall events, exposures, or behaviors with full accuracy, impacting on the reliability of the information.
• Loss to follow-up: It can be difficult to retain participants over long periods of time, which can result in bias if their characteristics are significantly different from those who remain.
• Limited control over study design: There are limits to how much influence researchers have on the design of these studies, especially when using existing data. This could potentially impact the quality of the results.
• Heterogeneity: Observational studies often involve diverse populations with varying characteristics. These differences in demographics, lifestyles, and other variables can make it difficult to identify patterns or apply the research to other populations
• Generalizability: The findings might not always be applicable to broader populations or different settings, as the researchers have limited control over variables and biases.

What is an experimental study?

An experimental study enables researchers to manipulate one or more variables to assess how they impact another variable. They are often used to compare the effects of medical interventions or treatments.This type of research is very reliable as researchers are able to control the confounding variables.

What makes a study an experiment?

A study is an experiment when one or more variables are changed to assess how they affect the outcome, and they’re used to test a hypothesis.

The different types of experimental studies

There are many different types of experimental study, each with its own advantages. Researchers select the type of study that they believe will deliver the most valid and reliable results.

Randomized controlled trials (RCTs)

RCTs are widely considered the pinnacle of experimental research, and are frequently used to assess the effectiveness and safety of new interventions.

After being randomly divided into groups, participants in one are given the experimental intervention, and the others (the control group(s)) are given a placebo or standard treatment. The results are then analyzed to assess the impacts of the new drug or treatment.

Crossover trials

Participants in crossover trials are given several experimental and control interventions in a random order to assess their success. These trials are effective at comparing long-term treatments for chronic conditions

Cluster randomized trials

Clusters of people – such as communities or clinics – randomly receive different interventions, and the data is assessed at group level.

Factorial trials

Participants in factorial trials receive different combinations of interventions simultaneously. This enables researchers to assess complex interventions involving various combinations of treatments.

Adaptive trials

During an adaptive trial, adjustments can be made to the intervention, sample size, or randomization ratios, based on interim trial results. This is helpful if there’s uncertainty about the study design, or if new information comes to light.

Non-inferiority and equivalence trials

A non-inferiority trial aims to show that a new treatment is not significantly worse than an established treatment, while an equivalence trial aims to prove that two treatments are equivalent (within a certain margin).

Pragmatic trials

A pragmatic trial analyzes an intervention in real-world clinical practice. It focuses on practical questions, such as whether it works when a healthcare provider implements it in a typical healthcare setting.

How are participants assigned in an experimental study?

Experimental studies use randomization and blinding techniques to minimize bias and reach valid conclusions about the intervention being tested. This design helps researchers assess the specific effects of the experimental drug beyond any placebo effect.

Randomization involves randomly assigning participants to either the experimental group, or control group. Participants in the control group usually receive a placebo or traditional intervention. The other group receives the new treatment.

In a blind study, the participants are unaware of which group they belong to. In double-blind studies, neither the participants or researchers know which is the experimental group, and which is the control group.

The benefits of an experimental study

Experimental studies offer several important benefits that contribute to the advancement of medical knowledge and patient care.

• Establishing causality: Experimental studies accurately observe and establish a cause-and-effect relationship between interventions and outcomes.
• Minimized bias: Randomly allocating participants minimizes selection bias to comparable groups, and reduces the impact of confounding variables.
• Controlled environment: Researchers can isolate the effects of the intervention from other factors, enhancing the study’s validity.
• Comparative effectiveness: Researchers can directly compare interventions or treatments against a placebo, a standard treatment, or other active interventions.
• Statistical rigor: Experimental studies use rigorous statistical methods to analyze the data.
• Evidence-based medicine: The high-quality evidence gathered helps healthcare practitioners make informed decisions about medical treatments.
• Regulatory approval and drug development: These studies are required in order for new drugs and medical devices to be approved by regulatory agencies, such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA).
• Innovation and discovery: Experimental studies allow researchers to discover new approaches to disease management, which enhances healthcare practices and improves patient care.

The challenges of an experimental study

Experimental studies gather vital insights that advance scientific developments and enhance patient countomes. However, they present their own challenges.

• Ethical considerations: Participants face the risk of the intervention causing adverse effects, so minimizing harm is a significant ethical challenge.
• Participant recruitment and retention: Recruiting participants can be difficult, especially if there are strict inclusion and exclusion criteria. Retaining participants during long studies can also be a challenge.
• Randomization and blinding: Implementing and maintaining blinding protocols can sometimes be difficult, especially if a study involves complex interventions.
• Placebo effect: If patients experience the placebo effect (psychological and physiological improvements due to a belief they’re receiving an active treatment) the reliability of the results can be compromised.
• Standardization of interventions: Interventions must be applied consistently across the groups to reduce bias and ensure the results are reliable.
• Crossover effects: In crossover trials, carryover effects from previous treatments could influence the impact of subsequent treatments, so effective ‘washout’ periods and careful study designs are important.
• Sample size and statistical power: Studies with groups that are too small might not detect significant differences, and could lead to inconclusive results.
• Adherence and compliance: If participants don’t comply with strict protocols, it can lead to bias and invalidate the results.
• Resource limitations: Experimental studies are often resource-heavy in terms of funding, staff, and time. As such, limited resources could impact a study’s quality and validity.
• Real-world applicability: The strict inclusion and exclusion criteria could limit the generalizability of the findings compared to diverse patient populations.

Observational vs experimental study

There are a few key differences between these two study types, and each has its strengths and limitations.

Researchers will select the most appropriate approach based on the research question, ethical considerations, practical constraints, and what they hope to achieve.

Study design

• Observational study: Researchers observe subjects and their behaviors or characteristics without intervening or manipulating any variables.
• Experimental study: Usually compares randomized groups of individuals, and involves the deliberate manipulation of variables to observe their impact.

Control over variables

• Observational study: Researchers have no control over variables, and instead study real-world situations without interference.
• Experimental study: Researchers control the conditions, and they manipulate one or more variables to establish cause and effect.

Randomization

• Observational study: Rather than being selected and randomized, participants are observed based on their characteristics or exposures.
• Experimental study: Participants are randomly assigned to experimental and control groups to eliminate bias.

Intervention

• Observational study: No interventions or treatments are given by the researchers, and instead, they observe naturally occurring events.
• Experimental study: Researchers deliberately intervene or manipulate the experimental group to assess the impact.

Causality

• Observational study: Observational studies can’t determine causation. They can only suggest relationships between variables.
• Experimental study: These studies are specifically designed to establish cause-and-effect relationships.

Purpose

• Observational study: The purpose of an observational study might be to explore new areas of research, generate hypotheses, or identify potential associations between variables.
• Experimental study: The purpose of an experimental study is usually to test hypotheses, establish causation, and determine the effectiveness or efficacy of an intervention.

Participating in an observational or experimental trial

Observational and experimental clinical studies are an incredible way of contributing to scientific discoveries and advancements in healthcare. The first step is finding the right study.

How to find research studies

There are a few ways you can locate research studies that might be suitable for you.

• Search clinical trial databases such as ClinicalTrials.gov which allow you to filter studies by specific criteria, such as medical condition or location.
• Specialized clinical trial platforms enable you to find clinical trials and studies by filtering through different parameters like health condition, geographic area, and qualification criteria.
• Contact local research institutions, universities, and hospitals to find out if they’re running any trials and looking for participants.
• Talk to your healthcare provider as they might be aware of clinical studies related to your condition.

Considerations before participating

Always consider the potential risks and benefits of a clinical trial before you volunteer, and have a detailed discussion with your healthcare provider.

We recommend taking the following steps if you’re considering taking part in a clinical trial.

• Read the study information carefully so you fully understand the purpose, potential risks, benefits, procedures, and eligibility criteria. If you have any concerns, talk to the relevant researchers or healthcare providers.
• Check you meet the eligibility criteria, which could include your age, medical history, and health status, alongside other factors.
• If you decide to participate, you need to provide consent. Carefully read the informed consent document before signing it, as it outlines the study details, your rights, the risks, and the benefits.
• Understand your rights as a participant – which include the right to withdraw if you feel uncomfortable or you don't want to continue.

Considerations during and after participating

There are also a few considerations to bear in mind both during the trial, and after you complete it.

• Participate actively and follow the agreed protocols, which might include attending appointments, taking medications or interventions, and reporting changes to your health or wellbeing.
• Stay in touch with the research team who can update you on the study's progress and new developments. Voice any concerns to them, including changes in your health.
• If you have a positive experience, tell people about your participation in the study (provided it isn’t confidential) as it might encourage others to get involved in this type of important research.

Conclusion

Although there are several differences between observational and experimental studies, the level of intervention is what sets them apart.

During an observational study, researchers observe subjects and gather data, but they have no control over the variables. Researchers in an experimental study, meanwhile, deliberately manipulate variables to analyze the impact.

Participants in both types of study play a vital role in advancing medical knowledge and scientific developments – improving the quality of life of millions of patients around the globe.