Why randomized controlled trials

To determine how a new type of short wave UVA-blocking sunscreen affects the general health of skin in comparison to a regular long wave UVA-blocking sunscreen, 40 trial participants were randomly separated into equal groups of an experimental group and a control group.

All participants' skin health was then initially evaluated. The experimental group wore the short wave UVA-blocking sunscreen daily, and the control group wore the long wave UVA-blocking sunscreen daily.

After one year, the general health of the skin was measured in both groups and statistically analyzed. The preventive effect of the nordic hamstring exercise on hamstring injuries in amateur soccer players: a randomized controlled trial. The American Journal of Sports Medicine, 43 6 , Natour, J. Pilates improves pain, function and quality of life in patients with chronic low back pain: a randomized controlled trial.

Clinical Rehabilitation, 29 1 , When the groups that have been randomly selected from a population do not know whether they are in the control group or the experimental group. Being able to show that an independent variable directly causes the dependent variable. This is generally very difficult to demonstrate in most study designs. Discussion continues as to whether a product is definitely safe without passing an RCT. Randomization prevents the skewing or deliberate manipulation of results.

Both participants and research scientists can influence results unless the researchers assign participants to groups at random. Scientists refer to this skewing of results as selection bias. An RCT gets rid of selection bias by removing the element of choice. For example, without randomization, scientists may consciously or subconsciously assign patients to the group receiving the active treatment if they look more likely to benefit from the experimental treatment.

This could make a treatment appear more beneficial than it actually is. On the other hand, if scientists are looking to demonstrate the ineffectiveness or potential danger of a certain treatment, they may assign participants who have a higher risk of complications or a lower chance of success to the group receiving the treatment. The risk of selection bias may also be high in trials by researchers who have received either direct or indirect funding from a pharmaceutical company looking to prove the efficacy and safety of a new drug.

For this reason, researchers must disclose any potential conflict of interest when conducting a clinical trial, as pharmaceutical manufacturers have a clear financial interest in achieving positive results.

Knowing which participants are getting the experimental drug can result in sound motivations as well as questionable ones. Doctors could have a well-intentioned influence over the results. Even selection bias with good intentions, such as researchers having concerns about the safety of a drug, is scientifically unsound.

If the active treatment seems to be producing severe side effects, for example, doctors may try to protect certain types of participant from the drug. Treating different subjects in different ways during the trial reduces the integrity of like-for-like comparisons, giving false results.

Randomization removes bias and truly allows for a direct comparison between two groups in a trial, providing a real representation of how the drug will react with the wider population after distribution.

The purpose of a control group in a randomized controlled trial is to help reduce the likelihood that any benefits or risks that the researchers identify during the trial occur due to factors outside of the experimental treatment. The absence of a control group would mean that the researchers could not attribute any improvement or decline in health to the drug or treatment.

Others factors about the clinical trial could explain the results. Without comparing what happens in similar participants facing similar conditions without getting the new drug, accurate measurement of any observed health changes would not be possible.

A control group is a key part of large trials. Enough people must be taking part to ensure that chance differences and unusual circumstances do not have a decisive effect on the results.

Researchers normally match people in a control group for age, sex, and ethnicity, along with any other factors that may influence the effect of a drug or treatment, such as body weight , smoking status, or comorbidities. The control group may receive a placebo.

Alternatively, they may receive standard treatment without the additional elements under investigation. In some cases, typically those investigating the benefits of an intervention to healthy individuals, such as a supplement, the control group may receive no treatment and simply consist of individuals similar to those receiving a supplement or therapy. The quality of the control group is important in terms of the similarity of its participants to those of the active group.

This also holds true for vulnerable populations in low-income countries in Asia and Sub-Saharan Africa. Few research groups have long-term core funding that enables them to undertake RCTs. Well designed, large-scale intervention studies generate so much data that they also have tremendous potential for spin-off and add-on studies.

In addition to expanding the relevance of the initial study, such studies provide important capacity-strengthening opportunities for young researchers. They provide them with excellent opportunities to design and lead their own research projects that will, in turn, build on the RCT results.

A RCT is a type of scientific experiment that aims to reduce bias when testing new interventions.