Important questions to ask when assessing the quality of a study:
- Is the study design suitable for answering the research question? For example, you can’t use a questionnaire to find out whether a new surgical procedure is better than a tried-and-tested approach. A randomized controlled trial (RCT) is needed instead.
- How were the participants approached and selected? Who was included in the study and who was excluded from the study? For example, people who have several medical conditions at the same time are often excluded from studies. As a result, it might not be possible to apply the study outcomes to patients in the “real world” who have several medical conditions at the same time.
- Was the researchers’ description of how they carried out the study detailed and understandable enough for others to be able to repeat the study and verify the results?
- Were there enough participants in the study to be able to answer the research question? When treatments are compared, there are nearly always small differences between their outcomes. Scientists then work out the likelihood that these differences could be due to chance rather than being true differences. Here it is important to know exactly how different the outcomes were and how many people participated in the study: The smaller the difference, the more participants are needed in order to consider the difference to be “real.”
- Are the endpoints that were used in the study suitable for demonstrating that patients benefit from the treatment? In a study on a diabetes medication, for instance, measuring blood sugar levels alone would not be enough. It would be more important to know whether the medication helps prevent long-term effects of diabetes such as amputations. Laboratory values like blood sugar levels (also referred to as “surrogate parameters”) alone are not enough to provide conclusive answers.
- Did the study last long enough? To find out whether, for example, a certain weight loss diet is effective, the participants’ weight should be checked again six months or one year after the end of the study – perhaps even after a longer period of time.
- How many participants dropped out of the study, and why? How many participants could no longer be monitored after the end of the main part of the study (“lost to follow-up”), and why not? Good studies should include these figures and say whether they influenced the outcomes. This may be the case, for instance, if a lot of people drop out of a study due to bad side effects.
- Apart from receiving the different treatments that were being compared in the study, were the groups treated the same otherwise? Differences are especially likely if it wasn't possible to "blind" the study participants or people receiving treatment properly. Blinding refers to ensuring that participants do not know which group they were assigned to.
- Was it really a fair comparison? It could be a problem, for instance, if a new medication was compared with a standard medication used at a lower dose than usual in daily practice.
- Was the success of treatment measured in the same way in both groups? For example, if the results of a blood test were used in one group, but both a blood test and an x-ray were used in the other group, that could change the outcome.