This review discusses how to critique a research study. Against the backdrop of health science research, with a strong clinical bias, the review discusses study design, outcome analyses and research relevance. Some global aspects of statistical analyses of the data is also provided. The aim of the review is to help dissect research data and determine if the research provides a strong enough base of support for the change it is seeking. This review will also help beginners in science and medicine gain facility with reading research articles and determine thier validity and importance.© BrainMass Inc. brainmass.com September 23, 2018, 5:50 pm ad1c9bdddf - https://brainmass.com/health-sciences/evaluation-measurement-and-research-methods/how-to-critique-a-research-study-176529
Thank you for seeking our help with your research report. Your question is quite general, so I will try to explain in general terminology. Of course, if there is anything in particular that you would like clarified, feel free to get back to me.
There are generally three major aspects that control the applicability of research results in health sciences, in particular. These criteria are more relevant for health science clinical research, but are also applicable to bench research. The general aspects are - applicability and relevance of work (what you choose to study), study design outcome analysis (how you choose to study), and statistical validity (how you process your study data). Let us consider these three aspects in some detail -
1. Applicability and relevance of work (what you choose to study)
It is intuitive that a research is only as widely acceptable as its relevance to day-to-day situations. In health sciences in particular, you will find research that spans the breadth of clinical practice or the depths of specialization. For example, you could study the effect of a medicine for cold or how to manage cancer in the rectum in a patient whose family has many people with colon cancer, as respective examples. When research covers a broad area, it is generally more relevant to day-to-day practice. However, because of inherent heterogeneity in the large numbers studied, the outcomes are bound to be varied as well. In our example, all common cold is not the same. Viral infections differ from bacterial infections, while children have different diseases than adults and so forth. But, in general, a study of common cold is bound to have a wide impact, because it is a common disease! Highly specialized studies are usually directly applicable to the patient population studied. But variability in large populations of people precludes the ability to extrapolate results to patients that were not directly studied. Patients with rectal cancer and a strong family history of colon cancer are a tight cohort and, hence, results are very applicable to all of them. But, they represent a small percent of patients and there is no reason to believe that anybody with any colon cancer will have the same outcome as this highly selected population of patients.
Another important concept concerning research applicability is the nature of study. For example, studies that compare interventional modalities are more applicable that observational studies. And, within the intervention group, studies that compare two radically different treatment methods are even fancier. Let us take the example of heart attack. Many people have studied C-reactive protein (CRP), a type of protein in blood, and how it changes in heart disease. This protein may help predict or diagnose heart disease, but does not help in treatment or prevention. So, despite the plethora of studies that have looked at it, CRP has not caught on. Alternatively, studies comparing angioplasty and bypass surgery to treat heart disease are directly relevant to patients and frequently make newspaper headlines.
This review discusses how to critique a research study. Against the backdrop of health science research, with a strong clinical bias, the review discusses study design, outcome analyses and research relevance. Some global aspects of statistical analyses of the data is also provided. The aim of the review is to help dissect research data and determine if the research provides a strong enough base of support for the change it is seeking.