You want your evidence to be of good quality. This makes your argument stronger. When looking at a research article, look at the authors. What are their credentials? Do they seem qualified? Are all of the authors from the same institution? Sometimes it may be better if they are from different institutions--this can help reduce bias.
The abstract can tell you a lot! This is where you will find information regarding the purpose of the study. Note the methods. Do they seem reasonable? Would this be a good way to carry out this study or does it seem strange to you? Look at the results. This is a good way to learn about what the study found and if there were any statistically significant findings. Look for a note of randomization in the abstract. If there was randomization, researchers want to let you know. They will state this.
When you begin reading further into the article, think about the sample used. Would it be generalizable to other populations? For instance, you would probably not generalize the results of a study on middle-aged adults to a population of 3rd graders. Was the sample size taken from geographically different areas? Sometimes using participants from only one area can increase bias. Also, think about the setting for the study. For instance, a study done in a small, rural hospital may not be completely generalizable to a large, urban institution. Generalizability may also be affected by whether the study was done in the country you are interested in.
In the discussion section, the authors will talk about the results of the study and their thoughts on it. Look for limitations here and think about how those limitations affect the quality and generalizability of the source.
Finally, look at the references. Do they seem outdated? Sometimes older studies are still relevant and can provide a lot of information. However, if the reference list consists mainly of old or outdated sources, the research may be outdated. Also, look at the types of references. Are they mostly publications from credible journals? Look at the number of references as well. Does the number seem appropriate or does it perhaps seem too small?
Forest plots are a graphic representation of the articles and findings in a meta-analysis.
For more information, read the article "Interpreting and understanding meta-analysis graphs: A practical guide."
Example forest plot:
Click to watch a YouTube tutorial on how to interpret your forest plot.
Independent Variable: The independent/manipulated variable is the one that you are able to change. It can be manipulated. Researchers manipulate the independent variable and analyze changes in the dependent variable that occur as a result of this manipulation.
Dependent Variable: The name for the dependent variable says it all. The dependent variable is dependent on the changes in the independent variable (or at least that is what researchers suspect).
Guide developed with assistance from S. Pruitt, student, SIUE School of Nursing, and 2014 URCA program assistant.
