One of the first things you need to look at on a website is where the article/blog is located. There are trusted websites to find information where the information they are providing they can back up using research and previous studies. Some good websites include:
Any reliable website should have data and sources to support any statements they make. A "source" can be any research article, institution, or clinical professional, but even this should be considered carefully. A general magazine article doesn't count! You can usually find these at the bottom of the page, or imbedded into the article.
It’s one thing to read articles summarizing research, but you can also actually read the research yourself. The article you read should give you a basic research question that the authors intend to answer, their predicted outcome (hypothesis), an operational definition of all study variables (i.e., they give you a measurable, observable definition of what they are assessing) as well as information on how they assessed it (e.g., tests, questionnaires, demographic of participants, etc.). In other words, they clearly follow the Scientific Method.
Research articles can be accessed using websites like Google Scholar. Google Scholar will help you make sure that the research you are reading is empirical and peer reviewed. Empirical research simply means that the research is based on something that was measured and observed. Peer reviewed means that the article, before being published in a journal, was reviewed by other experts in the field and determined to be valid. Note, however, that only some articles are available to the general public and for free. Some articles do require that you either purchase the article or are affiliated with a research institution (i.e., university). Still, there are many free sources available.
Before a scientist can publish an article, they must submit that article to a journal (e.g., Journal of the American Medical Association). Then, lead experts in that field are appointed by the journal to thoroughly review the article. Their objective is to dissect it to make sure that the article meets standards and contains valid research, without significant gaps. It is very difficult to get articles published through these means, as journals can easily and often do reject publications and/or suggest edits or revisions based on either the protocol or explanation of findings. This means that articles that do get published meet a high standard of writing, content, and research quality and have sometimes been reviewed and edited many times prior to publication (https://library.sdsu.edu/reference/news/what-does-peer-review-mean
).
Even when a set of authors have jumped through all of these hoops and made it to publication, you the reader should still look at these studies with a critical eye. One good question to ask yourself is “Was I given enough information to recreate this study and test these results, or are there significant gaps in the study?” (https://guides.libraries.psu.edu/emp).
Now, as research articles are typically meant for fellow researchers and colleagues, they frequently contain jargon, or words that relate to a specific field or profession that are hard for others to understand that aren’t familiar with that field. To break it down for you, research articles are typically divided into distinct sections.
- Abstract- this is the brief paragraph at the very beginning. This gives you a brief synopsis of the entire article and should tell you what they are measuring, why they are measuring it, the results, and what they concluded from the results. Some journals, however, leave the conclusion piece out and the reader must read the conclusions themselves (at the end!)
- Introduction- this is where they are going to give background on what their hypothesis is and why it is important to study/measure it. A background of the previous literature on the topic is also reviewed.
- Method- This is an important section to pay attention to, as this will give you information on how they got their results. This will include demographic information about participants as well as what their sample size was. The sample size (or number of people in the study) will typically be represented as N= Number of people. The sample size can be very important because they may have found some significant results, but if it was only with 2 people then it can be difficult to generalize those results to the entire population. Another thing to look for in this section is whether the study used a control group. A control group is a group of people who did NOT receive any treatment. This is used so researchers can compare them to the people who did receive treatment for any differences. The method is also important because it should list information on HOW they got their results.
- Results- This section is where they will go over any analyses run and what all the results mean. You may see a lot of numbers and symbols that you aren’t familiar with. For example, in psychological research, you will see the term “statistically significant” often. This means that the probability that the results found are not just due to chance is within a certain percentage, usually 5% or lower. Don't worry though; results are almost always clarified into more easily understood language in the next section!
- Conclusion- The conclusion is where the researchers will summarize the results and apply those results to real life situations and scenarios. The conclusion is also where the researchers will discuss any limitations to their study (e.g., generalization problems because the sample size was low or they didn’t have enough people from particular demographics to make broad statements). In addition, the conclusion will also discuss future implications for the study and what may still need to be researched in the future. This is the section that often makes the most sense to those not familiar with reading research studies.
You may see journal articles that are a “meta analysis”. This means that the researchers went through and ran analyses on several similar research studies in order to globally state the current understanding of a topic. In other words, these analyses are not producing new results, but they are collecting all of the results into one study (https://www.meta-analysis.com/pages/why_do.php?cart=). This is used to help summarize and make determinations from data on a large scale, which provides helpful direction for future research.
-Any article that claims that A CAUSES B.
Causation is a strong term and it is very difficult to say that one thing causes another. For example, there is a common misconception that vaccines cause autism, but there is no empirical, peer reviewed research showing this (https://www.ncbi.nlm.nih.gov/pubmed/24814559 ). If this statement alarms you, we refer you back to the review of what empirical and peer reviewed actually means - this has been heavily studied.
Another example: I could say that my headache was caused by temperature change outside, but it could also be because I’m dehydrated, my neck is tight, etc. That’s why it is more accurate to say that my headache is correlated with (or related to) the temperature change.
-Any article that is published in a magazine or a blog that is making strong claims.
Again, this is why research can be difficult to get published because it has to go through rigorous study by professionals. Everyone is entitled to their own opinion, but remember that just because something works for one person doesn’t mean that it will work for everyone. This is another reason why having many people in a study is important to make sure that the results can be generalized to the entire population.
With this information, I hope that you will see medical research in a new light and really check to make sure that you are reading and learning from established sources!
Stay tuned for a future blog post in the coming months that will dive into some common mental health myths that are still around, and are largely based on misguided interpretation of research.
Happy Reading!
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Kelsey McElroy, MA, CSP
Certified Specialist of Psychometry