Becoming a Critical Reader: Bias, Bias Everywhere!
Pretty much everyone would agree that there is bias in research. Most people would say that bias is inherently bad. While it absolutely can be a bad thing, it can’t be completely eliminated. So what can be done about bias in research?
There are many kinds of bias:
- Researcher bias: researcher sets out wanting to the study to prove something, and intentionally or unintentionally manipulates the study to make sure that happens
- Sponsor bias: The organization that sponsors the study either encourages researcher bias or manipulates the publication of the data. Some studies might be completely suppressed, some might have overly inflated press releases touting minimal results.
- Publication bias: Journals must be selective in what they publish due to space limitations, but I think it is fair to say that some journals may choose not to publish a study that might anger its audience.
But today I want to focus on READER bias:
Your first job in the critical reading of an article is to check your bias. We are all human, and so we all have bias. Sometimes it is hard to see your own biases. Take a look at the pictures below. In the first picture, we can tell that there is something there, but it is difficult to see. In this case, the letters are lined up with our angle of vision.
In this second picture, the letters are running the opposite way as our line of vision, and as you can see, suddenly that bias is crystal clear!
The same is true with our reading of the research. The biases that we have act as a filter that alters our reactions to the research. If we already have our minds made up that induction of labor = bad, then any research on labor induction is going to be seen through that filter. Any research that seems to place induction in a favorable light will be seen has highly suspicious. Any minor flaws will be exaggerated. Any research showing bad outcomes from inductions will likely get a “free pass” and flaws may be overlooked.
Murray Enkin, author of “A Guide to Effective Care in Pregnancy and Childbirth”, said this:
Perhaps the most important bias of all resides in the (potential) reader, who determines how (or if) the results will be read and interpreted.
I would agree with him. I have, over the years, seen the best and worst of research used to back up various points, ignoring the quality (of lack of it!) as long as it agrees with them. This is a normal human tendency, and one that is at the heart of many discussions about the available research.
But the good news is that reader bias isn’t impossible to overcome.
The solutions? Awareness of bias and a change of perspective! As you read, consider how this research might be read and understood by someone with a completely different perspective. When you read a study that really resonates as a great study with you, play “devil’s advocate” and pick it apart. Be merciless in looking for flaws, weaknesses and the other types of bias listed above. The same is true of seeing an article you disagree with. Look for strengths and solid evidence. Have an open mind to other possibilities. Sometimes when doing this, you’ll be able to see some aspects you would never have noticed otherwise.
So, here’s an exercise for you. Take a few minutes, and write down what your biases are when it comes to research. Which kinds of research, which methods, which topics do you particularly feel drawn to? Which ones seem silly or useless? For inspiration, you may want to read a personal commentary article written by Murray Enkin (2008) where he goes through his own personal biases. The things he feels a bias for or against may not be the same for you. I know I have a disagreement with one of his stated preferences. But taking the time to carefully think through your own personal biases, to clearly acknowledge the filters through which you view the research, can only help you as you try to step back and make a critical analysis of the research.
Reference: Enkin, M. W. (2008) Biases in evaluating research: Are they all bad? Birth: Issues in Perinatal Care. 35(1). 31-32.