What research can...and can't tell you

Mark Twain once said ‘There are three kinds of lies; lies, damned lies, and statistics.’ I think he had a fair point. Statistics can be used to hide the truth as often as they can be used to reveal the truth. Often, this is not done intentionally. You see, every one of us has unconscious biases. These are beliefs that we are not aware of having, that shape how we see the world and inform the questions that we ask. Researchers are no different. The questions they ask, and the way they design a study, is shaped by their biases. For example, if you look at research on heart disease done before the 1970’s, you will find that women were not included. It was assumed (wrongly) that research done on men could be generalised to women. This came from the belief that the male body represented the norm, and that unless you were studying the reproductive system, any findings resulting from research on male subjects could be applied to females. Another common bias is seeing the body as a kind of machine, rather than a biological system. For example, when an artery is blocked, causing angina (pain) and increasing a person’s risk of heart attack, doesn’t it make sense that opening it up would reduce the risk of dying of a heart attack? Of course, logically it makes perfect sense. However, research doesn’t support it. Research shows us that if a person has a heart attack and a device is then used to open the blocked artery, it will reduce that person’s risk of dying. But if that device is put in before the heart attack, there is no reduction in mortality. The reason we like the idea that opening that artery, is that we see the body as a kind of machine and the artery is like a pipe. When you open a pipe in a plumbing system, you have fixed the problem. But our bodies aren’t plumbing systems. To see them as one is a mistake. For this reason, it’s important to have people who are skilled at analyzing research, to help us understand what it means.

I’ll give you a recent example from research on birth. In February 2018, the results of a study called ARRIVE were published. This study looked at the effect that inducing labour at 39 weeks would have on the c-section rate and on newborn death. It found that inducing at 39 weeks reduced the c-section rate from 22.2% to 18.6%, a reduction of 3.6 percentage points. So inducing all mothers at 39 weeks is a good way to reduce the c-section rate, right? But what if I told you that walking during labour reduces the c-section rate by 10 percentage points? Or that having a doula cuts your risk of having a c-section by half? What if I told you that the hospitals in which this study was done, had a general c-section rate of 27%, but the rate for the women who were not induced in this study was 19%, a reduction of 8 percentage points? That means that being enrolled in this study reduced the risk of having a c-section by more than inducing at 39 weeks. There is a name for this phenomenon; it’s called the Hawthorne effect. Basically, it is known that when people know they are being observed, they behave differently, and that changes their results. Another factor in this research was that it was done in a highly medicalized setting, where there was no midwifery care. So, it really can’t be generalized to women who are receiving midwifery care. So, who does it apply to? Really what this study shows, is that for birthing people who want a medicalized birth, especially those who are at a higher risk for late term complications, induction at 39 weeks reduces the risk of caesarean and increases their satisfaction with their birth experience. So it is certainly valuable information that can be applied to many birthing people. You just need to understand whether it applies to your situation.

Here are 5 keys to using research evidence to help you make medical decisions for yourself.

1.       Does the research available apply to your specific health situation?

Much of the research that is done on birth applies only to specific groups of birthing people such as healthy people having a single baby or people with diabetes or people who are having their first baby over the age of 40. Your healthcare provider can help you understand which research applies to you.

2.       Research evidence can only tell you if you are at higher risk or lower risk of experiencing a complication. It cannot predict what will happen to you. Some people who have a low risk of postpartum hemorrhage will experience a hemorrhage and there are people at high risk who won’t. So the research evidence must be weighed against your individual wishes and values. Some people feel that having more medical intervention is better, while others will want to minimize them.

3.       Most research seeks to isolate and study specific factors in a controlled setting. For example: does starting an epidural in early labour, lengthen labour time or result in more c-sections in first time mothers who have a single baby? It does not take into consideration complex situations, which often occur in birth. Again, this is where it’s important to understand your own values as well as get advice from your care provider, who brings their own clinical expertise and experience.

4.       There are many aspects of birth that just don’t have any research.  For example, there is very little research that has been done on the effects of different birth interventions on breastfeeding success or postpartum depression. In these areas, your care provider may give you their opinion based on their experiences. This information may or may not be accurate. It’s important to understand when your care provider is giving you an opinion and when there is research evidence.

5.       You are the expert on you. No research can tell you what you should or should not do. Ultimately, you know how you feel and what is important to you. For some people, a medicalized birth with an epidural feels like the safest option. For others, avoiding medications is very important. Everyone has the goal of having a healthy baby, but you are the best one to decide how to get there.