Understanding Research: Colors, Happiness, and Weight Loss
by Monica A. Frank, Ph.D.
Recently, while I painted the interior of my home and was covered in yellow and green paint, I heard on the radio: “Research shows the colors green and yellow in your home make you happy.” My immediate reaction was “Great! We should be very happy here.”
But then, of course, my research-oriented mind started wondering: Maybe yellow and green don't make you happy but maybe happy people are more likely to decorate with yellow and green. Of course, the radio personality didn't clarify how this research was conducted but I suspect it wasn't a randomized design which means it could be open to interpretation.
As many of you may be aware from my writing, I have an issue with how media (mis)interprets health research. Often the public is provided information that is inaccurate or misleading. Even though the colors of house paint is a trivial example it can illustrate more important “facts” that are provided us on a daily basis.
This example shows how research may be presented as “causing” something when it actually is only related. For instance, yellow and green in the home may be related to happiness in some way but that doesn't necessarily mean that painting your home those colors will make you (“cause” you to be) happy.
Only if the study was a randomized design could the researchers determine causality. But a randomized design is harder to implement. In this case, it might be getting a group of people to agree to allow the researchers to paint their homes and then they live in those homes for a period of time while the researchers measure their happiness levels. Pretty involved and expensive, right? Which is why much research is not randomized but is just showing a relationship: people who live in homes painted yellow and green are happier. Such research only requires a one-time questionnaire but doesn't show us what causes what. Does happiness cause us to be attracted to certain colors or do certain colors make us happy?
Or is their some other explanation for the relationship?
Why is this important? Because when you understand the difference between causality and relatedness you can better evaluate information provided by the media. For example, the media might report that if you eat breakfast you are more likely to lose weight. However, that isn't what the research actually shows. The research indicates that people who have successfully lost weight tend to eat breakfast. It doesn't show that eating breakfast causes weight loss. It could be something that is associated (Brown et al., 2013). Maybe people who lose weight are hungrier in the morning. Maybe they exercise more and need the energy from a good breakfast. But if you believe the media reports and start eating breakfast as your main weight loss plan, you will be likely to gain weight instead.
Understanding research and causality can help you avoid these pitfalls. It also helps you to know when the information might be useful.
Brown, A.W., Bohan Brown, M.M. and Allison, D.B. (2013). Belief beyond the evidence: using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence. American Journal of Clinical Nutrition, 98, 1298-1308. DOI: 10.3945/ajcn.113.064410.
Copyright © 2016 by Excel At Life, LLC
Permission to post this article is granted if it includes this entire copyright
and an active link.