We read through a lot of health and wellness articles, news stories, and studies every week. Some are good, some are great, and some are less so. In that time, we’ve learned some important health and wellness writing phrases that may be confusing to people who don’t read them all the time.
Here at Medicareful Living, we don’t want to just help you to be healthier. We want to teach you how to find that out for yourself and understand what you’re reading. At the same time, knowing these terms will help you identify bad science reporting that uses vague or misleading terms to make something seem more groundbreaking or newsworthy than it really is.
It’s easy to misread risk factors in health writing, because you often see firm numbers that seem to tell the whole story. That’s not the case, and it’s important that you know the difference because it’s a likelihood percent change and a total likelihood percent. For example, when something lowers your risk, that doesn’t mean you won’t develop what’s at risk. If you have a 30 percent chance of developing a sickness, and eating a certain food is shown to lower your risk 40 percent, you don’t have negative 10 percent chance. It means your risk is lowered by 12 percent (40 percent of 30 percent) to an 18 percent chance risk. A similar misunderstanding occurs with headlines that claim a habit makes you 9 times more likely to develop cancer. Those numbers are called odds likelihood ratios, and are sometimes mistaken for being probabilities (percentages that something may happen). In reality, they are only used to compare the difference between two groups and can be misunderstood when seen at a glance. Even when used correctly, the effect may not be as large as you expect, since the numbers are only comparative and shouldn’t be used for estimating probability.
The problem is that misunderstanding the differences can make the results seem more impressive of a change than they actually are.
What difference does this make for you? Well, when you’re reading a study’s results (or a report on the study) and you see the findings of the study were that eating anchovies lowers your risk of cognitive decline by 10 percent, the results may seem significant, and depending on the hard statistics, they may be. But it may seem more impressive of a change than it actually is. Speaking of significance…
When you read that the results of a study were significant or that after eating a food for a month, brain function was significantly increased, it sounds, well, significant. It feels like there was a large or major change in the findings, but the word significant in science doesn’t specifically refer to the size or magnitude of the change, but probability. Generally, when talking about health studies, the phrase refers to statistical significance, which means the result likely isn’t due to chance. In other words, statistical significance is more closely defined as “real” than “meaningful,” though statistically significant results can be both.
Both the relevance and meaningfulness of a study’s findings require looking into the other research into the field as well as the real-world effects the study had.
Statistical significance on its own isn’t a great measure of effect for the overall study, though it can act as a good starting place. Instead, relevance and meaningfulness are key, though this is often inferred by the conclusions of the study. Both the relevance and meaningfulness of a study’s findings require looking into the other research into the field as well as the real-world effects the study had. Why is this all important to you, the reader? When you read a study or a health article and you see the results are significant, it’s easy to use the common definition of significant, which would be meaningful. But before you get excited, take a second to look at the context of the findings to determine if they are meaningful or relevant to our previous knowledge. This will help you to understand both the writing better and how to not get fooled.
Finally, when you’re reading an article, possibly one of our articles even, and you see uncertain language or hedging words, there’s often a reason for this, but the context of that is very important. When used in relation to the analysis of the results of a study, like “these findings could show…” there is a risk that the uncertainty is being used to color a certain finding with bias, intentionally or unintentionally. This can be especially problematic if the hedging phrases are being used by third party outlets reporting on the studies and applying analyses that may not actually be relevant. We’re very aware of this responsibility, but it’s still key that you, our readers, are aware of how much these hedging words can be used to change the reporting on a study.
Uncertainty, when used for things that you can’t possibly be certain of, reflects honesty.
That said, uncertainty isn’t always a bad thing in health writing. You’ll notice that we often say things like “making this health change can lower your risk…” or “you may be able to find a plan…” in our articles. It’s for a good reason. While uncertainty can be used to (purposefully or accidentally) add bias, so can making false promises and implying certainty when there can’t possibly be any. Everyone’s health and bodies are different, so what may curb somebody’s appetite and help them lose weight might not for somebody else. The treatment that will lower one person’s risk of cognitive decline by 30 percent may only lower it by 10 percent for another. Uncertainty, when used for things that you can’t possibly be certain of, reflects honesty.
Between each of these factors you should consider when reading a health or wellness article, there is a lot of grey space. In risk, a 23 percent decrease may be substantial or it may not. Statistical significance isn’t always what we’d consider to be significant. And uncertainty in writing can be a good thing or a bad thing. So, why did we make it more confusing to read this type of article?
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By knowing what to look out for, you can take an active role in understanding what you’re reading. Unfortunately, we can’t give you any rules across the board that’ll easily define what’s a good use of uncertainty and what’s not, or when statistical significance is both relevant and meaningful. What we can do is give you the understanding to figure that out for yourself and to call us out if we ever fall short (and we hope you do!). By being better health and wellness writers and readers, we can improve the general conversation and understanding surrounding these confusing topics.