Compare clinical significance and statistical significance; include which one is more meaningful to you when considering application of findings to nursing practice.
The difference between clinical and statistical significance is important because it affects how we understand and use research results.
Clinical significance is related to the relationship between a variable and clinical outcomes. Statistical significance is related to the relationship between a variable and statistical outcomes. The difference between statistical and clinical significance is important because it affects how we understand and use research results.
Statistical significance is a measure of how likely the results are to be due to chance. In other words, it’s an estimate of how likely your results are by chance alone (i.e., without any treatment). Clinical significance is a measure of how likely your results are for patient outcomes, such as reducing pain or improving function after surgery.
The two terms can be related but not identical: statistical significance gives you an idea about whether there’s a relationship between two variables—for example, does being born with chronic arthritis have anything in common with having high cholesterol levels?—while clinical significance tells us what that relationship might look like if we see it again in another patient with similar characteristics (for example: do people born with both conditions live longer than others?).
The research design affects the strength of your findings. If you are trying to make a decision about something, you need to know how much confidence you can have in the results.
In general, statistical significance has more meaning than clinical significance because it’s easier for random chance or error to affect one result than another—and this is especially true if there are multiple tests being performed on a small sample size (for example, if five people were tested for cancer and only one had cancer). But clinical significance may still be important when looking at larger populations or large numbers of cases studied over many years; these factors may cause some differences between individual patients that could not be detected by statistical testing alone.[5]
For example, suppose that a study concluded that patients who received care based on an intervention were 10% more likely to stay off medicine after discharge from hospital than those who received care without it. The difference is that clinical significance is related to the relationship between a variable and clinical outcomes (e.g., staying off medicine), while statistical significance is related to how many people are in each group versus how much they differed between groups.
In this case, there was no difference at all between the two groups—the data showed no increased risk of stopping taking medications for these two groups. This means that even though there were fewer people who discontinued their medication than expected for both groups (1% vs 2%), neither had any evidence supporting this type of practice or treatment plan
If you want to apply your findings to nursing practice, it’s important that you consider the research design when comparing statistical significance and clinical significance.
When assessing the relationship between a variable and clinical outcomes, both types of significance can be used as indicators of importance. Some researchers use statistical measures like p-values and t-tests for this purpose; others use other methods such as meta-analyses or prospective cohort studies that examine multiple variables together over time (i.e., they look at how one variable changes over time with another). In addition, some researchers only report results from their own study designs while others include all possible designs in their analyses—and sometimes these two approaches yield different conclusions!
Clinical and statistical significance are both important factors to consider in interpreting results from research. Clinical significance is a measure of the relationship between a variable and clinical outcomes, while statistical significance is a measure of the likelihood that the results are due to chance.
The difference between clinical and statistical significance can be illustrated by looking at two studies: one on pain relief after knee surgery, and another on postpartum depression. Both studies were conducted by researchers at Johns Hopkins University School of Nursing (JHU SN), who wanted to know if people would experience more severe chronic pain if they received intravenous morphine immediately after knee surgery than they did after waiting six hours before receiving any medication whatsoever (1). They also wanted to find out whether women who were depressed during pregnancy were more likely than non-depressed women not only during pregnancy but also after giving birth as well? The JHU SN published their findings in 2011 entitled “Chronic Pain After Knee Replacement Surgery: Does It Matter If You Get Medication Immediately or Not?”
So, are you ready to start considering how research findings can affect your practice? It’s a big step, but we’ve done the hard work for you by showing you how these two types of significance differ and which one is likely to be more meaningful to nurses.
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