Patients often hear that a treatment was statistically significant, but that phrase does not fully answer the most practical question: How much difference did it actually make? This is where the concept of effect size becomes useful. One common way to describe effect size is Cohen's d.
The term may sound like a technical detail for research papers, but the underlying idea is simple and helpful. At ATL Regen, we believe patients should understand not only whether treatment appears to work, but how large that treatment effect may be and whether it is likely to matter in everyday life.
Why how much matters
Imagine being told that a treatment produced a real effect. That sounds encouraging, but it leaves important questions unanswered: Was the improvement small or large? Was it noticeable to patients in daily life? Was it enough to justify the time, cost, and recovery involved?
These are the kinds of questions effect size tries to address. Patients do not want to know only whether a result exists. They want to know whether the result is meaningful.
What Cohen's d means in plain English
Cohen's d is a way of describing the size of a treatment effect. It compares the amount of change to the amount of variation in the data. Bigger values suggest a larger effect.
A common rough guide is:
- Around 0.2 = small effect
- Around 0.5 = medium effect
- Around 0.8 or more = large effect
These are not perfect cutoffs for every situation, but they are useful for understanding the general idea.
Why Cohen's d is different from a p-value
A p-value helps answer whether the observed result is likely to be real rather than random. Cohen's d helps answer how large that result appears to be.
Both matter. A treatment might have a low p-value, suggesting the change is real, but still only produce a small difference in practical terms. On the other hand, a treatment might show a large effect size, suggesting the difference is substantial. This is why effect size adds important context to statistical significance.
Why patients should care
Patients do not need to memorize effect-size formulas. They only need to understand why the concept matters. In plain terms, Cohen's d helps answer whether a treatment effect is likely to be minor, moderate, or large, whether the amount of change sounds meaningful enough to consider, and how it compares with other treatment options.
A practical example
Suppose a group of patients receives a non-surgical treatment and their pain scores improve on average. If the improvement is consistent and large compared with how much patients vary from one another, Cohen's d will be higher. That suggests the treatment effect is not only real, but substantial.
For patients, the more practical translation is this: a larger effect size suggests a higher likelihood that patients actually felt and functioned better in a way that mattered.
Why effect size is only part of the picture
Even a useful effect-size number does not answer everything. Cohen's d does not tell you whether the treatment is right for your specific diagnosis, whether the improvement lasted long term, whether the effect applies to all subgroups equally, whether multiple pain generators were involved, or whether the patient also improved function, not just pain.
This is why effect size should support clinical judgment, not replace it.
Why regenerative medicine needs this kind of discussion
PRP and other regenerative treatments are often marketed with broad claims. Patients deserve more precision than that. They should know not only that a treatment has some evidence behind it, but also whether the size of the benefit appears large enough to matter in daily life.
That is why ATL Regen values a more transparent discussion of outcomes. When the numbers are explained clearly, patients can make better choices.
Why understanding the numbers builds trust
When practices explain not just that a treatment works, but how the effect is measured and how large that effect appears to be, the conversation becomes more grounded and more trustworthy. That kind of transparency matters, especially when a patient is trying to choose between continued conservative care, PRP, another image-guided option, or a surgical pathway.
Schedule a consultation
If you are considering PRP or another non-surgical option and want help understanding what treatment outcome numbers actually mean for your situation, ATL Regen can help connect the data to your diagnosis, goals, and next step.
A consultation is the best way to move from statistics in the abstract to a plan that makes sense in real life.
