What is the difference between statistical significance and clinical significance? Explain why statistically significant results in a study do not always mean that the study is clinically significant. Provide an example. Response 1: (Erika)

What is the difference between statistical significance and clinical significance? Explain why statistically significant results in a study do not always mean that the study is clinically significant. Provide an example. Response 1: (Erika)

The difference between statistical significance and clinical significance, from what I understood in the literature was that there may be a casual link or association in scientific studies, and expressed by a probability value. One of the examples used, that helped me to better understand it was, “a drug lowered cholesterol levels an average of 195 to 178. Analysis indicated that this decrease was statistically significant; however, because any cholesterol value below 200 is considered to be within normal range, there is no clinical significance to this finding.” In-other-words, if the tested subjects had a cholesterol above 200 and the tested drug had lowered their levels either close to the 200 or even at the 200 level, then it would have had clinical significance and would then make sense to apply it as a practice intervention. (Schmidt & Brown, 2019, p.370) Basically, statistically significant results do not always mean the results have a clinical significance because it depends on the data utilized for the study and results. As the example noted above the average was within normal range then it would not be useful in a clinical practice. Again, that’s if I understood this topic correctly and the question.

Response 2: (herman)

In research studies, there can be clinical significance or statistical significance. Clinical significance is regarded as the event where a result or a course of treatment has had genuine and quantifiable effects (Dahlberg et al., 2020). That means that the treatment under trial is relevant clinically due to the fact that it is practical in causing the effect it was intended to. In that case, it means that a research is considered to be clinically significant when its effects are practical in the real world. On the other hand, statistical significance is where an effect is likely or unlikely to happen by chance (Schober et al., 2018). That means that statistical significance depends on probability while clinical significance depends on the size effects.

According to Dahlberg et al. (2020), studies can reach statistical significance but provide evidence that is not clinically meaningful, or results could not be statistically significant but very clinically relevant. That means that the study findings or the null hypothesis being studied is found to be true but in real life, the results cannot be applied. For example, a treatment regimen could be found to be effective from the point of statistical significance, however, the treatment cannot be applied in real life due to the side effects on humans.