Pharmacologists use several key ideas to check if the results of clinical trials are trustworthy. Here’s a simpler look at those ideas:
Study Design: They look closely at randomized controlled trials (RCTs). These studies are often the best type of evidence. They usually give a clear effect size with a 95% confidence interval (CI), which means we can be pretty sure about the results.
Sample Size: It's important to have a big enough group of participants. Usually, they aim for at least 30 people in each group to find out if the treatment really works.
Statistical Analysis: They check for p-values, which tell them if the results are statistically significant. A common threshold is , meaning there's less than a 5% chance that the results happened by chance. They also look for confidence intervals that don’t cross important values, as this shows real differences.
Reproducibility: They make sure the trial's results can be repeated by other researchers. It’s even better if the studies are done with different groups of people to confirm the findings.
Bias and Confounding: They check for any biases that might affect the results. For example, selection bias or confirmation bias can lead to misleading conclusions.
Long-term Follow-Up: Finally, they look at data over a long time to see if there are any side effects or lasting benefits from the treatment.
By using these principles, pharmacologists can better understand and trust the outcomes of clinical trials.
Pharmacologists use several key ideas to check if the results of clinical trials are trustworthy. Here’s a simpler look at those ideas:
Study Design: They look closely at randomized controlled trials (RCTs). These studies are often the best type of evidence. They usually give a clear effect size with a 95% confidence interval (CI), which means we can be pretty sure about the results.
Sample Size: It's important to have a big enough group of participants. Usually, they aim for at least 30 people in each group to find out if the treatment really works.
Statistical Analysis: They check for p-values, which tell them if the results are statistically significant. A common threshold is , meaning there's less than a 5% chance that the results happened by chance. They also look for confidence intervals that don’t cross important values, as this shows real differences.
Reproducibility: They make sure the trial's results can be repeated by other researchers. It’s even better if the studies are done with different groups of people to confirm the findings.
Bias and Confounding: They check for any biases that might affect the results. For example, selection bias or confirmation bias can lead to misleading conclusions.
Long-term Follow-Up: Finally, they look at data over a long time to see if there are any side effects or lasting benefits from the treatment.
By using these principles, pharmacologists can better understand and trust the outcomes of clinical trials.