Study Types in Orthopaedics Research: Is My Study Design Appropriate for the Research Question?

Avoiding Systematic Bias in Orthopedics Research Through Informed Variable Selection: A Discussion of Confounders, Mediators, and Colliders

There are 3 common variable types in orthopedic research-confounders, colliders, and mediators. All 3 types of variables are associated with both the exposure (eg, surgery type, implant type, body mass index) and outcome (eg, complications, revision surgery) but differ in their temporal ordering. To reduce systematic bias, the decision to include or exclude a variable in an analysis should be based on the variable's relationship with the exposure and outcome for each research question. In this article, we define 3 types of variables with case examples from orthopedic research. Please visit the followinghttps://youtu.be/V-grpgB1ShQfor videos that explain the highlights of the article in practical terms.

P-Values and Power in Orthopedic Research: Myths and Reality

The results of statistical tests in orthopedic studies are typically reported using P-values. If a P-value is smaller than the pre-determined level of significance (eg, < .05), the null hypothesis is rejected in support of the alternative. This automaticity in interpreting statistical results without consideration of the power of the study has been denounced over the years by statisticians, since it can potentially lead to misinterpretation of the study conclusions. In this paper, we review fundamental misconceptions and misinterpretations of P-values and power, along with their connection with confidence intervals, and we provide guidelines to orthopedic researchers for evaluating and reporting study results. We provide real-world orthopedic examples to illustrate the main concepts. Please visit the followinghttps://youtu.be/bdPU4luYmF0for videos that explain the highlights of the paper in practical terms.