Interpreting Research Findings in Endodontics: A Biostatistical Primer

Statistical significance testing has long been the dominant method for making inferences in dental and endodontic research.Null hypothesis significance testing (NHST) assesses how compatible the data are with a null hypothesis.It does not prove a hypothesis to be true or false.This method has been criticized because it relies on the P-value, which is commonly misused, misinterpreted and provides limited information about the data.Therefore, it is recommended to complement NHST with effect sizes and their confidence intervals to support a more informative interpretation of the results.This biostatistical primer focuses on endodontics and presents practical guidance on interpreting study findings from a clinical perspective.The paper addresses the common pitfalls of interpreting results based solely on the P-value and explains the importance of incorporating effect size and the associated confidence interval to determine the magnitude, direction, precision, and clinical relevance of the observed effect.This biostatistical guide provides a critical approach to interpreting research findings by using endodontic literature to translate statistical concepts into clinically meaningful interpretations.Overall, a shift away from binary significance testing based solely on P-values toward comprehensive measures is suggested to improve the translation of research into practice and ultimately support more informed, patient-centered clinical decisionmaking in endodontics.