Statistical Reporting in Plastic Surgery Research

Current discussions in plastic surgery research highlight the need for improved statistical reporting to enhance clarity and accuracy. Although existing literature addresses common reporting issues, this communication emphasizes the critical role of language in statistical interpretation. Terms like "statistical significance" and "confidence intervals" often mislead by implying importance and certainty, respectively. Instead, adopting "statistical divergence" and "uncertainty intervals" would better reflect their true meanings-divergence from a null model and uncertainty in parameter estimates. Moving beyond the rigid 0.05 threshold, a continuous interpretation of P values could reduce binary thinking, mitigate P-hacking, and improve transparency in small-sample studies. Additionally, redefining confidence intervals as uncertainty intervals would correct common misconceptions about their probabilistic nature. To address these issues, we recommend that journals provide clear author guidelines promoting precise terminology and framing statistical results in terms of divergence and uncertainty. Aligning language with statistical reality will reduce misinterpretation and strengthen research quality in plastic surgery.