<![CDATA[The validity of health research is shaped not only by the appropriateness of its design, but also by how carefully potential sources of bias are identified, minimized, and transparently reported. Bias—defined as a systematic error that distorts the estimation of relationships or effects—can emerge at any stage of the research process, including sampling, measurement, and data analysis. When the efforts to control bias are insufficiently described, readers are left with uncertainty regarding the credibility and reliability of the findings. This editorial emphasizes the importance of writing research methods that clearly and convincingly demonstrate strategies to minimize bias. A method can be considered methodologically sound when it not only applies appropriate techniques but also explicitly communicates how potential biases were anticipated and addressed. This paper discusses the main types of bias that commonly affect health research, explains why minimizing bias is essential for scientific validity and evidence-based decision-making, and outlines practical strategies for presenting bias-control efforts in a structured and transparent manner. Authors are encouraged to adopt a deliberate and systematic approach when reporting their methods, ensuring that readers can critically appraise the extent to which bias has been minimized. Ultimately, transparent reporting of bias-reduction strategies enhances the trustworthiness, interpretability, and overall impact of research evidence in healthcare.Keywords: bias minimization; health research methodology; internal validity; methodological transparency; scientific rigor; reporting quality]]>
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