This paper explores the theoretical contributions of saturation sampling in qualitative health research, emphasizing its role in defining the closure of a sample. The authors discuss the operational definition of theoretical saturation closure, the challenges in accepting and operationalizing intentional samples, the adequate size of the intentional sample, and the significance of valuing repetition or differences in sample reports. They also address the misuse of expressions containing the term "saturation" and propose possible metaphors to understand the concept. The paper highlights the importance of transparency and clarity in research reports, particularly in the data collection stage, and critically reflects on the methodological and technical foundations of saturation sampling. The authors provide examples and illustrate how the concept of saturation can be operationalized, emphasizing the need for researchers to explicitly state the criteria for sample closure to ensure the credibility and transparency of their findings.This paper explores the theoretical contributions of saturation sampling in qualitative health research, emphasizing its role in defining the closure of a sample. The authors discuss the operational definition of theoretical saturation closure, the challenges in accepting and operationalizing intentional samples, the adequate size of the intentional sample, and the significance of valuing repetition or differences in sample reports. They also address the misuse of expressions containing the term "saturation" and propose possible metaphors to understand the concept. The paper highlights the importance of transparency and clarity in research reports, particularly in the data collection stage, and critically reflects on the methodological and technical foundations of saturation sampling. The authors provide examples and illustrate how the concept of saturation can be operationalized, emphasizing the need for researchers to explicitly state the criteria for sample closure to ensure the credibility and transparency of their findings.