adatsaturáció

Adatsaturáció, often translated as data saturation, is a concept primarily used in qualitative research. It refers to the point at which no new information or insights can be gained from additional data collection. When a researcher reaches saturation, the themes and categories identified in their analysis become repetitive, and new data simply reinforces existing findings rather than expanding upon them.

The process of reaching saturation involves continuous data analysis alongside data collection. As researchers gather information, they begin to code and categorize it. As more data is collected, they look for emerging themes. If new data consistently fits into established themes or fails to introduce novel concepts, it suggests that saturation has been achieved. This process helps to ensure the thoroughness and depth of a qualitative study.

The exact number of interviews or observations required to reach saturation can vary significantly. It depends on factors such as the research question, the homogeneity or heterogeneity of the sample, and the complexity of the phenomenon being studied. There is no universal benchmark for saturation; rather, it is a judgment made by the researcher based on the analytical insights gained from the data. Recognizing saturation is crucial for efficiently allocating research resources and for confidently concluding that the research has adequately explored the subject matter.