What does triangulation in research refer to?

Triangulation in research refers to the practice of cross-validating data from different sources or perspectives. This approach enhances the validity and reliability of research findings by incorporating multiple viewpoints or data points. By utilizing diverse methods, researchers can confirm the consistency of the data across different sources, leading to a more comprehensive understanding of the research question.

For instance, if a study on mental health outcomes integrates qualitative interviews with quantitative surveys, it allows for a richer exploration of the topic. The findings from interviews may provide deeper insights that illustrate or explain trends observed in the survey data. By cross-referencing information, researchers can better identify patterns, nuances, or discrepancies, thus reinforcing confidence in their conclusions.

Other options such as using multiple data collection methods or collaborating with other researchers are related concepts but do not encapsulate the full essence of triangulation. Employing only quantitative methods, on the other hand, would be contrary to the principles of triangulation, as it limits the perspective to a single type of analysis.