What is meant by data triangulation in research?

Data triangulation refers to the practice of employing multiple methodologies or data sources to validate research findings. This approach enhances the credibility and reliability of the research outcomes by allowing researchers to corroborate evidence from different angles. By integrating various perspectives—such as qualitative and quantitative data or data from diverse sources—a more comprehensive understanding of the research question emerges.

For instance, if a researcher is studying patient satisfaction, they might use surveys, interviews, and focus groups to gather diverse insights. If all these methods point to similar conclusions, confidence in the results increases, minimizing potential biases that could arise from relying on a single source or method. This practice is essential in healthcare research, where the complexities of human behavior and experience require a multi-faceted view for accurate conclusions.