What is data triangulation and why is it used in community health evaluation?

• A. Using multiple data sources/methods to corroborate findings and enhance credibility and reliability.
• B. Collecting data from a single source to maintain consistency.
• C. Aggregating data into a single metric for reporting.
• D. Replacing data with expert opinions.

Answer: (A)

Data triangulation in community health evaluation means using more than one data source or method to study a problem. By gathering and comparing information from different angles—such as surveys (quantitative data), interviews or focus groups (qualitative data), and program records—you check whether findings point to the same conclusion. When multiple sources align, it strengthens credibility and reliability because each source has different biases and limitations, and agreement among them suggests the result reflects a real pattern rather than a single-method artifact. It also helps uncover context and nuances that a single method might miss.

For example, if survey data show a high rate of unmet needs, and community conversations reveal the specific barriers people face, together they provide a stronger basis for program decisions than either source alone. If sources diverge, analysts explore why—there may be subgroups with different experiences or data quality issues—and interpretations can be refined accordingly.

Relying on a single data source keeps findings consistent but weakens the ability to verify them; aggregating data into one metric can mask important variation; and replacing data with expert opinions removes empirical corroboration. Triangulation uses multiple sources and methods to bolster trustworthiness and depth in the evaluation.