Triangulation and Data Synthesis in Mixed Methods Research

Mixed methods research, which combines quantitative and qualitative approaches, is particularly valuable in health research conducted in conflict settings. Triangulation and data synthesis are essential components of mixed methods research, enabling researchers to gain a comprehensive understanding of the complex health challenges in conflict-affected populations. This article explores the importance of triangulation and data synthesis in mixed methods research in health in conflict settings, along with practical examples to illustrate their application.

1. Triangulation: Triangulation involves the integration of different sources of data, methods, or theories to validate or corroborate research findings. In health research in conflict settings, triangulation allows researchers to overcome the limitations of a single method or data source, leading to a more comprehensive understanding of the phenomenon under investigation. For example: • Quantitative-qualitative triangulation: In a study examining the impact of conflict on maternal health, quantitative data on maternal mortality rates can be triangulated with qualitative data from interviews with healthcare providers and women to gain a holistic understanding of the challenges and barriers to accessing maternal healthcare services. • Methodological triangulation: Researchers can use multiple data collection techniques such as surveys, focus groups, and document review to triangulate findings and enhance the validity and reliability of the research outcomes.
2. Data Synthesis: Data synthesis involves the integration of quantitative and qualitative data collected in a mixed methods study. It allows for a comprehensive analysis that combines numerical data and narrative descriptions to gain a deeper understanding of the research topic. Examples of data synthesis techniques in health research in conflict settings include: • Convergent synthesis: Researchers examine the quantitative and qualitative data separately and then merge the findings to identify patterns, similarities, or contradictions. • Exploratory sequential synthesis: Qualitative data collected initially inform the development of quantitative measures or survey instruments, which are then administered to a larger sample. The findings from both phases are integrated to provide a more comprehensive understanding of the research topic. • Explanatory sequential synthesis: Quantitative data are collected and analyzed first, followed by qualitative data collection to provide a deeper understanding of the quantitative findings, exploring the underlying factors, or contextualizing the numerical results.

Example: A mixed methods study is conducted to examine the mental health outcomes and coping strategies among internally displaced persons (IDPs) in a conflict-affected region. Quantitative surveys are administered to a representative sample of IDPs to gather data on mental health symptoms and associated risk factors. Simultaneously, qualitative interviews are conducted with a subset of participants to explore their lived experiences, coping mechanisms, and social support systems. Triangulation is employed by comparing the quantitative survey findings with the qualitative narratives, identifying common themes, and validating the quantitative results through qualitative insights. Data synthesis involves integrating the quantitative data on mental health symptoms prevalence with the qualitative findings on coping strategies, barriers to mental healthcare, and social support networks. This integrated analysis provides a comprehensive understanding of the mental health challenges faced by IDPs in the conflict-affected setting.

Conclusion: Triangulation and data synthesis are essential components of mixed methods research in health in conflict settings. These approaches enable researchers to overcome the limitations of single methods or data sources and gain a comprehensive understanding of the complex health challenges faced by populations affected by conflict. By combining quantitative and qualitative data, researchers can generate rich insights, identify patterns, and provide a holistic understanding of the research topic. The examples provided highlight the practical application of triangulation and data synthesis in health research in conflict settings, emphasizing their value in informing interventions and policies that address the specific health needs of conflict-affected populations.