Author Description

Designing a public health intervention requires knowledge about the current status of the concerned population in terms of the prevalence of the disease and the level of access, availability, quality, utilization and coverage of services. Information is either gathered from existing studies or by conducting studies that may be either quantitative or qualitative in nature or both. Quantitative studies enumerate the entire population or apply robust sampling methods to collect information from a representative sample of the population. Quantitative studies estimate disease burden, quantify opinions, behavior, and also help in finding relationships between variables i.e. access or quality and outcomes. Qualitative studies, however, explore in-depth a topic as opposed to "Yes"/"No" or pre-coded responses to understand barriers or enablers arising out of structural, behavioral, cultural, and economic factors. Qualitative studies also explore the why and how of the issues being explored till saturation or new information is added to the question explored by the researcher. While analyzing qualitative data, the analyst can code responses based on codes developed before data collection (deductive) or after data collection (inductive). This lends a structure to the data where responses can be arranged under specific themes. Combining different research methods to study issues is known as mixed-methods research, and in this study, the findings from quantitative and qualitative studies were triangulated to supplement relationships found or not found in these studies. This case study focuses on the planning and designing of a mixed-methods study, the data collection processes, and the challenges one has to be prepared.