Introduction

Data analysis involves synthesising the focus group data in a systematic manner to provide information that effectively responds to the research questions. Analysis of textual data can be a challenging task, as it involves identifying the meaning of information which is often in an unstructured and fragmented format because it originated from a group discussion. The large volume of textual data also poses a challenge to the analyst to identify how to segment the data into smaller, manageable parts for analysis. In essence, data analysis ‘is the process of moving from raw interviews to evidence-based interpretations that are the foundation for published reports’ (Rubin and Rubin 2005: 201). Textual data analysis needs to be conducted in a systematic, structured manner so that the conclusions reached are reliable and can be verified. This chapter describes the systematic process of textual data analysis from focus group discussions.

The data from focus group discussions are distinct from other types of qualitative data, because the information is collected from a discussion amongst a group of people. Therefore, the group context and the dynamic nature of a discussion need to be taken into consideration during analysis of the data. There are particular challenges in the analysis of data from a group discussion. First, the interaction between participants in a group discussion often leads to interrupted speech, contradictions of opinion, unfinished ideas, disagreements and misinterpretations between participants.