ANALYSING QUALITATIVE DATA
Qualitative data analysis can be time-consuming and subject to bias. This can be reduced by involving at least two people in the analysis who reach a consensus, possibly with an additional person to help resolve disagreements. Biases can also be reduced by having a comprehensive approach to data analysis, including transcribing and reading all the information obtained during data collection (e.g., through focus groups, phone interviews). These transcripts and notes are used to determine the main topics within the data. Usually, this will be closely related to your evaluation objectives and questions asked in the interviews. Once organised into topics, identify the theme that emerge in the data. If the topic is access to day centres, themes could include lack of facilities in the local area, lack of transportation, difficulty trusting family member to someone else's care.
Once you know which themes are coming up in each topic, you can rank these by frequency and compare across topics. These lists should be created independently by two or more researchers/evaluators and any discrepancies discussed and resolved. When the list of topics and themes is finalised, you can summarise the main points brought up in discussions of each theme.
Once you know which themes are coming up in each topic, you can rank these by frequency and compare across topics. These lists should be created independently by two or more researchers/evaluators and any discrepancies discussed and resolved. When the list of topics and themes is finalised, you can summarise the main points brought up in discussions of each theme.