Framework analysis is a systematic method for managing and analyzing qualitative data, particularly useful in large studies. The process typically involves five key stages.
Understanding the Framework Analysis Process
Framework analysis provides a structured approach to qualitative data, moving from initial immersion to the final interpretation of findings. It helps researchers manage large volumes of data by sorting and summarizing it according to themes.
Here are the core stages involved in conducting framework analysis:
Familiarisation
This initial stage involves immersing yourself in the data. It means reading transcripts, listening to audio recordings, and reviewing field notes to gain a thorough understanding of the breadth and depth of the material. The goal is to become intimately familiar with the participants' accounts, perspectives, and the overall context of the study.
- Activities include:
- Reading transcripts multiple times.
- Listening to audio recordings.
- Reviewing any other relevant data like field notes or documents.
- Making initial notes on overarching themes or interesting points.
Identifying a Thematic Framework
Building on the familiarization, this stage involves developing a thematic framework. This framework is an index of codes or categories that will be used to sort and organize the data. It can be developed inductively from the data itself, deductively from pre-existing theories or research questions, or through a combination of both. This framework becomes the structure for the subsequent analysis.
- Steps involve:
- Identifying key themes, concepts, and experiences emerging from the data.
- Creating an index of codes (thematic framework).
- Defining each code clearly.
- Testing the framework on a subset of the data and refining it as needed.
Indexing
This stage involves systematically applying the thematic framework to the entire dataset. Each transcript or data unit is read through, and the appropriate codes from the index are marked against relevant sections of the text. This process helps in categorizing and organizing the data according to the developed themes.
- Process:
- Reading through data line by line or section by section.
- Assigning codes from the thematic framework to relevant data segments.
- Ensuring consistency in coding across the dataset.
Charting
Charting involves summarizing the data by theme. Data that has been indexed under the same code is brought together into charts (often in a spreadsheet or database). Each chart typically represents a theme (row) and each participant or case represents a column. Within each cell, a summary of what that specific participant said or did in relation to that theme is recorded. This creates a matrix that allows for easy comparison across themes and participants.
- How it works:
- Creating matrices with themes (rows) and cases (columns).
- Summarizing indexed data into the relevant cells of the matrix.
- Maintaining references back to the original data for verification.
Mapping and Interpretation
This final stage involves synthesizing the charted data to describe and explain the phenomena being studied. The researcher looks for patterns, connections, variations, and relationships within and between the themes. This stage goes beyond simply describing the data to interpreting its meaning, drawing conclusions, and developing explanations or theories related to the research questions.
- Activities:
- Exploring relationships between themes.
- Identifying patterns, typologies, or causal links.
- Developing explanations and interpretations.
- Relating findings back to research questions and existing literature.
- Writing up the findings.
Here's a summary of the stages:
| Stage | Primary Activity | Goal |
|---|---|---|
| Familiarisation | Immersion in raw data (transcripts, notes) | Understand the data deeply |
| Identifying a Thematic Framework | Develop codes/categories based on data/theory | Create a structured index for sorting data |
| Indexing | Apply codes systematically to the entire dataset | Categorize data segments according to the framework |
| Charting | Summarize indexed data into thematic matrices | Organize data for easy comparison across themes/cases |
| Mapping and Interpretation | Analyze patterns and relationships in charted data | Explain findings, draw conclusions, develop theories |
These stages provide a clear, step-by-step process for analyzing qualitative data, making framework analysis a popular method in fields like health research and policy evaluation.
