The technique for assessing qualitative data is thematic analysis. Usually, it refers to a collection of texts, such as an interview or a transcript. The researcher carefully looks into the data to find common themes, which are recurring topics, ideas, and patterns of meaning. A lot has been published on thematic analysis by Braun &Clarke.
Types of Thematic Analysis
Now that you understand what thematic analysis is, it’s time to look at the different ways to do it. There are three forms of thematic analysis, which include:
- Coding Reliability Thematic Analysis
- Codebook Thematic Analysis
- Reflexive Thematic Analysis
Let’s examine each of these in turn:
Coding Reliability Thematic Analysis
Except in situations when the codes do not match the data, codebooks used for this type of analysis are normally fixed and hardly ever changed. The advantage of this kind of analysis is that it adds a level of intercoder reliability where coders must agree on the codes used, making the output more rigorous as the element of subjectivity is minimized. In other words, the prejudice inherent in having a single coder decide on themes is diminished when a group of coders agrees on which codes should be utilized and which should not.
Codebook Thematic Analysis
Codebook thematic analysis is often carried out from a deductive standpoint because it uses structured codebooks and established codes after which codebooks are produced. Most of the time, these codes come from a study of the data or an initial analysis of the data. In codebook theme analysis, where a codebook can be made by one or more researchers, deductive coding is often used.
Reflexive Thematic Analysis
It is the most adaptable of the three analysis approaches and does not utilize a codebook (a comprehensive list of code descriptions). As they go through the data using this kind of theme analysis, researchers can modify, eliminate, and add codes. Multiple researchers can work on reflexive theme analysis, although it can also be done alone. When multiple researchers participate in the coding process, it becomes more of a collaborative process where researchers can compile codes based on each coder’s unique discoveries rather than having to reach a consensus.
While dependability thematic analysis and codebook thematic analysis commonly include establishing codes before/at the start of the research process, reflexive thematic analysis typically requires developing codes at a later point of the analysis, which is typical of inductive coding.
Thematic Analysis in Six Phases
Below, experts have shared the method of thematic analysis including a six-phase process for conducting analysis in your dissertation proposal. These phases should be viewed as being completed in order, with each step building on the previous one. Recursive analysis refers to switching back and forth between each level.
These steps should not be thought of as rules, but rather as tools that guide research and make it easier to get involved with and study data in depth.
Stages of Thematic Analysis
- Phase of Familiarisation
- Phase of Coding
- The phase of Generating Themes
- Phase of Reviewing Themes
- The phase of Defining and Naming Themes
- Phase of Writing up
Stage.1: Phase of Familiarisation
To accomplish this, read the material several times until you feel completely at ease with it. If qualitative researcher chooses to do the transcribing themselves, the transcription process will acquaint the qualitative researcher with the data. Braun &Clarke advise drinking wine while carrying out this phase!
Stage.2: Phase of Coding
Thematic coding, which is a type of qualitative data analysis and is sometimes called “thematic analysis”, looks at how words are used and how sentences are put together to find themes in a piece of writing.
This entails creating succinct labels (codes!) that denote significant data characteristics that might be pertinent to addressing the research issue. A complete dataset should be coded, and all of the codes, together with all pertinent data extracts, should then be compiled for further analysis. On the other hand, this stage calls for a good, strong cup of coffee!
Stage.3: Phase of Generating Themes
In this stage, the codes and collected data are examined to find significant, more general patterns of meaning (potential themes). Data is then gathered that is pertinent to each potential theme. The researcher might then use the data to examine each potential theme’s viability.
A single journal article, an undergraduate project, masters dissertation, and a single analytical chapter in a PhD thesis should usually have between 2 and 6 themes and subthemes.
Stage.4: Phase of Reviewing Themes
Candidate themes are compared to the dataset to see if they accurately represent the data and address the research topic. Themes are usually refined, which occasionally entails splitting, combining, or discarding them. In this method, a theme is a pattern of shared meaning that is backed up by a main idea or concept.
Stage.5: Defining and Naming Themes
This phase entails creating a thorough examination of each subject, figuring out its scope and concentration, and figuring out the individual narrative. Additionally, descriptive names for each theme are chosen.
Stage.6: Phase Of Writing Up
In the last step, the analytical narrative and data extracts are put together, and the analysis is put into context by looking at what has already been written. Just like any other academic paper, a thematic analysis needs an introduction that explains the research topic, goals, and method. It also has a methodology section that explains how we gathered the data and how we carried out the analysis.
Themes do not just “emerge” from data or coding; they are not just in the data, waiting for the researcher to find them and extract them. The junction of the researcher’s theoretical presuppositions, analytical tools, expertise, and the facts themselves produces themes, which are imaginative and interpretive stories about the data. The process of developing topics involves the researcher’s activeness.
For novel qualitative researchers, thematic analysis offers an approachable technique. To use the approach effectively, one must have some theoretical knowledge and an awareness of the philosophical underpinnings of the research. For example, this entails comprehending the presumptions underlying consensus coding standards or coding dependability.