Methodology: Thematic Analysis Flashcards
What is thematic analysis?
A method that analyses qualitative data by finding patterns and themes within a data set.
Why should thematic analysis be used?
- It allows for flexibility in what the researcher wants to find with specification on any theory
- It provides rich, detailed data
- Can be used to analyse transcripts, secondary data, media, etc
Define ‘data corpus’.
A large collection of qualitative data texts being analysed for research.
Define ‘data set’.
A collection of related sets of qualitative data that is composed of separate elements but can be analysed as a whole.
Give an example of a data set in social psychology.
All the answers to an open question in a single questionnaire about obedience.
List the 6 stages of thematic analysis.
1) Familiarisation with the data
2) Coding
3) Searching for themes
4) Reviewing themes
5) Defining and naming themes
6) Producing the report
Briefly describe stage 1 of the process.
1) Familiarisation with the data
- Read through the data corpus
- If it is audio data, transcribe it
- Note any initial analytical observations
Briefly describe stage 2 of the process.
2) Coding
- Initial codes of labels using words or short phrases to identify important features of the data
- It can be done manually or with a software program
- Highlighting or post-it notes are a good way to indicate the origin of codes
- Code as many potential themes as possible
- All the data identified under the same code should be collated
Briefly describe stage 3 of the process.
3) Searching for themes
- Sort all the codes into broader patterns of meaning of themes
- Mind maps and tables are a good way to sort the codes
- Some codes may form main themes or sub-themes, or even get discarded
Briefly describe stage 4 of the process.
4) Reviewing themes
- Refining themes by combining or splitting or discarding on a mind map
- The themes should have a relationship and form a coherent pattern, if it doesn’t then the issue may be with the theme itself or the arrangement of data
- The themes should reflect the data corpus as a whole and the aim of the research
Briefly describe stage 5 of the process.
5) Defining and naming themes
- Each theme should be have a concise name and definition to immediately identify the ‘essence’ of each theme
- The researcher should conduct a detailed analysis on each theme (e.g. how the theme fits with the data as a whole)
- An overall narrative of the data will be formed with a final thematic map
Briefly describe stage 6 of the process.
6) Producing the report
- Final analysis and writing the report
- The audience must be considered to allow for coherent and appropriate language (e.g. writing for a scientific journal or a newspaper)
- Evidence for each theme should be provided
Evaluate 3 strengths of thematic analysis.
1) High inter-rater reliability - two researchers can both code the same data corpus to reach an agreement and remove subjectivity
2) High test-retest reliability - due to the standardised procedure of finding codes and collating them into themes it can be easily replicated for other data sets
3) High validity - qualitative data is rich and detailed that can provide insight into the respondent
Evaluate 3 weaknesses of thematic analysis.
1) Low generalisability - it can get time consuming to replicate this procedure on every open question in a questionnaire and so the sample size may be low to account for this
2) Low validity - the different codes and themes may not fully reflect what the data was trying to get across and so is open to misinterpretation by the researcher
3) Low validity - the data corpus is qualitative and so open to interpretation when identifying codes and themes therefore has an element of researcher bias
