Thematic Analysis

Question 1

Describe thematic analysis

Answer 1

• Uses themes to conceptualise meaning
• Context is important
• Analyse in a non-linear process; there is constant questioning and reflecting
• Identifies themes within a data set
• Organises and describes data in detail
• Flexible approach

Question 2

Define:

• Data corpus
• Data set
• Data item
• Data extract

Answer 2

• All data collected from project
• Selected data that is being analysed to answer a particular question
• Each individual piece of data that is collected to make up the data set
• Individual coded chunk of data that has been identified from the data item

Question 3

What is a theme

Answer 3

• Capture something important about the theme
• Represent level of patterned response/meaning within the data set
• Must be flexible when identifying themes
• Key is being consistent

Question 4

Describe breadth and depth

Answer 4

Breadth = Brief description of entire data
Depth = In detail description of certain parts of data

Question 5

Describe semantic and latent

Answer 5

Semantic = themes identified are within surface meaning only looks at exactly what participant has said
Latent = goes beyond surface meaning, identifies underlying meaning

Question 6

Describe inductive and deductive

Answer 6

Inductive = bottom up, themes identified strongly link to data, themes aren’t driven by researcher’s interests, process of coding data without trying to fit it in to pre-exisitng framework, data driven approach

Deductive = top down, theoretical analysis, themes driven by researcher’s interests, analyst driven approach

Question 7

What are the 5 steps to thematic analysis

Answer 7

1. Familiarising self with data
   - Reading and re-reading
2. Generating initial codes
   - Codes identify specific content that is interesting
   - Code as many potential patterns as there is interest for
3. Search for themes
   - Sort codes into themes
   - Codes that don’t fit into a themes should be discarded
4. Reviewing themes
   - Some themes may not have sufficient data o support them
   - Some themes may need dividing up
   - Needs to be clear distinction between themes
5. Defining themes
   - Define and name themes that have been identified so reader has clear sense of what theme is about
   - Analyse each theme
   - Check whether theme needs a sub-theme
6. Producing report
   - Tell story of data in meaningful way
   - Must have sufficient evidence fro each theme
   - Choose examples of extracts

Question 8

Advantages of thematic analysis

Answer 8

• Simple and easy to learn and do
• Flexible
• Results easy to interpret
• Summarise key features of data

Question 9

Disadvantages of thematic analysis

Answer 9

• ‘Anything goes’ critique

- No set standardised practise