1. Thematic Analysis

Question 1

What is qualitative research

Answer 1

• Emphasis is on words and feelings
• Fewer participants means deeper analysis
• Particular relevance to answering questions about understanding, opinions, and perceptions
• Range of methods underpinned by shared aims
  Looking at specialised and minority groups to see experiences of particular phenomenon- not looking at big samples and generalising to populations

Question 2

Main emphases of quant and qualitative

Answer 2

• Quantitative methods relate to numbers. Data must be able to be transformed into numbers and presented in terms of statistical patterns/associations.
• Qualitative methods relate to texts (words/pictures) a focus on values, processes, experiences, language and meaning. Qual methods provide:
• understanding of a topic in its contextual setting,
• provide explanations and accounts of why people do the things that they do,
• can help evaluate effectiveness and aid the development of theories and strategies.
• Not against each other- different tools for different jobs
  Qualitative can be used as a pilot study to generate quant studies- conduct interviews to find out about certain things to create a survey etc

Question 3

how can we use qualitative research?

Answer 3

• undertaken independently in its own right;
• part of a bigger study or trial, to provide deeper understanding of the quantitative (numerical) results;
  used to support the development of quantitative studies by informing or testing survey content and to explore the implementation of quantitative studies.

Question 4

main qualitative data collection methods

Answer 4

• Interviews
• Focus groups
• Observations
  OTHERS include: photo voice, documentary

Question 5

types of qualitative analysis

Answer 5

• Thematic analysis
• IPA (interpretative phenomenological analysis)
• Grounded theory
  OTHERS include narrative analysis, conversation analysis

Question 6

what is thematic analysis?

Answer 6

• Searching through data to identify any recurrent patterns.
• A theme is a cluster of linked categories conveying similar meanings and usually emerge through the inductive analytic process which characterises the qualitative paradigm
• Create themes through the text- co creation between you and the text
• Explicitly interpretative- not there waiting to find them we have to actively create them- not finding significance, up to us to decide what the themes are and where to go with the interview
• Come up with coherent and find evidence in the form of quotations- PSYC2 coursework we will be finding themes and quoting them- cannot do anything you like there is boundaries but within those we come up with theme ideas

Question 7

when can you use thematic analysis

Answer 7

• TA is a method that is
• “essentially independent of theory and epistemology and can be applied across a range of theoretical and epistemological approaches” (Braun & Clarke, 2006).
  Different forms of analysis are not mutually exclusive – you can combine different approaches to fit your research question.

Question 8

analytical considerations

Answer 8

• Analysis is iterative – you need to go back and forth between data analysis and collection and back and forth between data and analytical framework
• Go beyond the surface of your data – interpret and explain don’t just describe
• Inductive (data-driven) vs. deductive (analyst-driven)
• Cannot just explain the data- stuck with a 2:2
• Do not just describe what a theme is about- instead interpret the data and find hidden meanings- what does the theme mean? Look for connotations e.g. colour
  Talk about meanings in relation to theory, literature and research

Question 9

stages of thematic analysis (Braun & Clarke, 2006)

Answer 9

1. Familiarisation
   - Read, re read so youre familiar with your data and note your thoughts
   
   2. Generate codes
      
      • Systematically reduce data from messy heap to organised codes- keep memos
   3. Organise
      
      • Review codes and sort into broader categories/themes
   4. Check and review
      
      • Review themes- are they valid/do they reflect the data
   5. Finalise
      
      • Theme names, aim to interpret and explain topic (not just describe)
   6. Write up
      Detailed analysis of themes in results/discussion- explain what was in the data about each theme and use quotations as evidence

Question 10

familiarisation

Answer 10

• Start by reading your data a number of times (at least two!)
• Active reading – make notes on your initial thoughts, what is interesting in the data, are there any repetitions?
  Keep notes as these will act as the foundation for the next stage of analysis

Question 11

coding data (reduction)

Answer 11

• Work your way through the data in a systematic way
  
  • Code areas that come up a lot or common language used
• Apply label (code using key word/phrase) using Nvivo or by hand
  
  • Look for important parts of the transcripts which look at particular topics
• Review coding as you go
  
  • Make sure they are related to your research question
• You can code a segment of text to multiple codes
• Code generously in relation to your research question
• Code inclusively- remember to keep some surrounding data for context
• Memos- build on your initial note-taking and start to write memos to document and increase the transparency of your analysis

Question 12

creating themes/categories

Answer 12

• Review and consolidate
  
  • Review and consolidate codes into broader categories (i.e., themes)
    
    • Are there any duplicates?
    • Can any codes be amalgamated into higher order codes (emotion example from video)
• Generate
  
  • GENERATE BROADER CATEGORIES AND SUB-CATEGORIES (THEMES)
    
    • Use post-it notes, diagrams or mind maps
• Keep
  Keep writing memos

Question 13

reviewing themes

Answer 13

• Re-read individual themes and allocated data
  
  • Go back to the data and check that all extracts fit into that theme
• If extracts don’t fit into the theme?
  
  • Go back to the stage before stage 4, re-think, and re-categorise as necessary (you don’t want a red sock in a theme called ‘white washing’ – it will turn everything pink and skew the theme’s meaning)
• Review themes in relation to data set.
  
  • Do they reflect the meaning as a whole? (You don’t want themes about types of washing if most of the dataset is about football!)
• If themes don’t reflect the meaning as a whole?
  Go back to the previous stage, re-think and amend the themes

Question 14

define themes and write up

Answer 14

• When your thematic framework is finished, critically consider what each theme is really about and decide on a final name for themes
  
  • Remember to interpret and explain and not just describe!
• Write a detailed analysis of each theme
  
  • What is happening in the data in relation to this theme?
  • How can you explain this?
    Use sub-themes to give your analysis structure and clarity

Question 15

ensuring rigour in qualitative research

Answer 15

• Understand the context
• Comparing themes to pre-existing frameworks
• Triangulation of data/methods
• Researcher triangulation
• Audit trail/memo taking
• Provide thick descriptions and supporting data
• Reflexivity
• Sampling and deviant cases
• Transparency and level of detail
  Context and participants