Week 1-Thematic Analysis Flashcards
What is Qualitative Research?
-Emphasis is on words and feelings
-Fewer participants means a deeper analysis
-Particular relevance to answering questions about understanding, opinions, and perceptions
-Range of methods underpinned by shared aims
-10-12 participants are an ideal number
-Qualitative analysis is not meant to be generalisable so being un-generalisable is not a weakness
What do Quantitative Methods relate to?
Quantitative methods relate to numbers. Data must be able to be transformed into numbers and presented in terms of statistical patterns/associations.
What do Qualitative Methods relate to?
Qualitative methods relate to texts (words/pictures) a focus on values, processes, experiences, language and meaning.
What do Qualitative 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 (Strategies for how to deal with something e.g., health problems)
What can Qualitative Research be?
-Can be undertaken independently in its own right
-Be part of a bigger study or trial, to provide a deeper understanding of the quantitative (numerical) results
-Be used to support the development of quantitative studies by informing or testing survey content and to explore the implementation of quantitative studies.
What are the main qualitative data collection methods?
-Interviews
-Focus groups
-Observations
-OTHERS include: photo voice, documentary
What are the types of Qualitative Analysis?
-Thematic analysis
-IPA (interpretative phenomenological analysis)
-Grounded theory
-OTHERS include narrative analysis, conversation analysis
What is Thematic Analysis?
-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
-Looking at patterns of who is telling us the same thing (i.e., there’s always something in common with those experiencing similar situations)
-Categories=codes
What is Thematic Analysis according to Ely et al.,(1997)?
“Can be misinterpreted to mean that themes reside in the data, and if we just look hard enough, they will emerge. If themes reside anywhere, they reside in our heads from our thinking about the data and creating links as we understand them”
When can you use Thematic Analysis?
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.
-You can always use thematic analysis as it’s not tied to any theoretical position
What are some Analytical Considerations?
-Analysis is iterative – you need to go back and forth between data analysis and collection and between data and analytical framework (iterative = you go back and forth with the data analysis constantly refining your analysis and questions where further data collection may occur i.e, constant adjustments).
-Go beyond the surface of your data – interpret and explain don’t just describe (Describing is just saying the theme you’ve found and quotes: will just be stuck at a 2:2!)
-Inductive (data-driven) vs. deductive (analyst-driven)
What are the stages of thematic analysis?
(Braun & Clarke, 2006)
- Transcribe and immerse yourself in the data - familiarise
- Develop initial codes - generate (Codes=summary of a line or paragraph and its meaning)
-Try to make codes more informative and avoid them being one word e.g., “boredom is caused by waking up early” is better than just “boredom” - Searching for themes - organise
- Review themes – re-read, check and amend
- Define and name themes – finalise
- Write the report – write-up
What is involved in Step 1 Familiarisation?
-Start by reading your data several 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
What is involved in Step 2 Coding? (Data Reduction)
-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 keyword/or phrase - you can do this by hand or using Word/NVivo (Code areas that come up a lot or common language used. 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 do this on a selection of transcripts to generate a coding framework (20-30%)
-You’re not looking for everything in your data (i.e., not everything is relevant could just say it’s off-topic)
What are 4 Coding tips?
- You can code a segment of text to multiple codes.
- Code generously to your research question.
- CODE INCLUSIVELY – remember to keep some surrounding data for context (Code inclusively basically means don’t have too long a quote or too short i.e., 2-3 words).
- MEMOS – build on your initial note-taking and start to write memos to document and increase the transparency of your analysis.
