8: Thematic Analysis Flashcards
List the four approaches to thematic analysis.
Content Analysis.
Grounded Theory.
Consensual Qualitative Research.
Generic Thematic Analysis.
Describe content analysis and how it’s done. In modern data analysis, how is it usually done?
Straddles line of quantitative and qualitative. Count the instances of a particular content categories in a dataset, report them.
Computerized methods: Linguistic Inquiry and Word Count (LIWC); word clouds as exploratory qualitative analysis.
Describe grounded theory and how it’s done.
One of oldest qualitative techniques; way to analyze data and generate theory. Data collection and analysis are concurrent, until “theoretical saturation” is reached.
List the four steps to grounded theory. Provide examples.
- Identify Codes: e.g., irritated, hostile, frustrated, sad, fatigued, suicidal.
- Identify Concepts: e.g., anger & sadness
- Identify broad categories: e.g., depression.
- Develop Theory: two components to the way people experience depression.
Consensual qualitative research incorporates elements of what? How is it distinguishable? What epistemological stances does it take? Where is it popular?
Phenomenological and grounded theory.
Use of multiple analysts and auditors, seeking to find consensus among multiple researchers looking at same data.
Primarily social constructionist, with some post-positivist leanings in terms of reliability of measurement.
Popular in North America.
Why do people tend to like the Braun & Clarke (2006) approach to thematic analysis?
Can be used without ascribing to some of the extreme views that some qualitative researchers hold (e.g., postmodernism).
How should you choose a sample for thematic analysis?
Has to be theoretically interesting, convenience sample is inappropriate; only “exceptional” people should be in sample, should exemplify something of interest.
What are the two types of thematic analysis?
Inductive: begin analysis without preconceptions, simply describe what you find.
Theoretical: pay special attention to particular themes in the data which you decide on beforehand.
A thematic analysis will typically focus on what two types of themes? Define each.
Semantic: make no inferences; do not look beyond what participant has said or written.
Latent: examine underlying ideas, assumptions, conceptualizations shaping semantic content of the data, usually using theory (e.g., psychoanalysis).
In thematic analysis, what are the two epistemological views? In clinical psychology, a thematic analysis would most often take what view?
Essentialist/realist: reports experiences, meanings and the subjective reality of participants.
Constructionist: ways in which events, realities, meanings, experiences, etc. are the effects of a range of discourse operating within society.
Essentialist/realist.
There are six steps to conducting thematic analysis. What is the first? What are good ways to go about it?
Familiarizing yourself with the data: read and re-read all of your raw data, taking notes as you go.
Do own interviews and/or transcribe all your own data.
There are six steps to conducting thematic analysis. What is the second?
Generating the initial codes: have to decide on the size of the data items (i.e., split transcript into equal parts). Each item covers an equal unit of meaning.
Then assign a short code which summarizes the content of each data item equally. Codes use language, not numbers.
There are six steps to conducting thematic analysis. What is the third?
Searching for themes: begin to sort the codes into similar groups, called “themes.”
There are six steps to conducting thematic analysis. What is the fourth? What is the ideal goal?
Reviewing themes: cross-check codes with new themes; can themes account for ALL codes?
Ideally, themes would cover ALL the data; in practice, probably be one “garbage bin” theme for things that don’t fit anywhere.
There are six steps to conducting thematic analysis. What is the fifth? At this point, others should be able to do what?
Defining and naming themes: solidify final themes by providing short definition and name that summarizes data concisely, but completely. May be subthemes as well.
Others should be able to use these definitions to look for these sorts of themes in another dataset.