Thematic Analysis

Question 1

What is thematic analysis and what is it used for?

Answer 1

A method that is used to identify, analyse and synthesise patterns or themes across a data set. It can help to develop an in-depth understanding of participants’ experience.

Question 2

What are some practical contexts that thematic analysis can be applied to?

Answer 2

It can be used for social as well as psychological interpretations to inform policy, to guide applied research e.g. in a trial or intervention development, and work with patients or public research as collaborators.

Question 3

What are the six main steps of thematic analysis?

Answer 3

1. Familiarise yourself with the data: transcripts, noting
2. Generating initial codes: collating relevant data
3. Searching for themes: potential themes
4. Reviewing themes: checking if they work in relation to coded extracts (level 1) and entire data set (level 2)
5. Defining and naming themes: ongoing analysis to refine specifics
6. Producing report: selection of extracts, final analysis relating to research qs/literature

Question 4

What are the differences in inductive and deductive/theoretical research?

Answer 4

Inductive: bottom up, not driven by theoretical background, themes linked to data, research q may evolve during analysis, little resemblance to interview qs, no pre-defined coding frame

Deductive/theoretical: top down, driven by theoretical interests, themes linked to theory, research q or interviews, specific research q, may use a pre defined coding frame

Question 5

What are the differenes between data corpuses, sets, items and extracts?

Answer 5

Corpus- all data collected
Data set- all data from corpus used for a particular analysis
Item- piece of collected data
Extract- Identified chunk of data item

Question 6

What are data themes made up of?

Answer 6

Building blocks which can be seen as the codes, capturing something important about the data in relation to a research q; the key is the significance of the theme in relation to research

Question 7

How can data themes differentiate from data codes?

Answer 7

Themes capture common recurring patterns across data sets whereas codes tend to be more specific than themes and capture a single idea associated with data segments

Question 8

What are some questions that may be asked to go beyond the ‘surface’ of the data?

Answer 8

Asking what the theme means, the assumptions underpinning it, implications of this theme, conditions likely to have given rise to it