Thematic Analysis Flashcards

1
Q

Describe thematic analysis

A
  • 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
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2
Q

Define:

  • Data corpus
  • Data set
  • Data item
  • Data extract
A
  • 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
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3
Q

What is a theme

A
  • 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
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4
Q

Describe breadth and depth

A
Breadth = Brief description of entire data
Depth = In detail description of certain parts of data
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5
Q

Describe semantic and latent

A
Semantic = themes identified are within surface meaning only looks at exactly what participant has said
Latent = goes beyond surface meaning, identifies underlying meaning
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6
Q

Describe inductive and deductive

A

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

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7
Q

What are the 5 steps to thematic analysis

A
  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
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8
Q

Advantages of thematic analysis

A
  • Simple and easy to learn and do
  • Flexible
  • Results easy to interpret
  • Summarise key features of data
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9
Q

Disadvantages of thematic analysis

A
  • ‘Anything goes’ critique

- No set standardised practise

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