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Research 2 > Qualitative- thematic analysis > Flashcards

Qualitative- thematic analysis Flashcards

1
Q

Thematic Analysis

A

Thematic analysis involves the searching across a data set…to find repeated patterns of meaning.

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2
Q

What Constitutes a Theme?

A

A theme captures something important about the data in relation to the research question, and represents some level of patterned response or meaning within the data set.

there’s no hard rule about the prevalence of a topic in the data set for it to be a theme

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3
Q

Inductive thematic analysis

A
  • themes found within the data
  • data-driven
  • no or little reliance on pre-existing codes or theories
  • coding the data without trying to fit it into a preexisting coding frame or theoretical framework
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4
Q

Deductive/Theoretical Thematic Analysis:

A
  • applies existing theoretical frameworks to data to generate codes
  • eg: heterosexuality, the researcher may look for sex-drive discourse, have-hold discourse, permissive discourse, hegemonic masculinity
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5
Q

Semantic Themes

A
  • interpretive paradigm
  • not looking beyond the participant’s words
  • describes and summarizes what participants say and discuss broader implications
  • focus on individuals
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6
Q

Latent themes

A
  • social constructionist paradigm
  • identify underlying social forces, assumptions that shape the content of the data
  • focus on social forces
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7
Q

4 types of research questions

A
  1. overall research questions: ‘how is lesbian and gay parenting constructed?’
  2. narrower research question:
    - How is lesbian and gay parenting normalized
    - How are heterosexual parenting ideals present in constructions of lesbian/gay parenting
  3. questions you ask your participants
  4. questions that guide coding and analysis of the data
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8
Q

Data analysis

A
  • starts when you are collecting your data, transcribing it etc
  • coding and recoding
  • Writing is part of analysis NOT just end product
  • Data analysis is a cyclical process
  • Is a constant moving backward and forward between whole data set and coded sections
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9
Q

Engaging in Literature before analysis?

A

Depends on your type of analysis
Inductive vs Theoretical

Pro’s and Con’s of engaging in literate first:
Enhancing vrs Restricting analysis

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10
Q

Transcription

A
  • Transcribing is hard work, time consuming (10:1 hour ratio)
  • Verbatim: Do not change word order, or summarise.
  • Transcription about more than just words: NB to record: Pauses (and lenghs of pauses), laughs,gestures, emotions, emphasis, anger.
  • Transcribe your data as soon after the interview as possible to capture non-verbal elements
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11
Q

Phases of Thematic Analysis (Braun and Clarke)

A
  1. familiarizing yourself with the data
  2. generating initial codes
  3. searching for themes
  4. reviewing themes
  5. defining and naming themes
  6. producing the report
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12
Q
  1. Familiarizing yourself with your data
A

Immerse yourself in the Data:

  • Transcription
  • Listen to your interviewer recordings
  • Read, read and re-read your transcripts
  • Start making preliminary notes
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13
Q
  1. Generating initial codes
A
  • Selecting segments of data that appear interesting to you to, in relation to your research
  • Some codes will eventually become parts of themes, other codes might be discarded
  • A code may end up belonging to more than one theme
  • You will code and later recode (circular process!)
  • Expect contradictions in your data!
  • How to code: Highlighters, Software, Copy and past in word doc?
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14
Q
  1. Searching for themes
A
  • You will now have:
  • -a long list of codes
  • -And many extracts of data (quotes) that belong to these codes
  • Now you need to organize the codes into broader themes
  • How can different codes combine to form an over-arching themes?
  • Some themes are likely to have sub-themes (theme within a theme)
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15
Q
  1. Reviewing Themes
A
  • Your initial themes might later merge into a broader themes
  • You might realise some themes aren’t themes at all
  • Some themes might need to be broken down into separate themes
  • Look at your extracts, do the themes do justice to your participants’ words?
  • Go back to your transcripts, do your themes really reflect your data?
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16
Q
  1. Defining and Naming themes
A
  • Define the essence of each theme
  • For each individual theme conduct and write a detailed analysis.
  • Assess how your individual themes fit into the broader “story” of your data
  • Assess what your themes say about your research question
17
Q
  1. Writing up the research report
A
  • Don’t just summarise or paraphrase what your participants said according to each theme
  • Do explain what implications each theme has for your research question. What does this theme say about your topic?
  • Use quotes/extracts from your data to provide evidence of your themes and help the reader to understand the theme
  • Link your findings and interpretations to literature on the topic
18
Q

Some questions your write-up should cover

A
  • ‘What does this theme mean?’
  • ‘What are the assumptions underpinning it?’
  • ‘What are the implications of this theme?’
  • ‘Why do you think this theme was so prevent in the data? (eg social forces?)
  • ‘Why do people talk about this thing in this particular way (as opposed to other ways)?’
  • What was NOT said?
  • ‘What is the overall story the different themes reveal about the topic
19
Q

critique of thematic analysis

A
  • Pays little attention to the context of the interview
  • Breaks up/fragments participants’ narratives too much

Usually neglects to explore:

  • Why people may be invested in telling certain stories
  • What makes the telling of certain stories possible
  • The relationship dynamics interviewer-participant
  • Limited in examining the complex and subtle ways in which language is used.
20
Q

solution to thematic analysis critique

A

six and match with other more critical methods.

there is no hard/fast rule

21
Q

Key Issues in Qualitative Analysis

A
  • Importance of language
  • Silences, ambiguity & contradiction: You will find contradictions in your data, don’t hide them, embrace them.
  • Intuition & creativity
  • Reflexivity Importance of interview context
  • Importance of broader context
  • Links between raw data and interpretations
  • Linking interpretations to the literature

Research 2 (28 decks)

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