Qual Methods 2 Flashcards

1
Q

What is thematic analysis?

A
  • A method used to identify and analyse patterns across a text-based data set.
  • Foundational method that underpins many other approaches in qualitative research.
  • Flexible approach – can be used with a wide range of data sources and epistemological standpoints.
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2
Q

What is a theme

A
  • A theme is a patterned response in your data set that has meaning in relation to the research question.
  • No rules to help you classify themes (e.g., % of instances or length of response).
  • Prevalence may or may not be important - it depends on your research question:
  • Most common ways X is described
  • What people think of X
  • Why people enact X
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3
Q

Types of thematic analysis

A
  • Inductive TA – data-driven with extracted themes grounded in the data (while acknowledging researcher subjectivity).
  • Coding an accurate representation of the content in the entire data set.
  • Deductive TA – uses existing theory to guide analysis and the extraction of themes. It moves beyond the semantic meanings offered in the data set.
  • Detailed and nuanced approach to coding with one theme or a small group of themes across the whole data set.
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4
Q

Six phases of thematic analysis

Braun and Clarke 2006

A
  1. Familiarising yourself with your 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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5
Q

Familiarisation

A
  • “Transcribing data, reading and re-reading the data, noting down initial ideas” (Braun & Clarke, 2006).
  • Get to know your data
  • Repeated reading of your WHOLE data set
  • Active reading
  • End phase by making notes on overall observations on the data set
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6
Q

Generating initial codes

A
  • Coding interesting features of the data in a systematic fashion across the entire data set, collating data relevant to each code.
  • Coding: Process of identifying aspects of the data that relate to the research question.
  • Coding - inclusive, thorough & systematic, work through each data set item before proceeding to the next.
  • Codes provide the building blocks of analysis.
  • Approach to coding depends on the type of TA.
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7
Q

Coding can be done at the semantic or the latent level of meaning.

A
  • Semantic codes:
  • Provide a succinct summary of the explicit content of the data.
  • Based in the semantic meaning of the data.
  • Typically stay close to content of the data and to the participants’ meanings.
  • Latent codes:
  • Go beyond the explicit content of the data & provide an interpretation about the data content.
  • Invoke the researcher’s conceptual & theoretical frameworks to identify implicit meanings within the data.
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8
Q

Searching for themes

A
  • “Collating codes into potential themes, gathering all data relevant to each potential theme” (Braun & Clarke, 2006).
  • Reviewing codes & collated data relating to each code to identify similarity and overlap between codes:
  • Broad topics or issues around which codes cluster?
  • The basic process of generating themes & subthemes:
  • Cluster codes - sharing some unifying feature, so they reflect & describe a coherent and meaningful pattern in the data.
  • Starting to explore relationship between themes & how themes will work together to tell an overall story about the data.
  • End phase with a thematic map/table outlining candidate themes. Collate all data extracts relevant to each theme.
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9
Q

Reviewing the themes

A
  • “Checking if the themes work in relation to the coded extracts and the entire data set, generating a thematic ‘map’ of the analysis” (Braun & Clarke, 2006).
  • Do your tentative themes form a coherent pattern?
  • The codes within a theme should fit together meaningfully and be relevant to your research question.
  • Each theme should be distinct from another one.
  • Re-read WHOLE data set: codes may get discarded, new data coded and theme boundaries may get reworked.
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10
Q

Defining and naming themes

A
  • “On going analysis to refine the specifics of each theme, and the overall story the analysis tells; generating clear definitions and names for each theme” (Braun & Clarke, 2006).
  • Clearly define themes - need to be able to clearly state what is unique & specific about each theme & determining what aspect of the data each theme captures.
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11
Q

Producing the report

A

“The final opportunity for analysis. Selection of vivid, compelling extract examples, final analysis of selected extracts, relating back of the analysis to the research question and literature, producing a scholarly report of the analysis” (Braun & Clarke, 2006).

  • This is not a descriptive process –
  • Construct a narrative that explains the theoretical significance of your themes.
  • Provide support for your themes - limited, but vivid data extracts to support your argument.
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