RMB: Qual analyses & TA, WEEK 10 Flashcards
What is thematic analysis?
- Foundation for other types of qualitative analyses
- Process of identifying meaningful patterns (themes)
- A way or ordering and understanding participants’ social world
- Turning the mess of everyday talk into something meaningful
- Researcher is actively involved in the generation & organisation of these themes
- Good for looking across a data set
- Useful for identifying patterns
- Thematic analysis is flexible, can be used by different theoretical approaches, topics and is a good starting point for those new to qualitative methods
What constitutes a theme in thematic analysis?
• Recurrent ideas, topics, statements etc. that generate a pattern that may explain or add meaning to a person’s (or group of people’s) experiences
• These patterns (themes) are then brought together into a category which is then labelled by the researcher
• No set rules are available to determine a theme
• A theme must answer the research question
Cannot quantitatively measure a ‘key’ theme – if a theme contributes to answering the research question, then it is up to the researcher to decide if it is a key theme
Epistemology - Nature of Knowledge
• our knowledge may dictate our reality because our reality will seem to be based off what we know (how do we know what we know?) > how we come to know what we know in our reality
• Positivism: Human experience is knowable, universal and objective. Researching will lead to the full truth. Direct relationship between perception and true nature of the object and knowledge is seen as passive.
• Contextualism: Knowledge is a consequence of context and accounts, providing some insight into the nature of the truth. No single reality.
- Social constructionism: No claims about nature of reality. Language of ppt is a consequence of historical, cultural and social factors. Researching to investigate an account of the world, doesn’t claim for it to bear the truth. Knowledge is seen as active and shifts over time, creating impact and meaning to people
Ontology - Nature of Reality
- so what can be known and to what extent > what we know
- Basis of ontology is that there is more than one way to elicit peoples beliefs and what they see as real > why they hold these beliefs is the basis of epistemology
- Realism: Believes there is only one universal and pre social reality which holds true
- Critical realism: Accepts there is a pre social reality but is only partly accessed and participants accounts can only give limited insight into the reality of that phenomenon
- Relativism: No one reality, there are multiple which are equally important and participants accounts are a lived account of their reality
Problematic use of thematic analysis
- Thematic Analysis was developed as a way to systematise a general approach to interpreting Qualitative data
- Whilst there have been good examples of Thematic Analysis, there is also evidence of poor practice, characterised by a mashing of other approaches, i.e. grounded theory techniques, use of coding reliability measures, treating TA as one approach, confusing summaries of data domains or topics with fully realised theme
- Procedure is often prioritised over reflexive thought and decision-making > E.g. how many codes should I have? Is my coding accurate? Are my themes right?
- Instead…move towards ‘reflexive Thematic Analysis’ > Centrality of researcher subjectivity and reflexivity. Focus on deliberate, and well-thought-out methodological decisions that allowed for exploration, rather than recipe-following
What is reflexive thematic analysis?
• Associated with reflexivity in Qualitative research
• Researcher as active, and embedded, in the results
• Reflecting on, and understanding your position as a researcher in relation to the topic of study
• Thinking about how you think about the object of investigation and understanding the impact you have on how the topic is investigated
• Methodologically, theoretically, and epistemologically and ontologically transparent
• Being embedded in the decision-making of the project, avoiding recipe-like approaches,
Draws on informed judgement calls, rather than a recipe!
Reflexive thematic analysis: Not ‘getting it’ (them) vs
‘getting it’ (us)
There are several clusters of TA approaches each with different philosophical assumptions
and procedural practices that reflect these assumptions (we call these coding reliability
TA, codebook TA and reflexive TA).
Reflexive thematic analysis: TA is theoretically flexible
In specific iterations of TA, flexibility is more or less constrained by paradigmatic and epistemological assumptions around meaningful knowledge production; reflexive TA procedures reflect the values of a qualitative paradigm, centring researcher subjectivity, organic and recursive coding processes, and the importance of deep reflection on, and engagement with, data
Reflexive thematic analysis: Themes are themes
There are different conceptualisations of a theme – domain summaries versus patterns of shared meaning, underpinned by a central meaning-based concept.
Reflexive thematic analysis: Searching for themes
We now prefer the term ‘generating (initial) themes’ to emphasise that themes are not ‘in’ the data, pre-existing analysis, awaiting retrieval.
Big Q: Organic Processes
• Reflexive TA can be otherwise conceptualised as a big Q or organic process of generating insight
• Big Q’ research: inductive methods used to explore meaning construction
• Focus on philosophy and procedure, rather than tools and techniques
- Researcher, understands, enacts, explains, and justifies methodological decisions
Deciding what kind of qualitative analysis to use
• No ‘right’ or ‘wrong’ – focus is on selecting the most appropriate method
• This should be a considered to be a holistic process
• Focus should be on selecting a method that helps answer the research question.
There are some analytic techniques that afford flexibility and others which do not
Common types of qualitative analyses
• Thematic Analysis: Identification of common themes
• Interpretative Phenomenological Analysis: Attempting to understand participants’ experiences from their perspective (through themes which include descriptive, linguistic and conceptual comments)
• Discourse Analysis: Talk as social action – people convey their social position through their language and language itself is an interaction
• Conversational Analysis: Focus on how interactions are represented via talk and what action the talk represents in naturally occurring conversations (the process of interaction - how it is managed, constructed etc)
• Grounded Theory: Identification of a model/theory generated from the data (no preconceived ideas on what might be found)
Content Analysis: Count frequency of pre-defined behaviour
Features of IPA
• IPA is a methodology in its own right and adheres to a set of philosophical assumptions, TA is flexible to researcher positionality
• IPA and TA both embrace researcher subjectivity, in IPA this is explained by the double hermeneutic
• First hermeneutic: participant making sense of their experiences > Second hermeneutic: researcher making sense of the participants sense-making
- Interviews usually used in IPA > allows exploration of personal accounts + sense-making
- IPA assumes language reflects peoples thoughts, feelings + beliefs
- IPA doesn’t focus on broader social structures which act as constructive forces > prefers personal social contexts
- In-built philosophical assumptions, no flexibility > critical realism
- focus on personal experience + meaning-making
- Relies on small samples for depth of interpretation
Differences between IPA and TA
• Similarities in coding, but they tend to be more detailed and may draw on metaphor, psychological processes, and language use (i.e. pronouns)
• Similarities in thematic structure, but they tend to be more formalised, detailed, and individualised in IPA
- TA doesn’t need to be focused on the individual, can be used for groups e.g. focus groups
- TA is theoretically flexible > no assumptions made
- TA can use a broader approach using social discourses
- TA looks across datasets rather than focus on individual ones
- TA can be used on larger/more varied samples