Qualitative analysis Flashcards
What are the different forms of Transcription in qualitative analysis?
- Orthographic is most common – speech is transcribed verbatim using standard spelling conventions (play type script)
- More complex forms take account of different aspects e.g. Jefferson system
Prosody (phonemic aspects of spoken language e.g. intonation, stress)
Paralinguistics (non-phonemic aspects of language e.g. serious or jocular)
Extralinguistic (non-linguistic aspects e.g. gesture)
What do different qualitative data analyses have?
Different philosophical principles underlying them
What is thematic analysis?
- Method for identifying, analysing and reporting patterns (themes) within data
- It minimally organises and describes you data in rich detail
- However, frequently it goes further than this, and interprets various aspects of the research topic
- It is very flexible – you don’t need to have a particular philosophical position/ viewpoint to use it, e.g. sematic or latent; inductive or deductive, essentialist or constructionist
- Relatively easy and quick to learn and do
- Accessible to novice researchers
What does thematic analysis do?
- Summarises key features of a large body of data
- Highlight similarities and differences across a data set
- Can generate unanticipated insights
- Allows for social and psychological interpretations of data
- Results accessible to educated general public – useful for producing qualitative analyses suited to informing policy development
What are the six phases of thematic analysis?
- Data familiarisation – reading the data
- Generating codes – labelling ideas in the data that are relevant to the RQ
- Searching for themes – grouping related codes into candidate themes
- Reviewing themes – checking themes ‘fit’ the data and address the RQ
- Defining and naming themes – describing themes and selecting data extracts
- Producing the report/ paper – writing introduction, method, findings and discussion
What should you think about when orienting the analysis?
- The flexibility of TA is a key benefit but it is important to be clear about assumptions and theoretical framework
- What is the theoretical framework? Critical realist perspective which recognises the socially constructed nature of our understandings of reality and theorizes language as shaping the meaning of social and interpersonal worlds
- Inductive of deductive? Inductive approach – codes and themes were derived from the data, focusing on the experiences of the participants, rather than using rpe-defined set of concepts and assumptions
- Sematic or latent meanings? Both – describing ideas present in the data and the underlying meanings
What is data familiarisation?
- Reading and re-reading data (typically interview transcripts)
- Keep the research question in mind and make initial notes on first impressions – what is the obvious meaning of the data
- Aim for data immersion rather than analysis
- Tempting to turn initial impressions into themes but it is important not to rush the process to avoid being anecdotal
What is coding and what are first and second order codes?
• Codes identify a feature of the data (semantic content or latent) that appears interesting to the analyst and refers to ‘the most basic segment, or element, of the raw data or information that can be assessed in a meaningful way regarding the phenomenon
• Coding turns ideas about the data into concise labels ‘tags’ that can be understood independently of the data
• 1st order: often called descriptive or semantic, describes an idea/ feature of the data in the researcher’s own words. E.g.
- ‘sense of confidence in self and abilities’
- ‘having a large number of jobs’
• 2nd order: often called abstract, latent or interpretative, captures the underling meaning of an idea/ feature of the data. E.g.
- ‘structure and order in important’
- ‘Civvy colleagues are inefficient’
• Coding is a shift towards a systematic engagement with the data
• There is no definitive or accurate set of codes hidden in the data. Codes do not ‘emerge’ from the data
• The researcher creates a plausible and coherent set of codes based on the data and their own knowledge and skills
• Often code and recode the data a number of times as the researcher’s understanding of the data develops.
What is theme development?
• Searching for themes
• 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
• It has a ‘central organizing concept’ that brings the codes together
• ‘Searching’ is an active, constructive phase, shaping the codes into a coherent story that makes sense of the data
• At this stage, can be helpful to group codes into categories or candidate themes, these are tentative, temporary themes which may be problematic at first and refined as the analysis progresses e.g. post-it note approach
• Once you have a group of codes together you need to think of a theme heading. E.g.
- Army values constructed as superior to civilian values
• Themes need to be coherent and balanced
What are useful guiding questions to consider when reviewing and writing themes?
- Is this candidate theme evident across more than one or two data items? Or just a description of a specific interviewee
- Does each theme have a centrally organising concept? Or is there overlap between the themes? (shouldn’t have overlap)
- Do the themes answer the RQ?
- Do the themes capture all (or most) of the codes?
- Is there a clear fit between the themes and the data?
What does it mean that qualitative analysis is an iterative process?
making progress can mean returning to earlier phases of the analysis (e.g. coding and searching for themes)
What should you consider when defining and naming themes?
- theme names need to be concise, informative and catchy
- Thematic maps help you to see the overall structure of the analysis. Though each theme is distinct, they should form an overall story
What should you do when theme writing?
- Determine the exact ‘story’ told by each theme and overall. The ‘story’ is the analytic narrative built around data excerpts to tell the reader what you think is going on in the data, why this is important for your research question and why the reader should care about it.
- Select data extracts that provide clear and compelling illustrations of the point demonstrated in the analysis. Important to draw from across data set to provide evidence of a pattern in the data. Must also provide an interpretation of the data – ‘data do not speak for themselves’
- Write a theme definition i.e. an extended central organising concept
- Create good theme names that signal the focus and scope of the theme. Aim to be concise, informative and catchy (Braun and Clarke, 2012)
What key aims of qualitative research does a theme demonstrate?
- Describing variation in experience
- How meaning is constructed
- Focus on process