Qualitative methods 2 Flashcards
(38 cards)
How much is enough for an interview?
- no strict rules
- depends on:
- the amount of detail
- constraints
- nature of the research
- type of research and the purpose - if it is homogeneous (6-8 cases) or heterogeneous (10-20 cases)
Good semi-structured interview
- Broad topics and some questions
- Pace and direction = depends on the individual
- Don’t refer to interview guide to much
- Steer convo if it goes off topic
Setting up an interview
- entire privacy
- make sure the sound of the environment won’t drown out the conversation
- obtain consent to record and make sure they are aware of the implications of recording
Interviewing process
- knowing your scedual so it can flow
- interviewee = a co-enquirer rather than a research subject
- conversation not questions and answers
- be aware of questioning errors
Ending the interview
- usually from 20-90 mins long
- people find it hard to concentrate over 90 mins
- ask the pp if they would like to add anything
- make arrangements for a follow up interview
- store tape recording in a safe place - and it is password protected
- write process notes
- transcribe the interview
Transcribing
- 60 min interview may take up to 6+ hours to transcribe
- transcribe everything, add fillers, make notes about interpretation
- re-listen to recording and follow transcribed text
- return transcription to interviewee or follow up for confirmation of accuracy of transcription
- do not change word order or summaries
- include pauses, laughs, gestures etc
- transcribe soon after interview so you don’t forget non-verbal elements
What is special about qualitative interviews
- are social encounters - from a place of trust
- not just extracting information
- need to think carefully about how we establish relations with the people we are researching
What constitutes data
- more than just words
- how pps present themselves
- emotions they convey
- identifications
- the relations they establish with the researcher - for example if the pp is male does he talk over his female researcher
- reflexivity
Guidlines to good qualitative research
- be friendly
- treat pps with respect and gratitude
- treat pps as experts
- participants = co-inquirers
- listen intently, encouraging them to elaborate
Feminist research
- empower participants - equal relationship
- democratize research relationship
- research about women by women
- challenges the notion of being mutual and detached
How does qualitative research try correct the methodological issues with qualitative research
- seeing participants as agents and co-producers of knowledge
- giving a voice to the disempowered groups
- participant lead interviews
- Kvale disagrees with this and just says that it is ‘masking the power’ of a researcher
Asymmetric power distribution in an interview
- it is not dominance free - there are hierarchical and instrumental form of conversation where the interviewer sets the stage and script in accordance to the research
- interviewer = seeks understanding; interviewee = serves as a means
- meaning it is a one-way dialogue
- However pps can practice their agency by:
- not answering a question
- talking about something unrelated
- tell the researcher who they believe they want to hear
- start to question the interviewer
- withdraw from the interview
Interviewers monopoly of interpretation
- interviewer hold the monopoly of interpretation
- seen as the big interpreter
- is the only one who can report what the pp really meant
What is thematic analysis
Thematic analysis involves the searching across a data set…to find repeated patterns of meaning (themes).
What constitutes a theme
- something important about the data in relation to your research question
- represents some level of patterned response
- more instances does not necessarily mean the theme is more crucial
the phases of TA - Braun and Clarke (2006) (6)
- familiarize yourself with the data
- generating initial codes
- searching for themes
- reviewing themes
- defining and naming themes
- producing report
Theme 1 of TA
Familiarise yourself with the data
- listen to your interview recordings
- read, read and re-read your transcription
- make preliminary notes
Theme 2 of TA
Generating initial codes
- selecting segments of data that appear interesting to you to, in relation to your research
- some codes will become themes (broader units of analysis) and some you might discard
- codes for as many themes as possible
- a code may end up belonging to more than one theme
- expect contradictions
- code using highlighters, software, stickynotes etc
Theme 3 of TA
Searching for themes
- you will have a long list of codes and extracts of data
- interpretive analysis of the data occurs
- how can different codes combine to make themes
- some themes are likely to have sub-themes
Theme 4 of TA
Reviewing themes
- initial themes might merge into broader theme
- some themes you might discard
- some themes might need to be broken down
- aim for ‘internal homogeneity and external heterogeneity’ - themes should fit together meaningfully, but there should be distinctions between them
Theme 5 of TA
Defining and naming themes
- depends on the satisfaction of thematic map
- you should have an idea of what the themes are
- define the essence of each theme
- determine what aspect of the data each theme captures
- write an analysis for each theme
- assess how themes fit into the broader story
- assess what themes say about your research question
Theme 6 of TA
Producing the report
- analysis should be concise, coherent, logical, non repetitive and interesting of the story the data tells
- don’t just summaries what the pp said in the interview
- explain the implications of each theme
- back up with evidence
- use quotes to provide evidence and help the reader to understand
- link your findings to literature
- tell the story of your data
Pitfalls to prevent in TA
- failure to analyze the data at all
- using interview schedule as themes
- weak/ unconvincing analysis - too much overlap, inconsistent, bad examples
- mismatch between data and analytic claims = UNFOUNDED ANALYSIS
- fails to spell out its theoretical assumptions
Advantages of TA
- Flexibility.
- easy and quick method to learn, and do.
- don’t need experience of qualitative research.
- Results are accessible to educated general public.
- Can usefully summarise key features of a large body of data, and/or offer a “thick description”
- highlights similarities and differences across the data set.
- generates unanticipated insights.
- social as well as psychological interpretations of data.
- Can be useful for producing qualitative analyses suited to informing policy development.