Qualitative Methods Flashcards
Qualitative research
Relativist approach
Not one reality, aim to discover many
Takes into account people’s subjective experience of reality
Inductive: start with observations -> theory formed
Aim to find general themes, not one best answer Qualitative analyses (focus on content), emphasis on words
Relativism
Objectivity is not gold standard of correct research- cannot truly be obtained by humans-> interpret findings
Different assumptions needed to examine complex phenomena
Subjectivity is inevitable
Subjective influences explored through reflexivity:
- researcher reflects upon own attitudes, values, experiences, social and political context
Relativist position
Views realism as problematic as it is impossible to compare our representations of world with underlying reality
Truth is created and sustained through subjective social processes
How people make sense of the world regardless of how accurate they may be
Peoples perspectives, beliefs, experiences thoughts by listening to accounts
Interviews
Most common method of data collection
Subjective interpretations of individual experience
Exploratory and acknowledge diversity of human experience
Structured- set questions
Semi structured- some set Q’s, flexibility
Unstructured- conversation around a theme
Types of questions
Closed
Open
Leading
Non leading
Probes
Role of interviewer
Interview as social interaction
Role of interviewer key
Consider how influence the interview
Data is ‘co-produced’ depends what interviewer focuses on and what ppt chooses to present
Steinar Kvale 10 criteria of a good interviewer
1) knowledgeable and familiar with the topic of interview
2) clear- questions are simple, easy and short
3) structured- explanation of the structure and purpose
4) gentle- let people finish what they say
5) sensitive- listen
6) open- respond to what is important to interviewer
7) steering- know what is needed to find out, use questions and prompts
8) critical- prepared to challenge what is said
9) remembers- what has been said, refers back
10) interprets- summarising what has been said
General set up and practicalities
Choose a quiet room and consider safety and confidentiality
Check equipment
Toilets/ fire exit etc
Start with intro of purpose of research, be relaxed and friendly, check ppt ready to start
Check consent
Learn questions off by heart if possible
Maintain active listening and respond to what the person is saying
End well
Transcription
Systematic representation of language in written form
Orthographic
Word for word (vertabim)
Focuses on what words were spoken
Non- orthographic / phonetic
Not just words but non-verbal features
Paralinguistic (pauses, tone of voice, laughter, volume)
Extralinguistic (body language, gesture, facial expressions, gaze)
Focus on how words are spoke and how other people reacted
Playscript
Orthographic, vertabim record
Repetitions, hesitations, false starts etc are transcribed
Researcher decides whether to transcribe er, um, pauses etc
Used for analysis of the meaning of talk, thematic or phenomenological analysis
Investigates meaning- related aspects of spoken language
Do not take into account non verbal features
May miss key aspects of nature of interaction
Jeffersonian
Captures what was said and the way in which it was said
Reflects interview as social interaction
Transcribed according to set of symbols representing the non-linguistic features
Captures paralinguistic and extralinguistic features
Used for conversation analysis (talk-in-interaction), phonetic / phonological analysis
More systematic
Harder to learn, very time consuming
Less widely applicable
Positivism
One reality
Realism
Objective knowledge
Quantitative data collection
Universal laws
Pre existing truth
Post positivist / critical realism approach
Some subjectivity in research
Conducted in a social context
Research can produce knowledge that is more than accurate
Perception of reality comes from within as well as without
Perception of world, things around us, what makes sense of self-> complex interaction
Reality= ‘controller hallucination’- people agree on some truths
Everyone experiences a different reality, based on experiences, but shared biological mechanisms driving perception
Thematic analysis
Extract common topics and themes
Use of quotes to illustrate
Deductive: theory driven- based on theory
Inductive: data driven- based on data
Grounded theory: start with data, develop themes to generate theory
Phenomenological analysis: analysis of persons interpretation of a topic
Thematic analysis as basic method
Theoretically flexible
Suited to wide range of interests and theoretical perspectives
Works with wide range of research questions
Used to analyse different types of data
Works with small and large data sets
Involves core analytic processes common to most forms of qualitative research
What are themes?
Meaningful and coherent pattern in data
Represent concepts in the data
Created from our interpretation of the data
Must recur within and between accounts
Must be distinct from one another- minimal overlap
Allow data to be categorised and organised
How to create themes
Braun & Clarke
1) familiarisation with data
2) generating initial codes
3) switching for higher order themes
4) reviewing themes
5) defining and naming themes
6) writing up
Familiarisation with the data
Common to all forms of qualitative analysis
Researcher immersed herself in the data, becomes familiar with it
Transcribing, reading, re-reading, listening
Noting initial observations
Coding
Generating short labels for important/ interesting features of data relevant to research question
Every data item coded systematically
Capture a semantic and conceptual reading
Essential for systematic and deep engagement with data
Codes must be specific and work independently of the data
Match all codes to relevant extracts from the data
Generating themes
Themes are generated from codes- searching for similarities in the codes
Themes should be coherent and defined clearly
Researcher actively constructs themes
Collate all data relevant to each theme
Reviewing themes
Checking the themes work in relation to the coded extracts and full data-set
Reflect on whether themes are convincing
Define the nature of each theme, relationship between the themes
Refining theme structure- merge, split or discard
Create thematic map
Defining and naming themes
Write a detailed analysis of each theme
What story does this theme tell
How does this theme fit into the overall story about the data
Identifying the essence of the theme and constructing a concise informative definition and name for each theme
Writing up
Integral element
Involves weaving together the narrative and selected data extracts to form a coherent story
Final opportunity for analysis
Contextualise your analysis in relation to existing literature
Produce a scholarly report
Common errors
Providing extracts of data with little or no analysis
- use extracts to support an analysis beyond the specific content
- interpret the data
Using the interview questions as themes
- conduct analysis across the data, attention to content of responses
- don’t simply describe different responses
Weak or unconvincing analysis, themes not coherent
- provide relevant examples
- all themes should cohere around central idea
Mismatch between data and analysis
-check your data extracts support your interpretation
