Introducing Qualitative Research Flashcards
Qualitative research
Concerned with understanding the meaning of phenomenon
Quantitative is concerned with understanding the cause
Qualitative research should be credible (internally valid), transferable (externally valid), dependability (reliability) & confirmability (objectivity)
Wertz (2014); history of qualitative research
Aristotle’s inquiry’s were qualitative
Darwin’s comparable investigation of emotions & moral sense
Freud used case studies
Piaget, Vygotsky, Bartlett, Zimbardo & Festinger
Kahneman won noble prize
Michell (2003); quantitative imperative
View that studying something scientifically means measuring it
Measurement is thought to be necessary part of science & non-quantitative methods are thought to be pre-scientific
This imperative is motivated by idea that all attributes are fundamentally quantitative
A version of the Kelvin Dictum
When you can not measure it, when you cannot express it in numbers, your knowledge is a meagre & unsatisfactory kind
Michell (2009)
Most quantitative research is based on fact that psych attributes can be measured in quantitative way rather than empirical investigation of issue
Most quantitative researchers adopt a thinking that measurement is simply assignment of numbers to objects & events according to specific rules
Harre (2004)
Social & cognitive phenomena can be represented discursively (words/qualitatively)
Qualitative research as a paradigm
1) Assume there’s no one correct version of reality or knowledge (theres multiple)
2) claims knowledge must not be considered outside of context in which its generalised
3) focus on analysis of words that are not reducible to numbers
4) interested in meaning rather than reports & measuring of behaviour or internal cognitions
5) use of inductive, theory generating theory
6) anti-experimental setting
7) rejection of natural sciences as model of research
8) recognise researcher comes from subjective position
Broad differences between qualitative & quantitative
1) numbers vs words
2) shallow broad data vs narrow rich data
3) deductive theory testing vs inductive theory generating
4) values objectivity vs subjectivity
5) fixed method vs less fixed method
6) quickly completed vs longer time
Ontology
The form of reality
What can be known about reality?
Epistemology
The relationship between the investigatory & what can be discovered
How can we know?
Positivism to post-positivism
Methodology
How does the investigator go about finding out what they believe can be discovered?
Quantitative to qualitative
Ontology continuum
Realism -> critical realism -> relativism
Realism= pre-social reality exists that we can access through research (quantitative)
Critical realism; pre-social reality exists but we can only ever partially know it
Relativism; reality is dependent on the ways we come to know it
Research bias
Research bias fundamentally about trustworthiness/credibility
How to deal with research bias
Reflectivity; constantly thinking about potential biases & how you can minimise their effect
Negative-case sampling; attempt to locate & examine case that disconfirm your expectation
Can demonstrate trustworthiness by
Descriptive validity; shoe that what collected & observes is accurate e.g. multiple investigators
Interpretative validity; how accurate your interpretations portrait what the thinking & feeling of the pp e.g. pp check
Theoretical validity; going beyond concrete description & interpretation to explain succinctly the most amount of data e.g. multiple theories
Methodological integrity
1) fidelity to subject matter
2) utility in achieving research goals- selecting procedures to generate insightful findings that usefully answer their research questions
Subjectivity
Our humanness (subjectivity) should be part of research tool
Research seen as subjective process, cannot cast aside out values, mannerisms etc when doing research
Reflexivity
Requires awareness of researchers contribution to construction of meanings throughout research process
Acknowledgement of impossibility of remaining outside of ones subject matter while researching
Developing a rationale for quantitative research
General-> logical story leading to hypothesis -> specific
Developing rationale for qualitative research
Specific aim-> tell story that contextualises question -> general
Methods of collecting qualitative data
1) full interactive methods- interviews (semi-structured) focus groups
2) vignettes
3) story completion task
Designing a qualitative interview schedule
Brainstorm relevant questions
Opening introducing question & closing clean-up question
Sequence questions (logic flow, cluster topics)
Avoid leading questions
When & why we use focus groups
1) Generate unexpected/novel knowledge
2) open, supportive environment
3) interaction between pp
4) mimic real life
5) diverse views, perspectives or understanding
6) accessing under-represented or marginalised social groups
Issues with focus groups
Pp- homogeneity vs heterogeneity, depends on issue
Sample size- 3-8 pp works best
Saturation- criteria for deciding no more focus group needed, more data wouldn’t contribute to study (no more new perspectives)
What to do in focus group
Need to create map to chart course within session (plan)
To generate discussion between pp
Often use stimulus material (e.g. images, exercises)
Vignettes
Presenting pp with completed story & asking them to respond to series of open ended questions about stories
Must appear plausible & real
Should reflect mundane occurrences
Contain sufficient context for understanding but vague enough to force pp to provide additional factors which influence their decisions
Story completion task
Pp complete or write story
Aims to understand something about the meanings pp construct of reality by the stories they tell
Ideal for researching topics where clear norms dictate social desirable viewpoints
Ideally suited to comparative research design- can compare responses of different groups
Sampling strategies
Quantitative research- random sample, aim for generalisability
Qualitative- purposive, aim for insight/understanding
Sampling about criteria for inclusion & exclusion (heterogeneity, homogeneity or both)
Common sampling techniques in qualitative research
1) convenience- pp accessible to researcher
2) snowballing- networking of researcher or pp
3) stratification- ensures diversity/range of groups
4) theoretical- selection governed by on-going research, what’s required to gain further insight
5) criterion- specific event or issue
Thematic analysis
Method for identifying, analysing, organising, describing & reporting themes found within data set
Code
Read transcripts & note down short comments to sum up segments of data, usually in margins of transcript
Theme
Captures something important about data in relation to research questions
Represents some level of patterned response or meaning within data set
Six steps to analysis
1) familiarisation/ immersion with data- analytic, active, critical
2) generation of initial codes- systematic, manifest (objective, surface, concrete) vs latent (implicit, hidden meaning) content
3) generating themes- collate codes into themes, hierarchy of themes
4) review themes- sub-themes, patterns
5) define & name themes- ensure themes don’t overlap, meaningful hierarchy
6) produce report- evidence of themes
Qualitative report structure
1) joint results & discussion section
2) sub-sectioned by themes
3) see examples for how to deal with data
4) coherent & persuasive argument
5) general discussion section
6) summing up
