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Samenvatting - Qualitative Research Methods
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Summary of Qualitative Reseach Methods, a combination of the lectures and the handbook advised and written by the lecturer.
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Qualitative Research Methods – Summary Chapter 6-10Chapter 6 Grounded Theory
Distinction “Generic Inductive Qualitative Model” and GT
- GIQM: principles that are often seen as characteristic of qualitative data analysis in general
(who do not necessarily correspond to what GT entails)
Overlaps with what I call pragmatic approaches to Qualitative Data Analysis, which lie in
between orthodox approaches and whatever-works approaches to QDA
o orthodox approaches; prescribed set of steps they expect you to follow to come up
with a great analysis, they have end goals more guidance
o you as a researcher can use anything as long as you come up with a qualitative end
result, that is convincing and believable you have maximum freedom but
minimum direction, have to find out yourself
o in between them = pragmatic approaches = GIQM find this in qualitative research
they tend to start from a set of guidelines (developed from orthodox
approaches/GT) – good to follow the guidelines but don’t have to follow steps, just a
more narrow form of steps to give you a direction
Guidelines in the pragmatic/GIQM approach to QDA (typical features of qualitative research)
1. Focus on research questions that are appropriate for qualitative research.
2. Collect and analyze data in a cyclical manner.
3. Reflect constantly on how data-collection and analysis can be improved.
4. Focus on interpretation of text as opposed to statistical analysis of quantitative data.
5. Apply a three-step coding process. 1 look at data and try to reduce the massive amount
into limited set of quotes 2. find relationships within the quotes 3. choose 2 key quotes to
base your story upon
6. Use writing as a key tool in analyzing (interpreting) data.
7. Sample text, cases or contexts based on their theoretical relevance.
8. Use (fairly) raw data, such as interview extracts or photo’s in presenting the outcome of
data-analysis.
9. Present your findings and their theoretical relevance together in an integrated way.
BUT; doing this =/= doing GT, GT is more than that, pragmatic is a nice middle ground, a little
guidance
Characteristics of Grounded Theory; some essential features of qualitative analysis that your analysis
must meet to describe it as GT
1. Theoretical Sampling Your sample cannot be determined in advance but must change in
function of the developing theory.
, 2. Constant comparative method This does not mean that you are going to compare
predefined concepts, groups or contexts, but the data as a whole and only in later phases will
your analysis be focused more on inductively (!) developed concepts, groups or contexts.
Compare every piece of additional data with the previous one in its totality cte compare
cases however after developing our basic theory we go into a more particular analysis and
compare cases
3. Developing a new theory GT must lead to new theoretical insights: mere testing of
existing theories and/or concepts is insufficient.
4. Theoretical saturation You do not stop collecting and analyzing data when you 'hear
nothing new', but only if you can fully / thoroughly explain or understand certain processes
or phenomena (fully developed concepts) . you reach saturation if you feel like you are not
gaining new insights anymore maybe interview someone else or ask new questions
5. Research questions Doing more than just describing or exploring: fully / thoroughly
explaining or understanding phenomena. Moreover, the research questions will almost
always change in terms of focus during the research.
6. Existing literature Ambivalent / suspicious attitude towards existing literature. Literature
should never determine research regarding the focus and interpretation of data, it can at the
most be inspiring. literature can make you aware but NOT push you in a particular
direction now GT’ers recognize the importance of reading: you can’t go into research with
an ‘empty head’
What to do before coding?
- Basic sampling and then theoretical sampling: see lesson on sampling. How we sample in GT
has to be studied for the exam.
- Drafting data-collection tools (see lesson on interview questions);
- Conducting interviews (see lesson on taking interviews) or observations (see lesson on
ethnography) and typing out data;
Process of coding = 3 phases reducing text to meaningful codes – reducing and integrating codes
– building a focused theory
1. Reducing text to meaningful codes
- Breaking down your data into small pieces.
- Sometimes also referred to as "categorizing", "labeling", "open coding" or "initial coding".
- How? Read text and label a piece of text, read text and label a piece of text...
Ask the following questions:
1. What is this about?
2. How relevant is this for my research?
3. Which code/label should I attach to this?
Coding your data: coding = give meaning to a piece of text (symbols, images,…) – interpret it
and give it meaning that affects your interpretation by asking particular kinds of questions to
the text what is this about? How relevant is it? Which label? GT will ask mainly
question 1 at the beginning of the theories: want you to have an open mind towards your
data – you have to code your data, cannot just read and interpret text
, - "Codes" are labels that give meaning to pieces of text; assigned by the researcher.
- "Fragments" are pieces of text:
Coding word by word (document analysis).
Code line by line or sentence by sentence (interviews).
Code incident per incident (observational study).
In this first phase there is a tension between "coding everything" and "only what is relevant
to your research questions".
We try to solve this in GT by coding as much as possible in the beginning in terms of what
appears to be in the data (regardless of the theoretical relevance), but as you progress you
focus more and more on what seems theoretically relevant. Research questions can evolve
GT gives you freedom – you can code anything, while content analysis is different – you have
to say what you will code – in GT no limit, coding everything that seems relevant
1.1 Phase 1 in Post Positivist GT (PPGT) – Strauss and Corbin
Strauss and Corbin: Open coding is: "The process of breaking down, examining, comparing,
conceptualizing, and categorizing data" (p. 61).
- You ask questions such as "what is this" and "what does it mean" about your data.
- You make concepts by giving meaning to pieces of text, whereby you assign short, more
abstract labels.
Example: we observe bodybuilders in a gym and find that they 'admire
themselves' (not the label 'the respondent looks at themselves in the mirror') and
'give advice' (not the label 'explain exercise to someone else’ ). all concepts
are grouped together in the category ‘admiring’
- At the same time they tell you to already move slowly towards the second phase of coding;
look for connections and link concepts together and create more abstract categories to which
they belong going more abstract: In this phase we will compare the many concepts we
develop and relate or group them, leading to overarching, even more abstract, categories.
And we will then describe those abstract categories in terms of properties and dimensions.
Easiest to compare properties with variables/characteristics and dimensions with
the values of those variables post positivistic logic in this - ° categories described
by the key variables and values attached to these
Example: we observe bodybuilders and identify those who mainly 'train', 'teach',
'converse' and 'admire' (abstract categories); We can then describe those
categories in terms of their "properties" (e.g., which, where, frequency of certain
exercises?) These can vary in terms of their "dimensions", e.g., how many
minutes per exercises?
, - Important step = ° more abstract categories by asking specific questions and making
comparisons such as;
o Asking "who", "what", "where", "why", "how", "how many" questions.
o What if it wasn't the case (flip-flop technique)? re-think the interpretation and
reconsider your own interpretations
o Making comparisons with contexts / positions or actors that are very different (far-
out comparison). for example; compare body builder looking in the mirror and ballet
dancer in the mirror – same reason? Maybe or maybe not helps you to rethink the
interpretations
o Making comparisons with contexts / positions or actors that differ on only one or a
few properties or characteristics (close-in comparison). Comparing someone that is
almost the same but some important features are different e.g. body builder that
is new in the gym looking in the mirror to an experienced body builder – same
reason?
o Studying / questioning extreme points of view, like never, always ... (waving the red
flag).
To make the researchers look at the data in a different (less obvious) way
Qualitative research is about making your own life hard constantly questioning the data
In conclusion: Fragments > Codes > Concepts (through labels) > Categories (properties & dimensions)
<> challenge these categories
1.2 Phase 1 in Constructivist GT (Charmaz)
Charmaz: Initial coding involves: "naming each word, line or segment of the data". Not open
coding but INITIAL CODING – key difference she wants you to stay as close as possible to what is
presented in text (try to keep the codes close to the respondent's meaning (in vivo codes)) and she
wants you to code using actions – in terms of what people DO (‘gerunds’) instead of general themes
Example; A piece of interview transcript where a respondent talks about a conflict between a
patient and a doctor: left side of next slide = 'thematic coding', right side of next slide = 'initial
CGT coding’. CGT = using more codes, more data, less abstract Difference? Series of
codes closer to the data such as ‘asserting self’ and ‘remaining unheard’, rather than ‘conflict
with doctor’
- Advantage:
o allows a stronger notion of agency bc you focus on actions and what people do (she’s
a constructivist, symbolic interactionism, importance of how people DEFINE and how
these definitions form behaviour and how people are not born with the definitions,
but they are constructed)
o does not just reduce something to theoretical concepts stimulates the researcher
to be open to different interpretations of the data because this way you are less
likely to reduce people to one-dimensional types
- She advices the researcher to focus on sensitizing concepts that belong to a constructivist
(Symbolic Interactionist) approach. says you don’t have to be a symbolic interactionist
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