Transcript An Introduction to Qualitative Research

An Introduction to
Qualitative Research
Anna Voce
Department of Public Health Medicine
Resources
• Ulin et al (2002) Qualitative methods: A field
guide for applied research in Sexual and
Reproductive Health. Family Health
International.
• Patton MQ (2002) Qualitative Research and
Evaluation Methods. 3rd Edition. Sage
Publications
• Resource CD
The complementary nature of
research approaches
Approaches to Research
• Positivist
– Objective, stable reality governed by context-free
cause-effect relationships
– Scientific, evidence-based, deductive knowledge
– Research methods structured, replicable,
experimental; results are quantifiable
• Interpretive
– Subjective, socially constructed reality, which
must be interpreted
– Knowledge influenced by multiple realities,
sensitive to context; research aims to uncover the
meaning of phenomena
– Researcher is a co-creator of meaning, brings own
subjective experience to the research, methods try
to capture ‘insider’ knowledge, research
conducted in natural settings
Mixing methodologies
“Let us be done with the arguments of
[qualitative versus quantitative methods]
… and get on with the business of
attacking our problems with the widest
array of conceptual and methodological
tools that we possess and they demand.”
Trow, 1957 In: Ulin et al. (2002) p. 49
“A paradigm of choices rejects
methodological orthodoxy in favour of
methodological appropriateness as the
primary criterion for judging
methodological quality ”
McKinlay JB (1993) In:Baum (1995) p.464
Choosing the appropriate
research methodology
• Quantitative research
– Descriptive (who, how many, where, when, how
often)
– Analytic (why – causal links)
– Applied (test interventions – what change)
• Quantitative methods on their own do not
offer sufficient understanding of the complex
web of relationships between the factors that
determine health and disease
• Qualitative methods help to:
– Explain the factors that influence health and
disease
– Understand how individuals and communities
understand health and disease
– Study the interactions between players who are
relevant to a public health issue
• Answer questions like:
– Why did it happen in that context? Why do some
participate and others not? How do professionals
exert their power?
Example:
Smoking and lung cancer
• Epidemiological research has established the
association b/t smoking and lung cancer
• Qualitative methodology helps to explain:
– The power of tobacco companies and advertising
– Reasons why people continue to smoke despite
the evidence
– Social meaning of smoking (eg among women
and the youth)
Integrating methods
• Match the research methodology to:
- The type of research question
- The nature of the problem being investigated
• Mixing methodologies
– Qual preliminary to QUANT (generate hypotheses)
– Quant preliminary to QUAL (guides purposive
sampling)
– QUANT followed-up by qual (helps interpret
findings)
– QUAL followed-up by quant (tests generalisability)
The process of
qualitative research
The steps in designing a
qualitative study
1. Establish the general problem to be
investigated
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Of interest to the researcher
2. Stating the purpose of the study
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Based on problem analysis
Arises from previous studies
Guided by literature review
Determined by who will use the research
results
3. Develop a conceptual/theoretical
framework for the study
4. Formulate general and specific research
questions (aims and objectives)
5. Select a qualitative research design
6. Select a sampling strategy
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Establish site of the research
Selection of participants
7. Ensure trustworthiness of the study
8. Determine data collection methods and
develop data collection tools
9. Establish how data will be managed and
analysed
10. Interpretation and discussion of findings
11. Prepare research report
Qualitative research designs
Types of qualitative
research designs
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The case study
Ethnography
Grounded theory
Phenomenology
Participatory research
The case study
The Case Study
• Interest is in an individual case rather than in a
method of inquiry
• Data may be quantitative or qualitative
• Focus on what can be learned from the
individual case
• A ‘case’ may be simple or complex
– Single child
– Class of children
Types of case study
• Intrinsic
– The case itself is of interest
• Instrumental case study
– A particular case is studied to provide insight into
an issue or to refine a theory
• Collective case study
– A number of cases are studied jointly in order to
investigate a phenomenon (instrumental study
extended to several cases)
Ethnography
Ethnography
• Rooted in anthropology
• Also called participant observation/
naturalistic enquiry
• Ethno = people
• Graphy = describing something
• Characterised by immersion
Role of the observer
• Complete observer
– Behind one-way mirror, invisible role
• Observer as participant
– Known, overt observer
• Participant as observer
– Pseudo-member, research role known
• Complete participant
– Full membership, research role not known
Amount of time in the field site
Not relevant
Researcher’s Focus of Attention
All details
in the
field
Amount of time in the field site
Not Important
Figure: Focusing in field research (Adapted from Neuman 1997)
Grounded Theory
Grounded Theory
• Rooted in social sciences
• Emphasises the development of theory
• Which is grounded in data systematically
collected and analysed (constant comparative
analysis to produce substantive theory)
• Theory must be faithful to the evidence
• Looks for generalisable theory - by making
comparisons across situations
• Focus is on patterns of action and interaction
Phenomenology
Features of Phenomenology
• Rooted in philosophy
• Central question: what is the meaning,
structure, and essence of the lived experience
of this phenomenon for this person/group of
people?
• How is each individual’s subjective reality
applied to make experiences meaningful?
• Analysis of the language used
Approaches to Participatory
Research
Participatory Action Research (PAR)
• Emphasises the political aspects of knowledge
production
• Concerned about power and powerlessness –
empowerment through conscientisation
(building self-awareness and constructing
knowledge)
• Importance of people’s lived experience –
‘honour the wisdom of the people’
• Concerned with genuine collaboration
• Democratic values
Action Research
• Build action theories - action science
• Aim is to develop effective action, improve
practice, and implement change
• Cyclical process, alternating between action
and reflection
Action-research groups
• Action-learning group – facilitated or selfdirected
– Emphasis on individual learning
– Reflection-in-action
– Reflection-on-action
• Action-research team
– Focus on operational problems
– Facilitated (technical to empowering continuum)
Sampling in qualitative research
Considerations in sampling
• Purpose of qualitative research
– Produce information-rich data
– Depth rather than breadth
– Insight rather than generalisation
• Conceptual rather than numerical
considerations
– Choose information-rich sites and respondents
Common sampling approach
• Purposive sampling
– Not haphzard
– Select information-rich cases
– Not the same as convenience sampling
Purposive Sampling Strategies
• Deviant case sampling
– Information rich cases that are unusual (e.g. In
Search of Excellence)
• Intensity sampling
– Excellent examples of the phenomenon of interest
but not highly unusual cases
• Heterogenous sampling
– Sample people with diverse characteristics to see
whether there are common patterns
• Homogenous samples
– Describe a particular sub-group in depth
• Typical case sampling
– To describe and illustrate what is typical to a
particular setting
• Snowball sampling
– Through informants identify others who know a
lot about the issue
• Opportunistic sampling
– Taking advantage of on-the-spot opportunities
Considerations in sample size
• Saturation
• Redundancy
• Minimum samples based on expected
reasonable coverage, given the purpose of the
study and constraints
Ensuring the trustworthiness of
qualitative research
Criteria for judging the quality and
credibility of qualitative research
• Criteria for judging the quality of qualitative
research specific to the research design
selected
• General criteria inlcude:
– Clear exposition of data collection and analysis
methods
– Generating and assessing rival conclusions
• Alternative themes, divergent patterns, rival
explanations
• Attention to negative cases
– Triangulation
• Methods – interviews, observations, document analysis
• Sources – public/private, over time, different
perspectives
• Analysts – multiple analysts, independent analysis and
compare findings
• Theories – to understand how diferent assumptions
affect findings, illuminate inconsistencies
– Respondent validation
– Reflexivity
• The researcher as research instrument
– Relevance
• Adds to/affirms existing knowledge
• Generalisable to similar settings
Ethical considerations
• Informed consent
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Possible risks and benefits
Voluntary participation
Assurances of confidentiality
Purpose of the research
How chosen to be a participant
Data collection procedures
Whom to contact with questions and concerns
Data Collection Methods
Observation
• Purpose of observation
– Describe the setting
– First-hand experience – assists with analysis
– See what is normally taken for granted or not
easily spoken about
– Confirm perceptions of respondents
• Requires training, preparation and discipline
• Develop an observation checklist
Types of observation
• Observer as outsider - unobtrusive
• Participant observation
• Mystery client technique
Sources of observational data
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The setting
The human and social environment
Historical information
Planned activities
Informal interactions and unplanned activities
‘Native’ language
Nonverbal communication
Unobtrusive observations
Documents
What does not happen
Oneself
Document review
• Negotiate access to important documents at
the beginning of the study
• Can help the researcher to identify what needs
to be pursued further in direct observation and
interviews
• Respect confidentiality – to what extent is the
document a public document?
• Use checklist to guide document review
Interviewing
• Purpose of interviews
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Elicit feelings
Thoughts
Opinions
Previous experiences
The meaning people give to certain events
Types of interviews
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Informal conversational interview
General interview guide approach
Standardised open-ended interview
Closed fixed-response interview
Combination of approaches
Types of questions
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Experience and behaviour questions
Opinion and value questions
Feeling questions
Knowledge questions
Background/demographic questions
Focus Group Discussion
• Purpose of FGD
– Get a variety of perspectives/reactions to a certain
issue
– In a short time
– Mainly for eliciting opinions, values, feelings
Advantages
• Cost-effective
• Quality of data enhanced by group
participants
• Can quickly assess the extent to which there is
agreement or diversity on an issue
• Enjoyable for participants
Limitations
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Restricts number of questions that can be asked
Responses by each participant may be constrained
Requires group process skills
Silences the minority view
Confidentiality not assured
Explores major themes, not subtle differences
Outside of natural setting
Holding a FGD
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Homogenous
Strangers
6-10 people
1-2 hours
2 FGD per type of respondent
Moderator and note taker
Prepare discussion guide
Qualitative data analysis
Stages in qualitative data analysis
• Qualitative data analysis is a non-linear /
iterative process
– Numerous rounds of questioning, reflecting,
rephrasing, analysing, theorising, verifying
after each observation, interview, or Focus
Group Discussion
• During data collection
– Reading – data immersion – reading and rereading
– Coding – listen to the data for emerging themes
and begin to attach labels or codes to the texts that
represent the themes
• After data collection
– Displaying – the themes (all information)
– Developing hypotheses, questioning and
verification
– Reducing – from the displayed data identify the
main points
• Interpretation (2 levels)
– At all stages – searching for core meanings of
thoughts, feelings, and behaviours described
– Overall interpretation
• Identify how themes relate to each other
• Explain how study questions are answered
• Explain what the findings mean beyond the context
of your study
Processes in qualitative data analysis
1. Reading / Data immersion
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Read for content
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Are you obtaining the types of information you
intended to collect
Identify emergent themes and develop tentative
explanations
Note (new / surprising) topics that need to be
explored in further fieldwork
– Read noting the quality of the data
• Have you obtained superficial or rich and deep
responses
• How vivid and detailed are the descriptions of
observations
• Is there sufficient contextual detail
• Problems in the quality of the data require a review
of:
– How you are asking questions (neutral or
leading)
– The venue
– The composition of the groups
– The style and characteristics of the interviewer
– How soon after the field activity are notes
recorded
• Develop a system to identify problems in the data
(audit trail)
- Read identifying patterns
- After identifying themes, examine how these are
patterned
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Do the themes occur in all or some of the data
Are their relationships between themes
Are there contradictory responses
Are there gaps in understanding – these require further
exploration
2. Coding –
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No standard rules of how to code
– Emergent
– Borrowed
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Record coding decisions
– Record codes, definitions, and revisions
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Usually - insert codes / labels into the margins
Building theme related files
– Cut and paste together into one file similarly coded
blocks of text
– NB identifiers that help you to identify the original
source
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Identify sub-themes and explore them in greater
depth
3. Displaying data
– Capture the variation or richness of each
theme
– Note differences between individuals and subgroups
– Return to the data and examine evidence that
supports each sub-theme
4. Developing hypotheses, questioning and
verification
– Extract meaning from the data
– Do the categories developed make sense?
– What pieces of information contradict my emerging
ideas?
– What pieces of information are missing or
underdeveloped?
– What other opinions should be taken into account?
– How do my own biases influence the data collection
and analysis process?
5. Data reduction
i.e.distill the information to make visible the most
essential concepts and relationships
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Get an overall sense of the data
Distinguish primary/main and secondary/subthemes
Separate essential from non-essential data
Use visual devices – e.g. matrices, diagrams
6. Interpretation
i.e. identifying the core meaning of the data,
remaining faithful to to the perspectives of the
study participants but with wider social and
theoretical relevance
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Credibility of attributed meaning
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Consistent with data collected
Verified with respondents
Present multiple perspectives (convergent and
divergent views)
Did you go beyond what you expected to find?