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Qualitative research

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  • 1. An Introduction to Qualitative Research Anna Voce Department of Public Health Medicine
  • 2. 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. 3 rd Edition. Sage Publications
    • Resource CD
  • 3. The complementary nature of research approaches
  • 4. 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
  • 5.
    • 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
  • 6. 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
  • 7.
    • “ 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
  • 8. 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
  • 9.
    • 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?
  • 10. 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)
  • 11. 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)
  • 12. The process of qualitative research
  • 13. The steps in designing a qualitative study
    • Establish the general problem to be investigated
      • Of interest to the researcher
    • Stating the purpose of the study
      • Based on problem analysis
      • Arises from previous studies
      • Guided by literature review
      • Determined by who will use the research results
  • 14.
    • Develop a conceptual/theoretical framework for the study
    • Formulate general and specific research questions (aims and objectives)
    • Select a qualitative research design
    • Select a sampling strategy
      • Establish site of the research
      • Selection of participants
  • 15.
    • Ensure trustworthiness of the study
    • Determine data collection methods and develop data collection tools
    • Establish how data will be managed and analysed
    • Interpretation and discussion of findings
    • Prepare research report
  • 16. Qualitative research designs
  • 17. Types of qualitative research designs
    • The case study
    • Ethnography
    • Grounded theory
    • Phenomenology
    • Participatory research
  • 18. The case study
  • 19. 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
  • 20. Types of case study
    • Intrinsic
      • The case itself is of interest
    • Instrumental case study
      • A particular case is st u died 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)
  • 21. Ethnography
  • 22. Ethnography
    • Rooted in anthropology
    • Also called participant observation/ naturalistic enquiry
    • Ethno = people
    • Graphy = describing something
    • Characterised by immersion
  • 23. 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
  • 24. Amount of time in the field site Researcher’s Focus of Attention Not relevant Not Important All details in the field Amount of time in the field site Figure: Focusing in field research (Adapted from Neuman 1997)
  • 25. Grounded Theory
  • 26. 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
  • 27. Phenomenology
  • 28. 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
  • 29. Approaches to Participatory Research
  • 30. 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
  • 31. 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
  • 32. Action-research groups
    • Action-learning group – facilitated or self-directed
      • Emphasis on individual learning
      • Reflection-in-action
      • Reflection-on-action
    • Action-research team
      • Focus on operational problems
      • Facilitated (technical to empowering continuum)
  • 33. Sampling in qualitative research
  • 34. 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
  • 35. Common sampling approach
    • Purposive sampling
      • Not haphzard
      • Select information-rich cases
      • Not the same as convenience sampling
  • 36. 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
  • 37.
    • 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
  • 38. Considerations in sample size
    • Saturation
    • Redundancy
    • Minimum samples based on expected reasonable coverage, given the purpose of the study and constraints
  • 39. Ensuring the trustworthiness of qualitative research
  • 40. 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
  • 41.
      • 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
  • 42.
      • Respondent validation
      • Reflexivity
        • The researcher as research instrument
      • Relevance
        • Adds to/affirms existing knowledge
        • Generalisable to similar settings
  • 43. Ethical considerations
    • Informed consent
      • 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
  • 44. Data Collection Methods
  • 45. 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
  • 46. Types of observation
    • Observer as outsider - unobtrusive
    • Participant observation
    • Mystery client technique
  • 47. Sources of observational data
    • 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
  • 48. 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
  • 49. Interviewing
    • Purpose of interviews
      • Elicit feelings
      • Thoughts
      • Opinions
      • Previous experiences
      • The meaning people give to certain events
  • 50. Types of interviews
    • Informal conversational interview
    • General interview guide approach
    • Standardised open-ended interview
    • Closed fixed-response interview
    • Combination of approaches
  • 51. Types of questions
    • Experience and behaviour questions
    • Opinion and value questions
    • Feeling questions
    • Knowledge questions
    • Background/demographic questions
  • 52. 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
  • 53. 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
  • 54. Limitations
    • 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
  • 55. Holding a FGD
    • Homogenous
    • Strangers
    • 6-10 people
    • 1-2 hours
    • 2 FGD per type of respondent
    • Moderator and note taker
    • Prepare discussion guide
  • 56. Qualitative data analysis
  • 57. 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
  • 58.
    • During data collection
      • Reading – data immersion – reading and re-reading
      • Coding – listen to the data for emerging themes and begin to attach labels or codes to the texts that represent the themes
  • 59.
    • After data collection
      • Displaying – the themes (all information)
      • Developing hypotheses, questioning and verification
      • Reducing – from the displayed data identify the main points
  • 60.
    • 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
  • 61. Processes in qualitative data analysis
    • Reading / Data immersion
      • Read for content
        • 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
  • 62.
      • 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)
  • 63.
      • Read identifying patterns
        • After identifying themes, examine how these are patterned
          • 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
  • 64.
    • Coding –
        • No standard rules of how to code
          • Emergent
          • Borrowed
        • Record coding decisions
          • Record codes, definitions, and revisions
        • 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
        • Identify sub-themes and explore them in greater depth
  • 65.
    • Displaying data
      • Capture the variation or richness of each theme
      • Note differences between individuals and sub-groups
      • Return to the data and examine evidence that supports each sub-theme
  • 66.
    • 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?
  • 67.
    • Data reduction
        • i.e.distill the information to make visible the most essential concepts and relationships
      • Get an overall sense of the data
      • Distinguish primary/main and secondary/sub- themes
      • Separate essential from non-essential data
      • Use visual devices – e.g. matrices, diagrams
  • 68.
    • 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
      • Credibility of attributed meaning
        • Consistent with data collected
        • Verified with respondents
        • Present multiple perspectives (convergent and divergent views)
        • Did you go beyond what you expected to find?

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