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 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

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

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

Qualitative research designs

Types of qualitative research designs 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 Instrumental case study 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 Observer as participant 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

Not relevant Researcher’s Focus of Attention Not Important 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 self-directed 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

Opportunistic sampling 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

General criteria inlcude: 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 Relevance The researcher as research instrument Relevance Adds to/affirms existing knowledge Generalisable to similar settings

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

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 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 Elicit feelings Thoughts Opinions Previous experiences The meaning people give to certain events

Types of interviews Informal conversational interview General interview guide approach Standardised open-ended interview Closed fixed-response interview Combination of approaches

Types of questions 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 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 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 re-reading 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 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

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 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

Coding – No standard rules of how to code Record coding decisions 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

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

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?

Data reduction Get an overall sense of the data 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

Interpretation Credibility of attributed meaning 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?