This document provides an overview of fundamentals of qualitative research. It discusses key topics such as what qualitative research is, developing qualitative research questions, common qualitative research designs including phenomenology, ethnography and grounded theory. It also covers qualitative data collection methods like in-depth interviews and focus groups. The document outlines the process of qualitative data analysis including coding, developing a code structure and analyzing themes. Finally, it discusses different types of qualitative analysis such as thematic analysis, content analysis and narrative analysis.

1. Fundamentals of
Qualitative Research
Admas Abera (MSc, Assistant Professor)
Epidemiology and Biostatistics Unit
School of Public Health,
Haramaya University

2. Overview of the chapter
Aim: To enhance students’ capacity to conceptualize, design and
conduct qualitative research in public health and health sciences.
Topics:
• What is a qualitative research?
• Developing a qualitative research question
• Qualitative research designs
• Data collection in qualitative research
• Qualitative data analysis (overview & types)
• Scientific rigor in qualitative research
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3. What is a qualitative
research?

4. Introduction
“Not everything that can be counted
counts, and not everything that
counts can be counted.”
Einstein
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5. Introduction
• What proportions of people with TB
discontinue their medications after
the intensive phase of treatment in 3-
moths period?
Can be answered Quantitatively
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6. Introduction
• Why do people on anti-TB
medication discontinue their
treatment after the intensive
phase?
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7. What is qualitative research?
“A scientific strategy which helps us to understand complex
social phenomena in natural (rather than experimental)
settings, giving due emphasis to the meanings, experiences
and views of participants.”
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8. What is qualitative research?
• A strategy for systematic collection, organization and
analysis of textual information.
• Uses inductive approaches to generate new insights
into a certain phenomena that are difficult to measure
quantitatively.
• They can characterize participant perspectives and
experiences in great depth
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9. How does Qualitative research
differ from Quantitative
research?

10. Qualitative Quantitative
Mixed
Systematic subjective approach
Approach: Inductive
Aim: To gain insight, explore depth,
generate hypotheses
Focus: complex & Broad
Sampling: Purposeful
Data collection: In-depth
interviews, FGDs, observations:
“Researcher as instrument”
Data Analysis: Iterative/exploratory
interpretation
Basic element of analysis: words
A formal, objective, systematic
process of obtaining information.
Approach: Deductive
Aim: Breadth, to test hypotheses,
examine cause & effect
Focus: Concise & Narrow
Sampling: Random
Data collection: Surveys, secondary
data
Data Analysis: Statistical tests,
Modelling
Basic element of analysis: numbers
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11. What are the goals of qualitative research?
Exploration What are the doctor-patient interaction in ART follow
up?
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Description What are the experiences of ART patients in terms of
taking them regularly and how they cope up with drug side
effects?
Interpretation How has the ART treatment affected the social and
economic life of patients with low income?

12. Developing a qualitative
Research Question

13. Well informed questions are key to
good research.
• Define the purpose of research
• Determine appropriate methodology for the study
• Guide study planning
• Frame analysis and your findings
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14. Topics suited to qualitative research
• The role of organizational context in implementing new
technology or practices
• Complex social processes
• Patient perceptions of healthcare access
• Beliefs, motivations underlying health behaviors
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15. Writing a research question
• State the aim of the study using action verbs
• Identify topic of interest
• Use neutral or non-directional language
• Define the sample and the setting
• Be precise!
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16. Sample qualitative research questions
• Why do women not deliver in health facilities in East Ethiopia?
• What are the behavioral and system level challenges to implement
electronic medical records at Hiwotfana hospital?
• Why do women with breast cancer present late to health facilies in
North-west Ethiopia?
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17. Formulating QUAL Research question
A well-developed research question is essential for the
success of the study
• Invest time in defining the research gap
• Ensure the question is feasible
• Use the research question to guide the choice of the
methods and analysis
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18. Critiquing a research question
Research question:
• The purpose of this research is to understand the knowledge,
beliefs, attitude, preferences and barriers of contraception
among women.
Better:
• To explore barriers of long-acting contraceptives among rural
women at high risk for unintended pregnancy in Ethiopia.
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19. Qualitative research
designs

20. Types of qualitative research designs
• Phenomenological
• Ethnography
• Narrative studies
• Grounded theory
• Historical studies
• Case studies
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21. Qualitative research designs
1. Phenomenological: Examine
human experiences through the
descriptions provided by the
people involved.
• These experiences are called
lived experiences.
• Data are obtained through
interviews
• Concept of “bracketing” is
applied: putting aside your own
ideas about a phenomenon
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23. Qualitative research designs
1. Phenomenology: Examine
human experiences through the
descriptions provided by the
people involved.
• These experiences are called
lived experiences.
• Data are obtained through
interviews
• Concept of “bracketing” is
applied: putting aside your own
ideas about a phenomenon
2. Ethnography: involve the
collection and analysis of data
about cultural groups.
“Learning from people”
• Ethnographers live with people
they are studying
• Data collection: Observation &
interview of key informants
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25. Qualitative research designs
3. Grounded theory: data are
collected and analyzed then a
theory is developed that is
grounded in the data.
• The theory generated is self-
correcting.
• More concerned with
hypothesis generation than
testing
E.g. Post radiotherapy care among
cancer patients.
4. Historical studies: concern
the identification, location,
evaluation, and synthesis of
data from the past.
“Learning from the past”
• Concerned with what can be
learned from past actions
and how these can be
applied for future actions
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27. Qualitative research designs
3. Grounded theory: data are
collected and analyzed then a
theory is developed that is
grounded in the data.
• The theory generated is self-
correcting.
• More concerned with
hypothesis generation than
testing
E.g. Post radiotherapy care among
cancer patients.
4. Historical studies: concern
the identification, location,
evaluation, and synthesis of
data from the past.
“Learning from the past”
• Concerned with what can be
learned from past actions
and how these can be
applied for future actions
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28. Qualitative research designs
5. Narrative research: involves
collection of data from personal
experience.
• Aims to explore and
conceptualize human experience
as it is represented in textual
format.
• Spoken or written stories
E.g. Autobiography, life history
6. Case studies: involves
in-depth examinations of
people or groups of people.
• Can be both quantitative or
qualitative depending on the
purpose
• E.g. diaries of DM patients on
insulin pump
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29. Data collection in
qualitative studies

30. Major qualitative data collection methods
Approach Application/Purpose
In-depth Interview Explore individual experiences and perceptions in rich
detail
Key Informant interview Are in-depth interviews with experts on specific area
(key informants)
Focus Groups Generate unique insights into shared experiences and
social norms
Observation (participant/non-
participants)
Learn about behaviors and interactions in natural settings:
study a cultural aspect of a particular setting or context
Document Review Review of available documents on specific topics
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31. In-depth Interviews
• Are guided conversations with
informants.
• We don’t know what we are
going to obtain during the
interview
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32. When to use in-depth interviews
• Individual perspectives and experiences
• Addressing sensitive topics
• Concerns about fear of reprisal
• When structured survey approaches do not work
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33. Sampling for interviews
• Aim is to identify “key informants”
• Goal is breadth not representativeness
• Size varies depending on the complexity of the research
question
• Determined by theoretical saturation (point at which no
new concepts emerge from the data)
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34. In-depth interviews
Data collection:
Interview guides
• Framework for the interviewer
• List of main questions and probes
• Open, non-directive
• Interviewer may diverge incase of emergent ideas
• Interviewer may reword questions, drop/add
questions, change questions
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35. Types of probes during in-depth interview
Silent Nod slowly..
Echo Repeat the last statement & ask respondent to continue
Direct Tell me more…
Detail Who, where, what, when, how…
Clarifying You said “X”, please clarify what you meant by that…
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36. In-depth interviews
Things to avoid during interview
• Influencing responses by asking
leading questions or conveying
own views (implicitly or explicitly)
• Moving too quickly from one topic
to another
• Interrupting the informant
Tips for good interview
• Know your questions and
probes well
• Rehearse your introduction
• Be aware of power
differentials
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37. Focus Group Discussions
(FGD)
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38. What is a FOCUS GROUP?
• Group of people with certain shared
characteristics
• Interactions and group dynamics is
essential when choosing focus groups
• Widens ranges of responses
• Activates forgotten details
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39. Focus groups are useful for…
• Characterizing social & cultural norms
• Sharing and comparing ideas
• Exploring potentially sensitive issues
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40. Designing FGDs
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41. FGD group size and number
6-10
participants
3-5
groups
per strata
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42. Analysis of FGD data
• The group is the unit of analysis (not individuals within it)
• View of one individual or theme of the group
• Response to question or emerged spontaneously
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43. Fundamentals of
qualitative data analysis

44. Qualitative data analysis
• An iterative process of whereby collected data is translated into
some form of explanation, understanding and interpretation of
the situation or people we are studying.
• There are 2 approaches:
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45. Qualitative data analysis
1. Deductive approach:
• Preliminary organizing framework is
developed.
• Initial codes are drawn from:
• Existing Literature
• Research expertise
2. Inductive approach:
• Participant experiences drive the
analysis (to group the data)
• Limits the possibility of the
researcher forcing preconceived
ideas
Integrated approach
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46. What are Codes?
• Codes are words or short phrases that represent the essence or
key attributes of narrative/verbal information.
• Used to codify or categorize data
• Coding is the process of organizing the data into “chunks” that
are alike
• Codes are developed into code structure
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47. Coding is an iterative process
Create initial
codes &
properties
Code 2-3
transcripts,
Negotiate and
revise
Code 3-5 transcripts,
Negotiate and revise
Create final code
structure, and
apply to all
ALWAYS READ
transcripts
freely before
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48. Code structure
• Compilation of the emerging codes
• Brief definitions and properties for each code (can include
quotes)
• Guidance when and how to use codes
• Evolves throughout the data analysis
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49. Be flexible in refining code structure
• Negotiation may be required
• Expand to encompass more ideas
• Merge into existing codes
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50. Process of qualitative data analysis
Step-1:
Organize
Data Step-2:
Identify
Framework
Step-3: Sort
Data into
Framework
Step-4: Use
Framework
for
descriptive
analysis
Step-5:
Second
order
analysis
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51. Steps in QDA
Step 1: Organize data
• Transcription and translation
of audio data
• Data cleaning
• Structure the data
Step 2: Identify framework
• Read, Read, Read…
• Identify framework (Inductive
Vs Deductive)
• Coding plan
Step 3: Sort data into
Framework
• Code the data
• Modify Code structure
• Data entry into software
Step 4: Conduct Analysis
• Identify recurrent themes and
patterns in the data
• Search data to answer your
research question
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52. Using software for analysis
• Increasingly seen as a standard
• Key to organizing large amount of data
• Supports transparency
• Software can support analysis but DOES NOT do
analysis for you!
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53. Overview of the chapter
Topics to be covered:
• What is a qualitative research?
• Developing a qualitative research question
• Qualitative research designs
• Data collection in qualitative research
• Qualitative data analysis (overview & types)
• Writing qualitative research
• Scientific rigor in qualitative research
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54. Types of Qualitative
Analysis
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55. Types of Qualitative analysis
1. Thematic Analysis
2. Content Analysis
3. Narrative Analysis
4. Discourse Analysis
5. Framework Analysis
6. Grounded theory analysis
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56. 1. Thematic Analysis
• Thematic analysis helps to identify, analyze, and
interpret patterns in qualitative data.
• Focuses on identifying patterns and ‘themes’.
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57. Thematic Analysis
Benefits:
 It’s one of the most accessible
analysis forms
 It’s an effective way to process
large amounts of data into
digestible summaries (themes)
Drawbacks:
 In a complex narrative, thematic
analysis can't capture the true
meaning of a text
 Subjective, and results may not
necessarily align with reality
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58. 2. Content Analysis
• Examines and quantifies the presence of concepts in text,
image, video, or audio messages.
• Procedure for categorization of verbal or behavioral data for the
purpose of classification, summarization and tabulation.
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59. Content Analysis
Advantages:
• You don’t need to directly
interact with participants to
collect data
• It doesn’t require high
investments or sophisticated
solutions
Drawbacks:
• Subjective interpretation
affects your results
• Less effective for complex
textual analysis
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60. 3. Narrative analysis
• Is used to interpret research participants’ stories or
experiences
• Every interview has narrative aspect that the researcher has to
sort out and reflect upon them, enhance them, and present
them in revised shape to readers.
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61. Narrative analysis
Advantages:
• The method provides you with a
deep understanding of
participants' actions — & the
motivations behind them
• Keeps experiences as wholes,
instead of fragmenting them
into themes that can be
interpreted differently
Drawbacks:
• It requires a lot of time and
manual effort to make
conclusions
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62. 4. Grounded theory analysis
• A method of conducting qualitative research to develop
theories by examining real-world data.
• The technique involves the generation of hypotheses and
theories based on data
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63. Grounded theory analysis
Advantages:
• It explains events that can’t
be explained with existing
theories
• The results are data-
informed, and therefore
represent the proven state of
things.
Drawbacks:
• Requires a lot of objectivity,
creativity, and critical thinking
• Overly theoretical
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64. 5. Discourse analysis
• Method of analyzing naturally occurring interactions or written
texts.
• Making sense of everyday social life.
• In contrast to content analysis, the method focuses on the
contextual meanings.
• What people think of a topic, and why they feel the way they
do about it.
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65. Which qualitative data analysis
method should you choose?
• The techniques are different in their intent and approaches.
• The choice of the method of analysis is driven by your research
question.
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66. Tools for helping the Analytical
Process
• Summaries
• Should contain the key points that emerge from undertaking
the specific activity
• Self Memos
• Allow you to make a record of the ideas which occur to you
about any aspect of your research, as you think of them
• Researcher Diary

67. Summary of QDA
• Qualitative data analysis is not easy or fast
• Best accomplished with multidisciplinary team
• Data collection and analysis are iterative processes
• Common approach is constant comparative method
• Code structure evolves inductively
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68. Writing the Qualitative
Research report
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69. Writing the Qualitative Research report
• Researcher analyzes data and writes the analysis in
back-and-forth reflective steps
• Writing the report is part of developing the
interpretation of the data
• Rich thick descriptions – places readers in the setting
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70. Challenges to writing qualitative research
• In addition to challenges of writing any report,
researcher prejudice/bias is another challenge
• Qualitative studies tend to be longer
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71. Qualitative research parts
• Similar to quantitative research
1. Introduction
2. Literature review
3. Methods:
4. Results:
• Differs from quantitative – Almost all findings are text based
• May use graphics to show relationship of key themes
5. Discussion:
• Limitations
• Implications of findings
• Future researches
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72. Writing Background/Problem Statement
• Position yourself in relation to earlier researchers.
• What has not been adequately addressed?
• What has been misrepresented by previous researchers?
• Why do you want to build on someone else’s work?
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73. Writing the methods section
• When/where the fieldwork or data collection was conducted’
• The study design employed
• The extent of the investigator involvement in the environment
during data collection
• Information about context, and participant recruitment
• Ethics statement
• Analysis plan
• Underlying framework
• Transcription
• Coding, and software used
• Determination of information saturation
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74. Writing the results section
• Qualitative studies contain a LOT of information – decide what
to present
• Back your writing with evidence “Quotes”
• Discrepant ideas should be included
• “Quantifying” how common the finding was
• Protect participants’ identity
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75. Writing the discussion section
• Similar with quantitative research
• High level overview of findings
• Implications of the findings
• Limitations
• Future research recommendations
• Overall conclusion
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76. Scientific Rigor in
Qualitative studies

77. Some criticism of qualitative studies
• Lacks reproducibility
• Lacks generalizability
• Researcher bias
• There are many papers
in health sciences that
can address these
problems
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78. Standards for rigor
Quantitative Qualitative Issues addressed
Internal Validity Credibility Truth value
External Validity Transferability Generalizability
Reliability Dependability or
trustworthiness
Consistency
Objectivity Confirmability Neutrality
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79. Strategies for ensuring validity/rigor
Creswell, 2007
Validity
Prolonged
Engageme
nt
Rich, Thick
descriptions
Triangulati
on
Member
Checking
Discrepant
Informatio
n
External
Auditor
Clarifying
Researcher
bias
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80. Thank You!
Any Questions?
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