Qualitative Research
Fufa Hunduma (MD, MPH)
Assistant Professor of FE

Definition of Qualitative Research
• Qualitative research is an interdisciplinary, transdisciplinary, and sometimes
counterdisciplinary field. It crosses the humanities and the social and physical
sciences. Qualitative research is many things at the same time. It is
multiparadigmatic in focus. Its practitioners are sensitive to the value of the
multimethod approach. They are committed to the naturalistic perspective, and
to the interpretative understanding of human experience. At the same time, the
field is inherently political and shaped by multiple ethical and political positions.
• Nelson et al’s (1992, p4)

Definition Cntd..
• ‘Qualitative Research…involves finding out what people think, and
how they feel - or at any rate, what they say they think and how they
say they feel. This kind of information is subjective. It involves
feelings and impressions, rather than numbers’
• Bellenger, Bernhardt and Goldstucker, Qualitative Research in Marketing,
American Marketing Association

Contd.
• Qualitative research is multimethod in focus, involving an
interpretative, naturalistic approach to its subject matter.
• Qualitative Researchers study “things” (people and their
thoughts) in their natural settings, attempting to make sense of,
or interpret, phenomena in terms of the meanings people bring
to them.

Contd..
• Qualitative research involves the studied use and collection of a variety
of empirical materials - case study, personal experience, introspective,
life story, interview, observational, historical, interactional, and visual
texts-that describe routine and problematic moments and meanings in
individuals lives.
• Deploy a wide range of interconnected methods, hoping always to get a
better fix on the subject matter at hand.

Positivist Paradigm
• Emphasises that human reason is supreme and that there is a single
objective truth that can be discovered by science
• Encourages us to stress the function of objects, celebrate technology
and to regard the world as a rational, ordered place with a clearly
defined past, present and future

Non-Positivist Paradigm
• Questions the assumptions of the positivist paradigm
• Argues that our society places too much emphasis on science and
technology
• Argues that this ordered, rational view of consumers denies the
complexity of the social and cultural world we live in
• Stresses the importance of symbolic, subjective experience

Qualitative v's Quantitative
Qualitative
Research
Quantitative
Research
Type of questions Probing Limited probing
Sample Size small large
Info. Per
respondent
much varies
Admin Requires skilled
researcher
Fewer specialist
skills required
Type of Analysis Subjective,
interpretative
Statistical
Type of research Exploratory Descriptive or
causal

Advantages of qualitative research
Qualitative research often tries to preserve the voice and perspective
of participants and can be adjusted as new research questions arise.
Qualitative research is good for:
• Flexibility- The data collection and analysis process can be
adapted as new ideas or patterns emerge. They are not rigidly
decided beforehand.
• Natural settings- Data collection occurs in real-world contexts or
in naturalistic ways.
• Meaningful insights- Detailed descriptions of people’s
experiences, feelings and perceptions can be used in designing,
testing or improving systems or products.

Popularity of Qualitative Research
• Generation of new ideas- Open-ended responses mean that
researchers can uncover novel problems or opportunities that they
wouldn’t have thought of otherwise.
• Usually much cheaper than quantitative research
• No better way than qualitative research to understand in-depth the
motivations and feelings of consumers
• Qualitative research can improve the efficiency and effectiveness of
quantitative research

Disadvantages of qualitative research
Researchers must consider practical and theoretical limitations in
analyzing and interpreting their data. Qualitative research suffers from:
• Unreliability -The real-world setting often makes qualitative research
unreliable because of uncontrolled factors that affect the data.
• Subjectivity - Due to the researcher’s primary role in analyzing and
interpreting data, qualitative research cannot be replicated. The
researcher decides what is important and what is irrelevant in data
analysis, so interpretations of the same data can vary greatly.

Contd..
• Labor-intensive- Although software can be used to manage and record large
amounts of text, data analysis often has to be checked or performed manually.
• Not representative of the population that is of interest to the researcher
• Limited generalizability- Small samples are often used to gather detailed data about
specific contexts. Despite rigorous analysis procedures, it is difficult to
draw generalizable conclusions because the data may be biased and
unrepresentative of the wider population.
• The multitude of individuals who, without formal training, profess to be experts in
the field

Qualitative Data Collection Techniques
• In depth Interviewing
• Focus Groups
• Participant Observations
• Ethnographic Studies
• Projective Techniques

Qualitative research methods
• Each of the research approaches involve using one or
more data collection methods.
• These are some of the most common qualitative methods:
• Observations: recording what you have seen, heard, or encountered
in detailed field notes.
• Interviews: personally asking people questions in one-on-one
conversations.
• Focus groups: asking questions and generating discussion among a
group of people.
• Surveys: distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts,
images, audio or video recordings, etc.

Methods of Qualitative Research
• Phenomenological Method
• Ethnographic Model
• Grounded Theory Method
• Case Study Model
• Historical Model
• Narrative Model

Approaches to qualitative research
• Qualitative research is used to understand how people experience the
world.
• While there are many approaches to qualitative research, they tend to be
flexible and focus on retaining rich meaning when interpreting data.
• Common approaches include
• grounded theory,
• ethnography,
• action research,
• phenomenological research,
• narrative research.
• Case Study Model.
They share some similarities, but emphasize different aims and

Contd..
Methodology Approaches What does it involve?
Grounded theory Researchers collect rich data on a topic of interest and
develop theories inductively.
Ethnography Researchers immerse themselves in groups or
organizations to understand their cultures.
Action research Researchers and participants collaboratively link theory to
practice to drive social change.
Phenomenological
research
Researchers investigate a phenomenon or event by
describing and interpreting participants’ lived experiences.
Narrative research Researchers examine how stories are told to understand
how participants perceive and make sense of their
experiences.

Frequently asked questions about qualitative
research
1. What’s the difference between quantitative and qualitative
methods?
• Answer: Quantitative research deals with numbers and
statistics, while qualitative research deals with words and
meanings.
• Quantitative methods allow you to test a hypothesis by
systematically collecting and analyzing data, while qualitative
methods allow you to explore ideas and experiences in depth.
2. What are the main qualitative research approaches?
3. What is data collection?
4. How do you analyze qualitative research?

Qualitative Research Analysis

Approach of
Qualitative
analysis
When to use Example
Content analysis To describe and categorize
common words, phrases, and
ideas in qualitative data.
A market researcher could perform content
analysis to find out what kind of language is
used in descriptions of therapeutic apps.
Thematic analysis To identify and interpret
patterns and themes in
qualitative data.
A psychologist could apply thematic analysis to
travel blogs to explore how tourism shapes
self-identity.
Textual analysis To examine the content,
structure, and design of texts.
A media researcher could use textual analysis
to understand how news coverage of
celebrities has changed in the past decade.
Discourse analysis To study communication and
how language is used to
achieve effects in specific
A political scientist could use discourse analysis
to study how politicians generate trust in
election campaigns.

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 is the analysis of qualitative data such as text data from interview
transcripts.
 Unlike quantitative analysis, which is statistics driven and largely
independent of the researcher, qualitative analysis is heavily
dependent on the researcher’s analytic and integrative skills and
personal knowledge of the social context where the data is
collected.
 A creative and investigative mindset is needed for qualitative
analysis, based on a ethically enlightened and participant-in-context
attitude, and a set of analytic strategies.
Qualitative Analysis

Qualitative data analysis
• Qualitative data can take the form of texts, photos, videos and audio.
For example, you might be working with interview transcripts, survey
responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
1.Prepare and organize your data. This may mean transcribing
interviews or typing up fieldnotes.
2.Review and explore your data. Examine the data for patterns or
repeated ideas that emerge.
3.Develop a data coding system. Based on your initial ideas,
establish a set of codes that you can apply to categorize your data.

Contd..
4. Assign codes to the data.
• For example, in qualitative survey analysis, this may mean going
through each participant’s responses and tagging them with codes in
a spreadsheet.
• As you go through your data, you can create new codes to add to
your system if necessary.
5. Identify recurring themes. Link codes together into cohesive,
overarching themes.
• There are several specific approaches to analyzing qualitative data.
Although these methods share similar processes, they emphasize
different concepts.

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Coding Techniques
• How can you analyze a vast set of qualitative data acquired through participant
observation, in-depth interviews, narratives of audio/video recordings, or
secondary documents?
• One of the key techniques used for analyzing text data is coding
– a process of classifying and categorizing text data segments into concepts or
“codes,” which can then be used to uncover patterns in the data.
• Coding is widely used in grounded theory research, but can also be used in
other qualitative methods that involve interpretation of text data.

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Content Analysis
 Content Analysis is a technique for gathering and analyzing the content of a text.
 The content refers to words, meanings, pictures, symbols, ideas, themes, or any message
that can be communicated.
 The text is anything written, visual, or spoken that serves as a medium of communication.
 Possible artifacts for study could be books, newspaper or magazine articles, advertisements,
poems, letters, laws, constitutions, dramas, speeches, official documents, films or
videotapes, musical lyrics, photographs, articles of clothing, or works of arts.
 All these works may be called as documents.

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The documents can be:
Personal – letters, diary, autobiography.
Non-personal – interoffice memos, official documents,
proceedings of a meeting.
Mass media – newspapers, magazines, fiction, films,
songs, poems, works of arts.

contd..
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 In content analysis, the researcher uses objective and systematic
counting and recording procedures to produce a quantitative
description of the symbolic content in a text.
 It may also be called “textual coding.”
 There are qualitative versions of content analysis.
 The emphasis here is quantitative data about a text’s content.

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Measurement and Coding
 Careful measurement is crucial in Content Analysis because a
researcher takes different and murky symbolic communication and
turns it into precise, objective, quantitative data.
 He or she carefully designs and documents the procedures for
coding to make replication possible.
 For Example,
 A researcher wants to determine how frequently television dramas
portray elderly characters in terms of negative stereotypes

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Observations can be structured
• Measurement in content analysis uses structured
observation i.e. systematic, careful observation based on
written rules.

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Frequency
Frequency simply means counting whether or not
something occurs and how often (how many times).
For Example,
 how many elderly people appear on a television program
within a given week?
 What percentage of all characteristics are they, or in what
percentage of programs do they appear

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Direction
 Direction is noting the direction of messages in the content along
some continuum (e.g., positive or negative, supporting or
opposed).
For Example
 The researcher devises a list of ways an elderly television character can
act.
 Some are positive (e.G., Friendly, wise, considerate) and some are
negative (e.G., Nasty, dull, selfish).

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Intensity
Intensity is the strength or power of a message
in a direction.
For Example,
 The characteristic of forgetfulness can be:
 Minor (e.g. Not remembering to take the keys when
leaving home, taking time to recall the name of someone
whom you have not seen in years) or
 Major (e.g., Not remembering your name, not recognizing
your children.

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Space
 A researcher can record the size of the text message or the amount
of space or volume allocated to it.
 Space in written text is measured by counting words, sentences,
paragraphs, or space on a page (e.g. square inches) for video or
audio text, space can be measured by the amount of time allocated.

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Manifest Coding
 Coding the visible, surface content in a text is called manifest
coding.
For Example,
 A researcher counts the number of times a phrase or word (e.g.
Red) appears in the written text, or whether a specific action
(e.g. Shaking hands) appears in a photograph or video scene.

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Latent Coding
 A researcher using latent coding (also called semantic
analysis) looks for the underlying meaning in the content of a
text.
For Example,
 the researcher reads the entire paragraph and decides
whether it contains vulgar themes or a romantic mood.

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Question Formulation:
 As in most research, content analysis researchers begin with a research
question.
 When the question involves variables that are messages or symbols,
content analysis may be appropriate.
For Example,
 How women are portrayed in advertisements?
 The construct here is the portrayal of women which may be measured by looking at the
activities they are shown to be doing, the occupations in which they are employed, the
way decision making is taking place, etc.
How to Conduct Content Analysis Research

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i) Unit of Analysis:
 A researcher decides on the unit of analysis (i.e. the
amount of text that is assigned a code).
 In the previous example each advertisement may be a unit
of analysis.

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ii) Sampling
 Researchers often use random sampling in content analysis.
 First, they define the population and the sampling element
For Example,
 The population might be all words, all sentences, all paragraphs, or all
articles in certain type of documents over a period of specified duration.
 Likewise, it could include each conversation, situation, scene, or episode
of a certain type of television program over a specified time period.

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iii) Inferences
 The inference a researcher can or cannot make on the
basis of results is critical in content analysis.
 Content analysis describes what is in the text.
 It cannot reveal the intentions of those who created the text
or the effects that messages in the text have on those who
receive them.

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Use of Secondary Data
I) Existing Statistics/Documents
 Prior to the discussion of secondary data, let us look at the
advantages and disadvantages of the use of content analysis that
was covered in the previous slides.
 In a way content analysis is also the study of documents through
which the writers try to communicate, though some of the
documents (like population census) may simply contain figures.

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II. Advantages of Content Analysis
1) Access to inaccessible subjects:
 One of the basic advantages of content analysis is that it allows
research on subjects to which the researcher does not have physical
access.
 These could be people of old civilizations, say their marriage
patterns.
 These could also be the documents from the archives, speeches of
the past leaders ( Quaid-e- Azam) who are not alive, the suicide
notes, old films, dramas, poems, etc.

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2.) Non-Reactivity:
 Document study shares with certain types of observations (e.g.,
indirect observation or non- participant observation through one-
way mirror) the advantage of little or no reactivity, particularly
when the document was written for some other purpose.
 This is unobtrusive.
 Even the creator of that document, and for that matter the
characters in the document, is not in contact with the researcher,
who may not be alive.

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3) Can Do Longitudinal Analysis
 Like observation and unlike experiments and survey, document
study is especially well suited to study over a long period of time.
 Many times the objective of the research could be to determine a
trend.
 One could pick up different periods in past and try to make
comparisons and figure out the changes (in the status of women)
that may have occurred over time.

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4) Use Sampling
 The researcher Can Use Random Sampling.
 One could decide on the population, develop sampling frame and
draw simple random sample by following the appropriate
procedure.
 For Example, how women are portrayed in weekly English news
magazines.

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5) Can Use Large Sample Size
Larger the sample closer the results to the population.
In experimentation as well as in survey research there could
be limitations due to the availability of the subjects or of the
resources but in document analysis the researcher could
increase the sample and can have more confidence in
generalization.

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6) Spontaneity
 The spontaneous actions or feelings can be recorded when they
occurred rather than at a time specified by the researcher.
 If the respondent was keeping a diary, he or she may have been
recording spontaneous feelings about a subject whenever he or she
was inspired to do so.
 The contents of such personal recording could be analyzed later on.

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7) Confessions
 A person may be more likely to confess in a document,
particularly one to be read only after his or her death, than in
an interview or mailed questionnaire study.
 Thus, a study of documents such as diaries, posthumously
published autobiographies, and suicide notes may be the only
way to obtain such information.

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8) Relatively Low Cost
• Although the cost of documentary analysis can vary widely
depending on the type of document analyzed, how widely
documents are dispersed, and how far one must travel to gain
access to them, documentary analysis can be inexpensive compared
to large-scale surveys.
• Many a time’s documents are gathered together in a centralized
location such as library where the researcher can study them for
only the cost of travel to the repository.

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9) High quality
 Although documents vary tremendously in quality, many
documents, such as:
 Newspaper Columns, are written by skilled commentators
and
 May be more valuable than, for example, poorly written
responses to mailed questionnaires.

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III. Disadvantages of Content analysis
1) Bias:
 Many documents used in research were not originally intended for research
purposes.
 The various goals and purposes for which documents are written can bias them
in various ways.
 For Example,
 Personal documents such as confessional articles or autobiographies are
often written by famous people or people who had some unusual
experience such as having been a witness to a specific event.
 While often providing a unique and valuable research data, these
documents usually are written for the purpose of making money.
 Thus, they tend to exaggerate and even fabricate to make good story.

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2) Selective Survival
 Since documents are usually written on paper, they do not
withstand the elements well unless care is taken to preserve
them.
 Thus, while documents written by famous people are likely to be
preserved, day-to-day documents such as letters and diaries written
by common people tend either to be destroyed or to be placed in
storage and thus become inaccessible.

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3) Incompleteness
 Many documents provide incomplete account to the researcher
who has had no prior experience with or knowledge of the events
or behavior discussed.
 A problem with many personal documents such as letters and
diaries is that they were not written for research purposes but
were designed to be private or even secret.
 Both these kinds of documents often assume specific knowledge
that researcher unfamiliar with certain events will not possess.

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4) Lack of Availability of Documents
In addition to the bias, incompleteness, and selective
survival of documents, there are many areas of study for
which no documents are available.
In many cases information simply was never recorded.
 In other cases it was recorded, but the documents remain
secret or classified, or have been destroyed.

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5) Sampling Bias
 One of the problems of bias occurs because persons of
lower educational or income levels are less likely to be
represented in the sampling frames.
 The problem of sampling bias by educational level is more
acute for document study than for survey research.

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6) Limited to Verbal Behavior
By definition, documents:
Provide information only about respondent’s verbal
behavior, and
Provide no direct information on the respondent’s
nonverbal behavior, either that of the document’s author
or other characters in the document.

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7) Lack of Standardized Format
 Documents differ quite widely in regard to their standardization of format.
 Some documents such as newspapers appear frequently in a standard
format.
 Large dailies always contain such standard components as editorial page,
business page, sports page, and weather report.
 Standardization facilitates comparison across time for the same newspapers
and comparison across different newspapers at one point in time.

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8) Coding Difficulties
For a number of reasons, including:
 Differences in purpose for which the documents were written,
 Differences in content or subject matter,
 Lack of standardization, and
 Differences in length and format, coding is one of the most difficult tasks
facing the content analyst.

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9) Data Must Be Adjusted For Comparability Over Time:
 Although one of the advantages of document study is that
comparisons may be made over a long period of time, since
external events cause changes so drastic that even if a common
unit of measure is used for the entire period,
 the value of this unit may have changed so much over time that
comparisons are misleading unless corrections are made.

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Conclusions On Qualitative Analysis
 In qualitative inquiry, it is acceptable to include numerical
quantities and analyze such data using quantitative
techniques.
 Such analysis is called mixed-method analysis.
For Example,
 While qualitative data from an interview transcript can be
analyzed qualitatively using content analysis,
 quantitative data collected during the same process can be
analyzed quantitatively using measures of central tendency,
correlation, and so forth.

Thank you!