Justify the Use of Qualitative Research Designs: Case Study vs Phenomenology

Instructions
One of the many tasks involved in writing a dissertation or a
research article is being able to justify the choice of one
methodology over others. Just as critical to the feasibility of a
study is the stated rationale for selecting a specific research
design. This week, you are introduced to two research designs
that have several features in common; there are also stark
contrasts that are identifiable.
For this week’s assignment, consider what you have learned
about the case study and phenomenological research designs.
Using the same research problem developed in Week 1, how
could you use these designs to gain insights to fulfill the
purpose of your study?
Begin by selecting the approach that best fits the problem. Use
the resources provided, and at least three other peer-reviewed
articles to defend your choice (two pages minimum). Create a
one-page critique of the other research design that includes
arguments why the design may not suitable for researching your
problem. Include a summary of the key arguments for your
choice.
Length: 3-4 pages
Your assignment should demonstrate thoughtful consideration
of the ideas and concepts presented in the course and provide
new thoughts and insights relating directly to this topic. Your
response should reflect scholarly writing and current APA
standards.
Upload your document and click the Submit to Dropbox button.
NORMAN, ELTON_BUS7380-8-3 2
NORMAN, ELTON_BUS7380-8-3 1

Justify the Use of Qualitative Designs: Case Study or
Phenomenology
BUS-7380 Assignment # 3
Elton Norman
Dr. Vicki Lindsay
19 October 2019
Hi Elton,
The topic of this week's assignment included reading all of the
material that was required satisfactorily to explain the required
information. With the required reading and the research project
that you discussed in week one's assignment, you were to
determine which of the two types of qualitative research designs
that you read about this week would fit your topic that you
explained in the first week's assignment by discussing and
critiquing within two pages how you would use that type of
design to plan your project. Then, you were to take one full
page to critique how the design that you found that would not
be suitable in fitting your proposed research project by using
key arguments, which you would have found in your required
reading. These required three pages of critique and discussion
did not include your introduction or conclusion of your research
paper. Therefore, this project was supposed to be succinct
enough to clearly and concisely explain your thought process in
a scholarly paper (using citations for all information) to only
include up to four pages total.
The feedback process for this paper, as well as your other

assignments, consisted of a four-part summary (four-parts listed
below), a few short, location-specific balloon-comments found
within the margins of the text, and the highlighting of grammar,
punctuation, or APA styling errors found within the text. Make
sure that you view your document with the track changes
(review toolbar) set to ALL MARKUP to be able to see all the
comments.
The summary is split into four parts. These four parts consist
of grammar/punctuation, conformity with APA style citations,
conformity with APA style references, and content. The order of
the parts listed does not intend to emphasize the importance of
the parts as the content is always the most important part of the
assignment. Therefore, it is listed in the end because normal
memory concentrates on what was heard / read last.
What was found:
Grammar/ Punctuation
There were a large number of issues with grammar and
punctuation errors within. These were marked with a
highlighted area. Within week one of your feedback, I sent you
a link to the Grammarly program. The Grammarly program is a
software program that is free of charge through the University.
It will help you to find errors in grammar and punctuation . It
might not find all of them, but it may find a large portion of
what you had wrong within this paper. Most of your problems
stemmed from the use of “therefore.” Watch your punctuation
around this word. It could lead to problems with run-on
sentences is if punctuated incorrectly.
Note the number of times that you see highlighted areas. These
are areas that have problems with grammar and punctuation. If
you download the Grammarly program, you will see what was
wrong with these areas so that you can fix them for the future.
APA style citations
Although you do have a number of paragraphs that do you have
citations within, all of the ideas do not seem to be cited by
authors. There is at least one area that does not have a citation
for at least 10 lines of your text. This text was full of definition

phrases and phrases that were the ideas of others.
APA style references
Remember that this assignment should have more than four
sources. There should be a large number of sources that stem
from your required reading, along with three sources that are
scholarly research articles that are used to defend your choice
of methodology. I believe that I see four sources that are
stemming from book-related sources that deal with case study
research. I do not see any scholarly sources that are peer-
reviewed to help defend your choice.
Visit your reference page for the problems that I have found.
Your references were not fully APA style formatted. Also,
there was missing information. You may want to focus on
making sure that what you have is correct for your sources.
Content
The topic of this week's assignment required the student to
determine which of the two qualitative research designs that you
read about this week would fit the topic that you had in week 1
and have been using going forward. You should use your
required reading more often. I should see a lot more information
stemming from the required reading with the citations and
references to back those required readings. Make sure that you
visit and use your required readings often within this course. It
is a very reading-intensive course, and to show that you have
read what is needed, it is best to use those readings to help
navigate your submission. You also should note what is in the
assignment. Usually, there is a minimum number of sources that
are required. This assignment stated that you needed to have
used many of the required readings and at least three peer-
reviewed journal articles to back up your claim to which of the
two methodologies would have been better for your week 1
research project.
You don’t seem to have very much information on
phenomenological studies. As well, you don’t show many
citations in that area. You need to show more explanation in
this field before you can say that it may not be the best

methodology to use for your project. If you searched for peer-
reviewed studies on this topic, you would most likely have
found more phenomenological studies than case reviews. This
would have shown you that others in your field have an altered
opinion than you do about using phenomenological designs for
this topic. If you used more required reading on this topic, you
might have changed your final opinion, as well. Don’t forget to
look at the negative and positive aspects of both types of
methodologies.
If you have any questions about any part of this, please feel free
to contact me via Skype or NCU email.
V. Lindsay, PhD 9.2/10 10/22/19
The approach that fits the problem
Case studies and phenomenological research designs can both
be used to research about the problem which is businesses being
unable to promote diversity in the workplace. Case studies
provide real life situations on the organizations that have been
successfully able to promote diversity in the workplace and
those that have not. In addition, case studies identify the most
appropriate strategies utilized by the successful organizations to
promote diversity. On the other hand, phenomenological
research designs indicate the perceptions and understanding of

individuals in regard to promoting workplace diversity. The
perceptions and understanding might not have been applied in
the actual world therefore their efficiency cannot be determined.
Therefore, case studies are the most appropriate for researching
the problem. Comment by Vicki Lindsay, PhD: Citations
needed throughout this first paragraph. Where did you find this
information?
The purpose of my study is to evaluate the impact of workplace
diversity in the modern workplace and the benefits accompanied
with it. The case study method is very useful in supporting this
research because through it I can investigate an organization
that has successfully been able to promote workplace diversity
and acquire extensive benefits from this. This is based on
reality therefore the results of the research will be accurate and
highly reliable (Yin, 2017). Through the case study method, it is
easier to investigate and explore different organizations that
have not been successful in promoting workplace diversity. The
method will make it easier to determine the impact of not
promoting workplace diversity on employee morale,
productivity and performance. Comment by Vicki Lindsay,
PhD: There are 2 problems here. One is that you need a comma
after the word it. This second is the use of “I” or “me” within
your work. However , the use of 1st person is not graded
because this was found problematic in the second submission,
and I said that nothing in the 2nd will be problematic in the 3rd
submission. Therefore, don't have 1st or 2nd person voice in
your APA style scholarly papers in the future. However, you are
not being counted off for it in this submission. Comment by
Vicki Lindsay, PhD: Citations needed for the negative thought
process as well.
Through the case study design, it will be possible to develop
new research in regard to workplace diversity. The findings of
the method are often valuable, and they can be utilized to
advance research in the field (Duff, 2018). For instance, after
studying various organizations, it will be possible to identify
the common strategies and barriers to promoting workplace

diversity. The common strategies can therefore be studied to
determine their effectiveness in promoting workplace diversity.
On the other hand, the barriers to promoting workplace
diversity can be studied and solutions recommended to avoid
them. Through the case study, it will be possible to provide new
insight into the research problem based on a real-life context.
Case studies provide insight to a phenomenon in a manner that
cannot be learned utilizing any other method. Unlike
phenomenological study designs, case studies do not just
provide perceptions and thoughts. They provide information
based on what has already happened. When it comes to
workplace diversity, it is important to acquire real life
information. This entails choosing two or three organizations
that have been successful in promoting workplace diversity and
others that have been successful and then finding common
trends. Comment by Vicki Lindsay, PhD: Putting a
“however” or “therefore” in the middle of the sentence without
using the proper punctuation is a major indicator of a run-on
sentence. Since “however” was placed in the middle of the
sentence – much like speech patterns – without proper
punctuation, it became a interuptor of the sentence. They can
also become run-on sentence. Try to only use “however” or
“therefore” as the introductory clause to forgo having to
remember exact punctuation for each case of use.
Comment by Vicki Lindsay, PhD: You seem to be missing
Citations for the last 10 or so lines of this paragraph.
Again, through the case study method, it is possible to
generalize data for illustrating statistical findings. The data
acquired from the case study is an illustration of why certain
organizations can successfully promote diversity and why others
are not. Case study research design is also less expensive
compared to other research methods therefore it is more
appropriate in conducting the research problem (Mills, 2017).
Comment by Vicki Lindsay, PhD: This is a an example of
how the use of therefore becomes a run on sentence without the
proper punctuation. Comment by Vicki Lindsay, PhD: It

depends on many factors as to how appropriate it may be with
financial factors. Sometimes a large, long, lognitiunal
quantitative methodology is needed and financial needs are not
as important as the reliability and validity that is found using
this type of methodology. So, before you state that it is a more
appropriate type of conducting research, you may want to
explain to whom the importance may lie. If it was a broke
college student who is working on a dissertation, a case study
may be more appropriate than a longitudinal study that will take
more time and money.
Critique of phenomenological study designs
Phenomenological study designs research on how an individual
understand or perceives an event or phenomena. In this case it
entails researching the perspectives of individuals towards
workplace diversity. The opinions and understanding of
different individuals may be useful in investing the research
problem but they are highly unreliable and may be inaccurate
(Mihas, 2019). In addition, it is much easier for the researcher
to introduce bias. This will lead to unreliable results of the
research problem. In case bias is introduced, the researcher will
present findings inclined to one position therefore it will be
impossible to determine the actual reasons why organizations
are able or unable to promote workplace diversity. The results
of this research are very difficult to present. This is because
they are highly qualitative therefore making it difficult to
present findings in a manner that individuals would find useful.
In addition, gathering data can take extensive time and
resources. Workplace diversity is something that has been
influenced by various factors including the different generations
in the workplace. It is therefore crucial to determine the impact
of this factors in the workplace and the role they play in
promoting workplace diversity. Determining the effect of the
factors based on a real-life context is more appropriate for
developing reliable findings. Phenomenological study designs
are not based on a real-life context therefore it is impossible to
accurately determine the impact of factors such as different

workplace generations. Based on the arguments presented, the
most appropriate method of researching the inability or
organizations to promote diversity in the workplace is the case
study method because it is based on a real-life context.
Comment by Vicki Lindsay, PhD: This is the plural form
of phenomenon. This sentence has a few problems Where the
the subject, verb, and direct object do not match in tense.
Comment by Vicki Lindsay, PhD: There are no citations
listed when discussing researcher bias. How do you know about
research bias? Comment by Vicki Lindsay, PhD: You
don’t seem to have very much information on phenomenological
studies. As well, you don’t show many citations in that area.
You need to show more explanation in this field before you can
say that it may not be the best methodology to use for your
project. If you searched for peer-reviewed studies on this topic,
you would most likely have found more phenomenological
studies than case reviews. This would have showed you that
others in your field have an altered opinion than you do about
using phenomenological designs for this topic.
References
Duff, P. (2018). Case study research in applied linguistics.
Routledge. Comment by Vicki Lindsay, PhD: Missing where
this was published
Mihas, P. (2019). Qualitative data analysis. In Oxford Research
Encyclopedia of Education. Comment by Vicki Lindsay,

PhD: This is not in APA style formatting. We're missing the
Editor of the Encyclopedia, where it was published, and the
publisher.
Mills, J., Harrison, H., Franklin, R., & Birks, M. (2017). Case
study research: Foundations and methodological orientations. In
Forum Qualitative Sozialforschung/Forum: Qualitative Social
Research (Vol. 18, No. 1, p. 17). DEU. Comment by Vicki
Lindsay, PhD: This is not in APA style formatting
Yin, R. K. (2017). Case study research and applications: Design
and methods.. e publications. Comment by Vicki Lindsay,
PhD: This is not in APA style formatting. The ellipsis is not
Correct in this reference. Missing the location and the publisher
. If it is an E publication , you will need to put the URL where
it was found.
Hi Elton,
I apologize for the lateness of this feedback. I was working with
another student in her dissertation. It was a rush job to be
perfected. Therefore, your feedback was put on hold to allow
for the other student's feedback. Since this was a PowerPoint
presentation feedback, it seems that this one would not put your
others at risk if this was later than normal.
The feedback for this assignment is going to be different from
the feedback that you received in your other submissions. A
PowerPoint presentation is not going to be looked at in the way
that paper submission is viewed. The author of the assignment
asked for the student to provide certain slides. These slides
dealt with the five types of design approaches in qualitative
methodology and how they fit with your research project. The
feedback will follow the exact way that the author asked for you
to conduct the PowerPoint presentation. I will use the exact
assignment and fill in what was positive or negative feedback
within that assignment.
*********************

Create an instructor’s presentation to teach students about
qualitative research designs. This week, you were presented
with three different qualitative research designs. Determine the
value of each of the five designs explored over the last two
weeks, and then critique the utility of each one relative to your
research problem. Create a narrated PowerPoint presentation
that includes the following:
Cover and references slides (these do not contribute to sliding
count)
The problem to be investigated (your problem statement from
Week 1)
A critique of five qualitative research designs
Comparison and contrast of the value of these designs
Defense of your selection of one of the designs covered this
week
Note: This presentation should be usable in a teaching
environment
Length: 8- to 10-slide PowerPoint narrated presentation.
Speaker notes (minimum 200 words per slide)
***************
Therefore, this project should have included the following
slides:
COVER (not part of the required 8-10 slides)
The problem to be investigated (your problem statement from
Week 1)
A critique of five qualitative research designs
(Read the above assignment) You were to critique the utility of
each one relative to
your research problem (I would think that this would take up 5
slides – one for each
type of design).
Comparison and contrast of the value of these designs
(Which would be the best for your given research project =
compare and contrast
while using your research project to be an example of what
would be a good idea

or a bad idea for this project.)
Defense of your selection of one of the designs covered this
week.
(Why did you pick the type of design covered? Defend it
against each of the
other types of designs)
REFERENCE (not part of the required 8-10 slides)
(This is the slide where your references will be seen in
APA format by the instructor.)
********************
YOUR FEEDBACK ACCORDING TO THE ASSIGNMENT
REQUIREMENTS. The red checkmark ( 3) signifies that this
slide exists and is correct. The information in the BLUE
GADUGI (this writing) is the feedback or what was found when
examining your PowerPoint submission.
3COVER (not part of the 8-10 slides)
3Slide with your problem statement from your week 1 research
problem.
3A critique of Grounded Theory’s utility to your research
problem (problem statement).
An informative study of the grounded theory design was
present. However, you should give me some more about how it
would be used within the problem statement. Explain…
3A critique of Phenomenology’s utility to your research
problem (problem statement).
An informative study of the Phenomenology design was present.
There seems to be an adequate amount of information about the
problem statement and how it could work within this design.
3A critique of Ethnography’s utility to your research problem
(problem statement).
An informative study of the Ethnography design was present,
and there is a relation to the research problem or the problem
statement. However, more explanation of the design should be
present before explaining it with your problem statement.
A critique of Narrative design’s utility to your research problem

An explanation of this design seems to be missing from your
submission.
3A critique of Case Study’s utility to your research problem
An informative study of the Case Study design was present, but
it did not relate to the research problem or the problem
statement, as explained in the assignment.
3Comparison and contrast of the value of these designs
(Which would be the best for your given research project =
compare and contrast
while using your research project to be an example of what
would be a good idea
or a bad idea for this project.)
Nice explanation of comparison and contrast of the designs. It
seems as if you may have mistaken biographic design as one
that should have been included in this instead of including
narrative design. There is a difference between them. However,
that one slide was missing but you added a fifth design to this
project and the comparison and contrast. Therefore, not having
a narrative design in your comparison is not weighing against
your submission because you do have a fifth design present.
3Defense of your selection of one of the designs covered this
week.
(Why did you pick the type of design covered? Defend it
against each of the
other types of designs)
Your reasoning of why phenomenology is a good approach is
given. You should defend your reasoning for using this
approach against the other four approaches. Think about the
methodology of the approach. Soon you will have to explain the
methodology itself as a part of your work.
3REFERENCE (not part of the 8-10 slides)
(This is the slide where your references will be seen in
APA format by the instructor.)

The slides are present. However, the APA style is problematic
because of the use of the design of the PowerPoint presentation.
It seems to use all caps while APA frowns on the use of all
caps. It also did not allow the italics of the journal and book
names to come through. There are also issues with the APA
style referencing because of missing parts of the references.
If you have any questions about any part of this or any future
assignment, please feel free to contact me via Skype or NCU
email.
V. Lindsay, PhD 8.8 /10 10/31/19
Instructions
Create an instructor’s presentation to teach students about
qualitative research designs. This week, you were presented
with three different qualitative research designs. Determine the
value of each of the five designs explored over the last two
weeks, and then critique the utility of each one relative to your
research problem. Create a narrated PowerPoint presentation
that includes the following:
· Cover and references slides (these do not contribute to sliding
count)
· The problem to be investigated (your problem statement from
Week 1)
· A critique of five qualitative research designs
· Comparison and contrast of the value of these designs
· Defense of your selection of one of the designs covered this
week
· Note: This presentation should be usable in a teaching
environment
Length: 8- to 10-slide PowerPoint narrated presentation.
Speaker notes (minimum 200 words per slide)
Your presentation should demonstrate thoughtful consideration
of the ideas and concepts presented in the course and provide

new thoughts and insights relating directly to this topic. Your
response should reflect scholarly writing and current APA
standards.
Linda Amankwaa, PhD, RN, FAAN
Abstract: Experienced and novice researchers, plan qualitative
proposals where evidence o f rigor
m ust be provided within the document. One option is the
creation o f a trustworthiness protocol
with details noting the characteristic o f rigor, the process used
to document the rigor, and then
a timeline directing the planned time for conducting
trustworthiness activities. After reviewing
several documents, an actual plan o f conducting
trustworthiness as not found. Thus, these authors
set out to create a trustworthiness protocol designed not only
for the dissertation, but a framework
for others who m ust create similar trustworthiness protocols for
their research. The purpose o f this
article is to provide a reference for the trustworthiness plan, a
dissertation example and showcase a
trustworthiness protocol that may be used as an example to
other qualitative researchers embarking
on the creation o f a trustworthiness protocol that is concrete
and clear.
K ey Words: Trustworthiness, Research Protocols, Qualitative
Research
C reating P rotocols for
T rustworthiness in Q ualitative

R esearch
Anything perceived as being of low or no value is also
perceived as being worthless, unreliable, or invalid. Research
that is perceived as worthless
is said to lack rigor. This means findings are not worth
noting or paying attention to, because they are unreliable.
To avoid this argument, proof of reliability and validity
in qualitative research methods is required. However,
some researchers have suggested that reliability and
validity are not terms to be used to explain the usefulness
of qualitative research. They believe that those terms are
to be used to validate quantitative research (Altheide &
Johnson, 1998; Leininger, 1994). Morse (1999) expressed
concern about qualitative research losing value by em-
phasizing when qualitative researchers fail to recognize
crucial importance of reliability and validity in qualita-
tive methods, they are also mistakenly supporting the
idea that qualitative research is defective and worthless,
lacking in thoroughness, and of unempirical value.
Guba and Lincoln (1981) stated that, "All research must
have 'tru th value', 'applicability', 'consistency', and
'neutrality' in order to be considered worthwhile. They
concluded that the end result of establishing rigor or
"trustworthiness," (the analogous for rigor in qualitative
research), for each method of research requires a differ-
ent approach. It was noted by Guba and Lincoln (1981),
Linda A m ankw aa, PhD , RN, FAAN, is an Associate
Professor in the Department o f Nursing at Albany State Uni-
versity in Albany, GA31705. Dr. Amankwaa may be reached
at: 229-430-4731 or at: [email protected]
within the rationalistic paradigm, criteria to reach the
goal of rigor are internal validity, external validity, reli-
ability, and objectivity. They proposed use of terms such
as credibility, fittingness, auditability, and confirmability

in qualitative research to ensure "trustworthiness" (Guba
& Lincoln, 1981). Later, these criteria were changed to
credibility, transferability, dependability, and confirm-
ability (Lincoln & Guba, 1985).
Lincoln and Guba (1985) suggested that the value of a
research study is strengthened by its trustworthiness. As
established by Lincoln and Guba in the 1980s, trustwor-
thiness involves establishing:
• Credibility - confidence in the 'tru th ' of the
finding
• Transferability - show ing that the findings have
applicability in other contexts
• D ependability - show ing that the findings are
consistent and could be repeated
• Confirmability - a degree of neutrality or the ex-
tent to w hich the findings of a stu d y are shaped
by the respondents and not researcher bias,
motivation, or interest.
For purposes of this discussion, this classic work is
used to frame trustworthiness actions and activities to
create a protocol for qualitative studies. Nursing faculty
and doctoral nursing students who conduct qualitative
research will find this reference useful.
Journal of C ultural Diversity • Vol. 23, No. 3 Fall 2016
mailto:[email protected]
Credibility Activities
Lincoln and Guba (1985) described a series of techniques

that can be used to conduct qualitative research that at-
tains the criteria they outlined. Techniques for establishing
credibility as identified by Lincoln and Guba (1985) are:
prolonged engagem ent, persistent observation, triangula-
tion, peer debriefing, negative case analysis, referential
adequacy, and member-checking. Typically member check-
ing is view ed as a technique for establishing the validity
of an account. Lincoln and Guba posit that this is the most
crucial technique for establishing credibility.
Transferability Activities
One strategy that can be em ployed to facilitate transfer-
ability is thick description (Creswell & Miller, 2000; Lincoln
& Guba, 1985). Thick description is described by Lincoln
and Guba as a w ay of achieving a type of external valid-
ity. By describing a phenom enon in sufficient detail one
can begin to evaluate the extent to which the conclusions
d raw n are transferable to other times, settings, situations,
and people. Since, as stated by M erriam (1995) it is the
responsibility of the consum er of research to determ ine
or decide if and how research results m ight be applied
to other settings, the original researcher m u st provide
detailed inform ation about the phenom enon of study to
assist the consum er in m aking the decision. This requires
the provision of copious am ounts of inform ation regard-
ing every aspect of the research. The investigator will
include such details as the location setting, atm osphere,
climate, participants present, attitudes of the participants
involved, reactions observed that m ay not be captured on
audio recording, bonds established betw een participants,
and feelings of the investigator. One w ord descriptors will
not suffice in the developm ent of thick description. The
investigator in essence is telling a story w ith enough detail
that the c o n su m er/read er obtains a vivid picture of the

events of the research. This can be accom plished through
journaling and m aintaining records w h eth er digital or
handw ritten for review by the consum er/reader.
Confirmability Activities
To establish confirmability Lincoln and Guba (1985)
suggested confirmability audit, audit trail, triangulation,
and reflexivity. An audit trail is a transparent description of
the research steps taken from the start of a research project
to the developm ent and reporting of findings (Lincoln &
Guba). These are records that are kept regarding w hat was
done in an investigation. Lincoln and Guba cite H alpern's
(1983) categories for reporting inform ation w hen develop-
ing an audit trail:
"1) Raw data - including all raw data, written field
notes, unobstrusive measures (documents); 2) Data
reduction and analysis products - including sum -
maries such as condensed notes, unitized information
and quantitative summaries and theoretical notes; 3)
Data reconstruction and synthesis products - includ-
ing structure o f categories (themes, definitions, and
relationships), findings and conclusions and a final
report including connections to existing literatures
and an integration o f concepts, relationships, and
interpretations; 4) Process notes - including method-
ological notes (procedures, designs, strategies, ratio-
nales), trustworthiness notes (relating to credibility,
dependability and confirmability) and audit trail notes;
5) Materials relating to intentions and dispositions -
including inquiry proposal, personal notes (reflexive
notes and. motivations) and expectations (predictions
and intentions); 6) Instrum ent development informa-
tion - including pilot forms, preliminary schedules,

observation form ats" (page#).
Using m ultiple data sources w ithin an investigation to
enhance understanding is called triangulation. Researchers
see triangulation as a m ethod for corroborating findings
and as a test for validity (Lincoln & Guba, 1985). Rather
than seeing triangulation as a m ethod for validation or veri-
fication, qualitative researchers generally use this technique
to ensure that an account is rich, robust, comprehensive
and well-developed (Lincoln & Guba, 1985).
D enzin (1978) and Patton (1999) identify four types of
triangulation: m ethods triangulation, source triangulation;
analyst triangulation; th eo ry /p ersp ectiv e triangulation.
They suggested that m ethods triangulation involves check-
ing out the consistency of finding generated by different
data collection m ethods. Triangulation of sources is an
exam ination of the consistency of different data sources
from w ithin the same m ethod (i.e. at different points in
time; in public vs. private settings; com paring people w ith
different viewpoints).
A nother one of the four m ethods identified by Denzin
and Patton includes analyst triangulation. This is the use
of m ultiple analysts to review findings or using m ultiple
observers and analysts. This provides a check on selective
perception and illum inate blind spots in an interpretive
analysis. The goal is to understand m ultiple ways of see-
ing the data. Finally, they described th eory/perspective
triangulation as the use of m ultiple theoretical perspectives
to examine and interpret the data.
According to Lincoln and Guba (1985) reflexivity is,
"A n attitude of attending system atically to the context
of know ledge construction, especially to the effect of the
researcher, at every step of the research process." They

suggested the following steps to develop reflexivity: 1)
Designing research that includes m ultiple investigators.
This fosters dialogue, leads to the developm ent of comple-
m entary and divergent understandings of a study situation
and provides a context in w hich researchers' (often h id -
den) - beliefs, values, perspectives and assum ptions can be
revealed and contested; 2) Develop a reflexive journal. This
is a type of diary w here a researcher m akes regular entries
during the research process. In these entries, the researcher
records methodological decisions and the reasons for them,
the logistics of the study and reflection u p o n w hat is h a p -
pening in term s of one's ow n values and interests. Diary
keeping of this type is often very private and cathartic; 3)
Report research perspectives, positions, values and beliefs
in m anuscripts and other publications. Many believe that it
is valuable and essential to briefly report in m anuscripts, as
best as possible, how one's preconceptions, beliefs, values,
assum ptions and position m ay have come into play during
the research process.
Dependability Activities
To establish dependability, Lincoln and Guba (1985) sug-
gested a technique know n as inquiry audit. Inquiry audits
are conducted by having a researcher that is not involved in
the research process examine both the process and product
of the research study (Lincoln & Guba, 1985). The purpose
is to evaluate the accuracy and evaluate w hether or not the
findings, interpretations and conclusions are supported by
the data (Lincoln & Guba, 1985).
Journal of Cultural Diversity • Vol. 23, No. 3 Fall 2016
Creating a Protocol for Qualitative Researchers

The creation of a protocol for establishing trustwor-
thiness within qualitative research is essential to rigor.
Further, we note that researchers rarely document how
or w hat their trustworthiness plan or protocol consisted
of within research documents. Thus, we posit here that
creating such a protocol prior to initiation of the research
study is essential to revealing trustworthiness within the
research process. By creating this plan a priori, the rigor
of qualitative research is apparent.
This history and purposed need for this article heralds
from a doctoral dissertation search to find examples of
trustworthiness protocols for direction to complete trust-
worthiness within doctoral qualitative research. Since none
could be found, discussions lead the researcher to create a
table that could used by those who are planning qualita-
tive studies. Another interesting point is that qualitative
researchers, unlike quantitative researchers, rarely create
protocol guidelines.
The establishment of trustworthiness protocols in quali-
tative research requires the use of several techniques. This
protocol will be detail specific so those researchers have
a guideline for trustworthiness activities. Such a protocol
guides prospective qualitative researchers in their quest
for rigor. Several tables are presented here. The first table
outlines the main topics within the trustworthiness proto-
col. The remaining tables outline the suggested activities
within trustworthiness protocol and for those creating a
trustworthiness protocol.
Table one is the basic criteria for a trustworthiness pro-
tocol using Lincoln and Guba (1985). However, researchers
may use other models of rigor. Creating a table aligned with
the planned model of rigor is the recommendation. The

following five table are examples of a "created" protocol
w ith examples of very specific activities related to each
trustworthiness criteria.
Summary
In summary, trustw orthiness is a vital com ponent
within the research process. Attending to the language of
trustworthiness and the important activities of reliabil-
ity, add to the comprehensiveness and the quality of the
research product. This discussion heralds the new idea
that trustworthiness must be planned ahead of time with
a protocol. This protocol must include dates and times
trustworthiness actions. We contend that researchers can
use the protocol by adding two columns which specify the
date of the planned trustworthiness action and the date the
action was actually completed. This information can then
be included in the audit trail thus authenticating the work
qualitative researcher and the rigor of the research.
REFERENCES
Altheide, D., & Johnson, J. (1998). Criteria for assessing
interpre-
tive validity in qualitative research. In N. K. Denzin, & Y. S.
Lincoln (Eds.), Collecting and interpreting materials, 283- 312.
Creswell, J. & Miller, D. (2000). D eterm ining validity and
qualita-
tive inquiry. Theory Into Practice, 39(3), 125-130.
Denzin, N. (1978). Sociological Methods. N ew York: M
cGraw-Hill.
Guba, E. & Lincoln, Y. (1981). Effective evaluation: improving
the
usefidness of evaluation results through responsive and

naturalistic
approaches. San Francisco, CA: Jossey-Bass.
Leininger, M. (1994). Evaluation criteria and critique of
qualitative
and interpretive research. Qualitative Inquiry, 1, 275-279.
Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic Inquiry. N ew
bury
Park, CA: Sage Publications.
Morse, J. (1999). Myth #3: Reliability and validity are n ot
relevant
to qualitative mquiry.Qualitative Heath Research, 9, 717.
Patton, M. Q. (1999). "Enhancing the quality and credibility of
qualitative analysis." HSR: Health Services Research. 34(5),
Part II, 1189-1208.
BIBLIOGRAPHY
Bitsch, V. (2005). Qualitative research: A grounded theory
example
and evaluation criteria. Journal of Argibusiness, 23 (1), 75-91.
Carpenter, R. (1995). G rounded theory research approach. In H.
J. Streubert & R. D. Carpenter(Eds-), Qualitative research and
in nursing: Advancing the humanistic imperative, 145-161.
C ohen D., Crabtree, B. (2006). Q ualitative Research
Guidelines
Project. July 2006. http://w w w .qualres.org/H om eRefl-3703.
htm l
Giacomini, M. & Cook, D. (2000). A u s e r's guide to
qualitative

research in health care. In Users' guides to evidence-based
medicine. Journal o f the American Medical Association,
284(4),
478-482.
Morse, J. Barrett, M., Mayan, M., Olson, K., & Spiers, J.
(2002).
Verification strategies for establishing reliability and valid-
ity in qualitative research. International Journal o f Q u a lita -
tive Methods, 1, 2, Article 2. Retrieved April 30, 2010 from
http: / / w w w .u alb erta.ca/-ijq rn /
Neuman, L. (2003). Qualitative and quantitative measurements.
In
Social research methods: Qualitative and quantitative
approaches,
fifth edition, 169-209.
Plack, M. (2005). H um an nature and research paradigm s:
Theory
meets physical therapy practice. The Qualitative Report, 10(2),
223-245.
Polit, D. & Hungler, B. (1999). Research control in quantitative
research. In N ursing research: P rin c ip le s a n d m e th o d s
,
sixth edition, 219-238. Lippincott.
Rubin, H. & Rubin, I. (1995). Qualitative interviewing: The art
of
hearing data. Thousand Oaks, CA: Sage Publications.
Siegle, D. (2002). Principles and m ethods in educational
research:
A web-based course from the University of Connecticut. Re-
trieved April 30, 2010 from http: / / w w w .gifted.uconn.edu/

siegle / research/qualitative / qualitativeInstructorNotes.html
Tobin, G. & Begley, C. (2004). M ethodological rigour w ithin a
qualitative fram ew ork. Journal of Advanced Nursing, 48(4),
388-396.
Table 1. Basic Trustworthiness Criteria (Lincoln & Guba, 1985)
Criteria Technique
Credibility Peer debriefing, m em ber checks, journaling
Transferability Thick description, journaling
Dependability Inquiry audit with audit trail
Confirm ability Triangulation, journaling
Journal of Cultural Diversity Fall 2016
http://www.qualres.org/HomeRefl-3703
http://www.ualberta.ca/-ijqrn/
http://www.gifted.uconn.edu/
Table 2. Credibility
Credibility R ecom m ended activities/plan
Peer 1. W rite plan within proposal.
debriefing/debriefer
2. Com m ission a peer to w ork with researcher during the tim e
of interviews and data
collection.

3. This person must com plete an attestation form to work with
researcher. Plan to meet
with this person after each interview.
4. During visits with the peer debriefer, research and peer
discuss interviews, feelings,
actions o f subjects, thoughts, and ideas that present during this
time. Discuss
blocking, clouding and other feelings of researcher. Discuss
dates and tim es needed
fo r these activities. W ill meet once a w eek fo r 30 minutes to
an hour.
5. Journal these meetings. W rite about thoughts that surfaced
and keep these dated for
research and evaluation during data analysis.
6. Need to be com puter files so that you may use this inform
ation within data analysis.
M em ber Checks 1. Outline different tim es and reasons you
plan to conduct m em ber checks or collect
feedback from m em bers about any step in the research process.
2. M em ber checks will consist o f com m unication with mem
bers after significant
activities.
3. These activities may include interviews, data analysis, and
other activities.
4. W ithin two weeks o f the interview, send mem bers a copy o
f their interview so that
they can read it and edit for accuracy.
5. W ithin two weeks o f data analysis com pletion, m em ber

will review a copy o f the final
them es.
6. M em bers are asked the question, “ Does the interview
transcript reflect your words
during the interview?”
7. C hoose negative cases and cases that follow pattern.
8. Be sure these check are recorded and are com puter files so
that you may use this
inform ation in data analysis.
Journaling plans 1. Journaling will begin with the writing o f
the proposal.
2. Journaling will be conducted after each significant activity.
These include each
interview, w eekly during analysis, after peer debriefing visits,
and them e production.
3. Journals will be audited by research auditor.
4. Journals will include dates, times, places and persons on the
research team.
5. Journals need to be com puter files so that you may use them
in data analysis.
Protocol Create a tim eline with planned dates fo r each activity
related to credibility before
com m encing the study. This protocol with dates and activities
should appear in the
appendix.

Table 3. Transferability
Thick Description Actions for this activity include:
1. Reviewing crafted questions with Peer reviewer for clarity.
2. Planning questions that call for extended answers.
3. Asking open ended questions that solicit detailed answers.
4. Interviewing in such a way as to obtain a detailed, thick and
robust response.
5. The object is to reproduce the phenomenon of research as
clearly and as detailed as
possible.
6. This action is replicated with each participant and with each
question (sub-question)
or statement.
7. This continues until all questions and sub-questions are
discussed.
8. The peer reviewer along with the researcher review responses
for thickness and
robustness.
9. There are two issues related to thick description here. The
first is receiving thick
responses (not one sentence paragraphs). The second is writing
up the responses of
multiple participants in such a way as to describe the

phenomena as a thick
response.
Journaling Actions for this activity include:
1. Planning journal work in advance is an option. Such that the
researcher could decide
what dates and how often the journal will occur.
2. Journaling after interview is common.
3. Journaling after peer-review sessions.
4. Journaling after a major event during the study.
5. Journal entries should be discussed with peer reviewer such
that expression of
thoughts and ideas gleaned during research activities can be
connected to
participants’ experiences.
6. Journals can be maintained in various formats. Information
for the journal can be
received in the form of emails, documents, recordings, note
cards/note pads. We
recommend that the researcher decide on one of the options.
7. Journaling includes dates of actions related to significant and
insignificant activities of
the research.
8. Journal may start on the first date a decision is made to
conduct the research.
9. Journaling ends when the research is completed and all
participants have been

interviewed.
10. As with each of the concepts here, create a timeline with a
date-line protocol for each
activity before commencing the study.
Protocol Create a timeline with planned dates for each activity
related to transferability before
commencing the study. This protocol with dates and activities
should appear in the appendix.
Journal of Cultural D iversity • Vol. 23, No. 3 Fall 2016
Table 4. Dependability
A udit Trail Com ponents o f the audit trail include:
1. Make the list of docum ents planned for audit during the
research work.
2. Com m ission the auditor based on plan for study.
3. Decide audit trail review dates and times.
4. See auditor inform ation below
5. W rite up audit trail results in the journal.
Journaling A ctions for this activity include:
I . Planning journal w ork in advance is an option. Such that
the researcher could decide what
dates and how often the journal will occur.

I I . Journaling after interview is common.
13. Journaling after a m ajor event during the study.
that expression of thoughts
and ideas gleaned during research activities can be connected to
participants’ experiences.
15. Journals can be maintained in various form ats. Information
fo r the journal can be received in
the form of emails, docum ents, recordings, note cards/note
pads. W e recom m end that the
researcher decide on one o f the options.
16. Journaling includes dates o f actions related to significant
and insignificant activities o f the
research.
18. Journaling ends w hen the research is com pleted and all
participants have been interviewed.
Auditor 1. The auditor is reviewing the docum ents fo r
authenticity and consistency.
2. The auditor may be a colleague or som eone unfam iliar with
the research such that activities
can be questioned fo r clarity.
3. The auditor should have som e com prehension o f the
research process.

4. Planning in advance fo r the tim e com m itm ent as an
auditor is crucial.
5. Should provide constructive feedback on processes in an
honest fashion.
6. Auditor, researcher, and participants should speak the same
language.
7. Must be able to create and maintain audit trail documents.
Protocol Create a tim eline with planned dates fo r each activity
related dependability before com m encing the
study. This protocol with dates and activities should appear in
the appendix.
Table 5. Confirmability
Triangulation 1. Determine triangulation methods
2. Document triangulation plans within journal.
3. Discuss triangulation results peer-reviewer
4. Decide if further triangulation is needed
5. Write up the triangulation results.
Journaling Actions for this activity include:
2. Planning journal work in advance is an option. Such that the

researcher could decide what
dates and how often the journal will occur.
19. Journaling after interview is common.
21. Journaling after a major event during the study.
that expression of thoughts
and ideas gleaned during research activities can be connected to
participants
experiences.
23. Journals can be maintained in various formats. Information
for the journal can be received
in the form of emails, documents, recordings, note cards/note
pads. We recommend that
the researcher decide on one of the options.
24. Journaling includes dates of actions related to significant
and insignificant activities of the
research.
Journaling ends when the research is completed and all
participants have been interviewed.
Protocol Create a timeline with planned dates for each activity
related confirmability before commencing the
study. This protocol with dates and activities should appear in
the appendix.

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Contents lists available at ScienceDirect
Currents in Pharmacy Teaching and Learning
journal homepage: www.elsevier.com/locate/cptl
Methodology Matters
Thematic analysis of qualitative research data: Is it as easy as it
sounds?
Ashley Castleberrya,⁎, Amanda Nolenb
a University of Arkansas for Medical Sciences, College of
Pharmacy, 4301 West Markham Street, Slot 522-4, Little Rock,
AR 72205, United States
b University of Arkansas at Little Rock, School of Education,
2801 S. University, Little Rock, AR 72204, United States
A R T I C L E I N F O

Keywords:
Qualitative
Thematic analysis
A B S T R A C T
Issue: We are seeing the use of qualitative research methods
more regularly in health professions
education as well as pharmacy education. Often, the term
“thematic analysis” is used in research
studies and subsequently labeled as qualitative research, but
saying that one did this type of
analysis does not necessarily equate with a rigorous qualitative
study. This methodology review
will outline how to perform rigorous thematic analyses on
qualitative data to draw interpreta-
tions from the data.
Methodological Literature Review: Despite not having an
analysis guidebook that fits every re-
search situation, there are general steps that you can take to
make sure that your thematic
analysis is systematic and thorough. A model of qualitative data
analysis can be outlined in five
steps: compiling, disassembling, reassembling, interpreting, and
concluding.
My Recommendations and Their Applications: Nine practical
recommendations are provided to
help researchers implement rigorous thematic analyses.
Potential Impact: As researchers become comfortable in
properly using qualitative research
methods, the standards for publication will be elevated. By
using these rigorous standards for
thematic analysis and making them explicitly known in your
data process, your findings will be
more valuable.

Issue
We are seeing the use of qualitative research methods more
regularly in health professions education, as well as pharmacy
education.1 Moreover, researchers recognize that qualitative
methods provide “a source of well-grounded, rich descriptions
and
explanations of processes in identifiable local contexts”2
meaning the descriptions arise from the data but provide insight
that goes
beyond only numbers. Additionally, mixed-methods approaches
combining qualitative and quantitative data analyses are
becoming
more popular in health professions practice and education.3
Qualitative research has been used in fields like education,
sociology, and anthropology for some time and has, excitedly,
gained
more traction in the health research and health professions
education fields but remains under utilized.2,4 This lag in
adoption is
likely due to the skepticism regarding the rigor of such methods
from researchers, including pharmacists, who are more
accustomed
to quantitative research methods using statistical tests to
“prove” an outcome and/or provide validity and reliability
evidence.5 While
quantitative research tends to focus on the frequency, intensity,
or duration of a behavior, qualitative research methods allow us
to
explore the beliefs, values, and motives that explain why the
behaviors occur. The primary aim of qualitative research is to
gain a
better understanding of phenomenon through the experiences of
those who have directly experienced the phenomenon,
recognizing

https://doi.org/10.1016/j.cptl.2018.03.019
⁎ Corresponding author.
E-mail addresses: [email protected] (A. Castleberry),
[email protected] (A. Nolen).
Currents in Pharmacy Teaching and Learning 10 (2018) 807–
815
1877-1297/ Published by Elsevier Inc.
T
http://www.sciencedirect.com/science/journal/18771297
https://www.elsevier.com/locate/cptl
http://crossmark.crossref.org/dialog/?doi=10.1016/j.cptl.2018.0
3.019&domain=pdf
the value of participants' unique viewpoints that can only be
fully understood within the context of their experience and
worldview.
The value of this approach to empirical research is that it
provides a richer, deeper understanding of the meanings that
people place
on actions, events, and relationships.6 In academic medical
education in general and in pharmacy education specifically,
qualitative
methods are used to explore the complex phenomenon
encountered by faculty, students, patients, and policymakers.7

The descriptive nature of qualitative approaches allows the
researcher to build a complex, holistic picture in a natural
setting.8
This approach has been described as a bricolage of a wide range
of interconnected methods to capture the essential essence of a
phenomenon.9 The methodological literature is in agreement
that qualitative research is a term that includes several research
designs
(e.g., case study, ethnography, grounded theory, narrative
inquiry, and phenomenology) characterized by specific design
assump-
tions, sampling procedures, data collection, and data analysis
protocols.10
One of the challenges to qualitative research is the open-ended
nature of data as opposed to numbers only. Examples of
qualitative
data can include interview transcripts, newspaper articles,
questionnaire responses, diaries, videos, images, or field
observations.
Text as data is often more difficult to reduce and identify
patterns than numbers as data. Thematic analysis (TA) is a data
analysis
strategy that is a commonly used approach across all qualitative
designs and is the subject of this methodology review. Often,
TA is
used in research studies and subsequently labeled as qualitative
research, without providing the necessary details about how the
analysis reduced the data into workable themes and the
emerging conclusions. Collingridge and Gantt note “an
understanding of the
standards of rigorous qualitative research and familiarity with
qualitative approaches has not kept pace with the growing
presence of

qualitative methods.”11
TA is a method of “identifying, analyzing, and reporting
patterns (themes) within data”.12 It is described as a descriptive
method
that reduces the data in a flexible way that dovetails with other
data analysis methods.13 It is used commonly because of the
wide
variety of research questions and topics that can be addressed
with this method of data analysis.14 TA of open ended
responses from
surveys or transcribed interviews can explore the context of
teaching and learning at a level of depth that quantitative
analysis lacks
while allowing flexibility and interpretation when analyzing the
data, but it should be undertaken with special care and attention
to
transparency of the method in order to ensure confidence in the
findings.12
This methodology review will outline how to perform TA on
qualitative data. This research method can greatly benefit
pharmacy
education, therefore it is imperative that studies be designed
and reported effectively to maintain the high standards of
educational
scholarship.15 By using sound and respected data collection and
analysis techniques, the researchers can build trustworthiness
and
credibility with their readers.6
Methodological literature review
In pharmacy education, the most common type of qualitative
data gathered is in the form of open-ended responses to ques-
tionnaires or reflections in written form. Additionally, content

from interviews and focus groups can be gathered. Designing
questions
to gather the data in these multiple formats is integral to ensure
collection of good data. While collecting the data can be very
fun and
exciting, the real fun begins when the data are analyzed.
Yin's book, Qualitative Research from Start to Finish, outlines a
general framework to design a qualitative research study:
collect and
record data, analyze the data, display and disseminate your
findings.6 For the remainder of this section, the focus will be
on the
analysis portion of the research process.
In general, analysis of qualitative data can be outlined in five
steps: compiling, disassembling, reassembling, interpreting, and
concluding.6 The process of TA will be described within this
framework.
Compiling
Compiling the data into a useable form is the first step to
finding meaningful answers to your research questions.
Compiling might
mean transcribing so that the researchers can easily see the data.
If your data needs transcribing from an interview or focus
group,
some experts recommend that you do the transcription
yourself.16 While this takes much more time then paying
someone to provide
this service for you, the closeness to the data that you achieve
during this process can jumpstart the other steps of the data
analysis
process. It seems intuitive, but the researcher needs to read and
reread the data to become intimately familiar with it. This

should
occur many times throughout the analysis process. In this phase,
the researcher is expected to transcribe interviews or focus
groups,
collate responses, and organize other textual data to be included
in the analysis. Transcription services can help the researcher to
save
time but it is even more important that the researcher know the
data intimately. In familiarizing themselves with the data,12 the
researcher acquires a sense of the entirety of the data and allows
a greater understanding of phrasing or the meaning of a term
when
viewed within the context of the whole. After getting your data
in a consistent and organized format, you are ready to begin
dissecting your data to discover its components.
Disassembling
After compiling and organizing the data, it must be separated.
Disassembling the data involves taking the data apart and
creating
meaningful groupings. This process is often done through
coding. Coding, in the realm of qualitative research, is defined
as “the
process by which raw data are gradually converted into usable
data through the identification of themes, concepts, or ideas that
have
some connection with each other.”5 Coding simply involves
researchers identifying similarities and differences in the
data.16
Kuper describes how qualitative research differs from
quantitative research in that “qualitative data analysis is largely
inductive,
A. Castleberry, A. Nolen Currents in Pharmacy Teaching and

Learning 10 (2018) 807–815
808
allowing meaning to emerge from the data, rather than the more
deductive, hypothesis centered approach favored by quantitative
researchers.”4 The meaning that “emerges from the data” is
often first seen as the data is disassembled or coded.
The activity of coding involves identifying interesting features
of the data systematically across the entire data set and occurs
at
multiple levels. Initially, codes are attached to units of data that
could vary in size (i.e., phrase, sentence, paragraph) but usually
codes encompass a complete thought. They can take the form of
a descriptive label that directly describes or is taken from the
text.
However, codes can also be more abstract and complex in the
form of metaphors or literary references.2 The code serves as a
tag used
to retrieve and categorize similar data so that the researcher can
pull out and examine all of the data across the dataset
associated
with that code.
The action of coding requires the researcher to ask specific
questions of the data as appropriate.17
• What is happening in the text?
• Who are the actors and what are their roles?
• When is it happening? (preceding event, during event, reaction
to event, etc.)
• Where is it happening?
• What are the explicit and implicit reasons why it is

happening?
• How is it happening? (process or strategy)
A coding strategy can be established before coding begins (a
priori) based on a careful review of previous research or
theory.18 If a
previous coding scheme has been used in other studies similar
to yours, you may choose to use this as the starting point for
your
scheme. This can be accomplished by reviewing the literature
inside and outside of your discipline to uncover a coding
scheme used
by others in similar context that could translate well to the new
research situation. If the scheme does not fit your data well,
modifications can be made. In contrast to a priori, the coding
scheme can be open or emergent–meaning that the scheme is
created as
coding ensues because there is no beginning structure of the
scheme but rather it develops during the coding process.
Saldana describes twenty-five coding methods categorized into
seven groups.19 These approaches provide guidance to the re-
searcher and answers the question, “How do I know what to
code for?” While twenty-five coding methods may seem
overwhelming,
Saldana suggests that many of these methods overlap in intent
and can be mixed and matched. For example, the “descriptive”
code is
a code applied to a basic topic from the data. Descriptive codes
could be used to identify a role, process, action, place or
something
that is easily identified. Another coding approach is “In Vivo”
coding that uses verbatim words or phrases from the
participants’
narrative to describe the unit of data. In Vivo codes provide
insight into how participants are talking about a phenomenon

since it
uses the participants’ voice when developing units of code. For
example, a participant might use the word “scripts” to refer to
prescriptions. This is a unique term that suggests a possible
micro-culture such as pharmacy that uses specific terminology.
Most
likely, the researcher would choose a combination of these
approaches to coding based on the purpose of the study and
guided by
their research questions.
As the researcher is coding, he or she is developing definitions
for each code or groups of codes. These definitions could be
thought of as inclusion and exclusion criteria in a quantitative
study, and they ensure that codes are applied reliably
throughout the
data. As the code book containing code definitions is developed
and refined, it is often necessary for the researcher to go back
and re-
code previously coded material to make certain that data
examined early in the analysis is coded in the same manner and
with the
same coding definitions/criteria as data addressed later in the
analysis. Researchers new to qualitative research methods often
ask,
“When can I stop coding and analyzing data?” When no new
themes are identified upon reviewing new data, researchers can
be
confident in their coding scheme.5
Because TA draws upon a substantial amount of textual data,
software programs are available to facilitate the organization
process. Collectively they are called Computer-Assisted
Qualitative Data AnalysiS or CAQDAS (pronounced “cactus” –
like the plant
in the desert). These can be helpful, but programs such as

Microsoft Excel and Access can be as effective. NVivo® (QSR
International
Pty Ltd), MAXQDA (VERBI GmbH), and ATLAS.ti®
(Scientific Software Development GmbH) are widely used tools
that provide
technological support to the qualitative research that
streamlines the data analysis process and allows for more
complex, deeper
analysis of the data. We have used NVivo® for several projects
and found it easy to use while creating beautiful graphical
displays for
the data.20 These software tools assist the researcher in looking
at patterns of codes and links between codes across large fields
of
data. Linguistic and semantic algorithms detect sequencing and
co-occurring phrasing in a reliable and systematic manner. A
common misconception is that CAQDAS software can analyze
the data for you–this cannot be farther from the truth. While
software
can assist researchers with organizing large amounts of
qualitative data, the researcher's mind is the power behind
analysis and not
any software program. Fig. 1 provides example coding with
NVivo®.
Reassembling
The codes, or categories to which each concept is mapped, are
then put into context with each other to create themes. A theme
“captures something important about the data in relation to the
research question, and represents some level of patterned
response or
meaning within the data set”.12 Braun and Clarke use a house
as an analogy to describe codes and themes-codes are the bricks
that
comprise the walls or themes.14 If simply put, themes are

patterns in the codes; they take the numerous pieces of related
code to show
a bigger picture of what is being portrayed. Themes can be
further divided into sub-themes.
Two common ways qualitative researchers put the data back
together within themes are hierarchies and matrices. Thematic
hierarchies provide a visual tool with which to articulate how
themes are subordinate or superordinate to each other.
Hierarchies are
Learning 10 (2018) 807–815
809
constructed by clustering similar codes to produce higher-order
codes. The researcher is then able to analyze the restructured
data at
multiple levels of granularity. The higher-order codes provide
the researcher a view across the broad, thematic landscape of
the data.
More detailed codes allow the researcher to examine fine
distinctions across instances. Matrices are constructed by
arranging par-
ticipant roles, themes, variables, emerging concepts, and data
sources into rows and columns to provide a broad visual
representation
that grounds findings in the data and context.2 Heath et al.
published an ‘insider's view’ to the method behind their study
on hospital
outpatient pediatric care.21 Table 1 is one of the matrices they
constructed showing participants (rows) and codes (columns).
They

constructed separate matrices for each category. Each cell
shows an excerpt of verbatim data from interview transcripts.
The matrix
provided an important analytical tool for the researchers to
examine how the participants viewed the role of pediatric
services in the
community by their role.
Both hierarchies and matrices are tools used to provide a
structure with which to reduce qualitative data as well as
communicate
relationships among groups, contexts, constructs, and codes.
Other tools to help visualize the data include flowcharts,
concept maps,
and diagrams.
During reassembly, the analytical thinking of the researchers is
evidenced. The researcher begins by gathering all relevant data
into each potential theme and continuously reviews each theme
to determine if it is robust in relation to the coded extracts and
data
set. Care must be taken to tell the story of the data and not
arrange the data to support the researchers’ theory or overreach
the data.7
When quality checking theme development, research should ask
a few key questions14:
• Is this a theme (it could be just a code)?
• If it is a theme, what is the quality of this theme (does it tell
me something useful about the dataset and my research
question)?
• What are the boundaries of this theme (what does it include
and exclude)?
• Are there enough (meaningful) data to support this theme (is
the theme thin or thick)?

• Are the data too diverse and wide ranging (does the theme
lack coherence)?
Review by multiple researchers can help to validate that the
groupings of data are consistent with the raw data by
establishing
inter-coder reliability. This can be easily accomplished through
NVivo® and other analysis software programs by comparing
coding
done by multiple researchers on the same text. A coding
comparison query will calculate percentage agreement among
coders as well
as a Kappa coefficient that considers the amount of agreement
that could be expected to occur due to chance. It is important to
note
that inter-relater reliability is not the “rule” when conducting
qualitative research. If the data include unstructured, interactive
interviews, Morse cautions against attempting to achieve inter-
coder reliability due the reflexive and complex nature of the
exchange
between the interviewer and the participant(s).22 Doing so
might unintentionally lead to an over-simplification of the
coding,
Fig. 1. Example of thematic analysis coding with NVivo(®)
software.
Learning 10 (2018) 807–815
810
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Learning 10 (2018) 807–815
811
analysis, and insights in an attempt to reach agreement across a
team of researchers.
If a researcher is working alone or shares the concern illustrated
by Morse when working with unstructured and complex qua-
litative data, establishing intra-coder reliability along with
member-checking or participant validation are a very suitable
alter-
natives.19,22 Intra-coder reliability allows you to assess the
consistency with which you are coding similar data. Experts
recommend
coding a portion of the data right way, waiting a few days, then
returning and re-coding the same data.2 Internal consistency
should
be in the range of 85–90% depending on the complexity of your
coding scheme. It is also recommended to review emerging
findings
with participants in order to affirm that their experiences are
represented accurately.22 Through this process you acquire
valuable
feedback throughout the analytic process that in turn supports
your ability to defend interpretations and conclusions.5,23
Interpreting
Unfortunately, data do not “speak for themselves”.6 This
critical stage in the research process involves the researcher
making

analytical conclusions from the data presented as codes and then
themes. Even though the steps of data analysis are listed in
linear
sequence, interpretation does not have to wait until the end of
the analysis process. In fact, interpretation by the researcher
should be
happening during the first three steps (compiling,
disassembling, and reassembling).6
Yin explains that there is no checklist to constitute good
interpretation, but there are five qualities that should be the
goal of all
qualitative interpretations. First, the interpretation should be
complete. Readers should be able to see the beginning, middle,
and end
of how the interpretations were drawn. Second, the
interpretations should be fair in that other researchers should
reach the same
interpretation if given the same data. Third, the interpretations
should also be accurate and representative of the raw data.
Fourth, in
the context of current literature, good studies will add value to
our understanding of the topic. Fifth, data methods and
subsequent
interpretations should be credible and gain respect from
colleagues.6
Once data has been reassembled through coding, the researcher
is then able to extract excerpts from the data and view them in
relation to and in the concert with each other. Doing so allows
the researcher to begin to start focusing on interpreting what is
going
on within and across varied experiences, beliefs, and histories
and thus begin to identify thematic patterns across the data.
Themes
capture an essence of the phenomenon under investigation in

relation to your research question or purpose of the study. These
usually are abstract and difficult to identify from reading over
raw data the first few times. Furthermore, in TA, the importance
of the
theme is not dependent upon how often it appears or how much
data is contained within the theme. Rather, the importance is
related
to whether it captures something important in relation to the
overall research questions.
As part of this level of the analysis, researchers will often
develop a thematic map which is a visual representation of
themes,
codes, and their relationships (Fig. 2).24 These maps usually
involved detailed descriptions of the themes including
describing the
patterns identified across the coded data. Braun and Clarke
provide an example of how thematic maps evolve throughout a
study as
the researchers’ thinking about the themes and how they relate
to each other evolve.12 This visual representation provides
another
level of analysis in TA that allows the researcher to place the
themes in the larger context of the larger landscape of the
phenom-
enon.25
Qualitative data analysis software is particularly useful in
developing data visualizations in the form of a three-
dimensional map
of code clusters. By viewing your re-assembled data in this
way, you are able to see relationships and connections among
constructs
that are not readily apparent. Fig. 3 provides example data
visualization in NVivo® showing how codes cluster together in
the text

across the data. The size of the nodes suggests how often that
code is present across the data. The colors indicate families of
codes or
codes with meanings or functions. The diagram can be rotated
in any direction to get a clearer view of any particular code.
This
particular figure is from a content analysis of academic
department chair job postings across 20 years.26
These major themes become the starting point in interpreting
how the themes relate to each other. Be cautious to not simply
restate one's codes and themes as interpretations. Your
interpretations should be at higher levels than themes. This
means that
interpretations should include discussions of relationships
between themes and more global findings in the context of all
codes, which
is broader and more general than the specific codes, or themes.
Another way to identify interpretations from the data is to
answer
research questions after the data has been coded. After all,
research questions are where studies start and end. When you
have enough
clarity to write the subtitle for your manuscript, you know you
have arrived at your interpretations.6 Interpretations should
arise
easily from your data and become the foundations for your
conclusions.
Concluding
In the context of TA, raw data forms codes and codes form
themes and thematic maps. Identifying and defining these
themes leads
to interpretations. Conclusions are the response to the research
questions or purpose of the study.6 All research should start

with a
plausible research question and analysis should always answer a
question; it just could be that the question shifted slightly over
the
course of the data analysis process.14
While the qualitative research community resists establishing a
single set of evaluative standards to determine research quality,
some journals may require adherence to certain guidelines in
order to publish qualitative research. Qualitative researchers
ascribe to
common values of transparency of data analysis and recursive
interpretations.27 Research must yield results that are open for
careful
scrutiny into the researchers’ decision making throughout the
analysis process. This can be accomplished with a detailed
description
of coding procedures and criteria, detailed description of how
codes and patterns of codes led to themes and resulting
interpretation.
It is worth noting that conclusions from qualitative research are
not usually generalizable.23,28 The conditions in which
qualitative
research is conducted can often not be replicated. This is not a
hindrance or limitation to the research, but rather a feature of
the
Learning 10 (2018) 807–815
812
research to be acknowledged. Readers should assess how

findings can be transferred and applied to their own area of
practice.4,5 This
process, termed analytical generalization, allows the reader to
identify differences and similarities between the research
context and
their situations in order to determine relevance and applicability
of study findings.11
Recommendations and their applications
1. Surround yourself with a team of researchers with expertise
in qualitative research. Whether you are just starting this type
of research
or have been conducting it for years, the power of a team and
mentorship cannot be overstated.5
2. To increase the consistency of the coding process, multiple
coders should be used. This quality assurance process will
ensure that your
coding scheme and interpretations are illustrative of your data.
If it is not possible to have multiple coders, keep detailed notes
of
decisions you make regarding coding the data and reassembling
the data into themes.23
3. Know your own biases and report these openly in your
manuscripts. In qualitative studies, the researcher is a part of
the research
process itself and thus brings their worldview in addressing the
research questions.5 Therefore, it must be clear to the reader
who
the investigator is and how their background could bias
findings.29
4. When reporting, include direct quotations from your data that
are brief and targeted to show readers the quality of your

coding, theme
generation, and subsequent conclusions. This can be a large step
towards transparency and dependability. Readers will be more
likely to accept your conclusions when they see that they are
rooted in empirical participant data.16 Try to avoid simply
providing
numbers to quantify how many participants mentioned each
theme. This may be appropriate for certain data, but it should
not be
the only data represented in a qualitative study.
5. To increase reliability, use sound research methods for
collecting and analyzing data as described in this review.
According to Collinridge
and Grantt, “qualitative researchers who adopt reliable,
qualitative methods and conduct their analyses in a competent
manner
are expected to produce results that enrich our understanding of
the meanings that people attach to social phenomena.”11
6. Answer your research questions. Aligning data collection
methods with your research questions while obtaining results
that cor-
relate with other previously published data will increase
validity.11,30
7. Take your time when coding for it is foundational to the data
analysis process and should not be rushed. TA is hard work. If
you are
growing data weary, take a break from your work and return to
it with fresh eyes. Be flexible in your analysis. If your inter-
pretations are not coming easily, consider recoding the data to
make sure you didn't miss key concepts.
Fig. 2. Example thematic map for visual representation of
themes, codes, and their relationships.24

Reprinted from Concept Maps: Theory, Methodology,
Technology Proc. of the First Int. Conference on Concept
Mapping, Volume 1, Daley, B. J., Using
concept maps in qualitative research, 191-197, Copyright 2004,
with permission from Author.
Learning 10 (2018) 807–815
813
8. Don't be afraid to start again. The data analysis process for
TA is not linear nor does it necessarily occur once all of the
data are
collected. The process is recursive in nature where the
researcher moves in and out of each phase of analysis. For
example, upon
examining patterns to establish a theme, the researcher might
identify an unexpected pattern that can be further defined with
additional coding and re-assembling.
9. Allow the readers to trust you and your work. Make sure that
you are transparent about your analysis process (credibility),
provide
adequate detail of study content so the reader can determine if
the findings are generalizable (transferability), indicate con-
sistency in your research to show repeatability (dependability),
and ensure that your results arise from the data and not your
biases (confirmability).
Potential impact
By following these steps for TA of qualitative data, researchers

can present work that is trustworthy and credible. An example
of
both using and explicitly describing sound qualitative analysis
processes is found in Austin's article entitled “Continuous
Professional
Development: A Qualitative Study of Pharmacists’ Attitudes,
Behaviors, and Preferences in Ontario, Canada.”31
In this study, forty-two pharmacists participated in small, 90-
min focus group sessions with an experienced facilitator who
facilitated discussion on continuing professional development.
Data gathered included field notes and direct participant
quotations.
CAQDAS software was used to assist in the coding of raw data
that was further refined into themes and subthemes.
Confirmation of
major themes was achieved through constant comparison with
field notes and member checking. Direct quotes were used
within the
body of the manuscript to allow the reader to verify thematic
coding and ensure that conclusions were then drawn from the
in-
terpretations of themes.
Benefits of following these recommendations include
recognized validity and reliability of your qualitative work.
Additionally,
researchers who have not tried any type of qualitative methods
previously could follow these steps and produce insightful
work.12
There is no magic prescription for how to best analyze
qualitative data. In fact, analysis can even change during
analysis; this
flexibility is often noted as one of the strengths and advantages
of qualitative research. But despite not having an analysis

guidebook
that fits every research situation, these general steps will help
you make sure that your analysis is systematic and thorough.27
As more
researchers become comfortable in properly using qualitative
research methods, the standards for publication will be elevated.
By
using these rigorous standards for TA and making them
explicitly known in your data process, your findings will not
only be valued in
the arena of pharmacy education, but in other fields of study as
well.
Fig. 3. Example of data visualization available with NVivo(®)
showing how codes cluster together in the text across the data.
Learning 10 (2018) 807–815
814
Disclosure
Authors have nothing to disclose in relation to this manuscript.
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http://refhub.elsevier.com/S1877-1297(17)30060-6/sbref0001

http://cmc.ihmc.us/cmc-proceedings/
http://refhub.elsevier.com/S1877-1297(17)30060-
6/sbref0029Thematic analysis of qualitative research data: Is it
as easy as it sounds?IssueMethodological literature
reviewCompilingDisassemblingReassemblingInterpretingConclu
dingRecommendations and their applicationsPotential
impactDisclosureReferences
Q
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International Journal of Nursing Studies 49 (2012) 360–371
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do
UAGOL: A guide for qualitative data analysis
rnadette Dierckx de Casterlé a,*, Chris Gastmans b, Els Bryon
c, Yvonne Denier b
entre of Health Services and Nursing Research, Faculty of
Medicine, Catholic University of Leuven, Kapucijnenvoer 35
blok d - bus 7001, 3000 Leuven, Belgium
entre for Biomedical Ethics and Law, Faculty of Medicine,
Catholic University of Leuven, Kapucijnenvoer 35 blok d - bus
7001, 3000 Leuven, Belgium

entre for Biomedical Ethics and Law & Centre for Health
Services and Nursing Research, Faculty of Medicine, Catholic
University of Leuven, Kapucijnenvoer 35
k d- bus 7001, 3000 Leuven, Belgium
What is already known about the topic?
Qualitative data analysis is a complex and challenging
part of the research process which has received only
limited attention in the research literature.
� During the analysis process of qualitative data, quite a lot
of researchers are struggling with problems that com-
promise the trustworthiness of the research findings.
� There is a lack of guidelines on how to analyze the mass
of qualitative interview data.
What this paper adds
� A theory- and practice-based guide that supports and
facilitates the process of analysis of qualitative interview
data.
R T I C L E I N F O
icle history:
ceived 27 June 2011
ceived in revised form 14 September 2011
cepted 16 September 2011
ywords:

alitative research
alysis
erview data
A B S T R A C T
Background: Data analysis is a complex and contested part of
the qualitative research
process, which has received limited theoretical attention.
Researchers are often in need of
useful instructions or guidelines on how to analyze the mass of
qualitative data, but face
the lack of clear guidance for using particular analytic methods.
Objectives: The aim of this paper is to propose and discuss the
Qualitative Analysis Guide
of Leuven (QUAGOL), a guide that was developed in order to
be able to truly capture the
rich insights of qualitative interview data.
Method: The article describes six major problems researchers
are often struggling with
during the process of qualitative data analysis. Consequently,
the QUAGOL is proposed as a
guide to facilitate the process of analysis. Challenges emerged
and lessons learned from

own extensive experiences with qualitative data analysis within
the Grounded Theory
Approach, as well as from those of other researchers (as
described in the literature), were
discussed and recommendations were presented. Strengths and
pitfalls of the proposed
method were discussed in detail.
Results: The Qualitative Analysis Guide of Leuven (QUAGOL)
offers a comprehensive method
to guide the process of qualitative data analysis. The process
consists of two parts, each
consisting of five stages. The method is systematic but not
rigid. It is characterized by iterative
processes of digging deeper, constantly moving between the
various stages of the process. As
such, it aims to stimulate the researcher’s intuition and
creativity as optimal as possible.
Conclusion: The QUAGOL guide is a theory and practice-based
guide that supports and
facilitates the process of analysis of qualitative interview data.
Although the method can
facilitate the process of analysis, it cannot guarantee automatic
quality. The skills of the

researcher and the quality of the research team remain the most
crucial components of a
successful process of analysis. Additionally, the importance of
constantly moving between
the various stages throughout the research process cannot be
overstated.
� 2011 Elsevier Ltd. All rights reserved.
Corresponding author.
E-mail address: [email protected]
. Dierckx de Casterlé).
Contents lists available at SciVerse ScienceDirect
International Journal of Nursing Studies
journal homepage: www.elsevier.com/ijns
20-7489/$ – see front matter � 2011 Elsevier Ltd. All rights
reserved.
i:10.1016/j.ijnurstu.2011.09.012
http://dx.doi.org/10.1016/j.ijnurstu.2011.09.012
http://www.sciencedirect.com/science/journal/00207489
http://dx.doi.org/10.1016/j.ijnurstu.2011.09.012
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B. Dierckx de Casterlé et al. / International Journal of Nursing
Studies 49 (2012) 360–371 361
An experience-based and detailed description of the
strengths and pitfalls of the Qualitative Analysis Guide of
Leuven (QUAGOL).
. Introduction
Imagine, a study about nurses’ involvement in euthana-
ia.1 The data are collected through in-depth interviews
ith nurses having experience in the care for patients
equesting euthanasia. The first respondent is a man,
orking in a neutral hospital, with a positive attitude
ward euthanasia. He has 10 years of experience in
ncology care and has been involved in 8 euthanasia cases.
he man speaks fluently and with conviction about the
ubject. ‘Respecting the patient’s euthanasia request’ seems

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