The Qualitative Report 2018 Volume 23, Number 11, How To Article 1, 2622-2633
Data Analysis Methods for Qualitative Research:
Managing the Challenges of Coding, Interrater Reliability, and
Michael J. Belotto Biomedical Research Alliance of New York, Hyde Park, New York, USA
The purpose of this article is to provide an overview of some of the principles
of data analysis used in qualitative research such as coding, interrater
reliability, and thematic analysis. I focused on the challenges that I experienced
as a first-time qualitative researcher during the course of my dissertation, in
the hope that how I addressed those difficulties will better prepare other
investigators planning endeavors into this area of research. One of the first
challenges I encountered was the dearth of information regarding the details of
qualitative data analysis. While my text books explained the general
philosophies of the interpretive tradition and its theoretical groundings, I found
few published studies where authors actually explained the details pertaining
to exactly how they arrived at their findings. Some authors even confirmed my
own experience that few published studies described processes such as coding
and methods to evaluate interrater reliability. Herein, I share the sources of
information that I did find and the methods that I used to address these
challenges. I also discuss issues of trustworthiness and how matters of
objectivity and reliability can be addressed within the naturalistic paradigm.
Keywords: Qualitative Research Data Analysis, Coding, Interrater Reliability,
The purpose of this commentary is to help students and new researchers navigate the
course of qualitative data analysis, in particular, areas that are not often explained in
publications of qualitative research studies, such as coding, interrater reliability, and thematic
analysis (Campbell, Quincy, Osserman, & Pederson, 2013). In order to convey some of the
challenges I faced as a first-time qualitative researcher, it is necessary to explain some of the
details of my research. In trying to decide on the topic of my dissertation to complete a degree
in public health, I thought about the difficulties I faced in my previous profession: a paramedic
in the New York City 9-1-1 system. During my 12-year career in Emergency Medical Services
(EMS), it seemed that many of the people I met were planning to pursue careers in other health
professions, focusing on medical school, physician’s assistant, or nursing, or other public safety
careers such as police officer or firefighter. This impressed upon me the notion that EMS was
viewed as a transient career. Therefore, I chose to focus my dissertation on the issue of career
longevity in the EMS profession. In particular, I examined if individuals came to this vocation
with preconceived notions, and if so, whether preemployment expectations were aligned or
misaligned with postemployment experiences. I further examined how alignment or
misalignment of expectations and experiences contributed to job satisfaction and the intention
to stay or leave the field.
Rapid turnover of emergency medical technicians (EMTs) and paramedics was a
phenomenon I also personally experienced during my tenure as a director of a hospital-based
EMS department. The importance of this problem was supported in the literature by projections
Michael J. Belotto 2623
for an aging U.S. population (U.S. Census Bureau, 2014), expected increases in age-related
medical emergencies, driving greater demand for EMS professionals (U.S. Department of
Labor, Bureau of Labor Statistics, 2014), and EMS agencies’ reported problems with both
recruitment and retention of staff (Freeman, Slifkin, & Patterson, 2009). While my literature
review yielded various studies of burnout and turnover in professionals such as emergency
room physicians, nurses, and social workers, job satisfaction and employment longevity in the
field of EMS was not well studied (Alexander, Weiss, Braude, Ernst, & Fullerton-Gleason,
2009; Perkins, DeTienne, Fitzgerald, Hill, & Harwell, 2009; U.S. Department of
Transportation, National Highway Traffic Safety Administration, 2008, 2011). In fact, the
review of the literature revealed a dearth of studies pertaining to EMS in general (Huot, 2013).
Therefore, I chose a qualitative, phenomenological design for the method of inquiry for my
I chose the qualitative approach because it is appropriate in the early stages of research,
when the important variables relevant to a particular subject of inquiry may not yet be known
(Creswell, 2009). An advantage of the interpretive paradigm is it allows the researcher to
understand a phenomenon through a process of exploration of initial suspicions and
development of preliminary theories (Trochim & Donnelly, 2008). In my own
phenomenological research (Belotto, 2017), I found that the semi-structured interview allowed
me to ensure that I elicited the same core information from each participant, while also
providing me with the flexibility to probe more deeply into the rich descriptions of experiences
that participants shared. This enabled me as the researcher, rather than leading, to follow the
participants, as they guided me to the relevant factors associated with career longevity in the
Given this context of the purpose and methodology of my research, herein are the
specific challenges I faced and how I addressed them. I begin with a discussion of the
development of my interview questions for an area of research that was young and for which
no questionnaires existed. I further explain how I addressed the validity of my interview
questions. I proceed to describe how I developed a system to code the interview transcripts.
My process of assessing interrater reliability is also explained. Finally, I discuss how I
synthesized the data into an organization of themes to interpret the findings of the research.
The lack of a current, validated questionnaire for a study such as mine presented a
number of challenges. First, this required that I create interview questions that would ensure
that I obtained the information necessary to address my research questions. Using the methods
explained by Lawshe (1975), I became familiar with the procedures to establish the content
validity of my core interview.
I assembled a panel with expertise in areas relevant to my research, including human
resources, research ethics, qualitative research, and the EMS profession. Panel members
assessed the effectiveness of the interview questions to address the research questions (see
Appendix A). A 4-point Likert scale (no relevance, low relevance, moderate relevance, and
strong relevance) was used rather than an odd number of choices, so that neutral comments
were avoided (Lynn, 1986). Taking into account the number of panel members, the formula
provided by Lawshe yielded a content validity ratio threshold, at which the degree of
concurrence of the panel would not be considered to have occurred by chance, at an alpha level
of .05. Therefore, questions yielding scores below the threshold were eliminated, thus
increasing the overall content validity index of the core interview instrument. Finding 11
individuals with varied and relevant expertise to my study who were both qualified and willing
to take the time to participate on the panel, developing and collecting the surveys, aggregating
2624 The Qualitative Report 2018
and analyzing the data, creating the tables to display the data, interpreting and writing the
results, and finally, making the necessary revisions to the interview questions added
approximately two months to the project.
Quality Assurance of the Data
After IRB approval of the study, the first participant’s interview was conducted,
recorded, and transcribed. In contrast to quantitative studies, the data analysis process began
immediately upon the enrollment of the first participant and was continuous. This process of
simultaneously recruiting participants, conducting interviews, and analyzing the data was
challenging. For example, excessive time spent on data analysis resulted in recruitment and
enrollment lags, which in turn resulted in a disruption to the scheduling of interviews and the
stream of recordings sent for transcription, thus ultimately limiting transcripts available for
analysis. Constant attentiveness was required to keep all aspects of the study flowing steadily.
I started the analysis process in keeping with what Ulin, Robinson, and Tolley (2005)
described as, immersing one’s self in the data. This meant continually reading the transcripts
to familiarize myself with the content. I assessed the quality of the data, whether responses
were ambiguous or contradictory and whether I was getting the information I needed to answer
my research questions. I also scrutinized my interview technique for bias, whether questions
were asked in a neutral manner, unexpected findings had emerged, or opportunities to probe
more deeply into responses were missed. For example, one participant provided a rich
description of how he progressed to various positions in the EMS profession, such as becoming
an educator and flight medic. This had resulted in a lengthy career of over 20 years. In
reviewing the transcript; however, I realized that I had not obtained all the information I
needed. Upon following up with this individual and probing more deeply into his thoughts
about the profession in general, he revealed that he did not think that his career was typical and
stated that he felt that for most of the workforce, EMS was a transient profession. Regularly
reviewing the quality of my data, becoming more familiar with the content, and scrutinizing
my interview technique all led to revisions and continual refinements of the interview process.
In the review of each participant’s transcript, the “meaning units,” the words and
sentences that conveyed similar meanings, were identified and labeled with codes (Graneheim
& Lundman, 2004). The coding process allowed for the interpretation of large segments of text
and portions of information in new ways. Assessing how these meaning units were linked led
to the identification of themes. As I reviewed my data, I struggled to attach codes to various
sections of text that represented those meaning units, as there seemed to be endless choices of
words to characterize the experiences that participants described.
As the endless choices of characterizations were resulting in the creation of a very large
number of codes, I returned to the literature to find more information about coding qualitative
data. After finding and familiarizing myself with the Saldaña (2009) code book resource, I
decided to use a method of “structural coding,” whereby, I labeled passages with terms that
were related to the research questions. For example, since my study explored the relationship
between the alignment of preemployment career expectations and postemployment
experiences, job satisfaction, and the intention to leave the EMS profession, I used labels for
codes such as expectations, aligned experience, misaligned experience, satisfaction, and intent
Michael J. Belotto 2625
to leave. This method greatly reduced the number of codes and provided a context to create
categories of codes or code families that were related to my research questions.
For some experiences, I used a secondary label that referred to a family of challenges
of the profession such as, the physical challenges of the job, working with the pain of spinal
injuries, or the psychological challenges of coping with illness and deaths of patients. Finally,
I utilized a “descriptive method” of coding to create a label that conveyed the essence of what
I was hearing. For example, when a paramedic stated that he had not anticipated the burden of
physical injuries that ultimately led to a decision to leave the field, a primary theme of the
study; this was coded as “intent to leave -physical injury concern.” This approach addressed
some of the challenges resulting from the open-ended questioning that is used in qualitative
research, where participants may provide lengthy and complex responses, digress, or discuss
multiple themes, all which can greatly add to the difficulty of coding, and potentially reduce
interrater reliability (Campbell et al., 2013).
While computer assisted qualitative data analysis software (CAQDAS) programs have
become popular for processing large amounts of qualitative data, trying to learn the principles
of coding and qualitative data analysis, while also becoming competent at navigating the
functions of CAQDAS proved to be extremely difficult. Therefore, since CAQDAS was not an
option for me, I decided to manually code my data. Rather than utilizing the old tried and true
method of using numerous different colored pencils to outline sections of text, I developed a
somewhat more technological variation of that approach. Using Microsoft WORD
functionality, I highlighted sections of text and using the tracked changes and new comment
functions, I added my codes in the margins of the transcripts.
As I analyzed each study participant’s interview, I also developed a codebook (see
Appendix B). The codebook listed all the codes used for each participant’s transcript; thereby,
documenting exactly how every single passage of text was evaluated. The codebook
continually grew as subsequent participants discussed new topics, requiring additional codes.
To assess my analysis of the data, I utilized the tool of interrater reliability. To establish
trust and confidence in the findings of the research, rigor was necessary to confirm the
consistency of the study methods (Thomas & Magilvy, 2011). I employed the method of
triangulation, whereby, I sought peer debriefing on my interpretations (Denzin, as cited in
Guba, 1981). The enrollment of 10 participants in my study resulted in approximately 200
pages of transcribed interviews. Due to this substantial amount of data, in keeping with the
recommendations in the literature, I evaluated interrater reliability by analyzing a sample of
texts (Barbour, 2001; Campbell et al., 2013; Hallgren, 2012; Kurasaki, 2000; Marques &
Influenced by the methods of Hruschka et al. (2004), I conducted three rounds of
reliability checks. After review of the first two participants’ transcripts, I had generated 126
codes. I then shared the transcripts with two independent researchers. A meeting was held
whereupon the feedback indicated that the coding scheme would have to be modified, as it was
just not practical due to the large number of codes. It was at this point that I discovered the
Saldaña (2009) coding methods and implemented the coding process previously described.
Finding independent researchers who were both knowledgeable and willing to dedicate
themselves to coding lengthy transcripts was extremely difficult. Due to the time constraints
of the two independent researchers, a single independent coder was used for the second round
of reliability checks. The use of one or more independent coders is supported in the literature
by multiple authors (Barbour, 2001; Campbell et al., 2013; Creswell, 2009). After the
independent researcher coded the transcript of the first participant using the improved coding
2626 The Qualitative Report 2018
method, we compared how we interpreted each segment of text and calculated our level of
concordance. Using the methods of Campbell et al. (2013), we calculated an initial discriminant
capability of 72%. The discriminant capability of the coding scheme is a measure of the level
of intercoder reliability. We then used the method of negotiated agreement to reconcile the
remaining differences and recorded how many were reconciled and how many disagreements
prevailed. We also maintained a record of how reconciliation was achieved (i.e., if the
independent coder deferred to me or I to her). We repeated this process for a third round of
reliability checks which yielded similar results.
Development of Themes
Upon completion of the coding of all 10 transcripts, I proceeded to the next step in my
approach to the analysis of the data. This required that I develop a method to analyze the overall
content of the data. At first, trying to fathom the meaning of 200 pages of words was
overwhelming, and I could not find in my text books nor in any of the published studies how
to manage this task. I constructed a content analysis table to identify which codes were used
for each participant. The content analysis table was essentially a template of the codebook;
however, at this stage, it was used to analyze aggregate data.
When the template was used for individual participants during the coding process, the
comment number generated in the transcript by the tracked changes function in Microsoft Word
was placed in the box with the corresponding code. In this way, by viewing the code book, I
could go to the exact passage in the transcript to verify where that code was used. When the
template was used to analyze overall content, the subject identifying number was placed in the
box with the corresponding code. For example, if subject number one said they went into the
profession thinking it was a stepping stone to other careers, then the number one was placed in
the “yes” box for preconceived notions, for the code “transient career perception.” I then
repeated this process for each subject’s responses.
Utilizing the content analysis table in this way, I was able to cluster items of data that
were related. Since I coded the data with labels that were related to my research questions, the
patterns that emerged led to the identification of categories. I then examined the patterns that
had been placed together for the emergence of overarching themes (Percy, Kostere, & Kostere,
2015). If an additional second level of a pattern emerged, I categorized it as a secondary theme.
For example, the psychological challenges of coping with illness and deaths of patients
emerged as a primary theme, while participants also indicated that this was an expected
challenge of the profession. However, some participants added that coping with the grief of
family members who were suffering the losses of their loved ones was also particularly
challenging. This was considered to be a secondary theme pertaining to the psychological
challenges of the occupation. Since these decisions were subjective, I also used direct
participant quotes to support the rationale for each theme. The aggregate analysis table enabled
me to identify and distinguish the trends of various participant experiences. Handling and
sorting the data in this way greatly facilitated the identification of emerging primary and
secondary themes as illustrated in Table 1.
I then interpreted the data with regard to how those emerging themes addressed my
research questions and whether initial suspicions were supported. I also questioned whether
individual experiences that appeared to be disconfirming cases actually contested my initial
beliefs. For example, while two participants did express apprehension about physical injuries,
they did not indicate that this was a source of job dissatisfaction or that this was associated with
the intention to leave the profession. Upon further examination, it became clear that these
participants were paramedic students who were the youngest individuals in the study and did
not yet have the years of experiences similar to the seasoned paramedics. When the essence of
Michael J. Belotto 2627
their sentiments was actually compared to the notions of the veteran paramedics at similar time
points in their careers, it became apparent that these descriptions were not disconfirming cases.
Rather, when comparable career time points were assessed, the notions of the students were
actually consistent with how the veterans had felt when they were first entering the profession.
The exploration of experiences that appeared to be contradictory to the emerging themes served
to further enhance the credibility of the findings of the research (Booth, Carrol, Llott, Low, &
Emerging Categories and Themes
Categories Primary Themes Secondary Themes Vocational Influence Altruism Career Longevity Perception Transient Profession EMT to Paramedic Professional Growth
Self-Efficacy & Excitement Challenges of the Profession Physical Challenges Physical Injury
Psychological Challenges –
Illness and Death of Patients
Grief of Family
Importance of Relationships
Negative Relationships with
Partners / Colleagues –
During the course of completing my dissertation, many issues emerged as a result of
conducting a qualitative research study. I observed that few authors of published qualitative
studies provided a “how to” manual describing the details of their analyses. In keeping with
the goal of this commentary, to help new researchers to navigate the path of qualitative data
analysis, herein is my summary of the major obstacles I faced and the most helpful resources
that I found to overcome these challenges.
A number of textbooks were helpful in describing the philosophical groundings of the
interpretive tradition (Creswell, 2009; Trochim & Donnelly, 2008; Ulin, Robinson, & Tolley
2005). As a new qualitative researcher, this information was extremely meaningful to me as it
edified me with regard to core values of the naturalistic paradigm. As I lived through the
dissertation experience for approximately two years, I developed a greater appreciation for
qualitative research principles and the importance of qualitative exploratory research.
For example, I had read about concepts such as spending time in the field to develop a
rapport with participants to establish trust (Dooley, 2007). While I appreciated the concept, as
2628 The Qualitative Report 2018
I continued my journey as a qualitative researcher, I began to actually experience this
phenomenon, in particular with paramedic students. As I continued to listen to participants’
poignant descriptions of their experiences and feelings about topics such as how they dealt with
death, the suffering of family members, and working with the agonizing pain of what were
often career ending spinal injuries, I came to understand their extraordinary commitment to
“my” research. I believe my presence at classes and descriptions of my own career created a
rapport for participants to volunteer their time and to commit to sharing their personal feelings.
As these stakeholders embraced the research topic’s relevance to their own careers, I believe
at that point it became “our” research.
Guidance on specific issues, such as establishing the content validity of my interview
questions was found in an article published by Lawshe (1975). This author provided all the
necessary information, including how to calculate the content validity index of my interview
and how to interpret the result. I found the most comprehensive resource on coding to be the
coding manual by Saldaña (2009). This work of over 200 pages is filled with explanations of
what codes are and their functions, different types of coding methods, and sample texts with
examples of how they were coded.
I found two studies that actually discussed coding schemes and how interrater reliability
was assessed in detail. The fact that researchers rarely discuss coding reliability was confirmed
by Campbell, Quincy, Osserman, and Pederson (2013) in their overview of coding schemes
and interrater reliability. During the conduct of HIV research at the Centers for Disease Control
and Prevention (CDC), Hruschka et al. (2004) discuss how they used different coding processes
for different types of studies. These authors provided details of how they created codebooks,
and how they dealt with factors impacting interrater reliability, such as long interviews with a
greater number of codes. The assessment of the trustworthiness of research findings is
discussed in articles by Guba (1981), Thomas and Magilvy (2011), and Whittemore, Chase,
and Mandle (2001). These authors provide explanations of topics such as credibility,
dependability, and confirmability of research results.
One of the recurring themes I found in the literature of qualitative research was that
there is not just one best way to do it (Campbell et al., 2013). Finding the most efficient method
will be determined by the type of study, the researcher, and available resources If available
resources to conduct the trial are limited or if there are time restrictions pertaining to
completing the study, I would advise new researchers to consider curtailing the number of
research questions. In my experience, having to analyze the data with regard to four research
questions did add significantly to the amount of time and work required to complete the study.
While the literature does support having more than one research question (Creswell, 2009;
Miles & Huberman, 1994; Simon, 2011), I would advise new researchers to be prepared, as
this does add length to the interview and increases the amount of time required for additional
coding and analysis.
To complete my first attempt at qualitative research, I used aspects of various
documented processes and developed my own methods that were relevant to my research and
my situation. My challenges were shaped by my own context, my findings in the literature, my
time deadlines to complete a dissertation, and my limitations as a first-time qualitative
researcher. I hope that this analysis and the sources I have provided will assist future
researchers and students to come.
Michael J. Belotto 2629
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Michael J. Belotto 2631
Appendix A: Core Interview Questions
Research Question 1
What are the preconceived notions of EMTs
and paramedics prior to entering the
vocation and their notions of the vocation
after facing the realities of the job?
1. Let’s start off by talking about what you expected from the
2. What was the most important influence for entering this
3. How did your early experiences compare to what you
4. What about your experiences now?
Is your experience of the job now how you thought it would
be after working in the field for (# of years participant has
5. If alignment between expectations and experiences is
different now than how you felt early in your career, what
Research Question 2
How does alignment or misalignment
between preemployment and
postemployment perceptions of the vocation
affect EMTs and paramedics?
6. Did the alignment or misalignment between your
expectations and experiences affect you?
7. When you first started working in the field, how did you
feel about your career choice?
8. What about now?
How do you feel about your career choice now?
Research Question 3
How does alignment or misalignment
between the notions of the vocation prior to
and following entry into the profession
contribute to job satisfaction or
9. What was the most important thing that made you feel
satisfied about your job?
10. What was the most important thing that made you feel
dissatisfied with your job?
11. How did the relationship between your expectations and
experiences affect how you felt about EMS work?
12. Has how you felt about the job changed over time?
13. If your job satisfaction has changed over time, what was
the most important issue affecting your change in satisfaction?
Research Question 4
How does job satisfaction or dissatisfaction
contribute to the intent to stay in or leave
14. Do you plan to work as an EMT/paramedic in the field
15. Are you planning to leave the EMS profession?
16. For those planning to leave the profession:
What is the most important factor affecting your decision to
leave the profession?
17. For those planning to stay in the profession:
What is the most important issue affecting your decision to
stay in the profession?
2632 The Qualitative Report 2018
Appendix B: Code Book
Subject # ___
Phenomenon of Interest
(Expectations) Preconceived Notions
Dissatisfaction Intent to
Formed prior to entering profession
Formed after entering profession
Please add “S” or “D”
to phrase #
YES NO YES NO YES NO YES NO Please add
“N/E” for no effect
Career Perception – Transient Career
Career Perception – Path to Other Profession (Health, Public Safety)
Career Perception – Fieldwork- Longevity / Retirement in EMS (this means working on the ambulance)
Career Perception – Longevity / Retirement in EMS (this means EMS position other than fieldwork on ambulance, such as: supervisor, dispatcher, educator)
Challenges – Physical Challenges
Challenges – Psychological Challenges
Challenges – Psychological Challenges – Patient Deaths
Challenges – Psychological Challenges – Family Member Grief
Vocational Influence – Altruism
Vocational Influence – family member in health field
Personality –Diversity of Practice–enjoy different types of calls
Personality – Diversity of Partners – enjoy working with different partners
Personality – enjoy adrenaline rush
Professional Growth – EMT to Paramedic – increased capability – autonomy
Relationships –Partners (positive, negative) – camaraderie with colleagues
Relationships – with Other Health Professionals
Michael J. Belotto 2633
I currently serve as a member of the Biomedical Research Alliance of New York
(BRANY) IRB, responsible for the review of research protocols. I also serve as a research
compliance auditor, responsible for reviews of investigators’ sites, to ensure the conduct of
research is in compliance with federal regulations and ethical guidelines. Correspondence
regarding this article can be addressed directly to: firstname.lastname@example.org.
Copyright 2018: Michael J. Belotto and Nova Southeastern University.
Belotto, M. J. (2018). Data analysis methods for qualitative research: Managing the challenges
of coding, interrater reliability, and thematic analysis. The Qualitative Report, 23(11),
2622-2633. Retrieved from https://nsuworks.nova.edu/tqr/vol23/iss11/2
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