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

Thematic Analysis

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,

Thematic Analysis

Introduction

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

study.

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

EMS profession.

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.

Content Validity

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.

Data Analysis

Coding

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.

Interrater Reliability

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 &

McCall, 2005).

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, &

Cooper, 2013).

Table 1

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

Increased Physical

Challenges with

Advancing Age

Alternative

Occupational

Opportunities

Psychological Challenges –

Illness and Death of Patients

Grief of Family

Members

Importance of Relationships

Negative Relationships with

Partners / Colleagues –

Dissatisfaction

Acceptance of

Negative Relationships

Camaraderie

Conclusion

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 Questions

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

EMS vocation.

2. What was the most important influence for entering this

profession?

3. How did your early experiences compare to what you

expected?

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

been working)?

5. If alignment between expectations and experiences is

different now than how you felt early in your career, what

changed?

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

dissatisfaction?

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

the profession?

14. Do you plan to work as an EMT/paramedic in the field

until retirement?

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

Notions Experience/Alignment

Experiences Satisfaction/

Dissatisfaction Intent to

Leave

Formed prior to entering profession

Formed after entering profession

When no

preconceived notion

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

Professional Growth – EMT to Paramedic – increased capability – autonomy

Relationships –Partners (positive, negative) – camaraderie with colleagues

Relationships – with Other Health Professionals

Michael J. Belotto 2633

Author Note

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: [email protected].

Copyright 2018: Michael J. Belotto and Nova Southeastern University.

Article Citation

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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