"My First Project" Blog Series
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"My First Project" Blog Series
My first major project using Dedoose was also the centerpiece of my doctoral dissertation.
I had become fascinated with a phenomenon that felt ordinary in my own life but academically underexplored: the way my cat Samson functioned within my African American family.
Some might have called our anthropomorphic language excessive. We called it natural. Samson was woven into our family system in ways that felt entirely real. Watching how we collectively related to him made me curious. What did it mean when an animal occupied that kind of relational space—especially within a specific cultural context?
From this personal experience, I knew I wanted to study the human–animal bond. What I didn’t realize was how deeply personal that journey would become, or how much I would rely on qualitative analysis software to help me hold the complexity of the work.
As I explored the human–animal bond literature, I discovered a persistent gap. Much of the research relied on homogeneously White and female samples. While those studies offered important insights, they reflected only part of the story. Race, culture, and lived context were often absent. Even as public conversations about pets expanded—particularly during COVID—there remained little exploration of how African American adults experience attachment and grief in relation to companion animals.
At the same time, I was navigating my own grief. After 17 years by my side, Samson became ill, and I made the decision to euthanize him.
What began as personal curiosity and lived experience became academic inquiry. That journey became my dissertation, and my first major project using Dedoose.
From that moment, one question guided the study:
What is the meaning of grief for African American pet owners who have experienced pet loss?
At first glance, the question appears simple. But it carries emotional, cultural, and social layers. It required attention not only to loss itself, but to identity, family dynamics, community narratives, and the ways grief can be seen, or rendered invisible within cultural contexts.
Data were collected through semi-structured interviews with 23 African American adults who had experienced pet loss in adulthood.
Participants shared detailed accounts of their pets, the circumstances surrounding the loss, the aftermath, and the cultural and environmental contexts that shaped their coping processes. These were not brief responses. They were emotionally rich narratives filled with nuance, memory, and meaning.
Because the stories were so expansive, data saturation was not reached until the final interview. By that point, I had accumulated a substantial body of qualitative material that required careful management, sustained attention, and thoughtful analysis.
Like many qualitative researchers, I encountered the usual challenges of data collection: scheduling conflicts, cancellations, and no-shows. I also experienced something new in my research journey—imposter participants. A few individuals attempted to participate despite not meeting the study’s inclusion criteria, which required additional procedural clarity and discernment.
Yet the most significant challenge was not logistical. It was emotional.
Participants entrusted me with deeply personal stories of loss. Many described their grief as minimized or misunderstood. As I analyzed the data, a pattern became increasingly clear: participants often experienced their pet loss as invisible—not only within broader society, but sometimes even within their own families.
Holding those stories required care.
At times, I questioned whether I could do them justice. At the same time, I recognized that I was contributing knowledge that felt purposeful and overdue.
I was introduced to Dedoose by a seasoned qualitative researcher who spoke highly of its functionality. At the time, I trusted the recommendation without fully realizing how central the platform would become to my workflow. Using Braun and Clarke’s six-phase thematic analysis framework, Dedoose became the organizational backbone of the project.
The project workspace was structured across four primary areas: the Media workspace, where interview transcripts were uploaded; the Codes workspace, which housed the evolving codebook; the Excerpts workspace, containing coded segments of data; and the Memos workspace, where all analytic documentation was stored.
The memo function quickly became indispensable.
I established four memo groups to organize my thinking throughout the analytic process:
Because this was a phenomenological study, reflexivity was essential. The ability to electronically link memos to specific excerpts and codes allowed me to create a transparent analytic trail while remaining grounded in methodological rigor.
The coding process was both iterative and substantial.
In the first round of analysis, I generated 371 codes across 1,198 text applications. A second round of refinement reduced that number to 275 codes applied to more than 1,500 segments of text. After merging overlapping meanings and clarifying conceptual boundaries, I ultimately consolidated 239 unique codes. The volume and evolution of codes reflected not only the richness of the data, but the iterative nature of thematic analysis itself. From there, initial theme development produced 38 candidate themes, which were refined through multiple rounds of review into eight main themes and 25 subthemes.
This level of complexity required flexibility. The Codes workspace made it possible to move, merge, rename, and reorganize codes without losing analytic clarity. Given the volume of data, that adaptability was essential.
The Excerpts workspace became particularly valuable during the writing phase. Being able to retrieve all excerpts connected to a specific code or theme allowed participant voices to remain central in the final narrative, while keeping the analytic structure intact.
One of the most powerful aspects of Dedoose for me was its qualitative visualization tools. These included code presence charts, code application charts, code co-occurrence analysis, and the code cloud.
The co-occurrence feature was especially illuminating. It allowed me to identify meaningful relationships between concepts such as invisibility and identity, or cultural expectation and coping. These visualizations helped me step back from line-by-line coding and see broader thematic patterns emerging across participants.
Additionally, the use of descriptors allowed me to compile structured contextual information—such as household composition—and examine patterns across cases. Even within a qualitative study, this capability added analytic nuance, enabling cross-case comparison while remaining grounded in participant narratives.
When the data felt overwhelming, Dedoose provided structure. It created a container within which reflexivity, rigor, and creativity could coexist.
Following Braun and Clarke’s six phases of thematic analysis, I moved from familiarization and initial coding to searching for themes, reviewing them, defining and naming them, and ultimately producing the written report.
Each phase required iteration. Themes were not identified in a single pass; they were refined through sustained engagement with the data. I evaluated candidate themes to ensure they represented shared meaning patterns rather than simple topics. I assessed boundaries, coherence, and alignment with the research question. Throughout this process, I used Dedoose visualizations alongside manual mind mapping to confirm thematic integrity and deepen conceptual clarity.
By the time I reached the final writing stage, the analytic process was clearly documented within the memo workspace. The themes felt grounded, supported by rich excerpts, and aligned with the central question guiding the study.
If I had one piece of advice for new users, it would be this:
Don’t rush the process.
Let your codes breathe. Let your themes surprise you.
Qualitative analysis is not a linear checklist. Your first round of coding will not be your last. Use the memo workspace generously. Document your thinking. Revisit your codebook. Explore the visual tools. Step back—and then return.
For me, Dedoose did more than organize data. It supported my development as a researcher. It allowed me to hold emotionally complex material without losing structure. And it helped me tell a story that participants trusted me to tell.
I now find myself in the position of mentoring others in the use of this valuable tool, much like the researcher who first introduced it to me.
This project began with a question about the human–animal bond, grief, and the African American experience. It ended with a deeper understanding of visibility, identity, and meaning—and a profound appreciation for the tools that helped bring that understanding into focus.
Michele L. Whitney, PhD, is a human services scholar, educator, and qualitative researcher specializing in the human–animal bond, grief, and culturally responsive research. Her doctoral research explored African American pet loss experiences using thematic analysis and reflexive practice. She is the founder of Heart & Science, a new nonprofit organization dedicated to advancing research, education, and equity at the intersection of grief, identity, and the human–animal bond. Dr. Whitney mentors students and emerging scholars in qualitative methods and inclusive research practice.
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