Qualitative data analysis - Developing THEMES from CODES | "From Codes to Themes" episode 3

Theme development starts with a practical decision: keep coding detailed enough to notice when “good” and “bad” experiences actually reflect different underlying drivers. Using a hypothetical dataset about job retention among chefs and actors, the process begins after stage-two coding (focus codes) that groups initial detailed codes into broader buckets. From there, the work shifts into building themes—an explicitly manual, interpretive step where the analyst must be confident the emerging structure tells a coherent story about what shapes job satisfaction, which in turn is treated as closely connected to retention.

Rather than naming themes as “job retention factors,” the analysis pivots to job satisfaction because the dataset rarely frames answers in terms of leaving or staying. Instead, the material centers on whether people enjoy their work and why. That logic produces two main themes: factors positively influencing job satisfaction and factors negatively affecting job satisfaction. “Good things” and “bad things” remain temporary labels from the coding stage; they get replaced with wording that better matches the data and the study’s likely implications.

A key turning point comes from repeated reflection during coding: some experiences look like mixtures of workplace conditions and individual dispositions. For example, “work environment providing opportunity to take risks” differs from “willingness to take risks,” even though both relate to learning and growth. Because the coding was granular, the analyst can separate these overlapping ideas into distinct subthemes rather than collapsing them into vague categories like “training” or “self-development,” which would risk losing important nuance.

With the two main themes set, the analyst organizes subthemes into two types of factors: external (workplace/environment conditions) and personal internal (individual attitudes, traits, and readiness). Under the positive theme, internal factors include being passionate and dedicated, being willing to learn and develop, turning challenges into advantages, taking criticism on board, appreciating small things, and maintaining resilience and optimism. External factors include autonomy and control at work, access to learning and training opportunities, meaningful or emotionally engaging work, and the presence of like-minded people. The process also involves “cleaning” the wording so subthemes are consistent in grammar and form, and then aggregating coding counts (in NVivo terms) to check how many subthemes exist within each category and theme.

The negative theme follows a similar pattern, though it is treated as a smaller, secondary byproduct. Negative codes are consolidated and reworded into clearer subthemes such as boring work leading to burnout, meaningless or not engaging work, lack of confidence, and work that feels stale or unchanging. Some external conditions are also represented, including insufficient autonomy. Other items are reframed to generalize beyond a single quote—such as “not liking to be the center of attention,” which is recast as “work not matching personality.” Finally, overlapping ideas like “doing the job for publicity” are merged into broader notions of work lacking authenticity, which maps back to meaning and engagement.

Overall, theme development here is less about forcing a framework and more about iteratively translating detailed codes into a defensible thematic structure that fits what participants actually said—while keeping an eye on how those themes could inform practical guidance for improving retention through job satisfaction.