What underlying cause might lead to the oversimplification of themes during qualitative data analysis in thematic analysis?

Oversimplification often stems from a researcher’s pre‑conceptions or time pressure that pushes them to fit data into tidy categories. When analysts rush through coding or rely on a narrow set of codes, they miss nuance, treating complex narratives as simple patterns. This shortcut is driven by the desire for clear, publishable themes, which encourages trimming or ignoring contradictory details. For example, a study on student motivation might collapse “curiosity” and “fear of failure” into a single “engagement” theme, overlooking how they can coexist and shape learning differently. Thus, the root cause is a combination of cognitive bias and practical constraints that favor simplicity over depth.