3 Mistakes to avoid when presenting Qualitative Research findings

Qualitative findings often fail not because the data are weak, but because the writing blurs what the evidence actually comes from and overreaches beyond what the study can support. Three recurring problems show up in results chapters: unclear sourcing of claims, jumping to big conclusions from thin evidence, and implying causal relationships that qualitative designs usually can’t establish.

The first mistake is lack of clarity about where statements originate. Readers need to know whether a passage reflects participants’ own beliefs and experiences, prior literature, the researcher’s interpretation, or general “facts.” A common pattern is starting a section with a brief summary of a theme, then smoothly shifting from a specific participant’s account (e.g., “Participant 7 explained…”) into broader claims that sound like general knowledge (e.g., “abuse often happens in the UK” or “local people perceive migrants this way”). When that transition isn’t signposted, the chapter becomes hard to trust: it’s unclear whether the text is still reporting participants’ perspectives or has moved into literature-based or generalized assertions. The fix is to keep results and discussion clearly separated unless the chosen structure intentionally blends them, and to repeatedly cue the reader when the content is still grounded in individual or collective participant viewpoints (e.g., “most participants,” “some participants,” or “Participant X believed…”).

The second mistake is making sweeping claims—sometimes immediately after one quote or a small cluster of opinions. Qualitative research can generate meaningful insights, but it rarely supports definitive “this proves” conclusions. A frequent red flag is wording that turns implications into certainty: sentences like “this provides evidence that we should change policy,” “this shows we must do training,” or “this is evidence of a big problem” can overstate what the data justify. Even when the intended goal is practical change, the language should stay cautious and proposition-based—using phrasing such as “based on this, we may consider…” or “it is arguably…”—and should avoid presenting a single participant’s experience as a universal fact.

The third mistake is implying cause-and-effect. Qualitative studies can explore perceived relationships and offer hypotheses, but they are risky for causal claims. The transcript highlights how easily confounding factors can explain patterns that look causal. An example: if all men in a sample love football and all women hate it, it’s tempting to claim gender influences football preferences. Yet the real drivers could be country of origin, age differences, or other contextual variables—factors a qualitative study may not be designed to disentangle. The same caution applies to “test results” or “past experiences” leading to current struggles: qualitative work can suggest plausible mechanisms, but it shouldn’t present them as established causal effects.

As a practical workaround, the transcript recommends member checking. By returning to participants—at different stages and in different forms—to confirm whether interpretations match what they meant, researchers can strengthen confidence in nuanced claims, including perceived causal relationships. Member checking won’t justify nationwide policy certainty, but it can help validate whether a proposed interpretation reflects participants’ own understanding, allowing the writing to stay grounded while still offering thoughtful, testable propositions.