By default, qualitative analysis often means presenting common themes and supporting them with representative quotes from participants.
This is a great starting point, but typically fails to capture the true complexity of the data. More importantly, this simplistic strategy can provide weak support for your argument.
Pat Bazeley, a qualitative and mixed methods data analysis expert in Australia, believes we can do much better.
In her paper “Analysing Qualitative Data: More Than ‘Identifying Themes’‘” Bazeley suggests using theme analysis as a starting point for more complete modeling and theory building.
To begin, says Bazeley, we should “describe, compare, and relate” our data. This means outlining the characteristics of the data, then describing how people are addressing certain themes. Who is talking about this? Who isn’t?
Next, we must compare that theme across various contexts. How are different groups expressing these ideas? Also note any instances where there is no variation.
Finally, “relate this theme to others already written about…As you relate categories you will be helped to structure your data because relating is best done to categories already discussed.”
In other words, listing a series of disparate themes is often confusing and not very persuasive to readers. It’s vital to explore and explain the relationships between key themes.
In most situations this will require more than a simple hierarchical organization of your themes. A matrix display, flow chart, or typology can help develop researcher understanding in addition to better presenting your conclusions.
These strategies can help you explore more complex relationships such as how often things happen, in what ways things vary under different circumstances, and how outliers can further your understanding.
And what about those participant quotes? According to Bazeley :
Reliance on presenting brief quoted segments of text as ‘evidence’ encourages superficial reporting of themes, whereas building an argument requires that conclusions are drawn from across the full range of available texts.
She suggests adding quotes only in the final drafts of your paper. In early drafts write without using quotes and focus on wider evidence for each of your points.
As a result of building a stronger collection of themes sensitive to context and held together by well-defined connections, your analysis should do a better job engaging readers and make journal reviewers happy as well.