CASE STUDIES

Every good research project begins with a question about the world around us. The analytical examples I provide below offer a glimpse into how I approach two examples of such questions, and how I transform data into insights that matter.

EXAMPLE 1: Evaluating A New Public Health Intervention

The Question

What do consumers/patients think about a specific novel public health intervention (e.g., a new mental health treatment method)?

The Challenge

Typically, implementation scientists, public health experts, and others involved in designing and piloting new public health interventions operate on tight timeframes and budgets. They need to solve a problem fast – namely, they need to evaluate how and why a new intervention is (or isn’t!) working, using real-world data, but often with fewer labor hours and cost constraints than a standard research project.

That’s where rapid analysis comes in.

The Approach

Rapid analysis is, put simply, a suite of analytical tools that are meant to provide insights fast. Rapid analysis has been a core tool of mine for years, because it allows rigorous qualitative research to inform real-world decisions while those decisions are still being made. Rather than waiting months for a traditional analytic process (like narrative analysis), rapid approaches make it possible to identify meaningful patterns quickly without losing sight of the complexity of participants' experiences. I use summary templates and rapid matrix analysis for my analytical method here.

The Insight

My rapid analysis approach produces three key types of insights: (1) a list of recurrent themes in interview data, (2) a “tally” of how many times each of those themes popped up, and (3) example quotes – also known as “exemplars” – for each theme. Taken together, these things tell me what happened in the data, how often they happened, and (using the exemplars) more detail about the “why.”

The Impact

I’ve repeatedly worked with teams to use the rapid analysis approach described above to analyze qualitative data, and it’s resulted in thorough-yet-speedy evaluations of multiple new mental health interventions, all while eliminating formal transcription costs and reducing labor hours. That’s huge for teams that are working quickly and on a budget, when balancing rigor with pragmatism is critical!

EXAMPLE 1: Finding Meaning in In-Depth Interview Data

The Question

What did our interviewees say about their lived experiences with a specific phenomenon (e.g., their trajectories through the family law system)?

The Challenge

Semi-structured interviews often produce a vast array of intricate data on people’s perspectives and lived experiences. The challenge for research teams thus becomes: how do we make broader meaning of a rich dataset while still preserving its detail and nuance? In other words, can we identify big-picture themes and patterns, while still engaging and honoring the complexity our interviewees inherently bring to the table?

The Approach

For many projects, I like to use Braun & Clarke’s well-established and straightforward method for tackling semi-structured interview data (except for instances wherein a specific methodology might make more sense, like phenomenological analysis). In essence, thematic analysis is a multi-step process for familiarizing yourself with the data, identifying its core patterns (and divergences from those patterns!), noting example quotations, and writing up the results in a comprehensive yet nuanced way. And here’s what’s key: unlike rapid analysis, thematic analysis enables me as a researcher to engage with the data in a long-term, reflexive manner.

The Insight

Thematic analysis is a tried-and-true method because it tends to produce rich and comprehensive insights – it allows for a strong level of nuance in the final reporting process – even with “thick” qualitative data. If you’ve done thematic analysis well, you have lived with the dataset long enough that you know its contours and complexities. You can both connect subtle trends and describe subtle dissonances – and all of this ideally enables you to stay deeply true to the voice of the interviewee when reporting out results.

The Impact

Because of thematic analysis’ broad applicability, its rich insight, and its adaptability to multiple theoretical orientations, it is a powerful tool in my toolbox. This type of analysis has been successfully used by teams – including my own! – to produce novel, rich insights from qualitative and mixed methods datasets. As one of my favorite mentors once told me: your goal as a researcher is to be a “faithful witness” to the data you’ve collected. Thematic analysis can equip you to do just that.