Saturated with Qualitative Data

MCL Guidance

By Dan Dohan

The concept of saturation plays an essential role in qualitative scholarship, and we may ask too much of it. Metaphorically, saturation occurs when a project or an investigator is soaked through with insights about their focus of inquiry—an experience that occurs repeatedly in the course of a qualitative research project. This post examines how researchers invoke the idea of saturation, illustrating the different ways we invoke it at different points in our work. The post concludes with some thoughts on how to give saturation its proper due. It suggests some other terms that could ensure we use saturation less broadly and in more specific and defensible ways.

Data saturation is often associated with the grounded theory (GT) tradition, but saturation is relevant for all manner of qualitative research, not just GT. We draw on the concept of saturation when we formulate a research question and consider field sites and informants. We use it to assess progress and next steps while in the field. It comes into play as we review if there is enough data on hand and it is time to shift more fully to analysis. We refer to it when reporting results and justifying validity.

Health scientists often design and develop a project as they write a grant proposal. Saturation may be invoked when describing fieldwork plans, e.g. how many interviews I will conduct or how many days for each site visit. In quantitative, hypothesis-driven studies, investigators use power calculations to describe and justify their design decisions. A particular number of subjects from each group — given our hypotheses and what we know about the measures we are using — will provide the power to detect a statistically significant difference between groups.

It is natural for qualitative investigators to follow suit. We want to convey the thoughtful planning we put into research design and the legitimacy of our data collection goals. When writing a funding proposal, it is important to explain how a particular amount of data will lead to a definitive result. The temptation is to propose a number (12 interviews or a 3-day site visit) that has worked in previous projects or has appeared in published studies and then assert that, like a power analysis, this number will prove sufficient. In the context of project design, therefore, saturation means an expectation of “adequacy” — a meaning parallel to that of a statistical power calculation.

Some scholars have suggested saturation, in this sense of adequacy, can be calculated with precision, e.g., certain number of interviews or focus groups. Others maintain such attempts are empirically, contextually, or conceptually flawed and can have unintended and detrimental consequences. This definitional open-endedness may be uncomfortable for methodologists, but has a certain practical wisdom. We should be concerned when analysts assert with unreflective certainty that saturation equates to 12 interviews or 6 focus groups. This undermines the purpose of qualitative inquiry. On the other hand, if solid qualitative research often emerges from 12 interviews, it is useful to say that out loud.

A productive resolution to this dilemma is to describe the conceptual justification for believing, for example, that 12 interviews will produce interesting results. Who are the people you will interview, what do you expect them to say, how will you pursue the new questions that emerge as you hear their stories and come to understand their worlds. This type of justification describes the process by which you will become more adequately saturated with data. It focuses on the process in the context of your specific project. It takes a bit longer to explain, but it also provides an opportunity to envision how the project might unfold and to make explicit your own assumptions about what you might find.

Once a project is underway, saturation often arises during data collection. During interviews, when we feel we have heard this story before from others, we wonder if that means we have hit the point of saturation. During observation, when we feel we have seen this before or feel like we could have predicted that events would turn out a particular way, we wonder if that means we have hit the point of saturation. Saturation at these moments indicates we have achieved a degree of competence and comfort in the field. In some projects, this sense of comfort tracks with a clear answer or set of answers to our research question; it provides the opportunity to wrap up data collection and turn more fully towards analysis.

When projects are able to remain in the field, however, or when key aspects of inquiry remain unanswered, this feeling means a chance to gather data with greater focus and purpose—not an invitation to wrap things up. We build on new-found understanding of our informants’ world to ask questions in new, more skillful ways or to explore issues that previously had been unknown-unknowns. We recognize how additional interviews or observations can help fill in details and flesh out context. Saturation in this context means arriving at a deeper “understanding” and represents a chance for methodological iteration to confirm and extend our findings. We enact saturation-as-understanding through reflexive writing or, even better, reflexive engagement with our research team, knowledgeable colleagues, or with informants themselves.

During data analysis, while reading, discussing, sorting, and coding transcripts and fieldnotes, saturation captures a turning point. More reading and ongoing discussion is reiterating our insights without unearthing new ones. We can see the inter-connections within the data, e.g. the why and how of our informants’ situations. We recognize a consistency in how participants characterize their situation or describe their experiences. We can quickly draw parallels and contrasts between different participants’ experiences and we feel we can explain why or how of similarities and difference. The empirical pieces have fallen into place. The conceptual ideas are coherent. We see how each informs the others. We can trace the links. We have a conceptual chain. It may not be unbroken, but we know where the gaps are, and we likely have a sense for the kind of research and the sorts of data we would need to forge those last connections. This is saturation in the sense that GT coined the term. It indicates analytical “maturity.“ Sorting and reading, coding and combining has reached a point of diminished returns. It is time to turn to writing up what has been learned. 

When submitting those findings for publication in health sciences or health services journals, we are increasingly asked to address lists of criteria for research rigor such as COREQ and SRQR. Saturation, in this sense of analytical maturity, appears as one element among many. The embrace of COREQ and SRQR is part of a broad and laudable pattern in the health sciences towards greater research transparency and accountability. Their institutional enshrinement means they must be acknowledged and addressed for our voice to be heard in these fields. Research quality checklists have attracted some scorn among qualitative social scientists but mostly crickets.

Are we asking too much of saturation? Maybe. The multiple meanings of saturation at different points in the qualitative research process are often unarticulated and confusing. It is understandable that fieldworkers might want to assign saturation a numeric value or that journal editors want to require it in a checklist. It is tempting to re-define saturation to give it a more singular and precise meaning. But, we have a responsibility to not reify it numerically nor to grant it hegemony in a gatekeeping checklist.

Saturation is expansive and flexible because qualitative scholars collect, evaluate, and analyze data in expansive and flexible ways. It thus captures something essential about how qualitative research contributes to scholarly knowledge, both scientific and humanistic. It carries different meanings and significance when used by different scholars at different points of a research project. That is a feature not a bug.

Qualitative researchers can use saturation more precisely without reifying it numerically or bolstering its hegemony. Adding words or sentences allows us to specify whether we invoke the term to signify adequacy, understanding, or analytic maturity. It transforms an outcome — to declare something saturated — into a human process involving different types of intellectual work at different moments of a scholarly process. Qualitative scholars care about context and respect multi-vocality; that’s why we use the method. So, we should add a bit of context — here it indicates  “expected adequacy” and here it means “analytical maturity” — to make the concept of saturation expansive and flexible and precise.

It is also essential to defang its hegemony. We should not feel a need to invoke saturation at all when its meaning is communicated with other words or in other ways. This means taking a principled stand by pushing back on its uncritical or imprecise inclusion in checklists that gate-keep access to health services and health sciences journals. This is not an easy task, but it is worth scratching at, nevertheless.