Implementation science (IS) is truly pragmatic at its core, answering questions about how existing evidence can be best translated into practice to accelerate impact on population health and health equity. Qualitative methods are critical to support this endeavor as they support the examination of the dynamic context and systems into which evidence-based interventions (EBIs) are integrated — addressing the “hows and whys” of implementation [1]. Numerous IS frameworks highlight the complexity of the systems in which implementation efforts occur and the uncertainty regarding how various determinants interact to produce multi-level outcomes [2]. With that lens, it is unsurprising that diverse qualitative methodologies are receiving increasing attention in IS as they allow for an in-depth understanding of complex processes and interactions [1, 3, 4]. Given the wide variety of possible analytic approaches and techniques, an important question is which analytic approach best fits a given set of practice-driven research needs. Thoughtful design is needed to align research questions and objectives, the nature of the subject matter, the overall approach, the methods (specific tools and techniques used to achieve research goals, including data collection procedures), and the analytic strategies (including procedures used for exploring and interpreting data) [5, 6]. Achieving this kind of alignment is often described as “fit,” “methodological integrity,” or “internal coherence” [3, 7, 8]. Tailoring research designs to the unique constellation of these considerations in a given study may also require creative adaptation or innovation of analytic procedures [7]. Yet, for IS researchers newer to qualitative approaches, a lack of understanding of the range of relevant options may limit their ability to effectively connect qualitative approaches and research goals.

For IS studies, several factors further complicate the selection of analytic approaches. First, there is a tension between the speed with which IS must move to be relevant and the need to conduct rigorous research. Second, though qualitative research is often associated with attempts to generate new theories, qualitative IS studies’ goals may also include elaborating conceptual definitions, creating classifications or typologies, and examining mechanisms and associations [9]. Given the wealth of existing IS frameworks and models, covering determinants, processes, and outcomes [10], IS studies often focus on extending or applying existing frameworks. Third, as an applied field, IS work usually entails integrating different kinds of “insider” and “outsider” expertise to support implementation or practice change [11]. Fourth, diverse traditions have contributed to the new field of IS, including agriculture, operations research, public health, medicine, anthropology, sociology, and more [12]. The diversity of disciplines among IS researchers can bring a wealth of complementary perspectives but may also pose challenges in communicating about research processes.

Pragmatic approaches to qualitative analysis are likely valuable for IS researchers yet have not received enough attention in the IS literature to support researchers in using them confidently. By pragmatic approaches, we mean strategic combining and borrowing from established qualitative approaches to meet the needs of a given IS study, often with guidance from an IS framework and with clear research and practice change goals. Pragmatic approaches are not new, but they receive less attention in qualitative research overall and are not always clearly explicated in the literature [9]. Part of the challenge in using pragmatic approaches is the lack of guidance on how to mix and match components of established approaches in a coherent, credible manner.

Our motivation in offering this guidance reflects our experiences as researchers, collaborators, and teachers connecting qualitative methods and IS research questions. The author team includes two behavioral scientists who conduct stakeholder-engaged implementation science and regularly utilize qualitative approaches (SR and RL). The team also includes a sociologist and a social psychologist who were trained in qualitative methods and have rich expertise with health services and implementation research (AR and EA). Through conducting qualitative IS studies and supporting students and colleagues new to qualitative approaches, we noticed a regularly occurring set of concerns and queries. Many questions seem to stem from a sense that there is a singular, “right” way to conduct qualitative projects. Such concerns are often amplified by fear that deviation from rigid adherence to established sets of procedures may jeopardize the (perceived or actual) rigor of the work. While the appeal of recipe-like means of ensuring rigor is understandable, fixation on compliance with “established” approaches overlooks the fact that versions of recognizable, named approaches (e.g., grounded theory) often use different procedures [7]. As Braun and Clarke suggest, this “hallowed quest” for a singular, ideal approach leads many researchers astray and risks limiting appropriate and necessary adaptations and innovations in methods [13]. IS researchers seeking to broaden the range of approaches they can apply should take comfort that there is “no single right way to do qualitative data analysis […]. Much depends on the purpose of the research, and it is important that the proposed method of analysis is carefully considered in planning the research, and is integrated from the start with other parts of the research, rather than being an afterthought.” [14]. At the same time, given the wealth of traditions represented in the IS community, it can be difficult for researchers to effectively ensure and convey the quality and rigor of their work. This paper aims to serve as a resource for IS researchers seeking innovative and accessible approaches to qualitative research. We present suggestions for developing and communicating approaches to analysis that are the right “fit” for complex IS research projects and demonstrate rigor and quality.

Accordingly, section 1 offers guidance on identifying an analytic approach that aligns with study goals and allows for practical constraints. We describe three approaches commonly considered for IS projects: grounded theory, framework analysis, and interpretive phenomenological analysis, highlighting core elements that researchers can borrow to create a tailored, pragmatic approach. Section 2 addresses opportunities to ensure and communicate the rigor of pragmatic analytic approaches. Section 3 provides an illustrative example from the team’s work, describing the design and execution of a pragmatic analytic approach and the diversity of research and practice products generated.