Concurrent Pragmatic Mixed Methods — Simultaneous Pragmatic Mixed Methods Design
Concurrent Pragmatic Mixed Methods Design · Also known as: concurrent pragmatic design, pragmatic concurrent mixed methods, simultaneous pragmatic mixed methods
Concurrent pragmatic mixed methods is a research design that collects quantitative and qualitative data simultaneously within a pragmatic philosophical framework. Rather than privileging either positivism or constructivism, the pragmatic stance selects methods based on what best answers the research question. Both data strands are gathered in parallel, then merged at the interpretation stage to provide a fuller picture than either strand alone could yield.
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When to use it
Use this design when the research question genuinely requires both numeric and narrative evidence collected at the same time and when no prior philosophical commitment to quantitative or qualitative dominance exists. It suits program evaluations, applied social-science studies, and health-services research where breadth and depth are needed together. Do not use it when resources cannot support two simultaneous data collection efforts, when participants cannot contribute to both strands without undue burden, or when one strand logically depends on the results of the other — in that case a sequential design is more appropriate.
Strengths & limitations
- Collecting both strands simultaneously shortens overall data collection time compared to sequential mixed methods designs.
- The pragmatic stance keeps the researcher focused on answering the question rather than defending a philosophical position.
- Merged findings provide both the breadth of quantitative data and the depth of qualitative data, increasing completeness.
- Convergence or divergence between strands strengthens or meaningfully complicates interpretation.
- Widely applicable across disciplines — education, health sciences, organizational research, and policy evaluation.
- Running two full data-collection efforts in parallel demands substantial resources, time, and researcher expertise.
- Merging quantitatively and qualitatively derived results is analytically complex and requires explicit decisions about how integration is achieved.
- If the two strands produce divergent findings, interpretation can be difficult and may require a follow-up phase to resolve discrepancies.
- The pragmatic label can mask the need for principled methodological decisions — flexibility does not mean anything goes.
- Results from merged strands may be difficult to publish in journals that remain skeptical of mixed methods integration.
Frequently asked
How is concurrent pragmatic mixed methods different from concurrent triangulation design?
Concurrent triangulation specifically aims to cross-validate or corroborate findings from the two strands, typically giving them equal weight. The pragmatic variant is broader: integration may serve triangulation, complementarity, or expansion purposes, and the weighting of strands is determined by the research question rather than fixed in advance. In practice the designs often overlap; the pragmatic label signals the epistemological stance rather than a distinct structural difference.
Does 'pragmatic' mean I can skip justifying my methods?
No. Pragmatism as a research philosophy means methods are chosen for their fitness to answer the question, not for their ideological alignment. This still requires explicit justification of why each strand is appropriate, how they will be integrated, and how quality will be maintained in each tradition. Pragmatism enables flexibility; it does not exempt the researcher from rigor.
What does 'merging' the data actually look like?
Merging can take several forms: side-by-side comparison of quantitative results and qualitative themes in the discussion section; a joint display such as a matrix that maps quantitative frequencies against qualitative theme labels; transformation of qualitative codes into numeric counts for direct comparison; or building a narrative account that weaves both strands together. The method of merging should be chosen before data collection so the design supports it.
When should I prefer a sequential design instead?
Choose a sequential design when one strand's results need to inform the design of the other — for example, when qualitative findings will shape survey items (exploratory sequential) or when quantitative results need qualitative explanation (explanatory sequential). If no such dependency exists and resources allow parallel collection, the concurrent design is efficient; if dependency exists, the concurrent approach collapses the logic of the study.
How do I handle divergent results between the two strands?
Divergence is informative rather than problematic. Report it transparently, offer plausible explanations (different aspects of reality captured, measurement artifacts, sampling differences), and if resources allow, consider a follow-up phase to investigate the discrepancy. Suppressing or glossing over divergence undermines the added value of the mixed methods approach.
Sources
- Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483344379
- Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26. DOI: 10.3102/0013189X033007014 ↗
How to cite this page
ScholarGate. (2026, June 3). Concurrent Pragmatic Mixed Methods Design. ScholarGate. https://scholargate.app/en/research-design/concurrent-pragmatic-mixed-methods
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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- Concurrent Multiphase Mixed MethodsResearch Design↔ compare
- Concurrent Transformative Mixed MethodsResearch Design↔ compare
- Concurrent Triangulation Mixed Methods DesignResearch Design↔ compare
- Explanatory Sequential Mixed Methods DesignResearch Design↔ compare
- Pragmatic Mixed Methods DesignResearch Design↔ compare