Transparent reporting is essential for the credibility and reproducibility of any systematic review, and mixed methods reviews have additional reporting requirements beyond the standard PRISMA 2020 checklist.
Use the PRISMA 2020 statement as your baseline. The 27-item checklist and the build a PRISMA flow diagram provide the structural foundation for reporting your search strategy, screening process, and included studies. Your flow diagram should clearly indicate how many studies were quantitative, qualitative, and mixed methods at each screening stage.
Report your integration design explicitly. State whether you used a convergent, sequential, or multi-stage design and explain the rationale for that choice. Readers and peer reviewers need to understand the architectural logic of your synthesis before they can evaluate the results.
Describe your quality appraisal process for each study type. If you used the MMAT, report which version you used, how many reviewers appraised each study, how disagreements were resolved, and whether quality ratings influenced your synthesis (for example, through sensitivity analysis excluding low-quality studies).
Present quantitative and qualitative results separately before presenting integrated findings. This three-part structure (quantitative results, qualitative results, integrated findings) allows readers to evaluate each evidence stream independently and then assess whether the integration is well-supported by the component syntheses.
Use supplementary materials generously. Mixed methods reviews generate extensive data that cannot fit into a standard journal article. Full extraction tables, complete MMAT ratings, detailed search strategies for each database, and the full joint display matrix should be provided as appendices or supplementary files.
Register your protocol prospectively. PROSPERO accepts mixed methods systematic review protocols, and prospective registration strengthens the methodological credibility of your review. Include your planned integration design, synthesis methods, and quality appraisal approach in the protocol.
Navigating Paradigm Tensions and Common Challenges
Mixed methods systematic reviews sit at the intersection of two research traditions with fundamentally different assumptions about knowledge, evidence, and validity. Navigating these tensions is as important as mastering the technical methods.
Paradigm incompatibility is the most frequently cited challenge. Quantitative research operates within a positivist framework emphasizing objectivity, measurement, and generalizability. Qualitative research often operates within interpretivist or constructivist frameworks emphasizing subjectivity, context, and meaning. Critics argue that combining these traditions within a single synthesis produces incoherent findings. Proponents counter that pragmatism, which prioritizes practical utility over philosophical purity, provides a coherent epistemological foundation for mixed methods synthesis. The JBI Mixed Methods Methodology group explicitly endorses a pragmatist stance.
Quality criteria differences create practical problems during appraisal. Concepts like internal validity, statistical power, and reproducibility apply to quantitative studies but not to qualitative research, which uses criteria like credibility, transferability, dependability, and confirmability. The MMAT addresses this by providing design-specific criteria, but review teams still need members who understand both sets of quality standards.
Unequal evidence volumes are common. You may find 30 randomized trials and only 5 qualitative studies on a given topic, or vice versa. This imbalance can skew your integrated findings toward the larger evidence base unless you deliberately structure your synthesis to give appropriate weight to both streams. Sandelowski et al. (2006) recommended treating the smaller evidence stream as equally important during integration, regardless of volume differences.
Reviewer expertise gaps pose a practical barrier. Few researchers are trained in both quantitative meta-analysis and qualitative synthesis. Building a review team with complementary expertise is essential. At minimum, your team needs one member experienced in systematic review methodology for the quantitative stream and one experienced in qualitative evidence synthesis for the qualitative stream.
Publication bias affects evidence streams differently. Quantitative studies are subject to well-documented publication bias favoring statistically significant results. Qualitative studies face a different form of selective reporting, where certain themes or perspectives may be overrepresented. Your protocol should describe how you plan to assess and address publication bias in each stream.
For the qualitative side of a mixed-methods review, our qualitative data analysis support handles coding, theme development, and integration with quantitative results.
Example Research Questions and Matched Designs
Understanding how to match a research question to the right integration design is one of the most practical skills in mixed methods synthesis. The following examples illustrate this matching process.
"What is the effectiveness of telehealth interventions for managing chronic pain, and how do patients experience these interventions?" This question has two clear components: effectiveness (quantitative) and experience (qualitative). A convergent design is appropriate because both components share the same population and intervention, and the answers are most useful when compared side by side.
"Does cognitive behavioral therapy reduce anxiety in adolescents, and what factors explain variation in treatment response?" This question starts with a quantifiable effectiveness question and follows with an exploratory question. A sequential design (quantitative-first) is ideal. Conduct the meta-analysis first, identify sources of heterogeneity in treatment effects, and then use qualitative evidence to explore those sources.
"How should schools implement mental health screening programs to maximize uptake and effectiveness?" This broad implementation question requires multiple synthesis stages: a qualitative synthesis of implementation barriers and facilitators, a quantitative synthesis of screening accuracy and intervention outcomes, and a final integration stage that combines both into implementation recommendations. A multi-stage design fits best.
"What is the impact of community health worker programs on maternal mortality in low-income countries, and how do socio-cultural factors influence program delivery?" A convergent design with a framework synthesis approach works well here, using a health systems framework to organize both the mortality data and the socio-cultural findings into a coherent set of policy recommendations.
These examples demonstrate the principle that the research question drives the design, not the other way around. Formulating a clear, two-part question before selecting your integration approach prevents methodological confusion later. For guidance on structuring different types of systematic reviews, including mixed methods designs, see our comprehensive overview.
