Mixed-Methods Integration Quality Assessment

Welcome to this mixed-methods integration review. Your responses will help the team assess how well qualitative and quantitative strands converge and identify areas for improvement. Your responses are completely confidential and anonymized. Participation is voluntary and you may stop at any time. There are no right or wrong answers—we value your honest assessment based on your direct experience with this project. Responses will be shared only within the project team in aggregate form. Estimated time: 10–12 minutes.

Which components of this study did you directly contribute to? Select all that apply.

• Qualitative data collection
• Qualitative analysis
• Survey instrument/design
• Quantitative analysis
• Data integration/synthesis
• Interpretation/write-up
• Other

Overall, to what extent do the qualitative and quantitative results point to the same conclusions?

How substantial were the discrepancies between the qualitative and quantitative findings in this project?

How well were qualitative and quantitative strands integrated across stages (design, analysis, interpretation)?

Rank the following sources by their influence on the study's final conclusions, from most to least influential.

1. Qualitative evidence
2. Quantitative evidence
3. Integration/synthesis process
4. Stakeholder/community input

Based on the current evidence, which next steps should the team take? Select all that apply.

• Proceed to dissemination as is
• Make minor analytic refinements
• Substantive re-analysis
• Collect additional qualitative data
• Collect additional quantitative data
• Stakeholder/member-check discussion
• Revise theoretical framing
• Other

We'd like to explore your perspective on the integration process in a bit more depth. An AI moderator will ask you a couple of follow-up questions based on your experience with this project.

Based on your responses throughout this review, is there anything else the team should consider when interpreting or reporting the integrated results?

How many years of experience do you have with mixed-methods research?

• 0–1 years
• 2–4 years
• 5–9 years
• 10+ years

Thank you for completing this review. Your input will directly strengthen the team's integrated conclusions and help guide next steps.

How clear were the mixed-methods objectives at the study design stage?

Which strand—qualitative, quantitative, or both equally—contributed most to the study's key insights overall?

• Primarily qualitative
• Primarily quantitative
• Both contributed equally
• Difficult to determine

What types of discrepancies were present? Select all that apply.

• Directional disagreement (opposite signs/themes)
• Magnitude differences (size/strength)
• Subgroup inconsistency
• Timing/temporal mismatch
• Measurement/operationalization mismatch
• Sampling/coverage bias
• Analytic/modeling choices
• None observed
• Other

Which integration techniques were used in this project? Select all that apply.

• Joint displays
• Convergence coding matrix
• Data transformation (qualitize/quantize)
• Framework matrix
• Meta-inferences workshop or meeting
• Narrative weaving
• None of the above
• Other

How confident are you in the integrated conclusions of this study?

Which methodological training best describes your background? Select all that apply.

• Primarily qualitative
• Primarily quantitative
• Mixed-methods
• Evaluation-focused
• Implementation science
• Other

Which data sources were included in this integration? Select all that apply.

• Interviews
• Focus groups
• Open-ended survey responses
• Observational/field notes
• Administrative/transactional data
• Structured survey data
• Experiments
• Other

Briefly describe one example of clear convergence (or near-convergence) you observed between the qualitative and quantitative findings.

Describe the most consequential discrepancy you observed: what differed, and where it appeared.

What, if any, barriers limited the integration of qualitative and quantitative strands?

In which region are you primarily based? (Optional)

• Africa
• Asia
• Europe
• Latin America/Caribbean
• Middle East
• North America
• Oceania
• Prefer not to say

Rank the following actions to address discrepancies from highest to lowest priority.

1. Re-examine qualitative codebook/themes
2. Sensitivity checks/alternative specifications
3. Revisit measurement/construct alignment
4. Sample weighting or balance diagnostics
5. Collect targeted follow-up data
6. Cross-walk via joint display/convergence coding