Start with common questions and local understanding.
Define the research question, target population and intended comparison before preparing the questionnaire. Use common variables and scales while making participant-facing wording understandable in each language.
AI can assist with the first draft and supported translations. Researchers and local partners review concepts, terminology and method. A pilot is needed in each language.
Plan recruitment as part of the method.
Choose online links, your panel supplier, targeted distribution or interviewer-led fieldwork around the people you need to reach. Set eligibility rules, quotas and fieldwork responsibilities explicitly.
The platform records recruitment context and field sessions; it does not supply the sample design, guarantee representativeness or replace researcher judgement about who is missing.
Prepare for analysis before collecting the data.
Use stable variable codes and check question paths. Download labelled SPSS and CSV files with a codebook and flow diagram. Keep language, recruitment source and version available for interpretation.
Define and test measurement models if the study combines items into an index. Examine weighting, group differences and confidence intervals within their assumptions. Use an external statistical tool when the analysis requires it.
Share findings with their own context.
A report can bring components from several studies together without merging individual responses. Explain each study’s base and the limits of cross-country comparisons. Report-reader filters do not recalculate model results or change separate-study components.
Erasmus+ and Horizon Europe are examples of project contexts. Software support is not a promise of grant eligibility, successful funding or compliance with a particular call.