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This article presents the methodological toolkit for data collection (particularly questionnaire) design and development in use at Statistics Netherlands (NCBS). The (re-)design of a continuous survey of living conditions is used to illustrate five development steps: (1) project preparation and risk analysis; (2) a qualitative study using exploratory tools in a questionnaire laboratory; (3) a qualitative study in the field; (4) a quantitative pilot in the field; and (5) implementation. A pretesting program determines how, in Steps 1–4, respondents are consulted about design issues concerning both the questionnaire and its administration. ‘Respondent-friendly’ design changes can thus be implemented before Step 5. The model is meant as a flexible framework for deciding when to test what and by which tool. This includes the possibility of steps being omitted, repeated, combined, or interchanged. Various test tools, like focus groups and cognitive interviews, are conceived as special cases of meta-interviews, by which (meta-) data are collected about and in addition to the intended data collection. The authors propose to use an eclectic classification of measurement error risks as a framework for describing risk hypotheses and test results. Risk hypotheses mainly serve to guarantee efficient use of means and time available for Steps 1–4. Unanticipated meta-information is obtained in the process.
Akkerboom et al. (Sun,) studied this question.