How to Search a Research Questionnaire?

Building a research questionnaire starts with finding validated measurement items in prior studies—then tracing those items back to their original sources so they can be used (or adapted) correctly. The core workflow is to identify the construct(s) in the model, search for recent quantitative papers that measured those constructs with questionnaires, extract the exact Likert-scale statements used to operationalize each construct, and then verify where each questionnaire item came from.

A typical questionnaire begins with respondent demographics (such as age, department, and university/organization), followed by sets of statements tied to each construct. Each construct is measured through multiple items—statements like “The university provides equal opportunities for all its members”—that respondents rate on agreement/disagreement scales (often including options for strong agreement, agreement, neutrality, disagreement, and strong disagreement). The key point is that these items are not random: they are designed to measure a specific construct, and the construct’s definition should match the way the study intends to measure it.

To locate those items, the process begins on Google Scholar (or other databases such as Emerald, SAGE, SpringerLink, ScienceDirect, Taylor & Francis, and IEEE Xplore). For example, if the study focuses on “project success,” the search is narrowed to recent work (e.g., filtering to papers since 2017) to see what current researchers are using. From the resulting papers, the next step is to identify which ones actually used questionnaires in quantitative, survey-based research. Clues include the presence of structural equation modeling (SEM), survey measurement sections, and explicit discussion of measurement items.

Once a promising paper is found, the questionnaire items may appear in different places: sometimes inside tables in the results section, sometimes in the “measurement” or “questionnaire design” parts of the methodology, and sometimes only in appendices. For instance, one project-success paper provides items grouped under constructs such as comfort, competence, commitment, and communication. But those items may not align with how “project success” is defined in another framework (for example, the iron triangle of scope, time, and budget). That mismatch forces a deeper check: read how the construct is defined and where the measurement came from.

Crucially, items should not be copied blindly. If a paper used an existing scale (rather than developing its own), the measurement source must be traced to the original authors. The transcript illustrates this with a project-success measurement that was based on a four-group framework with 15 variables proposed by a named author; the correct approach is to locate that original scale and cite it properly. Another example shows that some papers transform factors into statements suitable for Likert-type responses, meaning researchers may need to draft statements carefully (as agreement/disagreement items, not yes/no or interrogative questions).

The same logic applies to other constructs such as servant leadership. Searching for “servant leadership” plus “impact,” “measuring,” or “measures” helps surface papers that explicitly develop or use questionnaire scales. When a paper reports a scale length that doesn’t match the items shown (e.g., “14-item scale” but only 13 visible), the remedy is to go back to the original source paper and use the complete, validated measure. The overall takeaway: find questionnaire items in recent quantitative studies, extract them from the correct sections, and always verify the original measurement source before using them in a new questionnaire.