Yavor Dragostinov
Papers
2
Total Citations
38
H-Index
2
About
Yavor Dragostinov is a researcher whose work sits at the intersection of psychometrics, trust, and mixed-methods research design. His primary contribution lies in the rigorous development of psychological measurement tools, most notably through his pioneering application of the mixed methods Delphi technique for scale construction. In his highly cited 2022 paper, Dragostinov demonstrated how this systematic, expert-consensus approach can be used to refine and validate questionnaire items, specifically for developing a novel Propensity to Trust scale. By integrating qualitative expert feedback with quantitative survey data administered to academic lecturers and professors, his work provides a robust methodological framework that enhances the content validity of new psychometric instruments. This research, which has accumulated over 35 citations, has been influential in establishing best practices for scale development, offering a replicable model for researchers seeking to create reliable measures of complex psychological constructs. Dragostinov’s contributions are particularly valuable for students and scholars in social and behavioral sciences who are designing their own surveys, as his work bridges the gap between theoretical construct definition and empirical measurement.
Research Focus
Key Achievements
Top Papers
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