Discovering semantic structures in psychological scales: A response-free front-end to efficient simplification.

Psychological scale refinement traditionally relies on response-based methods such as factor analysis, item response theory, and network psychometrics to uncover latent constructs and optimize item composition. Although methodologically rigorous, these approaches require large respondent samples and may be limited by data availability, cross-cultural comparability, and replication constraints. Recent advances in natural language processing suggest that the wording of questionnaire items contains construct-relevant semantic organization, offering a complementary response-free perspective. We in