Generating and analyzing personality questionnaires using large language models

The Five-Factor Model ("Big Five") is based on the lexical hypothesis that personality traits are encoded in language. Large language models (LLMs) offer new ways to explore personality through text. We developed an LLM-based method to generate and validate personality questionnaires from textual sources. Using the DSM-5 personality disorders section and a popular astrology book, we generated two questionnaires and administered them, alongside the Big-Five Inventory (BFI), to 600 adults. Internal consistency was high for the BFI and the DSM-based questionnaire but low for the astrology-based one. The LLM predicted human response patterns for both generated questionnaires. Individual items from both the DSM- and astrology-based questionnaires predicted diverse life outcomes at levels comparable to the BFI. These findings show that LLMs can construct personality measures and anticipate response patterns, offering a scalable framework for corpus-based personality research.