The impact of impression management on writing tendencies: Investigating faking susceptibility of open-ended personality assessments.

¯ = .63). Training sample configuration also influenced psychometric properties, such that training on a mixed sample of honest and motivated responses yielded the best results. Finally, AI-generated responses (fully synthetic and human-AI hybrid) received scores that varied considerably across models, though they typically were higher than human scores. However, a customized algorithm accurately differentiated human from AI responses with near-perfect accuracy (across seven large language models and for humans using AI), with only a 1% false positive rate. Collectively, these findings suggest that open-ended personality assessments, when paired with natural language processing scoring, have potential to offer a scalable, more faking-resistant approach to personality assessment. (PsycInfo Database Record (c) 2026 APA, all rights reserved).