Predicting Scientific and Artistic Creative Achievements in Adolescence: A Comprehensive Approach Integrating Personality, Motivation, and Cognitive Ability

Extensive knowledge about creative achievements and their association with personality traits, motivation, and cognitive ability has been derived from univariate studies in adult samples. In contrast, research on children’s talent development often focuses narrowly on academic performance, overlooking creative achievements as developmental milestones. To better understand the nomological net of childhood creativity, this study took a comprehensive, multimodal approach to explore predictors of creative activities and (scientific and artistic) creative achievements in N = 431 gifted secondary school students. Using self- and parent-reports, performance tests, and a machine learning approach, over 40 theoretically derived predictors from personality, motivation, and cognitive domains were analyzed. Our results broadly aligned with the pattern of associations from adult samples and revealed domain-specific differences. Important predictors identified by machine learning included openness, creative self-efficacy, artistic and investigative vocational interests, and divergent thinking. Structural equation modeling showed that intellectual curiosity and investigative interests were the strongest predictors of scientific creative achievement, whereas aesthetic sensitivity was the strongest predictor of artistic creative achievement. Creative activities partly mediated the associations. Our findings underscore the multidimensional nature of creativity in gifted adolescents during an important stage of talent development and highlight key factors by distinguishing robust predictors from simple correlates.