Automated scoring of adult ego development from sentence completions: interpretable maturity indicators derived by evolutionary prompt optimization.

Introduction: Ego Development Theory (EDT) describes systematic changes in how adults make meaning, but its principal measure, the Sentence Completion Test (SCT), requires resource-intensive expert scoring. Methods: We developed an automated scoring approach in which an evolutionary algorithm derives a small set of interpretable maturity indicators, each scored from sentence-completion responses by a domain-fine-tuned language model; a classifier trained on the resulting scores then predicts developmental stage. Performance was evaluated on an expert-scored dataset never used for feature discovery ( Results: The classifier agreed exactly with expert ratings in 86.1% of cases (quadratic-weighted κ = 0.93). By contrast, zero-shot prompting of two frontier language models with the full scoring manual yielded only 40.1-44.9% agreement, indicating that expert-comparable scoring is not achieved by prompting alone. The classifier's agreement replicated at 85.1% in the blinded comparison. In external validation, the indicators correlated with personality, coherence, and autonomy measures in theoretically expected patterns, and explained substantial additional variance in expert-rated developmental stage beyond Big Five traits (Δ Discussion: These results support automated ego-development scoring at agreement levels comparable to trained raters, and the indicators offer interpretable candidate dimensions of adult development for confirmatory and population-scale research.