Personality Assessment in Legal Contexts: Introduction to the Special Issue

Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research.

This article reports on an effort to explore the differences between two approaches to intuition and expertise that are often viewed as conflicting: heuristics and biases (HB) and naturalistic decision making (NDM). Starting from the obvious fact that professional intuition is sometimes marvelous and sometimes flawed, the authors attempt to map the boundary conditions that separate true intuitive skill from overconfident and biased impressions. They conclude that evaluating the likely quality of an intuitive judgment requires an assessment of the predictability of the environment in which the judgment is made and of the individual's opportunity to learn the regularities of that environment. Subjective experience is not a reliable indicator of judgment accuracy.

We systematically evaluated the peer-reviewed Rorschach validity literature for the 65 main variables in the popular Comprehensive System (CS). Across 53 meta-analyses examining variables against externally assessed criteria (e.g., observer ratings, psychiatric diagnosis), the mean validity was r = .27 (k = 770) as compared to r = .08 (k = 386) across 42 meta-analyses examining variables against introspectively assessed criteria (e.g., self-report). Using Hemphill's (2003) data-driven guidelines for interpreting the magnitude of assessment effect sizes with only externally assessed criteria, we found 13 variables had excellent support (r ≥ .33, p 50), 17 had good support (r ≥ .21, p .05), and 12 had no construct-relevant validity studies. The variables with the strongest support were largely those that assess cognitive and perceptual processes (e.g., Perceptual-Thinking Index, Synthesized Response); those with the least support tended to be very rare (e.g., Color Projection) or some of the more recently developed scales (e.g., Egocentricity Index, Isolation Index). Our findings are less positive, more nuanced, and more inclusive than those reported in the CS test manual. We discuss study limitations and the implications for research and clinical practice, including the importance of using different methods in order to improve our understanding of people.