Ahuna, J. K., & Becker, K. D. (2025).
Journal of Cognitive Engineering and
Decision Making, 19(1), 96–129.
Abstract
The Naturalistic Decision Making (NDM) paradigm is an emerging shift in how researchers study decision making in complex, real-world situations and design decision supports. The purpose of this scoping review was to describe how the NDM paradigm was applied in studies of mental health professionals. Six bibliographic databases were searched to identify NDM studies. Each study was charted for study features, participant demographics, decision contexts, and the essential characteristics of NDM research. The search identified 26 studies published from 1989 to June 2023. Approximately 35% of studies were published in a peer-reviewed journal. Quantitative (30.8%), qualitative (34.6%), and mixed (34.6%) methods were utilized in similar percentages of studies, with social workers (61.5%) most frequently represented in these studies. Approximately 69% of studies examined assessment decisions (versus diagnosis or treatment) and roughly 96% of studies examined individuals (versus teams). Most studies explored professionals’ decision making process (73.1%) and how proficient decision makers utilized their experience to make decisions (38.5%). The NDM literature among mental health professionals is growing, with many opportunities to understand clinical decision making using well-established NDM concepts and methods. The review concludes with recommendations for both NDM and mental health services researchers.
Here are some thoughts:
This scoping review reveals a significant underutilization and misalignment of Naturalistic Decision-Making (NDM) principles in research on mental health professionals' decision-making. Despite the complex, high-stakes, and information-rich environments in which mental health clinicians operate—conditions that align well with NDM's focus on real-world expertise—few studies meaningfully engage with core NDM characteristics. The authors conclude that the NDM paradigm remains underdeveloped in mental health research, limiting our understanding of how clinicians make effective decisions in practice. They call for more authentic NDM-based research to capture expert reasoning, support training innovations like decision-centered design and scenario-based learning, and ultimately improve clinical outcomes by bridging the gap between theory, practice, and real-world decision demands.