Complex decision-making in threatening environments

Many professions are asked to operate in environments that are inherently hostile and unpredictable (e.g., emergency services, military, and disaster support). Within these environments, they must make critical decisions based upon split-second assessments of environmental risks and upon predictions of the consequences of different courses of action. But the capacity to meet such cognitive demands may be seriously impeded by being in a threatened state (Lieberman et al., 2005), leading to mistakes, freezing, or impulsive action (McCall & Laycock, 2021). While training programs attempt to prepare individuals for working in threatening environments, research shows that trainees deviate from formal decision-making strategies during simulations of real-world complexity and threat (van den Heuvel, Alison, & Crego, 2012). A better understanding of how individuals negotiate uncertainty while under threat may therefore have important implications for improving screening and training individuals for optimal performance in these types of environments (McCall & Laycock, 2021). I propose to examine the effect of threat on complex decision-making in naturalistic environments and to do so both with civilian and expert (i.e., military) samples.
To achieve this goal, I will integrate a classic paradigm from the complex decision-making literature within a virtual reality (VR) environment. This environment will allow me to manipulate threat (McCall, Hildebrandt, Bornemann, & Singer, 2015) naturalistically and to replicate the cognitive demands of an operational environment. This environment will also allow me to measure potentially critical variables such as visual attention, speed of movement, and subjective experience (McCall, Hildebrandt, Hartmann, Baczkowski, & Singer, 2016). I will plan and execute three phases of enquiry, spanning all research opportunities during the MA in social research methods and PhD.
In Phase 1, I will develop and validate the VR platform to test adaptive decision-making (VRIGT). The design of VRIGT will be based on the established Iowa gambling task (IGT) (Bechara, Damasio, Damasio, & Anderson, 1994). Within VRIGT, the basic structure of the IGT will remain unchanged. However, the task will take place in a virtual building which the participant is attempting to exit. I will replace the IGT cards with doors, cash with time, and the bank with time left to escape. The aim is not to bank cash but to escape quickly. Validation will be achieved by correlating the performance of participants across three conditions (VR, desktop display and classic IGT application).
Phase 2 will add threat to the VRIGT simulation and conduct a study that addresses the question, what is the effect of threat on adaptive decision-making performance? Participants will be asked to negotiate the VRIGT in both threatening (e.g., the potential for explosive devices in the world) and non-threatening conditions. As the VRIGT is designed around a single environment, variation between conditions can be isolated to manipulations of threats themselves.
In Phase 3, will use the VRIGT to test individual differences in complex decision-making in a relevant real-world population, trainees from the UK Royal Marines. Here I will test the effects of specialist training and experience (operational exposure) on adaptive decision-making.
Through this project, I hope to shed light on complexity as a meaningful factor in understanding cognitive performance in threatening and unpredictable environments. Achieving this will help address legacy issues of ecological validity in this field. Moreover, it may lead directly to improvements in real-world training and screening for professionals who work in high-risk environments. I believe this will ultimately help combat unsafe and unethical practice in hostile and unpredictable environments.