Not according to plan: Cognitive failures in marksmanship due to effects of expertise, unknown environments, and the likelihood of shooting unintended targets.

Shooting errors have multi-faceted causes with contributing factors that include sensorimotor activity and cognitive failures. Empirical investigations often assess mental errors through threat identification, yet other cognitive failures could contribute to poor outcomes. The current study explored several possible sources of cognitive failures unrelated to threat identification with live fire exercises.

Don't Shoot Me: Potential Consequences of Force-on-Force Training Modulate the Human Stress Response.

Jensen, AE, Bernards, JR, Hamilton, JA, Markwald, RR, Kelly, KR, and Biggs, AT. Do not shoot me: potential consequences of force-on-force training modulate the human stress response. J Strength Cond Res 37(9): 1761-1769, 2023-Close-quarters combat (CQC) engagements trigger the "fight-or-flight" response, activating the sympathetic nervous system and hypothalamic-pituitary-adrenal axis in response to perceived threats.

Perception during use of force and the likelihood of firing upon an unarmed person.

Stress can impact perception, especially during use-of-force. Research efforts can thus advance both theory and practice by examining how perception during use-of-force might drive behavior. The current study explored the relationship between perceptual judgments and performance during novel close-combat training.

How unintentional cues can bias threat assessments during shoot/don't-shoot simulations.

Objective: Identify whether contextual information may unintentionally alter decision-making during lethal force training.

Background: Lethal force decisions inherently involve a threat assessment, where an individual learns to identify a threat and use force commensurate to the situation. This decision is ultimately subject to numerous cognitive influences, particularly during training where artificial factors may bias decision-making.

Real-time visualization of cross-sectional data in three dimensions.

This paper describes a technique for viewing and interacting with 2-D medical data in three dimensions. The approach requires little pre-processing, runs on personal computers, and has a wide range of application. Implementation details are discussed, examples are presented, and results are summarized.