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Using natural language processing to measure cognitive load during use-of-force decision-making training

NCJ Number
307749
Journal
Policing: An International Journal of Police Strategies & Management Volume: 46 Issue: 2 Dated: 2023 Pages: 227-242
Author(s)
Vivian Ta-Johnson; Joel Suss; Brian Lande
Date Published
2023
Length
16 pages
Annotation

This article reports on a research study that sought to examine police officers’ verbal behavioral data from two use-of-force de-escalation projects; its goal is to enable police trainers to facilitate the development of adaptive training strategies that will improve use-of-force training via the reduction of cognitive load.

Abstract

Few studies have tested the efficacy of instruction based on cognitive load theory in police use-of-force (UoF) training due to limitations of existing cognitive load measures. Although linguistic measures of cognitive load address these limitations, they have yet to be applied to police UoF training. The authors of this paper set out to address the issue; they used officers’ verbal behavioral data from two UoF de-escalation projects to calculate cognitive load and assess how it varied with officer experience level.  They further analyzed the verbal data to examine specific thought patterns that contributed to heightened cognitive load across officer experience levels. Across both studies, responses from less-experienced officers contained greater usage of cognitive language than responses from experienced officers. Specific cognitive processes that contribute to cognitive load in specific situations were also identified. This paper enables police trainers to facilitate the development of adaptive training strategies to improve police UoF training via the reduction of cognitive load, and also contributes to the collective understanding of how less experienced and experienced officers differ in their UoF decision-making. Publisher Abstract Provided