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The missing consequences: A fourth flaw of experiments

Published online by Cambridge University Press:  13 May 2022

Adam Thomas Biggs Open the ORCID record for Adam Thomas Biggs [Opens in a new window]
Adam Thomas Biggs*
Affiliation:
Naval Special Warfare Command, Coronado, CA 92155, USA. adam.t.biggs.mil@socom.mil
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Abstract

Decisions are affected by the potential consequences as much as any factor during the decision-making process. This prospective influence represents another flaw overlooked by most experiments that raises questions about the use of certain laboratory paradigms. Lethal force encounters are a prime example of this problem, where negative consequences of slow decisions and wrong decisions should be considered alongside behavior.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e69
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Biggs, A. T., Cain, M. S., & Mitroff, S. R. (2015). Cognitive training can reduce civilian casualties in a simulated shooting environment. Psychological Science, 26(8), 1164–1176.CrossRefGoogle Scholar
Biggs, A., & Doubrava, M. (2019). Superficial ballistic trauma and subjective pain experienced during force-on-force training and the observed recovery pattern. Military Medicine, 184(11–12), e611–e615.CrossRefGoogle ScholarPubMed
Biggs, A., Pettijohn, K., & Gardony, A. (2021). When the response does not match the threat: The relationship between threat assessment and behavioural response in ambiguous lethal force decision-making. Quarterly Journal of Experimental Psychology, 74(5), 812–825.CrossRefGoogle Scholar
Blacker, K. J., Pettijohn, K. A., Roush, G., & Biggs, A. T. (2021). Measuring lethal force performance in the lab: The effects of simulator realism and participant experience. Human Factors, 63(7), 1141–1155.CrossRefGoogle ScholarPubMed
Cesario, J., & Carrillo, A. (in press). Racial bias in police officer deadly force decisions: What has social cognition learned? In Carlston, D. E., Johnson, K. & Hugenberg, K. (Eds.), The Oxford handbook of social cognition (2nd ed.). Oxford University Press.Google Scholar
Correll, J., Wittenbrink, B., Park, B., Judd, C. M., & Goyle, A. (2011). Dangerous enough: Moderating racial bias with contextual threat cues. Journal of Experimental Social Psychology, 47, 184–189.CrossRefGoogle ScholarPubMed
Cox, W. T. L., & Devine, P. G. (2016). Experimental research on shooter bias: Ready (or relevant) for application in the courtroom? Journal of Applied Research in Memory and Cognition 5, 236–238.CrossRefGoogle Scholar
James, L., Klinger, D., & Vila, B. (2014). Racial and ethnic bias in decisions to shoot seen through a stronger lens: Experimental results from high-fidelity laboratory simulations. Journal of Experimental Criminology, 10, 323–340.CrossRefGoogle Scholar
James, L., Vila, B., & Daratha, K. (2013). Results from experimental trials testing participant responses to White, Hispanic and Black suspects in high-fidelity deadly force judgment and decision-making simulations. Journal of Experimental Criminology 9, 189–212.CrossRefGoogle Scholar
Nieuwenhuys, A., & Oudejans, R. R. (2010). Effects of anxiety on handgun shooting behavior of police officers: A pilot study. Anxiety, Stress, & Coping, 23(2), 225–233.CrossRefGoogle ScholarPubMed
Nieuwenhuys, A., & Oudejans, R. R. (2011). Training with anxiety: Short- and long-term effects on police officers’ shooting behavior under pressure. Cognitive Processing, 12(3), 277–288.CrossRefGoogle Scholar
Oudejans, R. R. D. (2008). Reality-based practice under pressure improves handgun shooting performance of police officers. Ergonomics, 51(3), 261–273.CrossRefGoogle ScholarPubMed
Patton, D., & Gamble, K. (2016). Physiological measures of arousal during soldier-relevant tasks performed in a simulated environment. In Schmorrow, D. D. & Fidopiastis, C. M. (Eds.), Foundations of augmented cognition: Neuroergonomics and operational neuroscience: 10th international conference, AC 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17–22, 2016, Proceedings, Part I (pp. 372–382). Springer International Publishing.CrossRefGoogle Scholar
Sim, J. J., Correll, J., & Sadler, M. S. (2013). Understanding police and expert performance: When training attenuates (vs. exacerbates) stereotypic bias in the decision to shoot. Personality and Social Psychology Bulletin, 39, 291–304. doi: 10.1177/0146167212473157CrossRefGoogle Scholar
Taverniers, J., & De Boeck, P. (2014). Force-on-force handgun practice: An intra-individual exploration of stress effects, biomarker regulation, and behavioral changes. Human Factors, 56(2), 403–413.CrossRefGoogle ScholarPubMed
Taverniers, J., Smeets, T., Van Ruysseveldt, J., Syroit, J., & von Grumbkow, J. (2011). The risk of being shot at: Stress, cortisol secretion, and their impact on memory and perceived learning during reality-based practice for armed officers. International Journal of Stress Management, 18(2), 113–132.CrossRefGoogle Scholar
Taylor, P. L. (2020). Dispatch priming and the police decision to use deadly force. Police Quarterly, 1098611119896653.Google Scholar
Wessel, J. R. (2018). Prepotent motor activity and inhibitory control demands in different variants of the go/no-go paradigm. Psychophysiology, 55(3), e12871.CrossRefGoogle ScholarPubMed