The effects of threat on complex decision-making: evidence from a virtual environment

Harman, J. L., Zhang, D. & Greening, S. G. Basic processes in dynamic decision making: How experimental findings about risk, uncertainty, and emotion can contribute to police decision making. Front. Psychol.10, 2140 (2019).Article 
PubMed Central 

Google Scholar 
Lieberman, H. R. et al. The fog of war: Decrements in cognitive performance and mood associated with combat-like stress. Aviat. Space Environ. Med.76, C7–C14 (2005).
Google Scholar 
Penney, G., Launder, D., Cuthbertson, J. & Thompson, M. B. Threat assessment, sense making, and critical decision-making in police, military, ambulance, and fire services. Cogn Tech Work24, 423–439 (2022).Article 

Google Scholar 
Williams, B. S. Heuristics and biases in military decision making. Mil. Rev.90, 40 (2010).
Google Scholar 
Starcke, K. & Brand, M. Effects of stress on decisions under uncertainty: A meta-analysis. Psychol. Bull.142, 909–933 (2016).Article 

Google Scholar 
Funke, J. Complex problem solving. Encyclopedia of the Sciences of Learning 682–685. (Heidelberg, Springer, 2012).Azriel, O. & Bar-Haim, Y. Attention bias. in Clinical Handbook of Fear and Anxiety: Maintenance Processes and Treatment Mechanisms 203–218 (American Psychological Association, Washington, DC, US, 2020). https://doi.org/10.1037/0000150-012.Vytal, K., Cornwell, B., Arkin, N. & Grillon, C. Describing the interplay between anxiety and cognition: From impaired performance under low cognitive load to reduced anxiety under high load. Psychophysiology49, 842–852 (2012).Article 
PubMed Central 

Google Scholar 
Fanselow, M. S. The role of learning in threat imminence and defensive behaviors. Curr. Opin. Behav. Sci.24, 44–49 (2018).Article 
PubMed Central 

Google Scholar 
Yechiam, E. Robust consistency of choice switching in decisions from experience. Judgm. Decis. Mak.15, 74–81 (2020).Article 

Google Scholar 
Silver, D., Singh, S., Precup, D. & Sutton, R. S. Reward is enough. Artif. Intell.299, 103535 (2021).Article 
MathSciNet 

Google Scholar 
Paret, C. & Bublatzky, F. Threat rapidly disrupts reward reversal learning. Behav. Res. Ther.131, 103636 (2020).Article 

Google Scholar 
Keinan, G. Decision making under stress: Scanning of alternatives under controllable and uncontrollable threats. J. Personal. Soc. Psychol.52, 639 (1987).Article 
CAS 

Google Scholar 
Schwabe, L. et al. Stress modulates the use of spatial versus stimulus-response learning strategies in humans. Learn. Mem.14, 109–116 (2007).Article 
PubMed Central 

Google Scholar 
Starcke, K. & Brand, M. Decision making under stress: A selective review. Neurosci. Biobehav. Rev.36, 1228–1248 (2012).Article 

Google Scholar 
Gonzalez, C. Learning and dynamic decision making. Top. Cognit. Sci.14, 14–30 (2022).Article 

Google Scholar 
Kahneman, D. Prospect theory: An analysis of decisions under risk. Econometrica47, 278 (1979).Article 
MathSciNet 

Google Scholar 
Hertwig, R., Barron, G., Weber, E. U. & Erev, I. Decisions from experience and the effect of rare events in risky choice. Psychol. Sci.15, 534–539 (2004).Article 

Google Scholar 
Buelow, M. T. & Suhr, J. A. Construct validity of the iowa gambling task. Neuropsychol. Rev.19, 102–114 (2009).Article 

Google Scholar 
Bechara, A., Damasio, A. R., Damasio, H. & Anderson, S. W. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition50, 7–15 (1994).Article 
CAS 

Google Scholar 
Brevers, D., Bechara, A., Cleeremans, A. & Noel, X. Iowa gambling task (IGT): Twenty years after—gambling disorder and IGT. Front. Psychol.https://doi.org/10.3389/fpsyg.2013.00665 (2013).Article 
PubMed Central 

Google Scholar 
Wemm, S. E. & Wulfert, E. Effects of acute stress on decision making. Appl. Psychophysiol. Biofeedback42, 1–12 (2017).Article 
PubMed Central 

Google Scholar 
Byrne, K. A., Cornwall, A. C. & Worthy, D. A. Acute stress improves long-term reward maximization in decision-making under uncertainty. Brain Cognit.133, 84–93 (2019).Article 

Google Scholar 
Sokol-Hessner, P., Raio, C. M., Gottesman, S. P., Lackovic, S. F. & Phelps, E. A. Acute stress does not affect risky monetary decision-making. Neurobiol. Stress5, 19–25 (2016).Article 
PubMed Central 

Google Scholar 
Preston, S. D., Buchanan, T. W., Stansfield, R. B. & Bechara, A. Effects of anticipatory stress on decision making in a gambling task. Behav. Neurosci.121, 257–263 (2007).Article 
CAS 

Google Scholar 
Simonovic, B., Stupple, E. J., Gale, M. & Sheffield, D. Stress and risky decision making: Cognitive reflection, emotional learning or both. J. Behav. Decis. Mak.30, 658–665 (2017).Article 

Google Scholar 
Simonovic, B., Stupple, E. J. N., Gale, M. & Sheffield, D. Performance under stress: An eye-tracking investigation of the iowa gambling task (IGT). Front. Behav. Neurosci.https://doi.org/10.3389/fnbeh.2018.00217 (2018).Article 
PubMed Central 

Google Scholar 
Nowacki, J. et al. Decision making in response to physiological and combined physiological and psychosocial stress. Behav. Neurosci.133, 59–67 (2019).Article 

Google Scholar 
Baker, C., Pawling, R. & Fairclough, S. Assessment of threat and negativity bias in virtual reality. Sci. Rep.10, 17338 (2020).Article 
ADS 
CAS 
PubMed Central 

Google Scholar 
Kane, H. S., McCall, C., Collins, N. L. & Blascovich, J. Mere presence is not enough: Responsive support in a virtual world. J. Exp. Soc. Psychol.48, 37–44 (2012).Article 

Google Scholar 
McCall, C., Hildebrandt, L. K., Bornemann, B. & Singer, T. Physiophenomenology in retrospect: Memory reliably reflects physiological arousal during a prior threatening experience. Conscious. Cognit.38, 60–70 (2015).Article 

Google Scholar 
McCall, C. et al. The underwood project: A virtual environment for eliciting ambiguous threat. Behav. Res.https://doi.org/10.3758/s13428-022-02002-3 (2022).Article 

Google Scholar 
Franken, I. H. & Muris, P. Individual differences in decision-making. Personal. Individ. Differ.39, 991–998 (2005).Article 

Google Scholar 
Haines, N., Vassileva, J. & Ahn, W.-Y. The outcome-representation learning model: A novel reinforcement learning model of the iowa gambling task. Cognit. Sci.42, 2534–2561 (2018).Article 

Google Scholar 
Steingroever, H., Wetzels, R. & Wagenmakers, E.-J. Validating the PVL-delta model for the Iowa gambling task. Front. Psychol.https://doi.org/10.3389/fpsyg.2013.00898 (2013).Article 
PubMed Central 

Google Scholar 
Sullivan-Toole, H., Haines, N., Dale, K. & Olino, T. M. Enhancing the psychometric properties of the iowa gambling task using full generative modeling. Comput. Psychiatr.6, 189–212 (2022).Article 
PubMed Central 

Google Scholar 
Ben Hassen, N., Molins, F., Paz, M. & Serrano, M. -Á. Later stages of acute stress impair reinforcement-learning and feedback sensitivity in decision making. Biol. Psychol.180, 108585 (2023).Article 

Google Scholar 
Molins, F., Ayuso, C. & Serrano, M. Á. Emotional stress and decision-making: An emotional stressor significantly reduces loss aversion. Stress24, 780–786 (2021).Article 

Google Scholar 
Aram, S. et al. The iowa gambling task: A review of the historical evolution, scientific basis, and use in functional neuroimaging. SAGE Open9, 2158244019856911 (2019).Article 

Google Scholar 
Halfmann, K., Hedgcock, W., Bechara, A. & Denburg, N. L. Functional neuroimaging of the iowa gambling task in older adults. Neuropsychology28, 870–880 (2014).Article 

Google Scholar 
Oberdörfer, S., Heidrich, D., Birnstiel, S. & Latoschik, M. E. Enchanted by your surrounding? Measuring the effects of immersion and design of virtual environments on decision-making. Front. Virt. Real.https://doi.org/10.3389/frvir.2021.679277 (2021).Article 

Google Scholar 
O’Brien, H. L., Cairns, P. & Hall, M. A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. Int. J. Human–Comput. Stud.112, 28–39 (2018).Article 

Google Scholar 
Lehne, M. & Koelsch, S. Toward a general psychological model of tension and suspense. Front. Psychol.https://doi.org/10.3389/fpsyg.2015.00079 (2015).Article 
PubMed Central 

Google Scholar 
Gansler, D. A., Jerram, M. W., Vannorsdall, T. D. & Schretlen, D. J. Comparing alternative metrics to assess performance on the Iowa gambling task. J. Clin. Exp. Neuropsychol.33, 1040–1048 (2011).Article 

Google Scholar 
Pasion, R. et al. Meta-analytic evidence for a reversal learning effect on the iowa gambling task in older adults. Front. Psychol.https://doi.org/10.3389/fpsyg.2017.01785 (2017).Article 
PubMed Central 

Google Scholar 
Bechara, A., Damasio, H., Tranel, D. & Damasio, A. R. The Iowa gambling task and the somatic marker hypothesis: Some questions and answers. Trends Cognit. Sci.9, 159–162 (2005).Article 
CAS 

Google Scholar 
Ahn, W.-Y., Busemeyer, J. R., Wagenmakers, E.-J. & Stout, J. C. Comparison of decision learning models using the generalization criterion method. Cognit. Sci.32, 1376–1402 (2008).Article 

Google Scholar 
Ahn, W.-Y. et al. Decision-making in stimulant and opiate addicts in protracted abstinence: evidence from computational modeling with pure users. Front. Psychol.https://doi.org/10.3389/fpsyg.2014.00849 (2014).Article 
PubMed Central 

Google Scholar 
Worthy, D. A., Pang, B. & Byrne, K. A. Decomposing the roles of perseveration and expected value representation in models of the Iowa gambling task. Front. Psychol.https://doi.org/10.3389/fpsyg.2013.00640 (2013).Article 
PubMed Central 

Google Scholar 
Ahn, W.-Y., Haines, N. & Zhang, L. Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Comput. Psychiatr.1, 24–57 (2017).Article 

Google Scholar 
Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci.7, 457–472 (1992).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).
Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Soft.https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: Tests in linear mixed effects models. J. Stat. Softw.82, 1–26 (2017).Article 

Google Scholar 
Lenth, R. V. Emmeans: Estimated Marginal Means, Aka Least-Squares Means. (2023).Gabry, J., Simpson, D., Vehtari, A., Betancourt, M. & Gelman, A. Visualization in Bayesian workflow. J. R. Stat. Soc. A182, 389–402 (2019).Article 
MathSciNet 

Google Scholar 
Delacre, M. & Klein, O. Routliers: Robust Outliers Detection. (2019).Green, P. & MacLeod, C. J. simr: An R package for power analysis of generalised linear mixed models by simulation. Methods Ecol. Evolut.7, 493–498 (2016).Article 

Google Scholar 
Ernst, M. et al. Decision making in adolescents with behavior disorders and adults with substance abuse. AJP160, 33–40 (2003).Article 

Google Scholar 
Grillon, C., Pellowski, M., Merikangas, K. R. & Davis, M. Darkness facilitates the acoustic startle reflex in humans. Biol. Psychiatr.42, 453–460 (1997).Article 
CAS 

Google Scholar 
Elliot, A. J. & Maier, M. A. Color and psychological functioning. Curr. Dir. Psychol. Sci.16, 250–254 (2007).Article 

Google Scholar 
Kruschke, J. K. Rejecting or accepting parameter values in bayesian estimation. Adv Methods Pract. Psychol. Sci.1, 270–280 (2018).Article 

Google Scholar 
Bechara, A., Tranel, D. & Damasio, H. Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain123, 2189–2202 (2000).Article 

Google Scholar 
Zeif, D. & Yechiam, E. Autism is not associated with poor or enhanced performance on the iowa gambling task: A meta-analysis. Neurosci. Biobehav. Rev.113, 440–447 (2020).Article 

Google Scholar 
Frey, R., Hertwig, R. & Rieskamp, J. Fear shapes information acquisition in decisions from experience. Cognition132, 90–99 (2014).Article 

Google Scholar 
Dubois, M. & Hauser, T. U. Value-free random exploration is linked to impulsivity. Nat Commun13, 4542 (2022).Article 
ADS 
CAS 
PubMed Central 

Google Scholar 
Simon, L., Jiryis, T. & Admon, R. Now or later? Stress-induced increase and decrease in choice impulsivity are both associated with elevated affective and endocrine responses. Brain Sci.11, 1148 (2021).Article 
CAS 
PubMed Central 

Google Scholar 
Asutay, E. & Västfjäll, D. The continuous and changing impact of affect on risky decision-making. Sci. Rep.12, 10613 (2022).Article 
ADS 
CAS 
PubMed Central 

Google Scholar 
Västfjäll, D. et al. The arithmetic of emotion: Integration of incidental and integral affect in judgments and decisions. Front. Psychol.https://doi.org/10.3389/fpsyg.2016.00325 (2016).Article 
PubMed Central 

Google Scholar 
Bagneux, V., Thomassin, N., Gonthier, C. & Roulin, J.-L. Working memory in the processing of the iowa gambling task: An individual differences approach. PloS one8, e81498 (2013).Article 
ADS 
PubMed Central 

Google Scholar 
Luhmann, C. C., Ishida, K. & Hajcak, G. Intolerance of uncertainty and decisions about delayed, probabilistic rewards. Behav. Ther.42, 378–386 (2011).Article 

Google Scholar