Evidence map›Paper›PMID 39349575›Full record

ArticleScientific reports2024

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

Aaron Laycock, Guy Schofield, Cade McCall

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Aaron LaycockDepartment of Psychology, University of York, York, YO10 5DD, UK. aaron.laycock@york.ac.uk.ORCID http://orcid.org/0000-0001-5494-8858
Guy SchofieldDepartment of Archaeology, University of York, York, YO10 5GB, UK.
Cade McCallDepartment of Psychology, University of York, York, YO10 5DD, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals living and working in dangerous settings (e.g., first responders and military personnel) make complex decisions amidst serious threats. However, controlled studies on decision-making under threat are limited given obvious ethical concerns. Here, we embed a complex decision-making task within a threatening, immersive virtual environment. Based on the Iowa Gambling Task (IGT), a paradigm widely used to study complex decision-making, the task requires participants to make a series of choices to escape a collapsing building. In Study 1 we demonstrate that, as with the traditional IGT, participants learn to make advantageous decisions over time and that their behavioural data can be described by reinforcement-learning based computational models. In Study 2 we created threatening and neutral versions of the environment. In the threat condition, participants performed worse, taking longer to improve from baseline and scoring lower through the final trials. Computational modelling further revealed that participants in the threat condition were more responsive to short term rewards and less likely to perseverate on a given choice. These findings suggest that when threat is integral to decision-making, individuals make more erratic choices and focus on short term gains. They furthermore demonstrate the utility of virtual environments for making threat integral to cognitive tasks.

Indexed as

Decision MakingAdultChoice BehaviorFemaleGamblingHumansMaleRewardVirtual RealityYoung AdultChoice perseverationComplex decision-makingComputational modellingIowa gambling taskReward sensitivityThreatVirtual reality

Identifiers

PMID39349575
PMCPMC11442743

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.