Evidence map›Paper›PMID 35422888›Full record

ArticleBehavioural neurology2022

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers.

Laura Mas-Cuesta, Sabina Baltruschat, Antonio Cándido, Andrés Catena

Abstract read
In one paragraph

Article in Behavioural neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

4 authors.

Laura Mas-CuestaMind, Brain and Behavior Research Center, Campus de Cartuja s/n, University of Granada, 18011 Granada, Spain.ORCID https://orcid.org/0000-0002-5424-6415
Sabina BaltruschatCardiff University Brain Research Imaging Centre, Maindy Rd, Cardiff CF24 4HQ, UK.ORCID https://orcid.org/0000-0002-2719-4322
Antonio CándidoMind, Brain and Behavior Research Center, Campus de Cartuja s/n, University of Granada, 18011 Granada, Spain.ORCID https://orcid.org/0000-0002-3973-8219
Andrés CatenaSchool of Psychology, University of Granada, Campus de Cartuja s/n, 18011 Granada., Spain.ORCID https://orcid.org/0000-0002-0775-5751

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

Indexed as

Automobile DrivingGray MatterBrainHumansPersonalityRisk-Taking

Identifiers

PMID35422888
PMCPMC9005327

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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.