↓ Skip to main content

Psychopathy-related traits and the use of reward and social information: a computational approach

Overview of attention for article published in Frontiers in Psychology, January 2013
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
11 X users
reddit
2 Redditors

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
105 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Psychopathy-related traits and the use of reward and social information: a computational approach
Published in
Frontiers in Psychology, January 2013
DOI 10.3389/fpsyg.2013.00952
Pubmed ID
Authors

Inti A. Brazil, Laurence T. Hunt, Berend H. Bulten, Roy P. C. Kessels, Ellen R. A. de Bruijn, Rogier B. Mars

Abstract

Psychopathy is often linked to disturbed reinforcement-guided adaptation of behavior in both clinical and non-clinical populations. Recent work suggests that these disturbances might be due to a deficit in actively using information to guide changes in behavior. However, how much information is actually used to guide behavior is difficult to observe directly. Therefore, we used a computational model to estimate the use of information during learning. Thirty-six female subjects were recruited based on their total scores on the Psychopathic Personality Inventory (PPI), a self-report psychopathy list, and performed a task involving simultaneous learning of reward-based and social information. A Bayesian reinforcement-learning model was used to parameterize the use of each source of information during learning. Subsequently, we used the subscales of the PPI to assess psychopathy-related traits, and the traits that were strongly related to the model's parameters were isolated through a formal variable selection procedure. Finally, we assessed how these covaried with model parameters. We succeeded in isolating key personality traits believed to be relevant for psychopathy that can be related to model-based descriptions of subject behavior. Use of reward-history information was negatively related to levels of trait anxiety and fearlessness, whereas use of social advice decreased as the perceived ability to manipulate others and lack of anxiety increased. These results corroborate previous findings suggesting that sub-optimal use of different types of information might be implicated in psychopathy. They also further highlight the importance of considering the potential of computational modeling to understand the role of latent variables, such as the weight people give to various sources of information during goal-directed behavior, when conducting research on psychopathy-related traits and in the field of forensic psychiatry.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 4%
Netherlands 1 <1%
Germany 1 <1%
Australia 1 <1%
Unknown 98 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 16%
Student > Master 16 15%
Student > Bachelor 15 14%
Researcher 13 12%
Student > Doctoral Student 11 10%
Other 17 16%
Unknown 16 15%
Readers by discipline Count As %
Psychology 48 46%
Neuroscience 14 13%
Medicine and Dentistry 10 10%
Computer Science 3 3%
Agricultural and Biological Sciences 3 3%
Other 4 4%
Unknown 23 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 March 2023.
All research outputs
#1,610,317
of 23,539,593 outputs
Outputs from Frontiers in Psychology
#3,254
of 31,371 outputs
Outputs of similar age
#15,439
of 284,770 outputs
Outputs of similar age from Frontiers in Psychology
#165
of 969 outputs
Altmetric has tracked 23,539,593 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 31,371 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.6. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 969 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.