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Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models

In economics, models of decision-making under risk are widely investigated. Since many empirical studies have shown patterns in choice behavior that classical models fail to predict, several descriptive theories have been developed. Due to an evident phenotypic heterogeneity, obsessive compulsive di...

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Autores principales: Cillo, Alessandra, Bonetti, Marco, Burro, Giovanni, Di Serio, Clelia, De Filippis, Roberta, Martoni, Riccardo Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377126/
https://www.ncbi.nlm.nih.gov/pubmed/30768599
http://dx.doi.org/10.1371/journal.pone.0211856
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author Cillo, Alessandra
Bonetti, Marco
Burro, Giovanni
Di Serio, Clelia
De Filippis, Roberta
Martoni, Riccardo Maria
author_facet Cillo, Alessandra
Bonetti, Marco
Burro, Giovanni
Di Serio, Clelia
De Filippis, Roberta
Martoni, Riccardo Maria
author_sort Cillo, Alessandra
collection PubMed
description In economics, models of decision-making under risk are widely investigated. Since many empirical studies have shown patterns in choice behavior that classical models fail to predict, several descriptive theories have been developed. Due to an evident phenotypic heterogeneity, obsessive compulsive disorder (OCD) patients have shown a general deficit in decision making when compared to healthy control subjects (HCs). However, the direction for impairment in decision-making in OCD patients is still unclear. Hence, bridging decision-making models widely used in the economic literature with mental health research may improve the understanding of preference relations in severe patients, and may enhance intervention designs. We investigate the behavior of OCD patients with respect to HCs by means of decision making economic models within a typical neuropsychological setting, such as the Cambridge Gambling Task. In this task subjects have to decide the amount of their initial wealth to invest in each risky decision. To account for heterogenous preferences, we have analyzed the micro-level data for a more informative analysis of the choices made by the subjects. We consider two influential models in economics: the expected value (EV), which assumes risk neutrality, and a multiple reference points model, an alternative formulation of Disappointment theory. We find evidence that (medicated) OCD patients are more consistent with EV than HCs. The former appear to be more risk neutral, namely, less sensitive to risk than HCs. They also seem to base their decisions on disappointment avoidance less than HCs.
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spelling pubmed-63771262019-03-01 Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models Cillo, Alessandra Bonetti, Marco Burro, Giovanni Di Serio, Clelia De Filippis, Roberta Martoni, Riccardo Maria PLoS One Research Article In economics, models of decision-making under risk are widely investigated. Since many empirical studies have shown patterns in choice behavior that classical models fail to predict, several descriptive theories have been developed. Due to an evident phenotypic heterogeneity, obsessive compulsive disorder (OCD) patients have shown a general deficit in decision making when compared to healthy control subjects (HCs). However, the direction for impairment in decision-making in OCD patients is still unclear. Hence, bridging decision-making models widely used in the economic literature with mental health research may improve the understanding of preference relations in severe patients, and may enhance intervention designs. We investigate the behavior of OCD patients with respect to HCs by means of decision making economic models within a typical neuropsychological setting, such as the Cambridge Gambling Task. In this task subjects have to decide the amount of their initial wealth to invest in each risky decision. To account for heterogenous preferences, we have analyzed the micro-level data for a more informative analysis of the choices made by the subjects. We consider two influential models in economics: the expected value (EV), which assumes risk neutrality, and a multiple reference points model, an alternative formulation of Disappointment theory. We find evidence that (medicated) OCD patients are more consistent with EV than HCs. The former appear to be more risk neutral, namely, less sensitive to risk than HCs. They also seem to base their decisions on disappointment avoidance less than HCs. Public Library of Science 2019-02-15 /pmc/articles/PMC6377126/ /pubmed/30768599 http://dx.doi.org/10.1371/journal.pone.0211856 Text en © 2019 Cillo et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cillo, Alessandra
Bonetti, Marco
Burro, Giovanni
Di Serio, Clelia
De Filippis, Roberta
Martoni, Riccardo Maria
Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title_full Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title_fullStr Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title_full_unstemmed Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title_short Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models
title_sort neurocognitive assessment in obsessive compulsive disorder patients: adherence to behavioral decision models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377126/
https://www.ncbi.nlm.nih.gov/pubmed/30768599
http://dx.doi.org/10.1371/journal.pone.0211856
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