Toma de decisiones en consumidores de cannabis

Abstract

Several neuropsychological studies have shown that chronic cannabis users have cognitive impairments, including decision-making process.Therefore, this study aims to evaluate the process, through the somatic marker hypothesis in a sample of 41 cannabis users compared with a control group of equal size, and to analyze the influence of age, sex, education level, age of onset and amount of daily consumption. In order to do that, the software "Cartas" (similar to the Iowa Gambling Task), was used, implementing its two versions: normal and reverse. The results show significant differences between cannabis users and control group in the normal and reverse task execution. By block analysis, the control group obtained higher scores in the normal task execution, however, in the reverse task, the differences between groups are present in the initial task execution but not final task execution. None of the analyzed variables (age, sex ...) are significantly related to task performance. These results suggest the existence of alterations in the decision making process of consumers cannabis, which may relate to the difficulty in generating somatic markers, and not for insensitivity punishments insensitivity.

Age of onset of cannabis use and decision making under uncertainty

“…However, the late-onset consumers showed more advantageous choices from the third block, although choices were always lower than those of the control group. These results are congruent with other works that found a relationship between drug use and alterations in the decision-making process ( Ahn et al, 2008 , 2011 , 2014 ; Alameda-Bailén, Paíno-Quesada & Mogedas-Valladares, 2012 ; Bechara & Damasio, 2002 ; Bechara, Dolan & Hindes, 2002 ; Bechara et al, 2001 ; Bolla et al, 2005 ; Grant, Conttoreggi & London, 2000 ; Mogedas-Valladares & Alameda-Bailén, 2011 ; Vélez, Borja & Ostrosky-Solís, 2010 ; Whitlow et al, 2004 ).…”

“…Cannabis, like other substances, negatively affects health, inducing respiratory problems and mental and cognitive alterations (psychosis, anxiety, dependence, etc.). Memory and learning disorders ( Crane et al, 2013 ; Jager et al, 2006 ), and executive dysfunctions ( Alameda-Bailén, Paíno-Quesada & Mogedas-Valladares, 2012 ; Alameda-Bailén et al, 2014 ; Crean, Crane & Mason, 2011 ; Fontes et al, 2011 ), are also neuropsychological disorders related to cannabis use. There is some consensus about the determinants of the short and long-term consequences of cannabis use: age of onset of consumption, consumption frequency, consumption duration, the amount of tetrahydrocannabinol in the cannabis, etc.…”

“…Among the cognitive functions impaired by cannabis use, the decision-making processes are the most studied ( Alameda-Bailén, Paíno-Quesada & Mogedas-Valladares, 2012 ; Alameda-Bailén et al, 2014 ; Mogedas-Valladares & Alameda-Bailén, 2011 ). Such processes highlights the somatic marker hypothesis ( Damasio, 1994 ), a research paradigm in which all the variations of the decision-making processes of the different communities are evaluated through the Iowa Gambling Task (IGT; Bechara et al, 1994 ).…”

“…IGT simulates a card game that allows studying decision-making processes in uncertain situations of everyday life in the laboratory. Healthy individuals make more advantageous choices, however, orbitofrontal damaged patients and people with addictions, among others, tend to choose cards from the most disadvantageous decks and cannot anticipate the consequences of their choices because of their difficulties to develop emotional signals related to the affective value of the different choices ( Alameda-Bailén, Paíno-Quesada & Mogedas-Valladares, 2012 ; Bechara, 2003 ; Bechara & Damasio, 2002 ; Bechara et al, 1997 ; Bechara, Tranel & Damasio, 2000 ; Mogedas-Valladares & Alameda-Bailén, 2011 ). In people with addictions, these difficulties to anticipate the consequences of their choices can be a consequence of drugs use, but also the cause of initiating consumption.…”

“…The PVL model has been applied to clinical samples and has allowed the identification of decision-making patterns in the IGT ( Ahn et al, 2008 , 2011 , 2014 ; Alameda-Bailén, Paíno-Quesada & Mogedas-Valladares, 2012 ; Alameda-Bailén et al, 2014 , 2017 ).…”