Prevalence and Factors Associated With Criminal Behavior Among Illicit Drug Users: A Cross-Sectional Study

Guimarães, Rafael Alves; Mesquita, Natália Silva; Lopes, Renata Silva; Lucchese, Roselma; Felipe, Rodrigo Lopes de; Vêra, Ivânia; Fernandes, Inaina Lara; Castro, Paulo Alexandre de; Monteiro, Luiz Henrique Batista; Silva, Graciele Cristina

doi:10.1080/10826084.2017.1284231

Cited by 14 publications

(11 citation statements)

References 28 publications

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“…Moreover, the pharmacological effects of polysubstance use may increase impulsivity in a cumulative and interactive manner (64–66), augment the probability of engaging in risky criminal behaviors, and subsequently lead to more arrests. Criminal behavior could also be the result of the effects of withdrawing from one or more substances (67). However, based on the available literature, we were not able to explain the relationship between cannabis alone and polysubstance use, which requires further investigations.…”

Section: Discussionmentioning

confidence: 99%

Trajectories of Dynamic Risk Factors as Predictors of Violence and Criminality in Patients Discharged From Mental Health Services: A Longitudinal Study Using Growth Mixture Modeling

et al. 2019

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Background: Individuals with severe mental illnesses are at greater risk of offenses and violence, though the relationship remains unclear due to the interplay of static and dynamic risk factors. Static factors have generally been emphasized, leaving little room for temporal changes in risk. Hence, this longitudinal study aims to identify subgroups of psychiatric populations at risk of violence and criminality by taking into account the dynamic changes of symptomatology and substance use. Method: A total of 825 patients from the MacArthur Violence Risk Assessment Study having completed five postdischarge follow-ups were analyzed. Individuals were classified into outcome trajectories (violence and criminality). Trajectories were computed for each substance (cannabis, alcohol, and cocaine, alone or combined) and for symptomatology and inputted as dynamic factors, along with other demographic and psychiatric static factors, into binary logistic regressions for predicting violence and criminality. Best predictors were then identified using backward elimination, and receiver operator characteristic (ROC) curves were calculated for both models. Results: Two trajectories were found for violence (low versus high violence). Best predictors for belonging in the high-violence group were low verbal intelligence (baseline), higher psychopathy (baseline) and anger (mean) scores, persistent cannabis use (alone), and persistent moderate affective symptoms. The model’s area under the curve (AUC) was 0.773. Two trajectories were also chosen as being optimal for criminality. The final model to predict high criminality yielded an AUC of 0.788, retaining as predictors male sex, lower educational level, higher score of psychopathy (baseline), persistent polysubstance use (cannabis, cocaine, and alcohol), and persistent cannabis use (alone). Both models were moderately predictive of outcomes. Conclusion: Static factors identified as predictors are consistent with previously published literature. Concerning dynamic factors, unexpectedly, cannabis alone was an independent co-occurring variable, as well as affective symptoms, in the violence model. For criminality, our results are novel, as there are very few studies on criminal behaviors in nonforensic psychiatric populations. In conclusion, these results emphasize the need to further study the predictors of crime, separately from violence and the impact of longitudinal patterns of specific substance use and high affective symptoms.

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Section: Discussionmentioning

confidence: 99%

Trajectories of Dynamic Risk Factors as Predictors of Violence and Criminality in Patients Discharged From Mental Health Services: A Longitudinal Study Using Growth Mixture Modeling

et al. 2019

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“…Therefore, consumption of this substance is associated with higher scores in the CAPP and the PCL-R, and a younger age of commencement of use with higher scores in the CAPP. This link with APD makes for a link between cannabis consumption and property offences and violent crime, and committing two or more offences (Table 6) 56 - 58 .…”

Section: Discussionmentioning

confidence: 99%

Personality disorders, addictions and psychopathy as predictors of criminal behaviour in a prison sample

Flórez

Ferrer²,

García³

et al. 2019

Rev. esp. sanid. penit.

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Aims: Disturbances in personality and addictions are associated with an increased risk of committing crimes and therefore of being imprisoned. In this study, the relationship between these factors is analyzed through a sample of inmates in the Prison of Pereiro de Aguiar, Ourense. Material and method: 204 inmates participated in this transversal simple blind design study. The following variables were analyzed: presence of personality disorders and psychopathy, history of addictive psychoactive substance use, criminal history and socio-demographic variables. Results: 101 (49.5%) inmates received a diagnosis of personality disorder, the most frequent being: narcissistic, 43 (21.08%); antisocial, 38 (18.63%); and paranoid, 29 (14.22%). The presence of any personality disorder was associated with an increase in the risk of committing crimes, especially violence and crimes against property. The most frequent personality disorders were associated with higher scores in the psychopathy assessment tools. Higher scores in the Psychopathy Checklist Reviewed (PCL-R) correlated with an increased risk of committing the following crimes: violent, against public health, against property and disorderly conduct. The consumption of addictive psychoactive substances was associated with the commission of crimes against property. Methadone stood out for its protective role against the commission of violent crimes. Discussion: This sample shows that inmates have a higher prevalence of personality disorders, psychopathy and consumption of addictive psychoactive substances. These three variables significantly increased the risk of committing crimes.

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“…A recent trend has been the concept of food “addiction” with a particular emphasis on “addiction” to sugar or to sweet taste. According to neurobiologists, “addictions involve persistent, compulsive, and uncontrolled behaviors that are both maladaptive and destructive” [ 1 , 2 ]. Overeating of palatable foods that inevitably lead to obesity is certainly maladaptive and is often characterized as both persistent and compulsive.…”

Section: Introductionmentioning

confidence: 99%

Sugars and Sweet Taste: Addictive or Rewarding?

Greenberg¹,

Peter

2021

IJERPH

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The notion of food “addiction” often focuses on the overconsumption of sweet tasting foods or so-called sugar “addiction”. In the extreme, some have suggested that sugar and sweet tastes elicit neural and behavioral responses analogous to those observed with drugs of abuse. These concepts are complicated by the decades long uncertainty surrounding the validity and reproducibility of functional magnetic resonance imaging (fMRI) methodologies used to characterize neurobiological pathways related to sugar and sweet taste stimuli. There are also questions of whether sweet taste or post-ingestion metabolic consequences of sugar intake would lead to addiction or excessive caloric intake. Here, we present a focused narrative review of literature related to the reward value of sweet taste which suggests that reward value can be confounded with the construct of “addictive potential”. Our review seeks to clarify some key distinctions between these constructs and questions the applicability of the addiction construct to human over-eating behaviors. To adequately frame this broad discussion requires the flexibility offered by the narrative review paradigm. We present selected literature on: techniques used to link sugar and sweet tastes to addiction neurobiology and behaviors; sugar and sweet taste “addiction”; the relationship of low calorie sweetener (LCS) intake to addictive behaviors and total calorie intake. Finally, we examined the reward value of sweet tastes and contrasted that with the literature describing addiction. The lack of reproducibility of fMRI data remains problematic for attributing a common neurobiological pathway activation of drugs and foods as conclusive evidence for sugar or sweet taste “addiction”. Moreover, the complicated hedonics of sweet taste and reward value are suggested by validated population-level data which demonstrate that the consumption of sweet taste in the absence of calories does not increase total caloric intake. We believe the neurobiologies of reward value and addiction to be distinct and disagree with application of the addiction model to sweet food overconsumption. Most hypotheses of sugar “addiction” attribute the hedonics of sweet foods as the equivalent of “addiction”. Further, when addictive behaviors and biology are critically examined in totality, they contrast dramatically from those associated with the desire for sweet taste. Finally, the evidence is strong that responses to the palatability of sweets rather than their metabolic consequences are the salient features for reward value. Thus, given the complexity of the controls of food intake in humans, we question the usefulness of the “addiction” model in dissecting the causes and effects of sweet food over-consumption.

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Prevalence and Factors Associated With Criminal Behavior Among Illicit Drug Users: A Cross-Sectional Study

Cited by 14 publications

References 28 publications

Trajectories of Dynamic Risk Factors as Predictors of Violence and Criminality in Patients Discharged From Mental Health Services: A Longitudinal Study Using Growth Mixture Modeling

Trajectories of Dynamic Risk Factors as Predictors of Violence and Criminality in Patients Discharged From Mental Health Services: A Longitudinal Study Using Growth Mixture Modeling

Personality disorders, addictions and psychopathy as predictors of criminal behaviour in a prison sample

Sugars and Sweet Taste: Addictive or Rewarding?

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