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Neurocognitive components of gambling disorder: Implications for assessment, treatment and policy

[PDF] Navas_et_al_2019_preprint.pdf (724.8Kb)
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URI: http://hdl.handle.net/10481/53073
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Autor
Navas, Juan F.; Billieux, Joël; Verdejo García, Antonio Javier; Perales López, José César
Editorial
Routledge
Materia
Gambling Disorder
 
Emotion Regulation
 
Cognitive Biases
 
Psychology
 
Neuroscience
 
Theoretical Models
 
Fecha
2019
Referencia bibliográfica
Navas, J. F., Billieux, J., Verdejo-García, A., & Perales, J. C. (In press). Neurocognitive components of gambling disorder: implications for policy, prevention, and treatment. In H. Bowden-Jones, C. Dickson, C. Dunand, & O. Simon (Eds.), Harm Reduction for Problem Gambling: A Public Health Approach. Routledge.
Resumen
Gambling disorder (GD) is now recognized as a behavioral addiction. Evidence has shown that GD and substance use disorders (SUDs) have shared vulnerability factors, similar clinical characteristics, and neurobiological overlaps. However, these similarities have somewhat overshadowed the specificities that account for the differences between GD and SUDs, as well as the considerable heterogeneity of patients with gambling disorder (PGD). In this chapter, we aim to disentangle the key neurocognitive components involved in GD, as well as those underlying heterogeneity among PGD. Core components include the brain mechanisms for gambling reinforcement, and their association with incentive sensitization and craving. With regard to heterogeneity, we will focus on specific gambling-related rewards, and automatic (model-free) versus strategic (model-based) emotion regulation processes. These components are integrated into a psychobiologically-informed, multidimensional model for gamblers’ characterization. In such model, individual differences in sensitivity to gambling reinforcement, basic emotion regulation mechanisms, and strategic emotion regulation are used to explain heterogeneity within the GD population, and serve to re-conceptualize previous attempts to cluster GD phenotypes based on clinical observations and empirical research. The proposed model has a number of implications for policy, prevention, and treatment. First, the consideration of GD as an addiction provides ground for harm-reduction approaches. Second, the transdiagnostic nature of key vulnerability factors justifies profiling of high-risk individuals for secondary prevention of disordered gambling (along with other externalizing problems). Third, understanding individual differences within the population of disordered gamblers yields a practical avenue for health services to incorporate tailored treatment protocols.
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