Assessment of risk full decision making in patients with antisocial and borderline personality disorders

Document Type : Research Paper



Risk full decision making (RDM) is a kind of cognitive process in which people choose the best option among unsafe and probably disadvantageous choices. Gambling task (GT) and delayed discounting task (DDT) are designed to objectively assess impulsivity and RDM. In this analytic cross sectional research, we compared the performance of patients with antisocial personality disorder and borderline personality disorder on GT and DDT with normal population.
Materials and Methods: Number of 24 males with antisocial personality disorder and 28 patients with borderline personality disorder (20 males, 8 females) were chosen by at hand sampling from patients referred to Roozbeh Hospital or a counseling center for ex-prisoners (2006-7) in Tehran. The participants were structurally interviewed in comparison with 25 normal samples from our data pool; this was based on the criteria of diagnostic and statistical manual of mental disorders, forth edition, text revised (DSM-IV-TR; SCID-II). Mean score of GT was calculated by the differences of choices from advantageous and disadvantageous cards. The hyperbolic delay discounting model was employed.
The κ parameter, representing rates of delay discounting, served as a parametric value operationalizing impulsivity. One way ANOVA was used to compare the three groups.
Results: Personality disorder patients had significantly greater κ parameter in delay discounting process in comparison with normal population. People with personality disorders chose more from disadvantageous cards in GT but no significant difference was found between groups.
Conclusion: Choosing more from disadvantageous cards in persons with antisocial personality disorder is related to impaired risk full decision-making and may represent the dysfunction of ventromedial prefrontal cortex. Higher values of κ parameter indicate that this group of patients can not tolerate the delayed rewards and they prefer more recent smaller ones.