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SABINA LA GRUTTA

Predictive signs and indicators of aggressiveness and violence: a comparison between a group of adolescents attending an external penal area, a group of prisoners and a group of patients with borderline personality disorder

  • Autori: LA GRUTTA S; LO BAIDO R; CASTELLI M; MARRAZZO G; SCHIERA G; GENTILE MC; SARNO L; ROCCELLA M
  • Anno di pubblicazione: 2006
  • Tipologia: Articolo in rivista
  • Parole Chiave: aggressiveness, violence, defence mechanism, symbolic function
  • OA Link: http://hdl.handle.net/10447/24361

Abstract

Aim. We considered the spreading and the increasing of aggressive and violent behaviours. The most of them have two common roots: lack of actual motivation and brutality. Our research intends to detect specific indicators and predictive signs of violent and aggressive behaviours. In order to this, scientific literature shows that the most reliable indicators and predictive signs are linked to structural personality features (e.g. defensive strategies, impulse control). Methods. This cross sectional study compares a group of 26 male adolescents with Conduct Disorder (F91.8), a group of 29 male patients with Borderline Personality Disorder (F60.31) and a group of 33 male prisoners with Antisocial Personality Disorder (F60.2). The protocol includes: the Structured Clinical Interview for DSM-IV Axis II Disorders (for the recruitment of adult groups); the Indicators of Aggressive Conduct and the Profile of Mood States (for the recruitment of the adolescent group); the Defense Mechanisms Inventory. Results. The performances of the groups about their predominant defensive strategies and starting emotional background are significantly different. Conclusions. We selected a profile where low emotional response supports aggressiveness and a profile where aggressiveness and violence are associated with “clinically significant” impulsivity. Therefore, on one hand this study allows us to detect some indicators and clinical predictors of aggressiveness and violence, on the other hand we identified the most risky profiles according to used instruments.