Gender is a crucial factor in the development of mental illnesses, with an essential influence on clinical characteristics and not only on the prevalence of each disorder. Gender differences in cannabinoid-related disorders are highlighted by different research fields (preclinical, clinical, socio-demographic studies), but few studies focused on differential symptom expression in cannabinoid-induced psychosis. This study aims at investigating qualitative and quantitative gender differences in specific psychopathological domains in a clinical sample of subjects affected by cannabinoid-induced psychotic disorder, without psychiatric comorbidity.
The study was carried out at the Psychiatric Inpatient Service of General Hospital of Perugia (Italy). In this cross-sectional gender study, 28 inpatients were enrolled, 14 males (M) and 14 females (F). Participants were administered a psychometric battery consisting of 7 tests (PANSS, NDS-I, YMRS, HAM-D, HAM-A, AQ, SSI) in order to investigate 7 psychopathological domains (Psychosis, Dysphoria, Mania, Depression, Anxiety, Aggressive Behaviour and Suicide Ideation). Scores obtained at each test were compared between male and females by using Mann-Whitney U test (p<0.05).
In this study, we observed that males present higher severity of psychotic symptoms, with prominent scores in PANSS positive and general psychopathology scale (p<0.001), and an important expression of aggressive behavior (p<0.001) compared with females. Female sample, instead, shows a greater expression of dysphoria and depressive domains (p<0.001) and a lower, but statistically significant, prevalence in the anxiety domains expression (p=0.01). By these observations, we could assert that in male group thought disorders are prominent. On the other hand, in female group affective disorder are prominent.
This study confirmed how gender influences the phenomenic expression of psychiatric disorders. In line with the precision medicine paradigm, a further clarification of different clinical profiles based on gender would allow the choice of a personalized treatment plan with better efficacy and accuracy indices.