Gender differences in cannabis use disorder symptoms: A network analysis

While cannabis use in women is increasing worldwide, research into gender differences in cannabis use disorder (CUD) symptomology is lacking. In response to limited effectiveness of addiction treatment, research focus has been shifting from clinical diagnoses towards interactions between symptoms as patterns of symptoms and their interactions could be crucial in understanding addictive processes. The aim of the current study was to evaluate the CUD symptom network and assess whether there are gender differences therein. A total of 1257 weekly cannabis users, including 745 men and 512 women participated in the study. All participants completed online questionnaires assessing the MINI DSM-5 CUD symptoms and additional items on cigarette use and the presence of psychological diagnoses. Gender differences were assessed for all variables and the Ising model was used to estimate the networks in men and women, applying network comparison tests to assess differences. The estimated networks were dense with all symptoms except ‘Tolerance’ and ‘Risky Use’ being highly central. There were gender differences in the prevalence of 6 (highest p-value = .043) of the 11 symptoms, but symptom networks were similar (structure: p = .941, strength: p = .973). Cigarette use was primarily connected to the network through withdrawal, indicating a potential role of nicotine use in cannabis withdrawal. Furthermore, there were gender differences in how mood and anxiety disorders connected to the network, indicating potential gender differences in how comorbidities are associated with CUD symptoms.

While men and women differ in symptom prevalence, the pattern and strength of the interactions between symptoms appear similar. However, the relation between cigarette co-use and withdrawal, as well as gender differences in the role of anxiety and mood disorders in the CUD network highlight the importance of research into comorbidity and gender difference therein and how this could affect treatment outcomes.