Drug and alcohol dependence · 2022
Gender differences in cannabis use disorder symptoms: A network analysis.
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Kroon Emese, Mansueto Alessandra, Kuhns Lauren, Filbey Francesca, Wiers Reinout, Cousijn Janna
Аннотация
BACKGROUND: 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 etiological mechanisms in addiction. The aim of this study was to evaluate the CUD symptom network and assess whether there are gender differences therein.
METHODS: A total of 1257 Dutch individuals reporting weekly cannabis use, including 745 men and 512 women, completed online questionnaires assessing DSM-5 CUD symptoms and additional items on plans to quit or reduce use, cigarette use, and the presence of psychological diagnoses. Gender differences were assessed for all variables and an Ising model estimation method was used to estimate CUD symptom networks in men and women using network comparison tests to assess differences.
RESULTS: There were gender differences in the prevalence of 6 of the 11 symptoms, but symptom networks did not differ between men and women. Cigarette use appeared to only be connected to the network through withdrawal, indicating a potential role of cigarette smoking in enhancing cannabis withdrawal symptoms. Furthermore, there were gender differences in the network associations of mood and anxiety disorders with CUD symptoms.
CONCLUSION: The association between smoking and withdrawal as well as gender differences in the role of comorbidities in the CUD network highlight the value of using network models to understand CUD and how symptom interactions might affect treatment.
METHODS: A total of 1257 Dutch individuals reporting weekly cannabis use, including 745 men and 512 women, completed online questionnaires assessing DSM-5 CUD symptoms and additional items on plans to quit or reduce use, cigarette use, and the presence of psychological diagnoses. Gender differences were assessed for all variables and an Ising model estimation method was used to estimate CUD symptom networks in men and women using network comparison tests to assess differences.
RESULTS: There were gender differences in the prevalence of 6 of the 11 symptoms, but symptom networks did not differ between men and women. Cigarette use appeared to only be connected to the network through withdrawal, indicating a potential role of cigarette smoking in enhancing cannabis withdrawal symptoms. Furthermore, there were gender differences in the network associations of mood and anxiety disorders with CUD symptoms.
CONCLUSION: The association between smoking and withdrawal as well as gender differences in the role of comorbidities in the CUD network highlight the value of using network models to understand CUD and how symptom interactions might affect treatment.