Gender differences in cannabis use disorder symptoms: A network analysis.


Journal

Drug and alcohol dependence
ISSN: 1879-0046
Titre abrégé: Drug Alcohol Depend
Pays: Ireland
ID NLM: 7513587

Informations de publication

Date de publication:
01 02 2023
Historique:
received: 27 06 2022
revised: 17 11 2022
accepted: 01 12 2022
pubmed: 25 12 2022
medline: 21 1 2023
entrez: 24 12 2022
Statut: ppublish

Résumé

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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 36565568
pii: S0376-8716(22)00470-7
doi: 10.1016/j.drugalcdep.2022.109733
pii:
doi:

Substances chimiques

Hallucinogens 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

109733

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest No conflict declared.

Auteurs

Emese Kroon (E)

Neuroscience of Addiction (NofA) Lab, Department of Psychology, University of Amsterdam, the Netherlands; ADAPT-laboratory, Department of Psychology, University of Amsterdam, the Netherlands. Electronic address: e.kroon@uva.nl.

Alessandra Mansueto (A)

ADAPT-laboratory, Department of Psychology, University of Amsterdam, the Netherlands; Centre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands; Psychological Methods, Department of Psychology, University of Amsterdam, the Netherlands; Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Amsterdam, the Netherlands.

Lauren Kuhns (L)

Neuroscience of Addiction (NofA) Lab, Department of Psychology, University of Amsterdam, the Netherlands; ADAPT-laboratory, Department of Psychology, University of Amsterdam, the Netherlands.

Francesca Filbey (F)

School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.

Reinout Wiers (R)

ADAPT-laboratory, Department of Psychology, University of Amsterdam, the Netherlands; Centre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands.

Janna Cousijn (J)

Neuroscience of Addiction (NofA) Lab, Department of Psychology, University of Amsterdam, the Netherlands; Department of Psychology, Education & Child Studies, Erasmus University Rotterdam, the Netherlands.

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Classifications MeSH