The relationship between cryptomarket drug purchase, social networks and adverse drug events: A cross-sectional study.

Adverse drug events Cryptomarkets Social network analysis Social networks

Journal

The International journal on drug policy
ISSN: 1873-4758
Titre abrégé: Int J Drug Policy
Pays: Netherlands
ID NLM: 9014759

Informations de publication

Date de publication:
04 Dec 2023
Historique:
received: 01 03 2023
revised: 04 10 2023
accepted: 02 11 2023
medline: 7 12 2023
pubmed: 7 12 2023
entrez: 6 12 2023
Statut: aheadofprint

Résumé

Drug use and trading are typically social activities; however, supply through cryptomarkets can occur without any in-person social contact. People who use drugs alone may be at higher risk of experiencing harms, for example, due to lack of others who may call for emergency assistance. Alternatively, cryptomarkets may be a source of harm reduction information and drugs with better-known content and dose, potentially reducing the risk of adverse events. This study examines relationships between cryptomarket use, drug-using social networks and adverse drug events for MDMA, cocaine and LSD. A subsample of 23,053 respondents from over 70 countries was collected in the 2018 Global Drug Survey. People who reported using MDMA, cocaine or LSD were asked about using cryptomarkets to purchase these drugs; any adverse drug events requiring medical treatment (combining seeking treatment and should have sought treatment but did not); and social networks who they had used the specific drug with. All measures referred to the last 12 months, hereon referred to as 'recent'. Binary logistic regressions examined relationships between cryptomarket use, drug-using social networks, and adverse drug events, controlling for age, gender, and frequency of drug use. Adverse events from any drug type were low (5.2%) and for each drug; MDMA (3.5%); cocaine (3.3%); and LSD (3.5%). After controlling for covariates, recent cryptomarket use was associated with increased likelihood of having no drug-using network for each drug type. People who recently used cryptomarkets were more likely to report adverse cocaine (AOR = 1.70 (1.22-2.37)) and LSD (AOR = 1.58 (1.12-2.09)) events. For those reporting a network size >1, network characteristics did not differ with recent cryptomarket use; however, those reporting recent cryptomarket use were more likely to report adverse LSD events (AOR = 1.86 (0.99-3.51)). People who reported purchasing drugs from cryptomarkets more commonly reported having no drug-using network, and cryptomarket purchase was associated with reported adverse events. Our results support the notion that cryptomarket use increases drug-related harm, but further disentanglement of multiple complex mechanisms is needed in future research.

Identifiants

pubmed: 38056221
pii: S0955-3959(23)00305-5
doi: 10.1016/j.drugpo.2023.104258
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104258

Informations de copyright

Copyright © 2023. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of Competing Interest ARW is the founder and owner of Global Drug Survey. AP has received untied educational grants from Seqirus and Mundipharma for study of opioid medications; these organisations had no role in study design, conduct or reporting. There are no other relevant interests to declare.

Auteurs

Leigh Coney (L)

National Drug and Alcohol Research Centre, UNSW Sydney, NSW, Australia. Electronic address: l.coney@student.unsw.edu.au.

Amy Peacock (A)

National Drug and Alcohol Research Centre, UNSW Sydney, NSW, Australia.

Aili Malm (A)

School of Criminology, Criminal Justice, and Emergency Management, California State University Long Beach, CA, USA.

Rasmus Munksgaard (R)

Department of Sociology and Social Work, Aalborg University, Denmark.

Judith Aldridge (J)

Department of Criminology, University of Manchester, Manchester, UK.

Jason A Ferris (JA)

Centre for Health Services Research, University of Queensland, Brisbane, Qld, Australia.

Larissa J Maier (LJ)

School of Pharmacy, University of California San Francisco (UCSF), San Francisco, CA, USA.

Adam R Winstock (AR)

Institute of Epidemiology and Health Care, University College London, London, UK; Global Drug Survey, London, UK.

Monica J Barratt (MJ)

National Drug and Alcohol Research Centre, UNSW Sydney, NSW, Australia; Social Equity Research Centre and Digital Ethnography Research Centre, RMIT University, Melbourne, Vic, Australia.

Classifications MeSH