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Contextualising Psychological Distress Among Regular Ecstasy Users: The Importance of Sociodemographic Factors and Patterns of Drug Use

NCJ Number
230991
Journal
Drug and Alcohol Review Volume: 29 Issue: 3 Dated: May 2010 Pages: 243-249
Author(s)
Jessica George; Stuart A. Kinner; Raimondo Bruno; Louisa Degenhardt; Matthew Dunn
Date Published
May 2010
Length
7 pages
Annotation

The current study aimed to examine the relationship between patterns of recent (last six months) ecstasy use and psychological distress among current, regular ecstasy users, controlling for sociodemographic risk factors and patterns of other drug use.

Abstract

Seven percent of the sample scored in the 'high' distress category and 55 percent in the 'medium' distress category. Patterns of ecstasy use were not independently associated with psychological distress. The strongest predictors of distress were female sex, lower education, unemployment, 'binge' drug use including ecstasy (use for more than 48 h without sleep), frequent cannabis use and daily tobacco use. Regular ecstasy users have elevated levels of psychological distress compared with the general population; however, ecstasy use per se was not independently related to such distress. Other factors, including sociodemographic characteristics and other drug use patterns, appear to be more important. These findings highlight the importance of targeting patterns of polydrug use in order to reduce drug-related harm among regular ecstasy users. Considerable concern has been raised about associations between ecstasy use and mental health. Studies of ecstasy users typically investigate varying levels of lifetime use of ecstasy, and often fail to account for other drug use and sociodemographic characteristics of participants, which may explain mixed findings. Data were collected from regular ecstasy users (n = 752) recruited from each capital city in Australia as part of the Ecstasy and related Drugs Reporting System (EDRS). Psychological distress was assessed using the Kessler Psychological Distress Scale (K10). Data were analysed using multinomial logistic regression. (Published Abstract)

Date Published: May 1, 2010