Early Identification of Locally Emerging Trends in Psychoactive Substance Use – Experience and Best Practice in Four European Localities

Abstract

Background: Timely information about trends in psychoactive substance use could yield tailored interventions and reduce potential harms. However, conventional epidemiological tools might have limited capacity to detect trends emerging on a local level. Objectives: The aim of this study was to explore best practice in the identification of new drug trends at the local level. Methods: A total of 33 key informants from seven European municipalities/regions were interviewed to describe trends in substance use in their locality and to provide expert insights on how these were identified. Semi-structured interviews were analyzed with open coding method. Results: Four case studies that described local trends and responses were compiled: onset of problematic GHB use in the Dutch municipality of Breda (1); emerging retail shops selling new psychoactive substances (NPS) across the regions of Czech Republic (2) and in the Portuguese Agueda and Coimbra (3); and use of drugs with unknown content in the Italian region of Emilia Romagna, and its city Bologna (4). “Early identifiers” in the four case studies were organizations that work directly with people who use drugs (PWUD), emergency departments, and local police. Efficient methods of horizontal and vertical information sharing, sometimes facilitated by communication platforms, were in place, such that included early warning systems on local, national, and supra-local level. Local-level identification systems appeared as best suited to provide locally relevant information. Conclusions: Best practice in identifying emerging trends should involve all relevant “early identifiers”, should consist of supra-local exchange platforms, integrate the qualities of local-level identification, and be facilitated by local-level coordinators.

Keywords:

• New psychoactive substances
• trends in substance use
• key informant interviews
• open coding
• trend identification and response

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the European Commission, Drug Prevention and Information Program under Grant JUST/2012/DPIP/AG/3600.