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Journal Article

Citation

Rogeberg O, Bergsvik D, Phillips LD, van Amsterdam J, Eastwood N, Henderson G, Lynskey M, Measham F, Ponton R, Rolles S, Schlag AK, Taylor P, Nutt D. Int. J. Drug Policy 2018; 56: 144-152.

Affiliation

Imperial College London, United Kingdom. Electronic address: d.nutt@imperial.ac.uk.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.drugpo.2018.01.019

PMID

29459211

Abstract

BACKGROUND: Drug policy, whether for legal or illegal substances, is a controversial field that encompasses many complex issues. Policies can have effects on a myriad of outcomes and stakeholders differ in the outcomes they consider and value, while relevant knowledge on policy effects is dispersed across multiple research disciplines making integrated judgements difficult.

METHODS: Experts on drug harms, addiction, criminology and drug policy were invited to a decision conference to develop a multi-criterion decision analysis (MCDA) model for appraising alternative regulatory regimes. Participants collectively defined regulatory regimes and identified outcome criteria reflecting ethical and normative concerns. For cannabis and alcohol separately, participants evaluated each regulatory regime on each criterion and weighted the criteria to provide summary scores for comparing different regimes.

RESULTS: Four generic regulatory regimes were defined: absolute prohibition, decriminalisation, state control and free market. Participants also identified 27 relevant criteria which were organised into seven thematically related clusters. State control was the preferred regime for both alcohol and cannabis. The ranking of the regimes was robust to variations in the criterion-specific weights.

CONCLUSION: The MCDA process allowed the participants to deconstruct complex drug policy issues into a set of simpler judgements that led to consensus about the results.

Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.


Language: en

Keywords

Alcohol; Cannabis; Drug policy; Multi-criterion decision analysis

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