How accurate are drug cryptomarket listings by content, weight, purity and repeat purchase?

Purpose: Drug cryptomarkets increase information available to market actors, which should reduce information asymmetry and increase market efficiency. This study aims to determine whether cryptomarket listings accurately represent the advertised substance, weight or number and purity, and whether there are differences in products purchased from the same listing multiple times. Design/methodology/approach: Law enforcement drug purchases – predominantly cocaine, methamphetamine, MDMA and heroin – from Australian cryptomarket vendors (n = 38 in 2016/2017) were chemically analysed and matched with cryptomarket listings (n = 23). Descriptive and comparative analyses were conducted. Findings: Almost all samples contained the advertised substance. In most of these cases, drugs were either supplied as-advertised-weight or number, or overweight or number. All listings that quantified purity overestimated the actual purity. There was no consistent relationship between advertised purity terms and actual purity. Across the six listings purchased from multiple times, repeat purchases from the same listing varied in purity, sometimes drastically, with wide variation detected on listings purchased from only one month apart. Research limitations/implications: In this data set, cryptomarket listings were mostly accurate, but the system was far from perfect, with purity overestimated. A newer, larger, globally representative sample should be obtained to test the applicability of these findings to currently operating cryptomarkets. Originality/value: This paper reports on the largest data set of forensic analysis of drug samples obtained from cryptomarkets, where data about advertised drug strength/dose were obtained

Piloting a classification framework for the types of evidence used in alcohol policymaking.

INTRODUCTION Most studies of alcohol policy have focussed on the role of industry. However, little is known about the evidence base used in alcohol policymaking or policymakers' actions in the field. Here, we mapped the different evidence types used in a case study to construct a classification framework of the evidence types used in alcohol policymaking. METHODS Using a case study from the state-level in Australia, we used content analysis to delineate the evidence types cited across six phases of a policymaking process. We then grouped these types into a higher-level classification framework. We used descriptive statistics to study how the different evidence types were used in the policymaking process. RESULTS Thirty-one evidence types were identified in the case study, across four classes of knowledge: person knowledge, shared knowledge, studied knowledge and practice knowledge. The participating public preferenced studied knowledge. Policymakers preferenced practice knowledge over all other types of knowledge. DISCUSSION AND CONCLUSION The classification framework expands on models of evidence and knowledge used across public health, by mapping new evidence types and proposing an inductive method of classification. The policymakers' preferences found here are in line with theories regarding the alcohol industry's influence on policymaking. The classification framework piloted here can provide a useful tool to examine the evidence base used in decision-making. Further study of evidence types used in policymaking processes can help inform research translation and advocacy efforts to produce healthier alcohol policies

How accurate are drug cryptomarket listings by content, weight, purity and repeat purchase?

Purpose: Drug cryptomarkets increase information available to market actors, which should reduce information asymmetry and increase market efficiency. This study aims to determine whether cryptomarket listings accurately represent the advertised substance, weight or number and purity, and whether there are differences in products purchased from the same listing multiple times. Design/methodology/approach: Law enforcement drug purchases – predominantly cocaine, methamphetamine, MDMA and heroin – from Australian cryptomarket vendors (n = 38 in 2016/2017) were chemically analysed and matched with cryptomarket listings (n = 23). Descriptive and comparative analyses were conducted. Findings: Almost all samples contained the advertised substance. In most of these cases, drugs were either supplied as-advertised-weight or number, or overweight or number. All listings that quantified purity overestimated the actual purity. There was no consistent relationship between advertised purity terms and actual purity. Across the six listings purchased from multiple times, repeat purchases from the same listing varied in purity, sometimes drastically, with wide variation detected on listings purchased from only one month apart. Research limitations/implications: In this data set, cryptomarket listings were mostly accurate, but the system was far from perfect, with purity overestimated. A newer, larger, globally representative sample should be obtained to test the applicability of these findings to currently operating cryptomarkets. Originality/value: This paper reports on the largest data set of forensic analysis of drug samples obtained from cryptomarkets, where data about advertised drug strength/dose were obtained.</p

Routine opioid outcome monitoring in community pharmacy: Pilot implementation study protocol

Increases in opioid use and related harms such as mortality are occurring in many high income countries. Community pharmacists are often in contact with patients at risk of opioid-related harm and represent an ideal point for intervention. Best practice in monitoring opioid-related outcomes involves assessing analgesia, pain functioning, mood, risks and harms associated with opioid use. Community pharmacists are well-placed to undertake these tasks. Objectives: Our pilot study will test the implementation of a computer-facilitated screening and brief intervention (SBI). The SBI will support pharmacist identification of opioid-related problems and provide capacity for brief intervention including verbal reinforcement of tailored information sheets, supply of naloxone and referral back to the opioid prescriber. The SBI utilises software that embeds study procedures into dispensing workflow and assesses opioid outcomes with domains aligned with a widely accepted clinical framework. Methods: We will recruit and train 75 pharmacists from 25 pharmacies to deliver the Routine Opioid Outcome Monitoring (ROOM) SBI. Pharmacists will complete the SBI with up to 500 patients in total (20 per pharmacy). Data will be collected on pharmacists’ knowledge and confidence through pre- and post-intervention online surveys. Data on feasibility, acceptability and implementation outcomes, including naloxone supply, will also be collected. Project impact: Our study will examine changes in pharmacists’ knowledge and confidence to deliver the SBI. Through the implementation pilot, we will establish the feasibility and acceptability of a pharmacist SBI that aims to improve monitoring and clinical management of patients who are prescribed opioids