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Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis.

ABSTRACT: BACKGROUND:Nonmedical prescription psychiatric drug use (NMPDU) is an increasing global health problem, with recent concern focusing on darknet cryptomarkets as sources of procurement. There is a shortage of evidence regarding comparative worldwide NMPDU trends, due in part to data collection difficulties. This problem is particularly marked for non-opioid drugs, particularly those psychiatric drugs which act on the central nervous system (CNS) and have high misuse potential and are associated with high levels of dependency and fatal overdose. This paper therefore has two goals: 1) to report on the kinds of psychiatric prescription drugs available on cryptomarkets, and 2) to use this data to uncover temporal and geographical trends in sales of these products, potentially informing policy regarding NMPDU more generally. METHOD:Digital trace data collected from 31 cryptomarkets in operation between September 2013 and July 2016 was analysed by country of origin descriptively and for trends in the sales for 7 psychiatric drug groupings, based on their main indication or intended use in psychiatric practice. RESULTS:Sedatives (such as diazepam and alprazolam) and CNS stimulants (mainly Adderall, modafinil and methylphenidate) had the greatest share of sales, but usage and trends varied by location. The UK has high and rising levels of sedative sales, whilst the USA has the greatest stimulant sales and increasing sedative rates. Sales of drugs used in the treatment of opioid dependency are also substantial in the USA. The picture is less clear in mainland Europe with high sales levels reported in unexpected Central and Northern European countries. There is evidence of a move towards the more potent sedative alprazolam - already implicated as a source of problematic NMPDU in the USA - in Australia and the UK. Sales of drugs such as antidepressants, antipsychotics, mood stabilisers and antidementia drugs - all drugs with limited abuse potential - were negligible, indicating minimal levels of online cryptomarket procurement for self-medicating mental health problems. CONCLUSION:Predominantly, psychiatric drugs with potent sedative, stimulant or euphoriant effects are sold on cryptomarkets and this varies by country. With some caveats regarding the limitations of cryptomarket digital trace data taken into account, the study of trends of these products sold online over time may offer a novel and increasingly important window onto wider drug purchasing habits.

SUBMITTER: Cunliffe J

PROVIDER: S-EPMC6900283 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis.

Cunliffe Jack J Décary-Hêtu David D Pollak Thomas A TA

The International journal on drug policy 20190214

<h4>Background</h4>Nonmedical prescription psychiatric drug use (NMPDU) is an increasing global health problem, with recent concern focusing on darknet cryptomarkets as sources of procurement. There is a shortage of evidence regarding comparative worldwide NMPDU trends, due in part to data collection difficulties. This problem is particularly marked for non-opioid drugs, particularly those psychiatric drugs which act on the central nervous system (CNS) and have high misuse potential and are asso ...[more]

PMID: 30772109

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Project description:ImportanceBetween 1997 and 2017, the United States saw increases in nonmedical prescription opioid use and its consequences, as well as changes in marijuana policies. Ecological-level research hypothesized that medical marijuana legalization may reduce prescription opioid use by allowing medical marijuana as an alternative.ObjectivesTo investigate the association of state-level medical marijuana law enactment with individual-level nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users and to determine whether these outcomes varied by age and racial/ethnic groups.Design, setting, and participantsThis cross-sectional study used restricted data on 627 000 individuals aged 12 years and older from the 2004 to 2014 National Survey on Drug Use and Health, a population-based survey representative of the civilian population of the United States. Analyses were completed from March 2018 to May 2018.ExposuresTime-varying indicator of state-level medical marijuana law enactment (0 = never law enactment, 1 = before law enactment, and 2 = after law enactment).Main outcomes and measuresPast-year nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users. Odds ratios of nonmedical prescription opioid use and prescription opioid use disorder comparing the period before and after law enactment were presented overall, by age and racial/ethnic group, and adjusted for individual- and state-level confounders.ResultsThe study sample included 627 000 participants (51.51% female; 9.88% aged 12-17 years, 13.30% aged 18-25 years, 14.30% aged 26-34 years, 25.02% aged 35-49 years, and 37.50% aged ≥50 years; the racial/ethnic distribution was 66.97% non-Hispanic white, 11.83% non-Hispanic black, 14.47% Hispanic, and 6.73% other). Screening and interview response rates were 82% to 91% and 71% to 77%, respectively. Overall, there were small changes in nonmedical prescription opioid use prevalence after medical marijuana law enactment (4.32% to 4.86%; adjusted odds ratio, 1.13; 95% CI, 1.06-1.20). Prescription opioid use disorder prevalence among prescription opioid users decreased slightly after law enactment, but the change was not statistically significant (15.41% to 14.76%; adjusted odds ratio, 0.95; 95% CI, 0.81-1.11). Outcomes were similar when stratified by age and race/ethnicity.Conclusions and relevanceThis study found little evidence of an association between medical marijuana law enactment and nonmedical prescription opioid use or prescription opioid use disorder among prescription opioid users. Further research should disentangle the potential mechanisms through which medical marijuana laws may reduce opioid-related harm.

Project description:BackgroundThe availability of central nervous system stimulants has risen in recent years, along with increased dispensing of stimulants for treatment of, for example, parent-reported attention-deficit/hyperactivity disorder in children and new diagnoses during adulthood. Typologies of drug use, as has been done with opioids, fail to include a sufficient range of behavioral factors to contextualize person-centric circumstances surrounding drug use. Understanding these patterns across drug classes would bring public health and regulatory practices toward precision public health.ObjectiveThe objective of this study was to quantitatively delineate the unique behavioral profiles of adults who currently nonmedically use stimulants and opioids using a latent class analysis and to contrast the differences in findings by class. We further evaluated whether the subgroups identified were associated with an increased Drug Abuse Screening Test-10 (DAST-10) score, which is an indicator of average problematic drug use.MethodsThis study used a national cross-sectional web-based survey, using 3 survey launches from 2019 to 2020 (before the COVID-19 pandemic). Data from adults who reported nonmedical use of prescription stimulants (n=2083) or prescription opioids (n=6127) in the last 12 months were analyzed. A weighted latent class analysis was used to identify the patterns of use. Drug types, motivations, and behaviors were factors in the model, which characterized unique classes of behavior.ResultsFive stimulant nonmedical use classes were identified: amphetamine self-medication, network-sourced stimulant for alertness, nonamphetamine performance use, recreational use, and nondiscriminatory behaviors. The drug used nonmedically, acquisition through a friend or family member, and use to get high were strong differentiators among the stimulant classes. The latter 4 classes had significantly higher DAST-10 scores than amphetamine self-medication (P<.001). In addition, 4 opioid nonmedical use classes were identified: moderate pain with low mental health burden, high pain with higher mental health burden, risky behaviors with diverse motivations, and nondiscriminatory behaviors. There was a progressive and significant increase in DAST-10 scores across classes (P<.001). The potency of the opioid, pain history, the routes of administration, and psychoactive effect behaviors were strong differentiators among the opioid classes.ConclusionsA more precise understanding of how behaviors tend to co-occur would improve efficacy and efficiency in developing interventions and supporting the overall health of those who use drugs, and it would improve communication with, and connection to, those at risk for severe drug outcomes.

Project description:ImportanceThere is concern that nonmedical prescription opioid use is associated with an increased risk of later heroin use initiation in adolescents, but to our knowledge, longitudinal data addressing this topic are lacking.ObjectiveTo determine whether nonmedical prescription opioid use is associated with subsequent initiation of heroin use in adolescents.Design, setting, and participantsThis prospective longitudinal cohort study conducted in 10 high schools in Los Angeles, California, administered 8 semiannual surveys from 9th through 12th grade that assessed nonmedical prescription opioid use, heroin use, and other factors from October 2013 to July 2017. Students were baseline never users of heroin recruited through convenience sampling. Cox regression models tested nonmedical prescription opioid use statuses at survey waves 1 through 7 as a time-varying and time-lagged regressor and subsequent heroin use initiation across waves 2 to 8 as the outcome.ExposuresSelf-reported nonmedical prescription opioid use (past 30-day [current] use vs past 6-month [prior] use without past 30-day use vs no past 6-month use) at each wave from 1 to 7.Main outcomes and measuresSelf-reported heroin use initiation (yes/no) during waves 2 to 8.ResultsOf 3298 participants, 1775 (53.9%) were adolescent girls, 1563 (48.3%) were Hispanic, 548 (17.0%) were Asian, 155 (4.8%) were African American, 529 (16.4%) were non-Hispanic white, and 220 (6.8%) were multiracial. Among baseline never users of heroin in ninth grade with valid data (3298 [97% of cohort enrollees]; mean [SD] age, 14.6 [0.4] years), the number of individuals with outcome data available at each follow-up ranged from 2987 (90.6%) to 3200 (97.0%). The mean per-wave prevalence of prior and current nonmedical prescription opioid use from waves 1 to 7 was 1.9% and 2.7%, respectively. Seventy students (2.1%) initiated heroin use during waves 2 to 8. Prior vs no (hazard ratio, 3.59; 95% CI, 2.14-6.01; P < .001) and current vs no (hazard ratio, 4.37; 95% CI, 2.80-6.81; P < .001) nonmedical prescription opioid use were positively associated with subsequent heroin use initiation. For no, prior, and current nonmedical prescription opioid use statuses at waves 1 to 7, the estimated cumulative probabilities of subsequent heroin use initiation by wave 8 (42-month follow-up) were 1.7%, 10.7%, and 13.1%, respectively. In covariate-adjusted models, associations were attenuated but remained statistically significant and current nonmedical prescription opioid use risk estimates were stronger than corresponding associations of nonopioid substance use with subsequent heroin use initiation.Conclusions and relevanceNonmedical prescription opioid use was prospectively associated with subsequent heroin use initiation during 4 years of adolescence among Los Angeles youth. Further research is needed to understand whether this association is causal.

Project description:ObjectiveTo examine whether sources of nonmedical use of prescription drugs (NMUPD) involving anxiolytics, opioids, and stimulants were associated with sociodemographic characteristics, NMUPD characteristics (eg, frequency), and other substance use.MethodNationally representative samples of US high school seniors (N = 18,549) were surveyed by self-administered questionnaires (2009-2016). Design-based latent class analysis and Rao-Scott χ2 tests were used to test associations among sociodemographic characteristics, NMUPD characteristics, other substance use behaviors (eg, binge drinking, cigarette smoking, marijuana use), and NMUPD sources.ResultsApproximately 11.0% of high school seniors reported past-year NMUPD (n = 1,917). A substantial proportion of nonmedical users obtained the prescription drugs from multiple sources (44.2%). Latent class analysis identified 5 subgroups of NMUPD sources (friend/relative sources, friend/purchased sources, own leftover prescription, multiple sources, and other sources). Nonmedical users who obtained prescription drugs from friend/purchased sources were more likely to be adolescent boys, whereas those who used their own leftover prescriptions were more likely to be adolescent girls. Nonmedical users who obtained prescription drugs from multiple sources were more involved in substance use. In contrast, adolescent nonmedical users who used their own leftover prescriptions were less involved in substance use.ConclusionGrowing evidence indicates that different NMUPD sources are associated with different substance use behaviors. All NMUPD sources should be discouraged, because they place individuals, families, and communities at risk. Patients and their families should receive education on how to manage and properly dispose of controlled medications to avoid diversion into the community. Prescribers are encouraged to check prescription monitoring programs and screen adolescents for substance use/misuse when prescribing controlled medications.

Dataset Information

Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis.

Publications

Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis.

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