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Background: There has been a rise in the illicit use of pharmaceutical opioids ("pain pills") in the United States. Conducted with young adult non-medical users of pharmaceutical opioids, this study uses qualitative methods and cultural consensus analysis to describe risk perceptions associated with pharmaceutical opioids and to determine patterns of cultural sharing and intra-cultural variation of these views.Methods: The qualitative sub-sample (n=47) was selected from a larger sample of 396 young adults (18-23 years old), who were participating in a natural history study of illicit pharmaceutical opioid use. Qualitative life history interviews, drug ranking task, and cultural consensus analysis were used to elicit participant views about risks and harms associated with pain pills and other drugs, as well as alcohol and tobacco.Results: Cultural consensus analysis revealed that the participants shared a single cultural model of drug risks, but the level of agreement decreased with the increasing range of drugs ever used. Further, those with more extensive drug use histories differed from less "experienced" users in their views about OxyContin and some other drugs. Overall, pain pills were viewed as addicting and potentially deadly substances, but these properties were linked to the patterns and methods of use, as well as characteristics of an individual user. Further, risks associated with pharmaceutical opioids were further curtailed because they "came from the doctor," and thus had a legitimate aspect to their use.Conclusions: This study highlights potential problems with universal approaches to substance use prevention and intervention among young people since such approaches ignore the fact that substance use education messages may be experienced differently depending on an individual's drug use history and his/her perceptions of drug risks. Findings reported here may be useful in the development of prevention and intervention programs aimed at reducing the harm associated with illicit use of pain pills. [ABSTRACT FROM AUTHOR]

Background: In consideration of rising opioid-stimulant deaths in the United States, this study explored rates of naloxone administration and survival in suspected opioid overdoses with, versus without, stimulants co-involved., Methods: The study analyzed 26,635 suspected opioid-involved overdoses recorded by law enforcement/first-responders in the Pennsylvania Overdose Information Network in 63 Pennsylvania counties, January 2018-July 2024. All measures, including suspected drug involvement, were based on first-responder assessment/report. Relative frequencies and chi-square tests were first used to compare suspected opioid overdoses with, versus without, stimulants (cocaine or methamphetamine) co-involved. Next, mediation analyses tested naloxone administration as a mediator in the association between stimulant co-involvement (in opioid overdoses) and survival., Results: Naloxone was reportedly administered in 72.2 % of the suspected opioid-no-cocaine overdoses, compared to 55.1 % of the opioid-cocaine-involved overdoses, and 72.1 % of the opioid-no-methamphetamine overdoses vs. 52.4 % of the opioid-methamphetamine-involved overdoses. With respect to survival rates, 18.0 % of the suspected opioid-no-cocaine overdoses ended in death, compared to 41.3 % of the opioid-cocaine overdoses; 18.1 % of the opioid-no-methamphetamine overdoses ended in death, versus 42.9 % of the opioid-methamphetamine overdoses. In mediation analyses (adjusted for demographics, county, year, and other drug co-involvement), naloxone administration mediated 38.7 % (95 % Confidence Interval [CI], 31.3-46.0 %) of the association between suspected cocaine co-involvement and survival and 39.2 % (95 % CI, 31.3-47.1 %) of the association between suspected methamphetamine co-involvement and survival., Conclusions: Among suspected opioid overdoses recorded in the Pennsylvania Overdose Information Network, stimulant co-involvement was associated with lower naloxone administration and higher fatality, with naloxone partially mediating the association between stimulant co-involvement and death., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Frank LoVecchio reports a relationship with AbbVie (antibiotics only) that includes: speaking and lecture fees. Abenaa Jones reports a relationship with National Institute on Drug Abuse that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The rate of medical cannabis use has increased in parallel with the number of states legalizing its use. Parkinson's disease (PD) patients are of particular concern due to their higher cannabis use rate than in the general US population (25-40 % PD patient cannabis users vs. ∼18 % in the general population), as well as their susceptibility to environmental contaminants in cannabis, including pesticides, toxic elements, solvents, microbes, and mycotoxins. In order to address the complex nature of this industry, we examined the changes in PD-related qualifying conditions in the U.S. from 2019 to 2023. We also conducted an online survey to gain insight into the knowledge, risk perceptions, and opinions regarding medical cannabis and contamination issues from physicians who treated PD patients. The number of states including PD-related qualifying conditions increased over the past 5 years from 28 to 36 states. These conditions included PD (increasing from 14 to 16 states), muscle spasms (14 to 24), anxiety (1 to 5), and pain (17 to 35). State-by-state comparisons revealed high variability in the language used to describe the different qualifying conditions. Online surveys were sent out to 45 neurologists and movement disorder specialists who primarily treated PD patients. The response rate was 44 % from nine states (AZ, CA, FL, MA, MN, WI, PA, IL, and NM). When asked if they were aware of any contaminants in cannabis products, we found that 65 % of the physicians were unaware of any contaminants commonly found in cannabis and only 25 %, 15 %, and 15 % of them were aware of pesticide, toxic element, and solvent contaminants, respectively. In their free-text opinion response on the health impact of cannabis-borne contaminants, "long-term effect" (35 %) and "comorbidities and PD prognosis" (40 %) were identified as the two most common themes. These results point to the need for further regulatory deliberation regarding risks and susceptibility to cannabis contaminants. Additionally, education is needed to inform physicians on cannabis safety issues. Further research will identify the implementation strategies to reduce contaminant exposure and protect patient health., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background: Opioid and substance misuse has become a widespread problem in the United States, leading to the "opioid crisis." The relationship between substance misuse and mental health has been extensively studied, with one possible relationship being that substance misuse causes poor mental health. However, the lack of evidence on the relationship has resulted in opioids being largely inaccessible through legal means., Objectives: This study aims to analyze social media posts related to substance use and opioids being sold through cryptomarket listings. The study aims to use state-of-the-art deep learning models to generate sentiment and emotion from social media posts to understand users' perceptions of social media. The study also aims to investigate questions such as which synthetic opioids people are optimistic, neutral, or negative about; what kind of drugs induced fear and sorrow; what kind of drugs people love or are thankful about; which drugs people think negatively about; and which opioids cause little to no sentimental reaction., Methods: The study used the drug abuse ontology and state-of-the-art deep learning models, including knowledge-aware Bidirectional Encoder Representations From Transformers-based models, to generate sentiment and emotion from social media posts related to substance use and opioids being sold through cryptomarket listings. The study crawled cryptomarket data and extracted posts for fentanyl, fentanyl analogs, and other novel synthetic opioids. The study performed topic analysis associated with the generated sentiments and emotions to understand which topics correlate with people's responses to various drugs. Additionally, the study analyzed time-aware neural models built on these features while considering historical sentiment and emotional activity of posts related to a drug., Results: The study found that the most effective model performed well (statistically significant, with a macro-F1-score of 82.12 and recall of 83.58) in identifying substance use disorder. The study also found that there were varying levels of sentiment and emotion associated with different synthetic opioids, with some drugs eliciting more positive or negative responses than others. The study identified topics that correlated with people's responses to various drugs, such as pain relief, addiction, and withdrawal symptoms., Conclusions: The study provides insight into users' perceptions of synthetic opioids based on sentiment and emotion expressed in social media posts. The study's findings can be used to inform interventions and policies aimed at reducing substance misuse and addressing the opioid crisis. The study demonstrates the potential of deep learning models for analyzing social media data to gain insights into public health issues., (© Usha Lokala, Orchid Chetia Phukan, Triyasha Ghosh Dastidar, Francois Lamy, Raminta Daniulaityte, Amit Sheth. Originally published in JMIRx Med (https://med.jmirx.org).)

Importance: Xylazine is increasingly reported in street drugs and fatal overdoses in the US, yet state-level data are limited, hampering local public health responses., Objective: To gather available state-level data on xylazine involvement in overdose deaths and in forensic drug reports., Design, Setting, and Participants: This cross-sectional study was a secondary analysis of 2019 to 2022 data from the National Forensic Laboratory Information System (NFLIS), National Center for Health Statistics, and individual states' medical examiner or public health agency reports. Data were analyzed from August to October 2023., Exposure: State., Main Outcomes and Measures: Yearly xylazine-related overdose deaths per 100 000 residents; xylazine NFLIS drug reports, both per 100 000 residents and as a percentage of all NFLIS drug reports (from samples of drugs seized by law enforcement and analyzed by NFLIS-participating laboratories)., Results: A total of 63 state-years were included in analyses of mortality rates, while 204 state-years were included in analyses of NFLIS reports. According to the publicly available data compiled in this study, at least 43 states reported at least 1 xylazine-related overdose death from 2019 to 2022, yet yearly totals of xylazine-related deaths were available for only 21 states. Of states with data available, xylazine-involved overdose death rates were highest in Vermont (10.5 per 100 000 residents) and Connecticut (9.8 per 100 000 residents) in 2022. In 2019, 16 states had zero xylazine reports included in NFLIS reports; in 2022, only 2 states had zero xylazine reports and all but 3 states had recorded an increase in xylazine's representation in NFLIS reports. In 2022, xylazine represented 16.17% of all NFLIS reports in Delaware and between 5.95% and 7.00% of NFLIS reports in Connecticut, Maryland, District of Columbia, New Jersey, and Rhode Island, yet less than 1.0% of NFLIS reports in 35 different states., Conclusions and Relevance: In this cross-sectional study of publicly available data on fatal overdoses and drugs analyzed by forensic laboratories, xylazine's reported presence in overdose deaths and forensic reports was concentrated in the eastern US yet extended across the country to encompass nearly all states. In spite of xylazine's geographic reach, yearly state-level numbers of xylazine-related overdose deaths were publicly available for less than half of all states.

The purpose of this qualitative study is to characterize the impacts of the COVID-19 pandemic on drug use experiences among persons who use illicit opioids (PWUO) in Arizona. Between 12/2020 and 05/2021, interviews were conducted via Zoom with 22 PWUO from across Arizona. Participants were recruited through Craigslist and social media ads, referrals by a local harm reduction organization, and other participants. The interviews were transcribed and analyzed using NVivo. Participants were 25-51 years of age, 36% were female, and 55% non-Hispanic White. Most reported past month use of heroin, and/or counterfeit (pressed) non-pharmaceutical fentanyl (NPF) pills. Nearly all reported changes in their drug use during the pandemic. Participants discussed profound negative impacts of social isolation with escalating mental health problems, boredom, and ease of hiding drug use from others, leading to increases in drug use. Loss of daily routines, employment difficulties, and challenges of accessing treatment due to COVID-19 restrictions were also driving factors for increased drug use. The growing availability of NPF pills during the pandemic led many individuals to transition from heroin to more frequent NPF pill use. The results emphasize the need for quality behavioral care services with an increased focus on economic and social support systems.

We understand the current crisis of overdose deaths to be driven by widespread opioid use, characterized by distinct 'waves' of drug use. The first wave was driven by prescription opioids, the second by heroin, and the third by illicit, non-pharmaceutical fentanyl and fentanyl analogues (henceforth, fentanyl). The purpose of this study is to describe opioid initiation within each of the three waves from the perspective of people who use illicit opioids, with a focus on emerging pathways into fentanyl use. The authors recruited sixty people reporting past-30-day illicit opioid use in Dayton, Ohio. Participants completed a brief survey and a semi-structured in-depth qualitative interview, conducted from March to November 2020 with a total of 13 in-person and 47 virtual interviews. The qualitative interviews were transcribed in their entirety and analyzed thematically using NVivo 12. We noted supply-side changes as influencing trajectories in all three waves. However, we also noted differences in the experiences of prescription opioid and heroin initiation, with these trajectories influenced by pharmacological effects, pain management, curiosity, intergenerational use, pricing, and peers. In comparison, most participants were unaware that they were initiating fentanyl, and many reported overdosing with their first use of fentanyl. We identified a trajectory into fentanyl with limited to no prior heroin use among a few participants. The increased risk of overdose with initiation into fentanyl use further emphasizes the need for an expansion of naloxone distribution and the implementation of more comprehensive measures, such as overdose prevention centers, drug testing, and a safer supply. Further research on the dynamics of the ongoing overdose death crisis in the era of fentanyl and the 4th wave of the overdose crisis is critical in developing responsive prevention and intervention strategies., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

From 2018 to 2021, seizures of counterfeit oxycodone pills containing non-pharmaceutical fentanyl or other novel synthetic opioids increased significantly contributing to continuing increases in overdose mortality in Northern America. Evidence suggests that counterfeit pills are distributed through cryptomarkets. This article presents data regarding the availability and characteristics of oxycodone pills advertised on one major cryptomarket between January and March 2022. Collected data were processed using a dedicated Named Entity Recognition algorithm to identify oxycodone listings and categorized them as either counterfeit or pharmaceutical. Frequency of listings, average number of pills advertised, average prices per milligram, number of sales, and geographic indicators of shipment origin and destination were analyzed. In total, 2,665 listings were identified as oxycodone. 48.2% (1,285/2,665) of these listings were categorized as counterfeit oxycodone, advertising a total of 652,699 pills (93,242.7 pills per datapoint) offered at a lower price than pharmaceutical pills. Our data indicate the presence of a large volume of counterfeit oxycodone pills both in retail- and wholesale-level amounts mostly targeting US and Canadian customers. These exploratory findings call for more research to develop epidemiological surveillance systems to track counterfeit pill and other drug availability on the Dark web environment.

Using the Arizona State Unintentional Drug Overdose Reporting System (AZ-SUDORS), the study aims to identify the social and drug characteristics of illicitly manufactured fentanyl (IMF)-related overdose deaths. The data include drug overdose deaths from July 1, 2019 to June 30, 2020. Decedents were categorized into four groups by types of opioids detected: (1) IMF-positive; (2) heroin-positive (negative for IMF); (3) pharmaceutical opioid-positive (negative for heroin or IMF); (4) nonopioid. Bivariate statistics were used to compare differences between IMF and other groups. Among 2,029 decedents, 77.8% tested positive for opioids. The IMF group included 57.9%, the heroin group included 9.5%, the pharmaceutical opioid group 10.5%, and the nonopioid group 22.2%. The IMF group was younger (mean age 35.0), more likely to be from a large urban area (78.2%), and with a greater proportion of ethnic/racial minorities (48.6%), compared to the other three groups. The IMF group was less likely to test positive for methamphetamine (24.9%), compared to heroin (63.7%) or pharmaceutical opioid groups (34.0%), but more likely to test positive for cannabis (31.3%), compared to the other three groups. Our data show disproportionate IMF impacts on younger persons and ethnic minorities. Interventions need to be tailored to account for distinct psychosocial profiles associated with IMF use.

Background: This study examined racial/ethnic and educational disparities in US synthetic opioid overdose mortality East and West of the Mississippi River., Methods: Using restricted-access 2018-2021 mortality data from the Centers for Disease Control and Prevention and population estimates from the American Community Survey, age-standardized rate ratios (SRRs) and 95% Confidence Intervals (CIs) were used to compare rates of synthetic opioid mortality by race/ethnicity and educational attainment level in the regions East and West of the Mississippi River., Results: Racial/ethnic disparities in synthetic opioid mortality rates, relative to the Non-Hispanic (NH) White population, were observed in the NH Black (SRR, 1.5 [95% CI, 1.5-1.6]) and NH American Indian/Alaska Native (SRR, 2.1 [95% CI, 1.9-2.2]) populations in the West, and the Puerto Rican (SRR, 1.3 [95% CI, 1.3-1.3]) and NH American Indian/Alaska Native (SRR, 1.5 [95% CI, 1.4-1.6]) populations in the East. Relative to those with a Bachelor's degree or higher: in the West, the synthetic opioid mortality rate was more than seven times as high for those with a high school diploma only (SRR 7.7 [95% CI, 7.4-8.0]), and in the East, approximately thirteen times as high for those with a high school diploma only (SRR, 13.0 [95% CI, 12.7-13.3]) or less than a high school diploma (SRR, 13.3 [95% CI, 13.0-13.7])., Conclusion: Disparities in rates of synthetic opioid mortality differ in the eastern and western US, supporting tailored responses within each region., Competing Interests: Declaration of Competing Interest No conflict declared., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: There are growing concerns about illicitly manufactured fentanyl (IMF) contamination of methamphetamine. This study aims to characterize the lay views and experiences with IMF-contaminated methamphetamine (IMF/meth) and identify participants with unknown IMF exposures through urine toxicology analysis., Methods: Between December-2019 and November-2021, structured interviews were conducted with 91 individuals who reported past 30-day use of methamphetamine and resided in Dayton, Ohio, USA. Lab-based urine toxicology analyses were conducted to identify fentanyl/analogs, methamphetamine, and other drugs. Bivariate analyses were conducted to identify characteristics associated with attitudes and experiences with IMF/meth, and unknown IMF exposures., Results: The majority (95.6%) of the study participants were non-Hispanic white, and 52.7% were female. Past 30-day use of methamphetamine was reported on a mean of 18.7 (SD 9.1) days, and 62.6% also reported past 30-day use of heroin/IMF. Most (76.9%) had a history of an unintentional drug-related overdose, but 38.5% rated their current risk for an opioid overdose as none. Besides fentanyl (71.9%), toxicology analysis identified nine fentanyl analogs/metabolites (e.g., 42.7% acetyl fentanyl, 19.0% fluorofentanyl, 5.6% carfentanil), and 12.4% tested positive for Xylazine. The majority (71.4%) believed that IMF/meth was common, and 59.3% reported prior exposures to IMF/meth. 11.2% tested positive for IMF but reported no past 30-day heroin/IMF use (unknown exposure to IMF). Views that IMF/meth was common showed association with homelessness (p = 0.04), prior overdose (p = 0.028), and greater perceived risk of opioid overdose (p = 0.019). Self-reported exposure to IMF/meth was associated with homelessness (p = 0.007) and obtaining take-home naloxone (p = 0.025). Individuals with unknown IMF exposure (test positive for IMF, no reported past 30-day heroin/IMF use) were older (49.9 vs. 41.1 years, p < 0.01), and reported more frequent past 30-day use of methamphetamine (24.4 vs. 18.0 days, p < 0.05). They indicated lower perceived risk of opioid overdose (0.1 vs. 1.9, scale from 0 = "none" to 4 = "high," p < 0.001)., Discussion: This study suggests a need for targeted interventions for people who use methamphetamine and expansion of drug checking and other harm reduction services., (© 2023. The Author(s).)

Introduction: With the increasing use of non-prescribed buprenorphine (NPB), we need more data to identify the longitudinal patterns of NPB use. The goal of this natural history study is to characterize heterogeneity in trajectories of NPB, other opioid use, and participation in medication for opioid disorder (MOUD) treatment among a community-recruited sample of individuals with current opioid use disorder (OUD)., Methods: The study recruited a community-based sample of 357 individuals with OUD who used NPB in the past 6 months in Ohio, United States, for baseline and follow-up assessments (every 6 months for 2 years) of drug use, treatment participation, and other health and psychosocial characteristics. The study used multiple imputation to handle missing data. We used a multi-trajectory latent class growth analysis (MT-LCGA) to find salient groupings of participants based on the trajectories of NPB, other opioid use, and treatment participation., Results: Over time, NPB use frequency declined from a mean of 14.6 % of days at baseline to 3.6 % of days at 24-month follow-up along with declines in heroin/fentanyl (56.4 % to 23.6 % of days) and non-prescribed pharmaceutical opioid (NPPO) use (11.6 % to 1.5 % of days). Participation in MOUD treatment increased from a mean of 17.0 % of days at baseline to 52.4 % of days at 24 months. MT-LCGA identified a 6-class model. All six classes showed declines in NPB use. Class 1 (28 %) was characterized by high and increasing MOUD treatment utilization. Class 2 (21 %) showed sustained high levels of heroin/fentanyl use and had the lowest levels of NPB use (2.2 % of days) at baseline. Class 3 (3 %) was characterized as the primary NPPO use group. Class 4 (5 %) transitioned from high levels of NPB use to increased MOUD treatment utilization. It had the highest levels of NPB use at baseline (average of 80.7 % of days) that decreased to an average of 12.9 % of days at 24 months. Class 5 (16 %) showed transition from high levels of heroin/fentanyl use to increased MOUD treatment utilization. Class 6 (27 %) showed decreased heroin/fentanyl use over time and low MOUD treatment utilization. Classes showed varying levels of improvement in psychosocial functioning, polydrug use, and overdose risks., Conclusion: Overall, our findings suggest that NPB use was generally self-limiting with individuals reducing their use over time as some engage in greater utilization of MOUD treatment. A need exists for continuing improvements in MOUD treatment access and retention., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends., Objective: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web forum data Prescription Drug Abuse Online Surveillance; analyzing patterns and trends of cannabis product use in the context of evolving cannabis legalization policies in the United States through analysis of Twitter and web forum data (eDrugTrends); assessing trends in the availability of novel synthetic opioids through the analysis of cryptomarket data (eDarkTrends); and analyzing COVID-19 pandemic trends in social media data related to 13 states in the United States as per Mental Health America reports., Methods: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontology, reusing existing knowledge, enumerating important terms in ontology, defining the classes, their properties and creating instances of the classes. The quality of the ontology was evaluated using a set of tools and best practices recognized by the semantic web community and the artificial intelligence community that engage in natural language processing., Results: The current version of the DAO comprises 315 classes, 31 relationships, and 814 instances among the classes. The ontology is flexible and can easily accommodate new concepts. The integration of the ontology with machine learning algorithms dramatically decreased the false alarm rate by adding external knowledge to the machine learning process. The ontology is recurrently updated to capture evolving concepts in different contexts and applied to analyze data related to social media and dark web marketplaces., Conclusions: The DAO provides a powerful framework and a useful resource that can be expanded and adapted to a wide range of substance use and mental health domains to help advance big data analytics of web-based data for substance use epidemiology research., (©Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 23.12.2022.)

This article uses participatory photography to explore the relationships animating efforts towards recovery from opioid use disorder (OUD) in the Dayton, Ohio area, an epicenter of illicit opioid use and overdose death. A photo-elicitation project was conducted with thirteen people who met the DSM-5 criteria for OUD. Photographs were used as prompts during qualitative interviews, which were thematically analyzed. Analysis of both visual and textual data demonstrated the ways in which recovery became an unfolding process of calculation as participants made strategic choices to navigate relations and encounters with things, people, and places. Relationships across each of these domains could, under some circumstances, serve as supports or motivators in the recovery process, but, in alternate settings, be experienced as "triggers" prompting a resumption of problematic drug use or, at the very least, a reckoning with the feelings and emotions associated with painful or problematic aspects of personal histories and drug use experiences. Findings highlight the importance of understanding recovery as a calibration of the ambiguous relations animating experiences of everyday life. We argue for continued emphasis on recovery as an active performance and ongoing practice of calculation-of risks and benefits, of supports and triggers, of gratification and heartbreak-rather than a goal or static state., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Worsening of the overdose crisis in the USA has been linked to the continuing proliferation of non-pharmaceutical fentanyl (NPF). The recent wave of NPF spread in the USA has been fueled by an increased presence of counterfeit pills that contain NPF. This qualitative study aims to characterize the motivation and practices of counterfeit NPF pill initiation and use among individuals using illicit opioids in Arizona., Methods: Between October 2020 and May 2021, semi-structured interviews were conducted with 22 individuals meeting the following eligibility criteria: (1) 18 years or older; (2) residence in Arizona; and (3) use of illicit opioids in the past 30 days and/or opioid use disorder treatment in the past 12 months. Participants were recruited through referrals by a harm reduction organization, craigslist ads, and referrals by other participants. Interviews were conducted virtually via Zoom. Qualitative interviews were transcribed and analyzed thematically using NVivo., Results: Out of 22 participants, 64% were male, and 45% were ethnic minorities. Age ranged between 25 and 51 years old. Participants noted significant recent increases in the availability of counterfeit NPF pills ("blues," "dirty oxys") that were most commonly used by smoking. The majority indicated first trying NPF pills in the past year, and the first use often occurred in situations of reduced access to heroin or pharmaceutical opioids. Participant decisions to switch over to more frequent NPF pill use or to maintain some levels of heroin use were shaped by local drug availability trends and personal experiences with NPF effects. They were also influenced by conflicting views of social acceptability of pharmaceutical-like drugs, perceived harms of NPF in terms of overdose risks and increased difficulty of quitting, and perceived benefits of switching to the non-injection route of opioid administration (e.g., from injecting heroin to smoking NPF pills)., Conclusion: Our findings highlight the need for the implementation of novel policy, treatment, and harm reduction approaches to address the growing unpredictability of drug supply and NPF pill-specific risks, attitudes, and behaviors., (© 2022. The Author(s).)

Introduction: Non-pharmaceutical fentanyl and related drugs (NPF) have contributed to increases in drug-related overdose mortality in the U.S. More data are needed to track the shifting composition of fentanyl-containing drug mixtures. The key aims of the study are to characterize the crime lab data from Montgomery County, Ohio on the increased cases of seized drugs containing mixtures of NPF and tramadol., Methods: Crime lab data on seized drugs in Montgomery County, Ohio (2015 - 2020) were analyzed to extract information on cases that tested positive for NPF and tramadol. Descriptive statistics are provided to characterize NPF/tramadol mixtures in terms of the quantity, weight, form of the drug seized (powder, tablet, capsule, residue), and the types of fentanyl analogs and other drugs identified., Results: In December 2017, the first case of NPF/tramadol mixture was identified in the amount of 0.2 g. Sub-sequently, cases containing NPF/tramadol increased significantly to 149 cases in 2018, 102 in 2019, and 134 in 2020. The total yearly amounts of seized NPF/tramadol mixtures increased to 373.27 g in 2018, 2,601.82 g in 2019, and 13,487.62 g in 2020. The majority (72.6%) of the cases were in powder form. There were 15 other drugs identified along with fentanyl with tramadol mixtures, including heroin (38.8%), 5.7% cocaine (5.7%), and methamphetamine (4.9%)., Conclusions: The addition of tramadol to NPF may be viewed as a harm mitigation strategy but contributes to the overall unpredictability of the illicit drug supply. According to Ohio legal statutes, identification of schedule IV drugs such as tramadol with fentanyl (schedule II) may provide a reduction in drug-related charges from a felony to a misdemeanor. More research is needed to characterize potential sources of tramadol in NPF-containing drugs., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Aim: Methamphetamine use has increased among individuals with opioid use disorder. The key aims of this study are to detail and contextualise lay knowledge, attitudes, and behaviours related to methamphetamine use in relation to opioid overdose risks in an area dominated by non-pharmaceutical fentanyl-type drugs (NPF)., Methods: The study recruited 41 individuals in Dayton, Ohio, who reported past 30-day use of methamphetamine and heroin/fentanyl. Interviews included structured and qualitative questions. Urine toxicology analysis was conducted to identify NPFs and other drugs. Open-ended interview sections were audio-recorded, transcribed, and analysed qualitatively using NVivo., Results: The mean age was 38.3 years, 51% were female, and 100% non-Hispanic white. Participants described an exceedingly unpredictable local opioid market that became saturated with NPFs. The sample tested positive for 10 NPFs, including fentanyl (100%), acetyl fentanyl (61%), tetrahydrofuran fentanyl (29%), and carfentanil (12%). Most participants believed that methamphetamine could help prevent and/or reverse an opioid-related overdose. Nearly half had personally used it to help manage overdose risks related to NPF. These beliefs were embedded in a lay understanding of how methamphetamine works to stimulate the cardiovascular system. They were acted upon in the context of last resort situations that were determined by a lack of immediate access to naloxone, ambiguities surrounding overdose symptomatology, and easy access to plentiful and inexpensive methamphetamine., Conclusion: Lay efforts to rely on methamphetamine to manage NPF-related overdose risks highlight the need for a continuing expansion of take-home-naloxone programs and implementation of other novel harm reduction approaches in communities affected by NPFs., Competing Interests: Declarations of Interest All authors declare that there are no conflicts of interest., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Novel synthetic opioids are fueling the overdose deaths epidemic in North America.Recently, non-fentanyl novel synthetic opioids have emerged in forensic toxicological results. Cryptomarkets have become important platforms of distribution for illicit substances. This article presents the data concerning the availability trends of novel non-fentanyl synthetic opioids listed on one cryptomarket., Methods: Listings from the EmpireMarket cryptomarket "Opiates" section were collected between June 2020 and August 2020. Collected data were processed using eDarkTrends Named Entity Recognition algorithm to identify novel synthetic opioids, and to analyze their availability trends in terms of frequency of listings, available average weights, average prices, quantity sold, and geographic indicators of shipment origin and destination information., Results: 35,196 opioid-related listings were collected through 12 crawling sessions. 17 nonfentanyl novel synthetic opioids were identified in 2.9 % of the collected listings for an average of 9.2 kg of substance available at each data point. 587 items advertised as non-fentanyl novel synthetic opioids were sold on EmpireMarket for a total weight of between 858 g and 2.7 kg during the study period. 45.5 % of these listings were advertised as shipped from China., Conclusions: Fourteen of the 17 non-fentanyl novel synthetic opioids were identified for the first time on one large cryptomarket suggesting a shift in terms of novel non-fentanyl synthetic opioids availability. This increased heterogeneity of available novel synthetic opioids could reduce the efficiency of existing overdose prevention strategies. Identification of new opioids underpins the value of cryptomarket data for early warning systems of emerging substance use trends., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This study aims to identify socio-demographic and psychosocial characteristics associated with the suicidal ideation among resettled Bhutanese refugees in the United States. Structured interviews were conducted with 200 resettled Bhutanese refugees in Columbus, Ohio. Multivariable logistic regression analysis was conducted to identify variables associated with suicidal ideation. Most participants were male (59.0%), married (77.9%), 55% reported no formal education, 12% were of Dalit ("lower") caste, and 6.2% reported suicidal ideation. Multivariable logistic regression analysis included four variables that were significant at p < 0.05 in bivariate analyses: caste, post-settlement difficulties, mental health diagnosis, and social support. Higher odds of suicidal ideation were linked to mental health diagnosis [adjusted odds ratio (AOR): 8.7], low social support (AOR: 23.6), and post-settlement difficulties (AOR: 1.4). In the multivariable model, untouchable caste had elevated odds of suicidal ideation but statistically not significant. Culturally competent mental health services are needed to support individuals at risk for suicidal ideation.

With the increasing legalization of medical and recreational use of cannabis, more research is needed to understand the association between depression and consumer behavior related to cannabis consumption. Big social media data has potential to provide deeper insights about these associations to public health analysts. In this interdisciplinary study, we demonstrate the value of incorporating domain-specific knowledge in the learning process to identify the relationships between cannabis use and depression. We develop an end-to-end knowledge infused deep learning framework (Gated-K-BERT) that leverages the pre-trained BERT language representation model and domain-specific declarative knowledge source (Drug Abuse Ontology) to jointly extract entities and their relationship using gated fusion sharing mechanism. Our model is further tailored to provide more focus to the entities mention in the sentence through entity-position aware attention layer, where ontology is used to locate the target entities position. Experimental results show that inclusion of the knowledge-aware attentive representation in association with BERT can extract the cannabis-depression relationship with better coverage in comparison to the state-of-the-art relation extractor., Competing Interests: The authors have declared that no competing interests exist.

Background: Across the U.S., methamphetamine use is expanding among people who use illicit opioids (PWUIO). Motives for methamphetamine use must be contextualized within the experiences of PWUIO, who may use methamphetamine not only to achieve euphoria, but also as a tactic of self-management. The overall aim of this study is to contextualize lay beliefs, practices, and experiences of methamphetamine use as a form of self-treatment of symptoms related to chronic opioid use among PWUIO in the Dayton Metro Area of Southwest Ohio, an epicenter of the ongoing opioid crisis., Methods: This paper draws on two phases of interviews conducted with 38 individuals who use both heroin/fentanyl and methamphetamine. This paper primarily analyzes qualitative data but includes supplementary information from the structured interview component. Qualitative interview sections were transcribed in their entirety and thematically analyzed., Results: Participants described learning about methamphetamine as a tactic to treat opioid withdrawal symptoms through social networks and through personal experimentation. Many participants suggested that methamphetamine was helpful in relieving exhaustion, alleviating some acute physical symptoms of opioid withdrawal, and providing a psychological distraction, although some admitted that methamphetamine use could incur additional health risks. To effectively use methamphetamine as a tactic of self-treatment, participants emphasized the importance of timing and dosing., Discussion: Among PWUIO in the Dayton area, methamphetamine use as a tactic to self-manage opioid withdrawal must be studied in relation to historical and evolving patterns of illicit opioid use and associated risks. More research is needed to understand the long-term health impacts of this emergent practice of polydrug use.

Background: The United States is facing a "triple wave" epidemic fueled by novel synthetic opioids. Cryptomarkets, anonymous marketplaces located on the deep web, play an increasingly important role in the distribution of illicit substances. This article presents the data collected and processed by the eDarkTrends platform concerning the availability trends of novel synthetic opioids listed on one cryptomarket., Methods: Listings from the DreamMarket cryptomarket "Opioids" and "Research Chemicals" sections were collected between March 2018 and January 2019. Collected data were processed using eDarkTrends Named Entity Recognition algorithm to identify opioid drugs, and to analyze their availability trends in terms of frequency of listings, available average weights, average prices, and geographic indicators of shipment origin and destination information., Results: 95,011 opioid-related listings were collected through 26 crawling sessions. 33 novel synthetic opioids were identified in 3.3 % of the collected listings. 44.7 % of these listings advertised fentanyl (pharmaceutical and non-pharmaceutical) or fentanyl analogs for an average of 2.8 kgs per crawl. "Synthetic heroin" accounted for 33.2 % of novel synthetic opioid listings for an average 1.1 kgs per crawl with 97.7 % of listings advertised as shipped from Canada. Other novel synthetic opioids (e.g., U-47,700, AP-237) represented 22 % of these listings for an average of 6.1 kgs per crawl with 97.2 % of listings advertised as shipped from China., Conclusions: Our data indicate consistent availability of a wide variety of novel synthetic opioids both in retail and wholesale-level amounts. Identification of new substances highlights the value of cryptomarket data for early warning systems of emerging substance use trends., Competing Interests: Declaration of Competing Interest No conflict declared., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Introduction: The opioid overdose crisis in the United States has prompted an expansion of treatment services, including pharmacotherapy with buprenorphine. However, many people who use illicit opioids (PWUIO) self-treat their opioid-use disorder (OUD) with non-prescribed buprenorphine (NPB) in lieu of attending formal treatment. The present study aims to qualitatively understand motivations of people who are self-treating their OUD with NPB., Methods: Qualitative study designed to supplement and contextualize quantitative findings from natural history study of buprenorphine diversion, self-treatment, and use of substance use disorder treatment services. Interviews were audio-recorded, transcribed, systematically coded and analyzed via Iterative Categorization., Study Setting: The Dayton, Ohio metropolitan area in the midwestern United States; a site previously characterized as high impact in the national opioid overdose crisis., Participants: Sixty-five individuals (35 men and 30 women) who met the DSM-5 criteria for OUD (moderate or severe) and had used NPB at least one time in the six months prior to their intake interview., Results: Participants described four key motivators for self-treating with NPB: perceived demands of formal treatment, the desire to utilize non-prescribed buprenorphine in combination with a geographic relocation, to self-initiate treatment while preparing for formal services, and to bolster a sense of self-determination and agency in their recovery trajectory., Conclusions: Use of NPB is a recognized self-treatment modality among PWUIO, with some PWUIO transitioning into sustained recovery episodes or enrollment in formal treatment. Understanding the motivations for opting out of treatment is crucial for improving forms of care for people with OUD., Competing Interests: Declaration of Competing Interest No conflict declared., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Unintentional drug overdoses have reached epidemic levels in the U.S. This study tests the hypothesis that people who have used non-prescribed buprenorphine more frequently in the past six months were less likely to experience a drug overdose during that same time period., Methods: Participants age 18 years or older with opioid use disorder who reported use of non-prescribed buprenorphine in the last six months were recruited from the Dayton, Ohio, area using a combination of targeted and modified respondent-driven sampling. Participants completed a structured interview, including six-month timeline follow-back, after informed consent. Logistic regression was used to test the association between (log-transformed) frequency of non-prescribed buprenorphine use and overdose in the previous six months, adjusted for confounding due to sex, homelessness, incarceration, substance use treatment, previous overdose, heroin/fentanyl injection, psychiatric comorbidity, and (log-transformed) frequencies of other (non-opioid) drug use., Results: Almost 89% of 356 participants were white, 50.3% were male, and 78.1% had high school or greater education. Over 27% (n = 98) reported experiencing an overdose in the past six months. After adjusting for confounding, greater frequency of non-prescribed buprenorphine use was significantly associated with lower risk of overdose (AOR = 0.81, 95% CI = 0.66, 0.98; p = .0286). Experiencing an overdose more than six months ago (AOR = 2.19, 95% CI = 1.24, 3.97); injection as the most common route of administration of heroin/fentanyl (AOR = 2.49, 95% CI = 1.36, 4.71); and frequency of methamphetamine use (AOR = 1.13, 95% CI = 1.02, 1.27) were strongly associated with increased risk of recent overdose in multivariable analysis., Discussion: The findings support our hypothesis that higher frequency of non-prescribed buprenorphine use is associated with lower risk of drug overdose, a potential harm reduction consequence of diversion. Improving the availability of buprenorphine though standard substance use disorder treatment, primary care, and other innovative methods is urgently needed., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2020. Published by Elsevier B.V.)

Background : U.S. is experiencing a surging trend of methamphetamine use among individuals who use opioids. More research is needed to characterize this emerging "twin epidemic." Objectives: The study aims to identify social and behavioral characteristics associated with methamphetamine use among individuals with opioid use disorder (OUD) in the Dayton, Ohio, area, an epicenter of the opioid crisis and an emerging frontier of methamphetamine epidemic. Methods: 357 adult individuals with current OUD were recruited using targeted and respondent-driven sampling. Structured interviews collected information on social and drug use characteristics. Multivariable Logistic Regression was used to identify characteristics associated with the past 6-month use of methamphetamine. Results: 49.7% were female, and 88.8% were non-Hispanic whites. 55.6% used methamphetamine in the past 6-months, and 84.9% reported first use of methamphetamine after initiation of illicit opioids. Methamphetamine use was associated with homelessness (aOR = 2.46, p  = .0001), lifetime history of diverted pharmaceutical stimulant use (aOR = 2.97, p  < .001), injection route of heroin/fentanyl use (aOR = 1.89, p  = .03), preference for fentanyl over heroin (aOR = 1.82, p  = .048), lifetime history of extended-release injectable naltrexone (Vivitrol)-based treatment (aOR = 2.89, p  = .003), and more frequent marijuana use (aOR = 1.26, p  = .04). Discussion: The findings point to the complexity of motivational and behavioral pathways associated with methamphetamine and opioid co-use, ranging from self-treatment and substitution behaviors, attempts to endure homelessness, and greater risk taking to experience euphoria. More research is needed to understand the causal relationships and the association between methamphetamine and Vivitrol use. Public health responses to the opioid crisis need to be urgently expanded to address the growing epidemic of methamphetamine use.

Background: Conducted in the Dayton Metropolitan area of Southwestern Ohio, this qualitative study explores the self-treatment practices of people who use illicit opioids (PWUIO) amidst the new risk environment produced by illicit, non-pharmaceutical fentanyl (NPF). We explore local perceptions of the presence of NPF in the Dayton area, and how this has both positively and negatively impacted practices of non-prescribed buprenorphine use among PWUIO., Methods: This study analyzes qualitative data from 63 interviews conducted between October 2018 and June 2019. Participants were selected from a larger longitudinal study on non-prescribed buprenorphine use among individuals with opioid use disorder. Qualitative interviews were transcribed in their entirety, and their transcriptions were analyzed using NVivo software, drawing on a mix of thematic and inductive coding., Results: Interview respondents ranged from 19 to 70 years old, with a mean age of 38.9 years. 54% of them were male, and 85.7% identified as non-Hispanic White. 98.4% of the sample had used heroin, and 93.7% of the sample reported use of NPF. Participants agreed NPF dominated the illicit opioids market in the area, and was perceived as both dangerous and desirable. The domination of NPF and associated overdose experiences prompted some to seek positive change and initiate self-treatment with non-prescribed buprenorphine. For others, NPF sabotaged established practices of harm reduction, as unanticipated experiences of precipitated withdrawals prompted some participants to give up non-prescribed buprenorphine use as a tactic of self-treatment., Discussion: The changing nature of heroin/NPF necessarily gives rise to new beliefs surrounding self-treatment attempts, treatment seeking behaviors, and harm reduction practices. While buprenorphine treatment continues to offer promising results for treating opioid use disorders, it is urgent to reconsider how the unpredictable biochemical mixture of NPFs circulating on the streets today may impact the initiation and success of treatment., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Aim: Non-prescribed buprenorphine (NPB) use increased in the US. This study aims to characterize heterogeneity in patterns of NPB and other opioid use among individuals with current opioid use disorder., Methods: The study recruited 356 participants in Dayton (Montgomery County), Ohio, area in 2017-2018 using targeted and Respondent Driven Sampling. Participants met the following criteria: 1) 18 years or older, 2) current moderate/severe opioid use disorder (DSM-5), 3) past 6-month NPB use. Latent class analysis (LCA) was conducted to identify subgroups based on past 6-month (days of NPB and heroin/fentanyl use; use of NPB to get high; use of non-prescribed and prescribed pharmaceutical opioids; participation in formal treatment) and lifetime (years since first NPB and other illicit opioid use) characteristics. Selected auxiliary variables were compared across classes using Asparouhov and Muthén's 3-step approach., Results: 49.7% were female, and 88.8% were non-Hispanic whites. 89% used NPB to self-treat withdrawal. LCA resulted in three classes: "Heavy Heroin/Fentanyl Use" (61%), "More Formal Treatment Use" (29%) and "Intense NPB Use" (10%). After adjusting for multiple testing, the following past 6-month variables differed significantly between classes: injection as a primary route of heroin/fentanyl administration (p < 0.001), cocaine use (p = 0.044), unintentional drug overdose (p = 0.023), and homelessness (p = 0.044), with the "Intense NPB Use" class having the lowest prevalences., Conclusion: Predominance of self-treatment goals and the association between more intense NPB use and lower risks of adverse consequences suggest potential harm minimization benefits of NPB use. More research is needed to understand consequences of NPB use over time., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Conducted in Dayton, Ohio, the study aims to characterize user knowledge and experiences with non-pharmaceutical fentanyl-type drugs (NPFs) and compare self-reports with urine toxicology for NPFs and heroin., Methods: Between May 2017-January 2018, 60 individuals who self-reported heroin/NPF use were interviewed using structured questionnaire on socio-demographics, NPF and other drug use practices. Unobserved urine samples were collected and analyzed using: 1) liquid-chromatography-tandem mass spectrometry (LC-MS/MS)-based method (Toxicology lab) to identify 34 fentanyl analogues, metabolites, and other synthetic opioids; 2) immunoassay-based method to screen for opiates (heroin). Sensitivity, specificity and Cohen's kappa were calculated to assess agreement between self-reports and urine toxicology., Results: The sample was 52% female, and over 90% white. Almost 60% reported preference for heroin, and 40% for NPF. Participants endorsed a number of ways of distinguishing heroin from NPF, including appearance (88.3%), effects (76.7%), taste (55%), and information provided by dealers (53.3%). Almost 80% felt confident they could distinguish heroin from NPF, but knowledge about fentanyl analogues was limited. LC-MS/MS testing identified 8 types of NPFs. Over 88% tested positive for NPFs, including 86% fentanyl, 48% carfentanil, 42% acetyl fentanyl. About 47% screened positive for opiates/heroin, and all of them were also positive for NPFs. When comparing self-reported use of NPF to urine toxicology, sensitivity and specificity were relatively high (84% and 83.3%, accordingly), while Cohen's Kappa was 0.445, indicating fair agreement. Sensitivity and specificity were lower for heroin (77.8% and 50.0%, accordingly), and Cohen's Kappa was 0.296, indicating low agreement between self-reports of heroin use and urine toxicology., Discussion: Nearly 90% of the study participants tested positive for NPF-type drugs. Participants were more likely to over-report heroin use and underreport NPF use. The majority had little knowledge about fentanyl analogues. Study findings will inform development of novel harm reduction approaches to reduce overdose mortality., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: There is a lack of information on illicitly manufactured fentanyl and fentanyl analogue-related (IMF) unintentional overdose death trends over time. The study analyzes IMF-related unintentional overdose fatalities that occurred between July 2015 and June 2017 in Montgomery County, Ohio, an area with the highest rates of unintentional overdose mortality in Ohio., Methods: LC-MS/MS-based method was used to identify fentanyl analogs and metabolites in 724 unintentional overdose death cases. The Chi-square statistic was used to assess differences over time in demographic and drug-related characteristics., Results: The number of unintentional overdose death cases testing positive for IMFs increased by 377% between second half of 2015 and first half of 2017. The majority of decedents were white (82.5%) and male (67.8%). The proportion of fentanyl-only (no other analogs) cases declined from 89.2%-24.6% (p < 0.001), while proportion of fentanyl analogue-containing cases increased from 9.8%-70.3% (p < 0.001) between the second half of 2015 and first half of 2017. The most commonly identified fentanyl analogs were carfentanil (29.7%), furanyl fentanyl (14.1%) and acryl fentanyl (10.2%). Proportion of IMF cases also testing positive for heroin declined from 21.6% to 5.4% (p < 0.001), while methamphetamine positive cases increased from 1.4%-17.8% (p < 0.001) over the same time period., Discussion: Emergence of fentanyl analogs contributed to substantial increases in unintentional overdose deaths. The data indicate a growing overlap between the IMF and methamphetamine outbreaks. Continuous monitoring of local IMF trends and rapid information dissemination to active users are needed to reduce the risks associated with IMF use., (Copyright © 2019 Elsevier B.V. All rights reserved.)

As America's opioid crisis has become an "epidemic of epidemics," Ohio has been identified as one of the high burden states regarding fentanyl-related overdose mortality. This study aims to examine changes in the availability of fentanyl, fentanyl analogs, and other non-pharmaceutical opioids on cryptomarkets and assess relationship with the trends in unintentional overdoses in Ohio to provide timely information for epidemiologic surveillance. Cryptomarket data were collected at two distinct periods of time: (1) Agora data covered June 2014-September 2015 and were obtained from Grams archive; (2) Dream Market data from March-April 2018 were extracted using a dedicated crawler. A Named Entity Recognition algorithm was developed to identify and categorize the type of fentanyl and other synthetic opioids advertised on cryptomarkets. Time-lagged correlations were used to assess the relationship between the fentanyl, fentanyl analog and other synthetic opioid-related ads from cryptomarkets and overdose data from the Cincinnati Fire Department Emergency Responses and Montgomery County Coroner's Office. Analysis from the cryptomarket data reveals increases in fentanyl-like drugs and changes in the types of fentanyl analogues and other synthetic opioids advertised in 2015 and 2018 with potent substances like carfentanil available during the second period. The time-lagged correlation was the largest when comparing Agora data to Cincinnati Emergency Responses 1 month later 0.84 (95% CI 0.45, 0.96). The time-lagged correlation between Agora data and Montgomery County drug overdoses was the largest when comparing synthetic opioid-related Agora ads to Montgomery County overdose deaths 7 months later 0.78 (95% CI 0.47, 0.92). Further investigations are required to establish the relationship between cryptomarket availability and unintentional overdose trends related to specific fentanyl analogs and/or other illicit synthetic opioids.

Aims: The purpose of this paper is to analyze characteristics of marijuana concentrate users, describe patterns and reasons of use, and identify factors associated with daily use of concentrates among U.S.-based cannabis users recruited via a Twitter-based online survey., Methods: An anonymous Web-based survey was conducted in June 2017 with 687 U.S.-based cannabis users recruited via Twitter-based ads. The survey included questions about state of residence, socio-demographic characteristics, and cannabis use including marijuana concentrates. Multiple logistic regression analyses were conducted to identify characteristics associated with lifetime and daily use of marijuana concentrates., Results: Almost 60% of respondents were male, 86% were white, and the mean age was 43.0 years. About 48% reported marijuana concentrate use. After adjusting for multiple testing, significant predictors of concentrate use included: living in "recreational" (AOR = 2.04; adj. p = .042) or "medical, less restrictive" (AOR = 1.74; adj. p = .030) states, being younger (AOR = 0.97, adj. p = .008), and daily herbal cannabis use (AOR = 2.57, adj. p = .008). Out of 329 marijuana concentrate users, about 13% (n = 44) reported daily/near daily use. Significant predictors of daily concentrate use included: living in recreational states (AOR = 3.59, adj. p = .020) and using concentrates for therapeutic purposes (AOR = 4.34, adj. p = .020)., Conclusions: Living in states with more liberal marijuana policies is associated with greater likelihood of marijuana concentrate use and with more frequent use. Characteristics of daily users, in particular, patterns of therapeutic use warrant further research with community-recruited samples., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: "Rosin tech" is an emerging solventless method consisting in applying moderate heat and constant pressure on marijuana flowers to prepare marijuana concentrates referred to as "rosin." This paper explores rosin concentrate-related Twitter data to describe tweet content and analyze differences in rosin-related tweeting across states with varying cannabis legal statuses., Method: English language tweets were collected between March 15, 2015 and April 17, 2017, using Twitter API. U.S. geolocated unique (no retweets) tweets were manually coded to evaluate the content of rosin-related tweets. Adjusted proportions of Twitter users and personal communication tweets per state related to rosin concentrates were calculated. A permutation test was used to analyze differences in normalized proportions between U.S. states with different cannabis legal statuses., Results: eDrugTrends collected 8389 tweets mentioning rosin concentrates/technique. 4164 tweets (49.6% of total sample) posted by 1264 unique users had identifiable state-level geolocation. Content analysis of 2010 non-retweeted tweets revealed a high proportion of media-related tweets (44.2%) promoting rosin as a safer and solventless production method. Tweet-volume-adjusted percentages of geolocated Twitter users and personal communication tweets about rosin were respectively up to seven and sixteen times higher between states allowing recreational use of cannabis and states where cannabis is illegal., Conclusion: Our results indicate that there are higher proportions of personal communication tweets and Twitter users tweeting about rosin in U.S. states where cannabis is legalized. Rosin concentrates are advertised as a safer, more natural form of concentrates, but more research on this emerging form of marijuana concentrate is needed., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The United States and numerous other countries worldwide are currently experiencing a public health crisis due to the abuse of illicitly manufactured fentanyl (IMF) and its analogues. This manuscript describes the development of a liquid chromatography-tandem mass spectrometry-based method for the multiplex detection of N = 24 IMF analogues and metabolites in whole blood at concentrations as low as 0.1-0.5 ng mL -1 . These available IMFs were fentanyl, norfentanyl, furanyl norfentanyl, remifentanil acid, butyryl norfentanyl, remifentanil, acetyl fentanyl, alfentanil, AH-7921, U-47700, acetyl fentanyl 4-methylphenethyl, acrylfentanyl, para -methoxyfentanyl, despropionyl fentanyl (4-ANPP), furanyl fentanyl, despropionyl para -fluorofentanyl, carfentanil, (±)- cis -3-methyl fentanyl, butyryl fentanyl, isobutyryl fentanyl, sufentanil, valeryl fentanyl, para -fluorobutyryl fentanyl, and para -fluoroisobutyryl fentanyl. Most IMF analogues ( N = 22) could be easily distinguished from one another; the isomeric forms butyryl/isobutyryl fentanyl and para -fluorobutyryl/ para -fluoroisobutyryl fentanyl could not be differentiated. N = 13 of these IMF analogues were quantified for illustrative purposes, and their forensic quality control standards were also validated for limit of detection (0.017-0.056 ng mL -1 ), limit of quantitation (0.100-0.500 ng mL -1 ), selectivity/sensitivity, ionization suppression/enhancement (87-118%), process efficiency (60-95%), recovery (64-97%), bias (<20%), and precision (>80%). This flexible, time- and cost-efficient method was successfully implemented at the Montgomery County Coroner's Office/Miami Valley Regional Crime Laboratory in Dayton, Ohio, where it aided in the analysis of N = 725 postmortem blood samples collected from February 2015 to November 2016., Competing Interests: The authors declare no competing financial interest.

Objective: Twitter data offer new possibilities for tracking health-related communications. This study is among the first to apply advanced information processing to identify geographic and content features of cannabis-related tweeting in the United States., Method: Tweets were collected using streaming Application Programming Interface (March-May 2016) and were processed by eDrugTrends to identify geolocation and classify content by source (personal communication, media, retail) and sentiment (positive, negative, neutral). States were grouped by cannabis legalization policies into "recreational," "medical, less restrictive," "medical, more restrictive," and "illegal." Permutation tests were performed to analyze differences among four groups in adjusted percentages of all tweets, unique users, personal communications only, and positive-to-negative sentiment ratios., Results: About 30% of all 13,233,837 cannabis-related tweets had identifiable state-level geo-information. Among geolocated tweets, 76.2% were personal communications, 21.1% media, and 2.7% retail. About 71% of personal communication tweets expressed positive sentiment toward cannabis; 16% expressed negative sentiment. States in the recreational group had significantly greater average adjusted percentage of cannabis tweets (3.01%) compared with other groups. For personal communication tweets only, the recreational group (2.47%) was significantly greater than the medical, more restrictive (1.84%) and illegal (1.85%) groups. Similarly, the recreational group had significantly greater average positive-to-negative sentiment ratio (4.64) compared with the medical, more restrictive (4.15) and illegal (4.19) groups. Average adjusted percentages of unique users showed similar differences between recreational and other groups., Conclusions: States with less restrictive policies displayed greater cannabis-related tweeting and conveyed more positive sentiment. The study demonstrates the potential of Twitter data to become a valuable indicator of drug-related communications in the context of varying policy environments.

Aims: The study seeks to characterize marijuana concentrate users, describe reasons and patterns of use, perceived risk, and identify predictors of daily/near daily use., Methods: An anonymous web-based survey was conducted (April-June 2016) with 673 US-based cannabis users recruited via the Bluelight.org web-forum and included questions about marijuana concentrate use, other drugs, and socio-demographics. Multivariable logistic regression analyses were conducted to identify characteristics associated with greater odds of lifetime and daily use of marijuana concentrates., Results: About 66% of respondents reported marijuana concentrate use. The sample was 76% male, and 87% white. Marijuana concentrate use was viewed as riskier than flower cannabis. Greater odds of marijuana concentrate use was associated with living in states with "recreational" (AOR=4.91; p=0.001) or "medical, less restrictive" marijuana policies (AOR=1.87; p=0.014), being male (AOR=2.21, p=0.002), younger (AOR=0.95, p<0.001), number of other drugs used (AOR=1.23, p<0.001), daily herbal cannabis use (AOR=4.28, p<0.001), and lower perceived risk of cannabis use (AOR=0.96, p=0.043). About 13% of marijuana concentrate users reported daily/near daily use. Greater odds of daily concentrate use was associated with being male (AOR=9.29, p=0.033), using concentrates for therapeutic purposes (AOR=7.61, p=0.001), using vape pens for marijuana concentrate administration (AOR=4.58, p=0.007), and lower perceived risk of marijuana concentrate use (AOR=0.92, p=0.017)., Conclusions: Marijuana concentrate use was more common among male, younger and more experienced users, and those living in states with more liberal marijuana policies. Characteristics of daily users, in particular patterns of therapeutic use and utilization of different vaporization devices, warrant further research with community-recruited samples., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Ohio is experiencing unprecedented loss of life caused by unintentional drug overdoses (1), with illicitly manufactured fentanyl (IMF) emerging as a significant threat to public health (2,3). IMF is structurally similar to pharmaceutical fentanyl, but is produced in clandestine laboratories and includes fentanyl analogs that display wide variability in potency (2); variations in chemical composition of these drugs make detection more difficult. During 2010-2015, unintentional drug overdose deaths in Ohio increased 98%, from 1,544 to 3,050.* In Montgomery County (county seat: Dayton), one of the epicenters of the opioid epidemic in the state, unintentional drug overdose deaths increased 40% in 1 year, from 249 in 2015 to 349 in 2016 (estimated unadjusted mortality rate = 57.7 per 100,000) (4). IMFs have not been part of routine toxicology testing at the coroner's offices and other types of medical and criminal justice settings across the country (2,3). Thus, data on IMF test results in the current outbreak have been limited. The Wright State University and the Montgomery County Coroner's Office/Miami Valley Regional Crime Laboratory (MCCO/MVRCL) collaborated on a National Institutes of Health study of fentanyl analogs and metabolites and other drugs identified in 281 unintentional overdose fatalities in 24 Ohio counties during January-February 2017. Approximately 90% of all decedents tested positive for fentanyl, 48% for acryl fentanyl, 31% for furanyl fentanyl, and 8% for carfentanil. Pharmaceutical opioids were identified in 23% of cases, and heroin in 6%, with higher proportions of heroin-related deaths in Appalachian counties. The majority of decedents tested positive for more than one type of fentanyl. Evidence suggests the growing role of IMFs, and the declining presence of heroin and pharmaceutical opioids in unintentional overdose fatalities, compared with 2014-2016 data from Ohio and other states (3-5). There is a need to include testing for IMFs as part of standard toxicology panels for biological specimens used in the medical, substance abuse treatment, and criminal justice settings.

Background: Synthetic Cannabinoid Receptor Agonists (SCRA), also known as "K2" or "Spice," have drawn considerable attention due to their potential of abuse and harmful consequences. More research is needed to understand user experiences of SCRA-related effects. We use semi-automated information processing techniques through eDrugTrends platform to examine SCRA-related effects and their variations through a longitudinal content analysis of web-forum data., Method: English language posts from three drug-focused web-forums were extracted and analyzed between January 1st 2008 and September 30th 2015. Search terms are based on the Drug Use Ontology (DAO) created for this study (189 SCRA-related and 501 effect-related terms). EDrugTrends NLP-based text processing tools were used to extract posts mentioning SCRA and their effects. Generalized linear regression was used to fit restricted cubic spline functions of time to test whether the proportion of drug-related posts that mention SCRA (and no other drug) and the proportion of these "SCRA-only" posts that mention SCRA effects have changed over time, with an adjustment for multiple testing., Results: 19,052 SCRA-related posts (Bluelight (n=2782), Forum A (n=3882), and Forum B (n=12,388)) posted by 2543 international users were extracted. The most frequently mentioned effects were "getting high" (44.0%), "hallucinations" (10.8%), and "anxiety" (10.2%). The frequency of SCRA-only posts declined steadily over the study period. The proportions of SCRA-only posts mentioning positive effects (e.g., "High" and "Euphoria") steadily decreased, while the proportions of SCRA-only posts mentioning negative effects (e.g., "Anxiety," 'Nausea," "Overdose") increased over the same period., Conclusion: This study's findings indicate that the proportion of negative effects mentioned in web forum posts and linked to SCRA has increased over time, suggesting that recent generations of SCRA generate more harms. This is also one of the first studies to conduct automated content analysis of web forum data related to illicit drug use., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: To harness the full potential of social media for epidemiological surveillance of drug abuse trends, the field needs a greater level of automation in processing and analyzing social media content., Objectives: The objective of the study is to describe the development of supervised machine-learning techniques for the eDrugTrends platform to automatically classify tweets by type/source of communication (personal, official/media, retail) and sentiment (positive, negative, neutral) expressed in cannabis- and synthetic cannabinoid-related tweets., Methods: Tweets were collected using Twitter streaming Application Programming Interface and filtered through the eDrugTrends platform using keywords related to cannabis, marijuana edibles, marijuana concentrates, and synthetic cannabinoids. After creating coding rules and assessing intercoder reliability, a manually labeled data set (N=4000) was developed by coding several batches of randomly selected subsets of tweets extracted from the pool of 15,623,869 collected by eDrugTrends (May-November 2015). Out of 4000 tweets, 25% (1000/4000) were used to build source classifiers and 75% (3000/4000) were used for sentiment classifiers. Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machines (SVM) were used to train the classifiers. Source classification (n=1000) tested Approach 1 that used short URLs, and Approach 2 where URLs were expanded and included into the bag-of-words analysis. For sentiment classification, Approach 1 used all tweets, regardless of their source/type (n=3000), while Approach 2 applied sentiment classification to personal communication tweets only (2633/3000, 88%). Multiclass and binary classification tasks were examined, and machine-learning sentiment classifier performance was compared with Valence Aware Dictionary for sEntiment Reasoning (VADER), a lexicon and rule-based method. The performance of each classifier was assessed using 5-fold cross validation that calculated average F-scores. One-tailed t test was used to determine if differences in F-scores were statistically significant., Results: In multiclass source classification, the use of expanded URLs did not contribute to significant improvement in classifier performance (0.7972 vs 0.8102 for SVM, P=.19). In binary classification, the identification of all source categories improved significantly when unshortened URLs were used, with personal communication tweets benefiting the most (0.8736 vs 0.8200, P<.001). In multiclass sentiment classification Approach 1, SVM (0.6723) performed similarly to NB (0.6683) and LR (0.6703). In Approach 2, SVM (0.7062) did not differ from NB (0.6980, P=.13) or LR (F=0.6931, P=.05), but it was over 40% more accurate than VADER (F=0.5030, P<.001). In multiclass task, improvements in sentiment classification (Approach 2 vs Approach 1) did not reach statistical significance (eg, SVM: 0.7062 vs 0.6723, P=.052). In binary sentiment classification (positive vs negative), Approach 2 (focus on personal communication tweets only) improved classification results, compared with Approach 1, for LR (0.8752 vs 0.8516, P=.04) and SVM (0.8800 vs 0.8557, P=.045)., Conclusions: The study provides an example of the use of supervised machine learning methods to categorize cannabis- and synthetic cannabinoid-related tweets with fairly high accuracy. Use of these content analysis tools along with geographic identification capabilities developed by the eDrugTrends platform will provide powerful methods for tracking regional changes in user opinions related to cannabis and synthetic cannabinoids use over time and across different regions., Competing Interests: Conflicts of Interest: None declared.

Aims: Several states in the U.S. have legalized cannabis for recreational or medical uses. In this context, cannabis edibles have drawn considerable attention after adverse effects were reported. This paper investigates Twitter users' perceptions concerning edibles and evaluates the association edibles-related tweeting activity and local cannabis legislation., Methods: Tweets were collected between May 1 and July 31, 2015, using Twitter API and filtered through the eDrugTrends/Twitris platform. A random sample of geolocated tweets was manually coded to evaluate Twitter users' perceptions regarding edibles. Raw state proportions of Twitter users mentioning edibles were ajusted relative to the total number of Twitter users per state. Differences in adjusted proportions of Twitter users mentioning edibles between states with different cannabis legislation status were assesed via a permutation test., Results: We collected 100,182 tweets mentioning cannabis edibles with 26.9% (n=26,975) containing state-level geolocation. Adjusted percentages of geolocated Twitter users posting about edibles were significantly greater in states that allow recreational and/or medical use of cannabis. The differences were statistically significant. Overall, cannabis edibles were generally positively perceived among Twitter users despite some negative tweets expressing the unreliability of edible consumption linked to variability in effect intensity and duration., Conclusion: Our findings suggest that Twitter data analysis is an important tool for epidemiological monitoring of emerging drug use practices and trends. Results tend to indicate greater tweeting activity about cannabis edibles in states where medical THC and/or recreational use are legal. Although the majority of tweets conveyed positive attitudes about cannabis edibles, analysis of experiences expressed in negative tweets confirms the potential adverse effects of edibles and calls for educating edibles-naïve users, improving edibles labeling, and testing their THC content., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Background: Increases in illicit pharmaceutical opioid (PO) use have been associated with risk for transition to heroin use. We identify predictors of transition to heroin use among young, illicit PO users with no history of opioid dependence or heroin use at baseline., Methods: Respondent-driven sampling recruited 383 participants; 362 returned for at least one biannual structured interview over 36 months. Cox regression was used to test for associations between lagged predictors and hazard of transition to heroin use. Potential predictors were based on those suggested in the literature. We also computed population attributable risk (PAR) and the rate of heroin transition., Results: Over 36 months, 27 (7.5%) participants initiated heroin use; all were white, and the rate of heroin initiation was 2.8% per year (95% CI=1.9%-4.1%). Mean length of PO at first reported heroin use was 6.2 years (SD=1.9). Lifetime PO dependence (AHR=2.39, 95% CI=1.07-5.48; PAR=32%, 95% CI=-2% to 64%), early age of PO initiation (AHR=3.08, 95%; CI=1.26-7.47; PAR=30%, 95% CI=2%-59%), using illicit POs to get high but not to self-medicate a health problem (AHR=4.83, 95% CI=2.11-11.0; PAR=38%, 95% CI=12%-65%), and ever using PO non-orally most often (AHR=6.57, 95% CI=2.81-17.2; PAR=63%, 95% CI=31%-86%) were significant predictors., Conclusion: This is one of the first prospective studies to test observations from previous cross-sectional and retrospective research on the relationship between illicit PO use and heroin initiation among young, initially non-opioid dependent PO users. The results provide insights into targets for the design of urgently needed prevention interventions., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Aims: Media reports suggest increasing popularity of marijuana concentrates ("dabs"; "earwax"; "budder"; "shatter; "butane hash oil") that are typically vaporized and inhaled via a bong, vaporizer or electronic cigarette. However, data on the epidemiology of marijuana concentrate use remain limited. This study aims to explore Twitter data on marijuana concentrate use in the U.S. and identify differences across regions of the country with varying cannabis legalization policies., Methods: Tweets were collected between October 20 and December 20, 2014, using Twitter's streaming API. Twitter data filtering framework was available through the eDrugTrends platform. Raw and adjusted percentages of dabs-related tweets per state were calculated. A permutation test was used to examine differences in the adjusted percentages of dabs-related tweets among U.S. states with different cannabis legalization policies., Results: eDrugTrends collected a total of 125,255 tweets. Almost 22% (n=27,018) of these tweets contained identifiable state-level geolocation information. Dabs-related tweet volume for each state was adjusted using a general sample of tweets to account for different levels of overall tweeting activity for each state. Adjusted percentages of dabs-related tweets were highest in states that allowed recreational and/or medicinal cannabis use and lowest in states that have not passed medical cannabis use laws. The differences were statistically significant., Conclusions: Twitter data suggest greater popularity of dabs in the states that legalized recreational and/or medical use of cannabis. The study provides new information on the epidemiology of marijuana concentrate use and contributes to the emerging field of social media analysis for drug abuse research., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Background: Illicit use of buprenorphine has increased in the U.S., but our understanding of its use remains limited. This study aims to explore Web-forum discussions about the use of buprenorphine to self-treat opioid withdrawal symptoms., Methods: PREDOSE, a novel Semantic Web platform, was used to extract relevant posts from a Web-forum that allows free discussions on illicit drugs. First, we extract information about the total number of buprenorphine-related posts per year between 2005 and 2013. Second, PREDOSE was used to identify all posts that potentially contained discussions about buprenorphine and opioid withdrawal. A total number of 1,217 posts that contained these terms were extracted and entered into NVivo data base. A random sample of 404 (33%) posts was selected and content analyzed., Results: Buprenorphine-related posts increased over time, peaking in 2011. The posts were about equally divided between those that expressed positive and negative views about the effectiveness of buprenorphine in relieving withdrawal symptoms. Web-forum participants emphasized that buprenorphine's effectiveness may become compromised because of the "size of a person habit," and/or when users repeatedly switch back and forth between buprenorphine and other illicit opioids. Most posts reported use of significantly lower amounts of buprenorphine (≤2 mg) than doses used in standard treatment. Concomitant use of other psychoactive substances was also commonly reported, which may present significant health risks., Conclusions: Our findings highlight the usefulness of Web-based data in drug abuse research and add new information about lay beliefs about buprenorphine that may help inform prevention and policy measures., (© American Academy of Addiction Psychiatry.)