Faculty Bibliography

BACKGROUND AND OBJECTIVES/OBJECTIVE:Ketamine is efficacious in treating treatment-resistant depression in medical settings and the drug was approved for such use by the US Federal Drug Administration in 2019. However, little is known about how use outside of medical settings relates to depression. We determined whether recreational ketamine use, relative to the use of other drugs, is related to the current experience of depression among adolescents. METHODS:We examined data from the 2016 to 2019 Monitoring the Future nationally representative survey of high school seniors in the United States (N = 15,673). We determined how past-year drug use and frequency of past-year drug use were associated with students reporting a high level of current depressive symptoms relative to other students. RESULTS:Ketamine use was associated with highest risk for a high level of depression (aPR = 1.55, 95% confidence interval [CI]: 1.24-1.94), followed by use of cannabis (aPR = 1.29, 95% CI: 1.19-1.39), and nonmedical use of tranquilizers (aPR = 1.22, 95% CI: 1.04-1.44) and amphetamine (aPR = 1.17, 95% CI: 1.01-1.34). Alcohol use was associated with decreased risk (aPR = 0.92, 95% CI: 0.85-0.99). With respect to frequency of past-year use, more frequent use of ketamine and cannabis was associated with increased risk for a high level of depression in a dose-response-like manner, with past-year use of ketamine and cannabis ≥10 times associated with increased risk for depression by 70% and 40%, respectively. DISCUSSION AND CONCLUSIONS/CONCLUSIONS:Past-year recreational ketamine use is a risk factor for reporting current depression than most other drugs. SCIENTIFIC SIGNIFICANCE/CONCLUSIONS:This was the first study to compare the risk of use of various drugs in relation to depression.

BACKGROUND:Dance festivals have been shown to be high-risk events for use of drugs such as ecstasy/MDMA and possible adverse effects associated with use. However, few studies have examined what makes festivals such risky environments. We aimed to determine festival-specific risk factors for adverse outcomes related to drug use. METHODS:In-depth interviews were conducted with 35 key informants in North America who deemed themselves experts in new psychoactive substances, and identified as drug checkers, sellers, or experienced users. Interviews were coded in an inductive manner, and we conducted thematic analysis to identify relevant themes. RESULTS:We identified four main themes focusing on festival attendance as a risk factor for risky drug use and related outcomes: attendees inexperienced with electronic dance music parties and party drugs, risky drug purchasing, risky drug use practices, and festival-specific environmental risk factors. Festivals attract a wide array of people not experienced with party drugs, yet drugs like ecstasy are commonly sought by such individuals inside festivals. Relying on strangers inside to purchase drugs is a risk factor for purchasing adulterated product. Fear of security/police at festivals leads to risky drug-taking such as ingesting one's full batch of drugs at the entrance. These risks are compounded by environmental factors including crowding, hot temperature, and lack of water (which lead to dehydration), long/consecutive event days (which can lead to exhaustion), and inadequate medical emergency response. CONCLUSIONS:We determined modifiable risk factors which can both inform future research and future prevention and harm reduction efforts in this scene.

BACKGROUND:Recent literature suggests that the gap in prevalence of binge drinking between men and women is closing, but little is known about sex-specific differences in trends and correlates of binge drinking among older Americans. METHODS:A total of 18,794 adults, aged 65 years and older were surveyed in the 2015-2019 National Survey on Drug Use and Health. We estimated trends in prevalence of past-month binge drinking (≥5 drinks on the same occasion for men and ≥4 drinks for women), stratified by sex. Correlates of binge drinking were estimated for men and women separately, focusing on demographic characteristics, chronic diseases, past-month tobacco and cannabis use, depression, and emergency department use. Multivariable generalized linear models using Poisson and log link were used to examine associations stratified by sex. RESULTS:Binge drinking among older men increased from 12.8% in 2015 to 15.7% in 2019 (p = 0.02) but remained stable among older women (7.6% to 7.3%, p = 0.97). In adjusted models, having a college degree was associated with higher risk of binge drinking among women (adjusted prevalence ratio [aPR] = 1.68, 95% CI: 1.13-2.50), but lower risk among men (aPR = 0.69, 95% CI: 0.56-0.85). Men who are separated or divorced were also at higher risk (aPR = 1.25, 95% CI: 1.05-1.50), but women were not. Both men and women reporting past-month use of tobacco (men aPR = 1.87, 95% CI: 1.61-2.17, women aPR = 2.11, 95% CI: 1.71-2.60) and cannabis (men aPR = 2.05, 95% CI: 1.63-2.58, women aPR = 2.77, 95% CI 2.00-3.85) were at higher risk of binge drinking. CONCLUSIONS:Binge drinking has increased among older men whereas it has remained stable among older women in the United States. Interventions should consider that although tobacco and cannabis use is associated with an increased risk of binge drinking among both older men and women, demographic correlates tend to differ by sex.

PURPOSE/OBJECTIVE:To outline a method for obtaining more accurate estimates of drug use in the United States (US) general population by correcting survey data for underreported and unknown drug use. METHODS:We simulated a population (n=100,000) reflecting the demographics of the US adult population per the 2018 American Community Survey. Within this population, we simulated the "true" and self-reported prevalence of past-month cannabis and cocaine use by using available estimates of underreporting. We applied our algorithm to samples of the simulated population to correct self-reported estimates and recover the "true" population prevalence, validating our approach. We applied this same method to 2018 National Survey on Drug Use and Health data to produce a range of underreporting-corrected estimates. RESULTS:Simulated self-report sensitivities varied by drug and sampling method (cannabis: 77.6-78.5%, cocaine: 14.3-22.1%). Across repeated samples, mean corrected prevalences (calculated by dividing self-reported prevalence by estimated sensitivity) closely approximated simulated "true" prevalences. Applying our algorithm substantially increased 2018 NSDUH estimates (self-report: cannabis=10.5%, cocaine=0.8%; corrected: cannabis=15.6-16.6%, cocaine=2.7-5.5%). CONCLUSION/CONCLUSIONS:National drug use prevalence estimates can be corrected for underreporting using a simple method. However, valid application of this method requires accurate data on the extent and correlates of misclassification in the general US population.