Associations Between Kratom-Related State Policy Environments and Kratom Use in a Nationally Representative Population in the United States.

Limited research has resulted in conflicting views on the risks versus benefits associated with kratom use. Despite no federal policy in the United States, individual states have implemented diverging policies through kratom bans, and legalization and regulation through Kratom Consumer Protection Acts (KCPAs). The Survey of Non-Medical Use of Prescription Drugs (NMURx) Program employs nationally-representative, repeated cross-sectional surveys on drug use. In 2021, weighted prevalence of past-12 month kratom use was compared across three state legal frameworks: no overarching state policy, KCPAs, and state bans. There was lower estimated prevalence of kratom use in banned states (prevalence: 0.75% (0.44, 1.06) relative to states with a KCPA (1.20% (0.89, 1.51)), and relative to states with no policies (1.04% (0.94, 1.13), though odds of use were not significantly associated with policy type. Kratom use was significantly associated with medicated treatment for opioid use disorder. While there were observed differences in the prevalence of past-12 month kratom use by state policy type, low uptake mitigated meaningful distinctions by limiting statistical precision, and potentially confounding effects, such as accessibility online. Future kratom-related policy decisions should be informed through evidence-based research.

Drug product dispensing and estimates of use in a general population survey as a signal detection problem.

PURPOSE: Understanding potential bias due to rarity of the outcome is important when monitoring newly approved drugs and drugs with low availability to the general public. Although there is an increasing use of online surveys to investigate health outcomes, the limits of inference due to drug availability have not been studied. The goal of this study was to quantify the relationship between dispensing of prescription drugs and estimates of use in an online general population survey. METHODS: An online repeated, cross-sectional survey from 2018 to 2020 was used to estimate the number of adults in the United States who used prescription drugs in the general population and compared to estimated number of prescriptions dispensed over an equivalent time period. Joinpoint regression was used to quantify thresholds. A sample of respondents was retested to estimate reliability statistics. RESULTS: A model with a single threshold was the best fit, with the estimated threshold of 565 000 (95% CI: 9500-11 600 000) prescriptions dispensed per year. Above the threshold, there was a significant association between dispensing and estimates (p < 0.001); below the threshold, the relationship was not significant (p = 0.912). Above the threshold, responses were more reliable than random chance, and reliability steadily increased with increased dispensing. CONCLUSIONS: These results suggest the threshold demarcates two distinct pharmacoepidemiological paradigms when investigating drug use in general population surveys. Dispensing can be used as a guide to determine the epidemiological paradigm that is best suited.

Non-medical use of benzodiazepines and GABA analogues in Europe.

AIMS: We investigated the prevalence of non-medical use (NMU) of benzodiazepines and GABA analogues in Europe. METHODS: Data were collected using the online Non-Medical Use of Prescription Drugs (NMURx) survey from France, Germany, Italy, Spain and the UK. RESULTS: The study included 55 223 eligible surveys which, after post-stratification weights were applied, represented approximately 260 million European adults. Lifetime NMU of benzodiazepines was highest in Spain (6.5%, 95% CI: 6.0-7.0) and lowest in Germany (1.7%, 1.5-2.0). Lifetime NMU of GABA analogues was highest in Germany (5.4%, 5.0-5.7) and lowest in France (2.2%, 1.9-2.5) and the UK (2.2%, 1.9-2.6) While no notable difference was observed for France or the UK, there was a higher prevalence of last 12-month NMU of benzodiazepines compared to GABA analogues in Italy (2.4 times higher) and Spain (3.0 times higher) and a higher prevalence of NMU of GABA analogues compared to benzodiazepines in Germany (2.6 times higher). CONCLUSION: This study shows that there is variation in NMU of benzodiazepines and GABA analogues among countries. Of particular interest is the high incidence of GABA analogue NMU in Germany and benzodiazepine NMU in Spain. Further research to identify factors and motivations responsible for the higher prevalence observed are essential to inform public health policies in those countries.

An Online Survey for Pharmacoepidemiological Investigation (Survey of Non-Medical Use of Prescription Drugs Program): Validation Study.

BACKGROUND: In rapidly changing fields such as the study of drug use, the need for accurate and timely data is paramount to properly inform policy and intervention decisions. Trends in drug use can change rapidly by month, and using study designs with flexible modules could present advantages. Timely data from online panels can inform proactive interventions against emerging trends, leading to a faster public response. However, threats to validity from using online panels must be addressed to create accurate estimates. OBJECTIVE: The objective of this study was to demonstrate a comprehensive methodological approach that optimizes a nonprobability, online opt-in sample to provide timely, accurate national estimates on prevalence of drug use. METHODS: The Survey of Non-Medical Use of Prescription Drugs Program from the Researched Abuse, Diversion and Addiction Related Surveillance (RADARS) System is an online, cross-sectional survey on drug use in the United States, and several best practices were implemented. To optimize final estimates, two best practices were investigated in detail: exclusion of respondents showing careless or improbable responding patterns and calibration of weights. The approach in this work was to cumulatively implement each method, which improved key estimates during the third quarter 2018 survey launch. Cutoffs for five exclusion criteria were tested. Using a series of benchmarks, average relative bias and changes in bias were calculated for 33 different weighting variable combinations. RESULTS: There were 148,274 invitations sent to panelists, with 40,021 who initiated the survey (26.99%). After eligibility assessment, 20.23% (29,998/148,274) of the completed questionnaires were available for analysis. A total of 0.52% (157/29,998) of respondents were excluded based on careless or improbable responses; however, these exclusions had larger impacts on lower volume drugs. Number of exclusions applied were negatively correlated to total dispensing volume by drug (Spearman ρ=-.88, P<.001). A weighting scheme including three demographic and two health characteristics reduced average relative bias by 31.2%. After weighting, estimates of drug use decreased, reflecting a weighted sample that had healthier benchmarks than the unweighted sample. CONCLUSIONS: Our study illustrates a new approach to using nonprobability online panels to achieve national prevalence estimates for drug abuse. We were able to overcome challenges with using nonprobability internet samples, including misclassification due to improbable responses. Final drug use and health estimates demonstrated concurrent validity to national probability-based drug use and health surveys. Inclusion of multiple best practices cumulatively improved the estimates generated. This method can bridge the information gap when there is a need for prompt, accurate national data.