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Introduction Cross-sectional surveys found behavioral heterogeneity among dual users of combustible and electronic cigarettes. Yet, prior classification did not reflect dynamic interactions between cigarette and e-cigarette consumption, which may reveal changes in product-specific dependence. The contexts of dual use that could inform intervention were also understudied. Methods This study conducted secondary analysis on 13 waves of data from 227 dual users who participated in a 2-year observational study. The k-means method for joint trajectories of cigarette and e-cigarette consumption was adopted to identify the subtypes of dual users. The time-varying effect model was used to characterize the subtype-specific trajectories of cigarette and e-cigarette dependence. The subtypes were also compared in terms of use contexts. Results The four clusters were identified: light dual users, predominant vapers, heavy dual users, and predominant smokers. Although heavy dual users and predominant smokers both smoked heavily at baseline, by maintaining vaping at the weekly to daily level the heavy dual users were able to considerably reduce cigarette use. Yet, the heavy dual users’ drop in cigarette dependence was not as dramatic as their drop in cigarette consumption. Predominant vapers appeared to engage in substitution, as they decreased their smoking and increased their e-cigarette dependence. They were also more likely to live in environments with smoking restrictions and report that their use of e-cigarettes reduced cigarette craving and smoking frequency. Conclusions Environmental constraints can drive substitution behavior and the substitution behavior is able to be sustained if people find the substitute to be effective. Implications This study characterizes subtypes of dual users based on the dynamic interactions between cigarette use and e-cigarette use as well as product-specific trajectories of dependence. The subtypes differ in not only sociodemographic characteristics but also contexts of cigarette and e-cigarette use. Higher motivation to use e-cigarettes to quit smoking and less permissive environment for smoking may promote substitution of cigarettes by e-cigarettes.

Background: The dopamine receptor D4 [DRD4] has been reported to be associated with substance use. Yet, the roles that health conditions and behaviors may play in such association are understudied.Objective: This longitudinal study investigated the potential mediation effects of chronic pain and delinquency in adolescence on the association between the DRD4 2-repeat allele and substance use in adulthood. Sex, witnessing violence, and experiencing violence were also examined as potential moderators for the mediation pathways.Methods: We used the restricted and candidate gene data from the National Longitudinal Study of Adolescent to Adult Health (Waves I-IV) to conduct secondary analysis (N = 8,671; 47% male). A two-step approach was adopted to examine the mediation effects regarding four substance use outcomes in adulthood: number of lifetime alcohol use disorder symptoms, lifetime regular smoker status, past-month smoking, and lifetime "pain killer" misuse. The moderation effects were investigated using stratification and permutation.Results: The DRD4 2-repeat allele was associated with all adulthood substance use outcomes through adolescent chronic pain and delinquency (AORs/IRR range 1.08-3.78; all ps

The use of electronic nicotine delivery systems (ENDS), including disposable e-cigarettes, has been prevalent. Existing chemical analyses of ENDS focused on e-liquids rather than aerosols and failed to consider particle sizes and aerosol respiratory deposition fractions, which are key factors for inhalation doses. This study investigated the organic chemical and metal constituents in size-segregated ENDS aerosol and assessed the deposited doses and health risks of these substances. Aerosol chemical analyses were conducted on two popular disposable ENDS products: Puff Bar (Grape) and Air Bar (Watermelon Ice). An ENDS aerosol was generated and delivered into a Micro-Orifice Uniform Deposit Impactor to collect size-segregated aerosol samples, in which organic chemicals and metals were analyzed. Daily and lifetime doses for each chemical were estimated. Cancer and non-cancer risk assessments were conducted based on the deposited doses. We found that e-cigarette aerosol contains certain harmful organic chemicals and metals documented to result in respiratory problems. Estimated respiratory cancer risks corresponding to chromium from both ENDS products and nickel from Air Bar (Watermelon Ice) were substantially above the conventionally acceptable risk. The method, findings, and implications can contribute to the extant literature of ENDS toxicity studies as well as inform tobacco regulation and future large-scale studies.

Existing studies of the impact of home rules on youth's vulnerability to e-cigarette use were based on cross-sectional data, youth or parent reports alone, as well as youth's perceptions and susceptibility. This study capitalizes on the restricted-use data of the Population Assessment of Tobacco and Health (PATH) Study to examine the longitudinal association between home rules for e-cigarette use and youth's vulnerability including initiation of use and regular use two years later. Secondary analysis was conducted on 1203 parent-youth pairs who participated in both Wave 4 (2016-2018) and Wave 5 (2018-2019) assessment of the PATH Study and while the youth were age 12-16 at Wave 4. Linear and logistic regressions were performed to examine the associations between having a strict home rule for e-cigarette use at Wave 4 and the youth's outcomes including perceived social norms, expectancies, susceptibility, initiation of use, and regular use of e-cigarettes at Wave 5, controlling for parent and youth factors. The results show that having a strict home rule for e-cigarette use was associated with youth's heightened level of perceived injunctive norms (β = 0.22, p 0.01), higher expectancy of harmfulness (β = 0.28, p 0.01) and lower odds for regular e-cigarette use (OR = 0.36, p 0.05). In conclusion, the findings of this study support the potential protective effects of implementing a strict home rule for e-cigarette use. Future intervention efforts may promote parents' awareness of the potential protective effects of a strict home e-cigarette rule on youth's normative belief, harm expectancy, and behavior of e-cigarette use.

Introduction Existing e-cigarette dependence scales are mainly validated based on retrospective overall consumption or perception. Further, given that the majority of adult e-cigarette users also use combustible cigarettes, it is important to determine whether e-cigarette dependence scales capture the product-specific dependence. This study fills in the current knowledge gaps by validating e-cigarette dependence scales using novel indices of dynamic patterns of e-cigarette use behaviors and examining the association between dynamic patterns of smoking and e-cigarette dependence among dual users. Methods Secondary analysis was conducted on the 2-week ecological momentary assessment data from 116 dual users. The Smoothly Clipped Absolute Deviation penalty (SCAD) was adopted to select important indices for dynamic patterns of consumption or craving and estimate their associations with e-cigarette dependence scales. Results The fitted linear regression models support the hypothesis that higher e-cigarette dependence is associated with higher levels of e-cigarette consumption and craving as well as lower instability of e-cigarette consumption. Controlling for dynamic patterns of vaping, dual users with lower e-cigarette dependence tend to report higher day-to-day dramatic changes in combustible cigarette consumption but not higher average levels of smoking. Conclusions We found that more stable use patterns are related to higher levels of dependence, which has been demonstrated in combustible cigarettes and we have now illustrated in e-cigarettes. Furthermore, the e-cigarette dependence scales may capture the product-specific average consumption but not product-specific instability of consumption. Implications This study provides empirical support for three e-cigarette dependence measures: PS-ECDI, e-FTCD, and e-WISDM, based on dynamic patterns of e-cigarette consumption and craving revealed by EMA data that have great ecological validity. This is the first study that introduces novel indices of dynamic patterns and demonstrates their potential applications in vaping research.

African Americans develop hypertension earlier in life than Whites and the racial/ethnic disparities in blood pressure level can appear as early as adolescence. Violence victimization, a prevalent environmental stressor among inner-city youth, may play a role in such disparities. In a sample of inner-city youth in the United States, the current study examines the relationship between violence victimization and hypertension while investigating the role of social support in moderating that relationship. We analyzed eight waves of data from a longitudinal study of African American youth ( n = 353, 56.7% female) from mid-adolescence (9th grade, mean age = 14.9 years old) to emerging adulthood (mean age = 23.1 years old) using probit regression. Higher levels of self-reported violence victimization during ages 14–18 was associated with more reports of hypertension during ages 20–23, after adjusting for sex, socioeconomic status, substance use, and mental distress. The relationship of violence victimization with hypertension was moderated by friends’ support, but not parental support. The association between victimization and hypertension was weaker and non-significant among individuals with more peer support compared to those with less support. Researchers have reported many instances of associations of early violence exposure to later risk for hypertension; however, most have focused on childhood maltreatment or intimate partner violence. We extend these findings to violence victimization in an African American sample of youth from adolescence to early adulthood, while examining social support modifiers. The disparity in African American hypertension rates relative to Whites may partly be explained by differential exposure to violence. Our findings also suggest that having supportive friends when faced with violence can be beneficial for young adulthood health outcomes.

Statewide medical marijuana laws (MMLs) in the U.S. may be associated with adolescent marijuana use behavior, attitudes toward marijuana use, and social norms. This study used data from the National Study on Drug Use and Health (2013-2016) to examine the associations of state MML with marijuana use, use frequency, and attitudes and perceived peer and parental social norms toward using marijuana. Propensity-score matching was used to reduce selection bias between states with and without MML (matched N = 50,000). Results showed that adolescents residing in states with MML had higher odds of using marijuana in the past month and past year (OR = 1.45 and 1.49

Research indicates that externalizing and internalizing pathways emanated in childhood are connected to later drinking behaviors; however, no study has investigated the contemporaneous effects of the two pathways using a person-centered approach that categorizes individuals based on their various developmental patterns. This study examined the distinct patterns of concurrent development of aggression and depressive symptoms in childhood and their associations with later drinking behaviors using data from a 15-year Taiwanese cohort since age 8 (N = 2854, 49% females). Group-based multi-trajectory modeling identified four aggressive-depressive trajectory groups: Moderate, Aggressive, Depressive, and Comorbid, which manifested a sequential risk gradient in alcohol use. Comorbid group, characterized by persistently high levels of aggression and depressive symptoms, has the highest levels of alcohol use and drinking problems and the earliest onset of drinking. Aggressive and Depressive groups have higher levels of alcohol use and earlier onset of drinking than Moderate group. These findings imply the importance of monitoring aggression and depressive symptoms simultaneously and continually in childhood to prevent later drinking.

Unnecessary/unsafe opioid prescribing has become a major public health concern in the U.S. Statewide prescription drug monitoring programs (PDMPs) with varying characteristics have been implemented to improve safe prescribing practice. Yet, no studies have comprehensively evaluated the effectiveness of PDMP characteristics in reducing opioid-related potentially inappropriate prescribing (PIP) practices. The objective of the study is to apply machine learning methods to evaluate PDMP effectiveness by examining how different PDMP characteristics are associated with opioid-related PIPs for non-cancer chronic pain (NCCP) treatment. This was a retrospective observational study that included 802,926 adult patients who were diagnosed NCCP, obtained opioid prescriptions, and were continuously enrolled in plans of a major U.S. insurer for over a year. Four outcomes of opioid-related PIP practices, including dosage ≥50 MME/day and ≥90 MME/day, days supply ≥7 days, and benzodiazepine-opioid co-prescription were examined. Machine learning models were applied, including logistic regression, least absolute shrinkage and selection operation regression, classification and regression trees, random forests, and gradient boost modeling (GBM). The SHapley Additive exPlanations (SHAP) method was applied to interpret model results. The results show that among 1,886,146 NCCP opioid-related claims, 22.8% had an opioid dosage ≥50 MME/day and 8.9% ≥90 MME/day, 70.3% had days supply ≥7 days, and 10.3% were when benzodiazepine was filled ≤7 days ago. GBM had superior model performance. We identified the most salient PDMP characteristics that predict opioid-related PIPs (e.g., broader access to patient prescription history, monitoring Schedule IV controlled substances), which could be informative to the states considering the redesign of PDMPs.

Background Existing studies on the health effects of e-cigarettes focused on e-cigarette users themselves. To study the corresponding effects on passive vapers, it is crucial to quantify e-cigarette chemicals deposited in their airways. Objective This study proposed an innovative approach to estimate the deposited dose of e-cigarette chemicals in the passive vapers' airways. The effect of the distance between active and passive vapers on the deposited dose was also examined. Methods The chemical constituent analysis was conducted to detect Nicotine and flavoring agents in e-cigarette aerosol. The Mobile Aerosol Lung Deposition Apparatus (MALDA) was employed to conduct aerosol respiratory deposition experiments in real-life settings to generate real-time data. Results For e-cigarette aerosol in the ultrafine particle regime, the deposited doses in the alveolar region were on average 3.2 times higher than those in the head-to-TB airways, and the deposited dose in the passive vaper's airways increased when being closer to the active vaper. Significance With prolonged exposure and close proximity to active vapers, passive vapers may be at risk for potential health effects of harmful e-cigarette chemicals. The methodology developed in this study has laid the groundwork for future research on exposure assessment and health risk analysis for passive vaping.

Understanding the co-use of e-cigarettes and alcohol, including the situational contexts and subjective effects associated with co-use in real-time is necessary for validating this behavior and informing intervention. Yet, the sparse literature has built upon retrospective data.This study recruited 686 college students who were currently using e-cigarettes from three campuses in the Midwest and South of U.S in Fall 2019-Fall 2021. An on-line survey was conducted to measure e-cigarette use patterns, GPA, e-cigarette and alcohol dependence symptoms, and respiratory symptoms. A 7-day ecological momentary assessment was used to collect real-time data on e-cigarette and alcohol use, situational contexts and subjective effects.Frequent drinking e-cigarette users reported more high-risk use behavior including consuming 6 + drinks/occasion and simultaneous use, and reported more e-cigarettes and alcohol related dependence symptoms and respiratory symptoms, compared to infrequent/non-drinker e-cigarette users. Alcohol quantity was positively associated with e-cigarette quantity among the high frequency drinking group. This study identified important use contexts that were associated with higher e-cigarette consumption including use of menthol or fruit flavored e-cigarettes, being in a car, and the presence of others. E-cigarette use and alcohol use both increased the levels of positive affect, physiological sensation, and craving for e-cigarettes, whereas only alcohol use significantly decreased negative affect. No interaction effects between e-cigarette use and alcohol use were found.The findings highlight the addiction and health risks associated with frequent co-use of e-cigarettes and alcohol, and also call for regulations on nontobacco flavorings in e-cigarette products.

Studies have shown some linkage between adverse childhood experiences (ACEs) and prescription opioid misuse. While preventable, once an individual is exposed to ACEs, they can have irreparable health impacts. Resilience could have protective effects on preventing those with ACEs from adulthood health-risk behaviors.

Secondary exposure to e-cigarette aerosol (passive vaping) will soon become a pressing public health issue in the world. Yet, the current knowledge about respiratory depositions of e-cigarette aerosol through passive vaping in human airways is limited due to critical weaknesses of traditional experimental methods. To fill in this important knowledge gap, this study proposed a special approach involving an upgraded Mobile Aerosol Lung Deposition Apparatus (MALDA) that consists of a set of human airway replicas including a head airway, tracheobronchial airways down to the 11th lung generation, and a representative alveolar section. In addition to the comprehensive coverage of human airways, the MALDA is easily transportable for providing efficient estimations of aerosol respiratory deposition. In this study, the MALDA was first evaluated in the laboratory and then applied to estimate the respiratory deposition associated with passive vaping in an indoor real-life setting. The results showed that the respiratory deposition data aligned closely with the conventional respiratory deposition curves not only in the head-to-TB region but also in the alveolar region. The strengths of MALDA demonstrate great promise for a wide variety of applications in real-life settings that could provide crucial information for future public health and indoor air quality studies.

Objective: Existing literature on young adults’ e-cigarette and polysubstance use focused on college students. This study examined the differences between college and noncollege groups on prevalenc...

Objective: E-cigarette use among college students has increased drastically in recent years. This study aims to inform development of a comprehensive measure of e-cigarette consumption for this population. Participants and Methods: This mixed-method study collected both quantitative and qualitative data from a sample of 43 experienced e-cigarette users from two college campuses, using a self-reported questionnaire and a semi-structured interview, in March-September of 2017. Results: College student users found some of the consumption questions in national surveys difficult to answer. Switching nicotine levels, mixing flavors, co-using with alcohol and marijuana, using with others who were vaping or drinking, and vaping in a car or indoor space were all common. The participants defined "regular user" based on ownership of a device rather than on quantity/frequency. Conclusions: A comprehensive e-cigarette consumption measure should cover the complex characteristics that are potentially associated with negative health consequences such as flavorings, co-use and social contexts.

Permutation tests are very useful when parametric assumptions are violated or distributions of test statistics are mathematically intractable. The major advantage of permutation tests is that the procedure is so general that it is applicable to most test statistics. The computational expense is, however, impractical in high-dimensional settings such as genomewide association studies. This study provides a comprehensive review of existing methods that can compute very small p-values efficiently. A common issue with existing methods is that they can only be applied to a specific test statistic. To fill in the knowledge gap, we propose a hybrid method of the sequential Monte Carlo and the Edgeworth expansion approximation for a studentized statistic, which is applicable to a variety of test statistics. The simulation results show that the proposed method performs better than competing methods. Furthermore, applications of the proposed method are demonstrated by statistical analysis on the genomewide association studies data from the Study of Addiction: Genetics and Environment (SAGE).

State-level prescription drug monitoring programs (PDMPs) have been implemented in most states. PDMPs enable registered prescribers to obtain real-time information on patients' prescription history to reduce non-medical use of controlled drugs. This study examined whether PDMP implementation and different levels of PDMP requirements were associated with physicians' patterns of prescribing opioid analgesics for patients with non-cancer chronic pain.This is a secondary analysis study using cross-sectional national data. Patients with non-cancer chronic pain from the 2012 National Ambulatory Medical Care Survey were included (weighted N=81,018,131; unweighted N=3295). Heckman two-step selection procedure employing two logistic regressions was used to explore the associations between PDMP requirements and physicians' prescribing behaviors, controlling for physician characteristics, patient characteristics, physician-healthcare system interaction, and physician-patient relationship, guided by the Eisenberg's model of physician decision making.State PDMP implementation status and requirement levels were not associated with physician opioid prescribing for non-cancer chronic pain treatment (p's ranged 0.30-0.32). Patients with Medicare coverage were more likely to be prescribed opioid analgesics than those with private health insurance (OR=1.55, p0.01). Hispanic patients were less likely to be prescribed opioid analgesics than non-Hispanic white patients (OR=0.61, p0.05).Findings indicated that the effectiveness of PDMPs on physicians' opioid prescribing tendency for non-cancer chronic pain treatment could not be supported. Policy makers should be aware of the need for redesigning PDMPs regarding requirements and enforcement for prescribers and related stakeholders. Future studies also are needed to identify characteristics contributing to PDMP effectiveness in reducing non-medical use of prescription opioids.

Aims This paper examined longitudinal marijuana use trajectories among drug-using youth presenting to the ED to inform intervention development. Methods Given interest in substance use and violence, this study oversampled those presenting with assault injuries. Assault-injured youth (ages 14–24) endorsing past 6-month drug use (n = 349), and a sex and age proportionally-sampled comparison group (n = 250) endorsing drug use, completed a baseline assessment and follow-ups at 6, 12, 18, and 24 months. Latent class trajectory analyses examined days of marijuana use over 2 years. Multinomial regression analyses examined baseline, 12-month and 24-month factors associated with substance use trajectory groups. Results Trajectory analyses identified 5 groups: Low (Low; 28.2%; n = 169); Intermittent (INT; 16.2%; n = 97); Moderate Decline (MD; 12.0%; n = 72); High decline (HD, 13.2%; n = 79) and Chronic (C; 30.4%; n = 182). At baseline, as compared to the Low group, the other trajectory groups were more likely to be male and have greater levels of physical aggression. At 12- and 24-months, negative and positive peer influences, incarceration and community violence were additional characteristics associated with the greater marijuana use trajectories (as compared to the Low group). Conclusions Interventions for drug-using youth presenting to the urban ED should address peer influences, physical aggression and community violence exposure, given the association between these characteristics and greater marijuana use trajectories.

Engagement in externalizing behavior is problematic. Deviant peer affiliation increases risk for externalizing behavior. Yet, peer effects vary across individuals and may differ across genes. This study determines gene × environment × development interactions as they apply to externalizing behavior from childhood to adulthood. A sample (n = 687; 68% male, 90% White) of youth from the Michigan Longitudinal Study was assessed from ages 10 to 25. Interactions between γ-amino butyric acid type A receptor γ1 subunit (GABRG1; rs7683876, rs13120165) and maladaptive peer behavior on externalizing behavior were examined using time-varying effect modeling. The findings indicate a sequential risk gradient in the influence of maladaptive peer behavior on externalizing behavior depending on the number of G alleles during childhood through adulthood. Individuals with the GG genotype are most vulnerable to maladaptive peer influences, which results in greater externalizing behavior during late childhood through early adulthood.

Objective Interpersonal violence is a significant public health problem, with substance use a key risk factor. Intensive longitudinal methods (ILMs) provide data on daily patterns/relationships between substance use and violence, informing prevention. Prior daily research has not focused on these relationships among urban minority samples. Methods Within an RCT comparing ILM assessment/schedule methods, 162-participants completed daily IVR (n = 81) or SMS (n = 81) assessments measuring 19 substance use and violence (partner/non-partner) behaviors daily for 90-days. GLMMs characterized between- and within-person predictors of daily violence. Results Participants [48.7%-female; age = 24.4; 62.3%-African-American; 66.7%-public assistance] completed an average of 46.5 daily reports [SD = 26.7]. Across 90-days, alcohol was characterized by episodic weekend use (average = 10 days-of-use, 34.4% drinking-days involved binge-drinking), while marijuana use was continuous (average = 27 days-of-use; 1.7 times/day), with no weekend differences. Among 118-violent conflicts, 52.5% occurred on weekends; 57.6% were with non-partners/peers; 61.0% involved perpetration/57.6% victimization; and 52.5% involved severe violence. For violence conflicts, 27.1% were preceded by alcohol/22.9% preceded by drug use. Between-person predictors of daily violence included retaliatory attitudes (AOR = 3.2) and anxiety (AOR = 1.1). Within-person predictors included weekends (AOR = 1.6), binge drinking (AOR = 1.9), non-medical prescription opioid use (AOR = 3.5) and illicit drug use (AOR = 8.1). Conclusion Among a high-risk urban minority sample, we found that higher baseline retaliatory attitudes and anxiety, as well as same-day binge drinking, non-medical prescription opioid use, and illicit drug use were associated with daily violence, likely reflecting both pharmacological and socio-contextual factors. Addressing substance use and retaliatory violence with tailored prevention efforts may aid in decreasing negative interpersonal violence outcomes.

Objectives Preadolescence substance exposure, which increases the risk of regular substance use, has been a public health concern. Although studies found that impulsivity is a predisposing factor of early substance exposure, the pathways through which impulsivity is associated with early substance exposure remain unclear. This study examined how family conflict mediates this association among U.S. preteens as family environment plays an essential role in pre-adolescent development. Methods Respondents (N = 11,800, 9–10 years old) from the Adolescent Brain Cognitive Development (ABCD) Study Release 2.01 (July 2019) were included in this study. Generalized structural equation modeling was performed to investigate the mediation effects of family conflict on the associations between childhood impulsivity and early exposure to alcohol and tobacco use, controlling for covariates based on the Problem Behavior Theory. Results Pre-adolescents with high impulsivity levels (≥90th percentile) were more likely to report early alcohol and tobacco exposure (total effect: ORs = 1.49 and 1.70, respectively), where 4.13% and 12.41% of the associations, respectively, were meditated by family conflict (indirect effect: ORs = 1.02 and 1.07; Sobel test ps = 0.022 and 0.005, respectively). Conclusions Family conflict mediates the associations between childhood impulsivity and early substance exposure among preteens, with higher impulsivity leading to more severe family conflicts that are, in turn, associated with a higher likelihood of early substance exposure. To prevent preteens with high impulsivity level from early use of substances, interventions may focus on reducing family conflicts such as parenting counseling that guides parents to strengthen conflict-resolution skills and create a stable home environment for preteens.

This study proposes a time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes. The motivating example demonstrates that this zero-inflated Poisson model allows investigators to study group differences in different aspects of substance use (e.g., the probability of abstinence and the quantity of alcohol use) simultaneously. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size increases; the accuracy under equal group sizes is only higher when the sample size is small (100). In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all settings. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size is larger. Moreover, the hypothesis test for the group difference in the zero component tends to be less powerful than the test for the group difference in the Poisson component. Copyright © 2016 John Wiley & Sons, Ltd.

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher’s combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

All fifty states have implemented prescription drug monitoring programs (PDMPs) to reduce misuse and diversion of controlled drugs. Interstate PDMP data sharing has been called for by clinical practitioners, but evidence to support the effectiveness of PDMP data sharing is lacking. This study examined whether PDMP interstate data sharing with bordering states was associated with prescriptions of opioids. This was a cross-sectional study that included patients with non-cancer chronic pain from the 2014 National Ambulatory Medical Care Survey (weighted N = 66,198,751; unweighted N = 2846). Multinomial logistic regression was performed to examine the association between PDMP interstate data sharing status and patients' being prescribed opioids for pain treatment, controlling for covariates guided by the Eisenberg's model of physician decision-making. Findings indicated that patients residing in states with interstate PDMP data sharing with all or partial bordering states were not less likely to be prescribed opioids compared to those living in states without interstate data sharing. Other factors such as patient age, health insurance type, new patient status, and physician adoption of electronic medical records were associated with the likelihood of patients' being prescribed opioids. This study concluded that current practice of interstate PDMP data sharing with bordering states was not associated with patients' being prescribed opioids for non-cancer chronic pain treatment. Future studies and policy efforts that unravel technological, legal, and political barriers to reciprocal and equal interstate data sharing with bordering states should be warranted to inform PDMP redesign and in turn, augment overall PDMP effectiveness in reducing misuse of prescription opioids.

Alcoholism is a heterogeneous disorder; however, characterization of life-course variations in symptomatology is almost nonexistent, and developmentally early predictors of variations are very poorly characterized. In this study, the course of alcoholic symptomatology over 32 years is differentiated, and predictors and covariates of trajectory class membership are identified. A community sample of alcoholic and neighborhood matched control families, 332 men and 336 women, was recruited based on alcoholism in the men. Symptoms were assessed retrospectively at baseline (mean age = 32) back to age 15 and prospectively from baseline every 3 years for 15 years. Trajectory classes were established using growth mixture modeling. Men and women had very similarly shaped trajectory classes: developmentally limited (men: 29%, women: 42%), developmentally cumulative (men: 26%, women: 38%), young adult onset (men: 31%, women: 21%), and early onset severe (men: 13%). Three factors at age 15 predicted class membership: family history of alcoholism, age 15 symptoms, and level of childhood antisocial behavior. Numerous measures of drinking and other psychopathology were also associated with class membership. The findings suggest that clinical assessments can be crafted where the profile of current and historical information can predict not only severity of prognosis but also future moderation of symptoms and/or remission over intervals as long as decades.

Summary This study proposes a two-stage approach to characterize individual developmental trajectories of health risk behaviours and to delineate their time varying effects on short-term or long-term health outcomes. Our model can accommodate longitudinal covariates with zero-inflated counts and discrete outcomes. The longitudinal data of a well-known study of youths at high risk of substance abuse are presented as a motivating example to demonstrate the effectiveness of the model in delineating critical developmental periods of prevention and intervention. Our simulation study shows that the performance of the model proposed improves as the sample size or number of time points increases. When there are excess 0s in the data, the regular Poisson model cannot estimate either the longitudinal covariate process or its time varying effect well. This result, therefore, emphasizes the important role that the model proposed plays in handling zero inflation in the data.

Background Retrospective timeline follow-back (TLFB) data and prospective daily process data have been frequently collected in addiction research to characterize behavioral patterns. Although previous validity studies have demonstrated high correlations between these two types of data, the conventional method adopted in those studies was based on summary measures that may lose critical information and the Pearson's correlation coefficient that has an undesirable property. This study proposes the functional concordance correlation coefficient to address these issues. Methods We use real data collected from a randomized experiment to demonstrate the applications of the proposed method and compare its analytical results with those of the conventional method. We also conduct a simulation study based on the real data to evaluate the level of overestimation associated with the conventional method. Results The results of the real data example indicate that the correlation between these two types of data varies across substances (alcohol vs. marijuana) and assessment schedules (daily vs. weekly). Additionally, the correlations estimated by the conventional method tend to be higher than those estimated by the proposed method. The simulation results further show that the magnitude of overestimation associated with the conventional method is greatest when the true correlation is medium. Conclusions The findings of the real data example imply that daily assessments are particularly beneficial for characterizing more variable behaviors like alcohol use, whereas weekly assessments may be sufficient for low variation events such as marijuana use. The proposed method is a better approach for evaluating the validity of TLFB data.

Background Existing longitudinal surveys focused on the association between ever use of e-cigarettes and combustible cigarette consumption, making it difficult to infer what characteristics of e-cigarette use could potentially change combustible cigarette use behavior, which may have long-term health consequences. Although e-cigarettes' efficacy of alleviating dependence symptoms was supported by studies conducted in laboratory settings, whether the results can be translated into symptom reduction in the real world and over time is an open question. Methods This study conducted secondary analysis on the Waves 1-2 data of the Population Assessment of Tobacco and Health (PATH) Study to examine the association between e-cigarette use characteristics (frequency, flavoring, and voltage adjustment) and combustible cigarette use outcomes (frequency, quantity, and symptoms), using the Heckman 2-step selection procedure with the selection bias controlled. The inclusion criteria ensured that we followed an adult cohort of exclusive combustible cigarette users at Wave 1. Results The result shows that higher frequency of e-cigarette use was associated with lower combustible cigarette consumption and dependence symptoms, controlling for the corresponding baseline cigarette use variable and other confounders. Given the frequency of e-cigarette use, the feature of voltage adjustment was not significantly associated with any of the cigarette use outcomes. Flavoring, on the other hand, was associated with lower quantity of cigarette use. Conclusions Exclusive smokers who start using e-cigarettes do indeed change the frequency and quantity with which they smoke cigarettes. E-cigarette use may also help reduce dependence symptoms.

This chapter provides a nontechnical review of new statistical methodology for longitudinal data analysis that has been published in statistical journals in recent years. The methodology has applications in four important areas: (1) conducting variable selection among many highly correlated risk factors when the outcome measure is zero-inflated count; (2) characterizing developmental trajectories of symptomatology using regression splines; (3) modeling the longitudinal association between risk factors and substance use outcomes as time-varying effects; and (4) testing measurement reactivity and predictive validity using daily process data. The excellent statistical properties of the methods introduced have been supported by simulation studies. The applications in alcohol and substance abuse research have also been demonstrated by graphs on real longitudinal data.

African American youth are among those at greatest risk for experiencing violence victimization. Notably, the mortality rate of cervical cancer for African American women is also twice that of white women. To date, we know of no literature using longitudinal data to examine how violence victimization relates to Papanicolaou (Pap) smear results or cervical cancer in this population. Our study examines how violence victimization during adolescence (age 15 to 18) influences psychological distress, perceived social support, heavy substance abuse, and sexual risk behaviors during emerging adulthood (age 20 to 23), and subsequent Pap smear outcomes during young adulthood (age 29 to 32).This study is based on 12 waves of data collected in a longitudinal study of 360 African American women from mid-adolescence (ninth grade, mean age = 14.8 years) to young adulthood (mean age = 32.0 years). We used structural equation modeling analysis to examine the hypothesized model.Violence victimization during adolescence had a direct effect on decreased social support, increased psychological distress, and increased heavy cigarette use during emerging adulthood. Better social support was also associated with fewer sexual partners during emerging adulthood and lower odds of abnormal Pap smear results during young adulthood. The effect of violence victimization on abnormal Pap smear was mediated by social support.Our results show that violence victimization during adolescence has long-term negative effects through multiple pathways that persist into adulthood. Our findings also suggest that social support may help to compensate against other risk factors. Interventions designed to address the perceived support may help victims cope with their experience.

Adolescent cannabis use has been associated with several negative outcomes. A previous study on an adult sample found alcohol and cigarette use to be associated with three cannabis use stages: initiation, reinitiation, and persistence, which represent distinct periods of use regarding progression and severity. Yet, the risk factors associated with these important stages have never been examined in a longitudinal study spanning adolescence to emerging adulthood.Using longitudinal data from Add Health Waves 1-3, 1775 nonusers, 200 prior users, and 384 current users of cannabis were identified who were at risk of cannabis use initiation, reinitiation, and persistence, respectively. Three logistic regressions were conducted to examine the effects of prior cigarette and alcohol use on the three cannabis use stages, controlling for sociodemographic factors.Early onset of cigarette use (OR=2.04, p=0.006) and higher alcohol use frequency (OR=1.40, p0.001) were associated with cannabis use initiation. Greater cigarette use quantity was associated with a lower likelihood of reinitiation of cannabis use (OR=0.58, p=0.02). Increased cannabis use frequency (OR=1.72, p=0.006) and higher alcohol use frequency (OR=1.32, p=0.048) were associated with persistence of cannabis use. Sociodemographic factors such as household income, sex, and being older adolescents were associated with different cannabis use stages.Prior cigarette and alcohol use affect the risk of initiation, reinitiation, and persistence of cannabis use. The specific risk factors vary across different cannabis use stages. Interventions to prevent adolescent cannabis use should recognize these different risk factors and tailor to the stages of cannabis use.

Statement-of-Purpose This analysis examined daily patterns of violence among emerging adults. Methods/Approach Participants (n=352) from a 2 year study (Flint Youth Injury Study) of drug-using youth seeking ED care (for assault or other reasons) were enrolled in a 2nd wave study, in which they were randomised to complete daily or weekly assessments. This analysis examines daily data (n=162); 19-items measured violence (aggression/victimisation, partner/non-partner) and associated substance use, and were collected prospectively via either IVR (n=81) or text (n=81) over 90 days. Results Participants [n=162; age=24.4; 62.3% African-American; 67% public assistance;59% ED visit for assault] completed an average of 48.3-daily reports [SD=26.9;range=1–89]. During the 90 day period, 27% of participants reported violence, with 65% reporting one violent day and 53% of violence days occurred on weekends. Among 118-violence days, 42% were with a partner (58% non-partner); 61% involved aggression (58%-victimisation); and 53% involved severe violence (e.g., beat-up, gun/knife). Among those involved with violence, 45% reported using drugs, alcohol, or both in the 3 hours before the encounter. Alcohol (OR=4.6,p Conclusion Among a high-risk sample, nearly a third of participants reported violent encounters during the 90 day period, with rates highest on weekends. Substance use preceded violent encounters on almost half of violence days, highlighting the relationships (e.g., acute pharmacological, clustering of problem behaviours) that exist between substance use and violence. Significance/Contribution Prior studies characterising daily violence behaviours are limited and data will aid future intervention development for violence prevention initiatives.

Background Interactive voice response (IVR) and short message service (SMS) systems have been used to collect daily process data on substance use. Yet, their relative compliance, use patterns, and user experiences are unknown. Furthermore, recent studies presented the potential of a hybrid weekly protocol requiring recall of behaviors in past week right after the weekend, in order to reduce the concerns about low compliance and measurement reactivity associated with daily data collection and also provide high quality data on the peak of use. Methods This study randomized substance users to four ( 2 × 2 ) assessment groups with different combinations of assessment methods (IVR or SMS) and schedules (daily or weekly). The compliance rates and use patterns during the experimental period of 90 days and user experiences reported after the period were compared across the groups. Results When IVR was assigned, the weekly schedule generated a higher compliance rate than the daily schedule. When SMS was used, however, the assessment schedule did not have an effect on compliance. While both the daily and weekly surveys via IVR can be completed within a short time, the weekly survey administered via SMS took much longer than its daily counterpart. Such an increased time consumption may offset the benefit of a less frequent assessment schedule. Conclusions IVR is a better choice for delivering the hybrid protocol of weekly collection of daily process data because of its higher compliance rate, shorter duration, and lower likelihood of interruption during data collection.

The debate about whether measurement reactivity exists in daily diary research on substance use is still unsettled due to the issues of study design and statistical methodology. This study proposes a time-varying effect model (TVEM) that characterizes the trajectory of substance use behaviors with nonparametric functions determined by the data rather than imposes presumed parametric functions. It also allows researchers to investigate the effect of measurement reactivity on not only the likelihood of using substances but also the amount of substance use. The TVEM was applied to analyze diary data on alcohol and marijuana use collected from an experiment, which randomized 307 participants in Michigan into daily and weekly assessment schedules during 2014–2016. This study found short-term measurement reactivity on alcohol use, but did not find a significant reactivity effect on marijuana use. The daily group had smaller odds of abstinence from drinking but lower expected drinking quantity in the first week of assessment, which dissipated by the second week. The results indicate that although daily self-monitoring could have short-term reactivity on substance use behaviors that tend to fluctuate across days, such as alcohol use, it does not affect substance use behaviors that are quite consistent, such as marijuana use. Our findings imply that although daily monitoring of drinking may motivate people to reduce the quantity consumed once they start to drink, it may also arouse their desire to start drinking. Yet, both effects tend to last only one week, as participants accommodate to the monitoring by the second week.

Aims Weexaminedtherelationshipbetweenalcoholexpectanciesinchildhoodandonsetof drinking,bingedrinking and drunkenness in adolescence and the influence of drinking onset on expectancy development. Design A prospec- tive, longitudinal study of children assessed for alcohol expectancies and drinking at four time-points between ages 6 and 17 years.Setting Community study of families at high risk for alcoholism conducted in a four-county area in the Midwestern United States. Participants The study involved 614 children; 460 were children of alcoholics and 70% were male. Measurements Expectancies about alcohol effects were measured using the Beverage Opinion Question- naire and child's drinking by the Drinking and Drug History—Youth Form. Findings Partial factor invariance was found for expectancy factors from ages 6 to 17 years. Survival analysis showed that social/relaxation expectancies in childhood predicted time to onset of binge drinking and first time drunk (Wald χ 2 , 1 d.f. = 3.8, P = 0.05 and 5.0, P < 0.05, respectively).The reciprocal effect was also present; when adolescents began drinking, there was an increase in social/relaxation expectancy and a concomitant increase in slope of the expectancy changes lasting throughout adolescence. Conclusions A reciprocal relationship exists between childhood alcohol expectancies and the develop- ment of alcohol involvement. Higher expectancies for positive effects predict earlier onset of problem drinking. Onset of use, in turn, predicts an increase in rate of development of positive expectancies.