Faculty Bibliography

BACKGROUND AND AIMS:Both local socio-economic conditions and prescription opioid supply are associated with drug overdose deaths, which exhibit substantial geographical heterogeneity across the United States. We measured whether the associations of prescription opioid supply with drug overdose deaths vary by local socio-economic conditions. DESIGN:Ecological county-level study, including 3109 US counties between 2006 and 2019 (n = 43 526 county-years) using annual mortality data. SETTING:United States. CASES:A total of 711 447 drug overdose deaths. MEASUREMENTS:We modeled overdose counts using Bayesian hierarchical Poisson models, estimating associations between four types of drug overdose deaths (deaths involving any drugs, any opioid, prescription opioids only and heroin), prescription opioid supply and five socio-economic indicators: unemployment, poverty rate, income inequality, Rey index (components include mean household income, % high school graduates, % blue-collar workers and unemployment rate), and American human development index (HDI; an indicator of community wellbeing). FINDINGS:Drug overdose deaths and all substance-specific overdose deaths were higher in counties with higher income inequality [adjusted odds ratios (aORs) = 1.09-1.13], Rey index (aORs = 1.15-1.21) and prescription opioid supply (aORs = 1.14-1.21), and lower in counties with higher HDI scores (aORs = 0.75-0.92). Poverty rate, income inequality and HDI scores were found to modify the effect of prescription opioid supply on heroin overdose deaths. The plot of the interactions showed that when disadvantage is high, increasing prescription opioid supply does not increase heroin overdose deaths. The less disadvantage there is, indicated by lower poverty rates, higher HDI scores and lower income inequality, the greater the effect of increasing prescription opioid supply relative to population size on heroin overdose deaths in US counties. CONCLUSIONS:In the United States, prescription opioid supply is associated with higher drug overdose deaths; associations are stronger in counties with less disadvantage and less income inequality, but only for heroin overdose deaths.

BACKGROUND AND AIMS:Low outcome prevalence, often observed with opioid-related outcomes, poses an underappreciated challenge to accurate predictive modeling. Outcome class imbalance, where non-events (i.e. negative class observations) outnumber events (i.e. positive class observations) by a moderate to extreme degree, can distort measures of predictive accuracy in misleading ways, and make the overall predictive accuracy and the discriminatory ability of a predictive model appear spuriously high. We conducted a simulation study to measure the impact of outcome class imbalance on predictive performance of a simple SuperLearner ensemble model and suggest strategies for reducing that impact. DESIGN, SETTING, PARTICIPANTS:Using a Monte Carlo design with 250 repetitions, we trained and evaluated these models on four simulated data sets with 100 000 observations each: one with perfect balance between events and non-events, and three where non-events outnumbered events by an approximate factor of 10:1, 100:1, and 1000:1, respectively. MEASUREMENTS:We evaluated the performance of these models using a comprehensive suite of measures, including measures that are more appropriate for imbalanced data. FINDINGS:Increasing imbalance tended to spuriously improve overall accuracy (using a high threshold to classify events vs non-events, overall accuracy improved from 0.45 with perfect balance to 0.99 with the most severe outcome class imbalance), but diminished predictive performance was evident using other metrics (corresponding positive predictive value decreased from 0.99 to 0.14). CONCLUSION:Increasing reliance on algorithmic risk scores in consequential decision-making processes raises critical fairness and ethical concerns. This paper provides broad guidance for analytic strategies that clinical investigators can use to remedy the impacts of outcome class imbalance on risk prediction tools.

PURPOSE/UNASSIGNED:We aimed to synthesize insights from systems science approaches applied to domestic and gender-based violence. METHODS/UNASSIGNED:We conducted a systematic review of systems science studies (systems thinking, group model-building, agent-based modeling [ABM], system dynamics [SD] modeling, social network analysis [SNA], and network analysis [NA]) applied to domestic or gender-based violence, including victimization, perpetration, prevention, and community responses. We used blinded review to identify papers meeting our inclusion criteria (i.e., peer-reviewed journal article or published book chapter that described a systems science approach to domestic or gender-based violence, broadly defined) and assessed the quality and transparency of each study. RESULTS/UNASSIGNED:Our search yielded 1,841 studies, and 74 studies met our inclusion criteria (45 SNA, 12 NA, 8 ABM, and 3 SD). Although research aims varied across study types, the included studies highlighted social network influences on risks for domestic violence, clustering of risk factors and violence experiences, and potential targets for intervention. We assessed the quality of the included studies as moderate, though only a minority adhered to best practices in model development and dissemination, including stakeholder engagement and sharing of model code. CONCLUSIONS/UNASSIGNED:Systems science approaches for the study of domestic and gender-based violence have shed light on the complex processes that characterize domestic violence and its broader context. Future research in this area should include greater dialogue between different types of systems science approaches, consideration of peer and family influences in the same models, and expanded use of best practices, including continued engagement of community stakeholders. SUPPLEMENTARY INFORMATION/UNASSIGNED:The online version contains supplementary material available at 10.1007/s10896-023-00578-8.

BACKGROUND:Common adolescent psychiatric symptoms cluster into two dominant domains: internalizing and externalizing. Both domains are linked to self-esteem, which serves as a protective factor against a wide range of internalizing and externalizing problems. This study examined trends in US adolescents' self-esteem and externalizing symptoms, and their correlation, by sex and patterns of time use. METHODS:= 338 896 adolescents, grades:8/10/12, years:1991-2020), we generated six patterns of time use using latent profile analysis with 17 behavior items (e.g. sports participation, parties, paid work). Groups were differentiated by high/low engagement in sports and either paid work or high/low peer socialization. Within each group, we mapped annual, sex-stratified means of (and correlation between) self-esteem and externalizing factors. We also examined past-decade rates of change for factor means using linear regression and mapped proportions with top-quartile levels of poor self-esteem, externalizing symptoms, or both. RESULTS:We found consistent increases in poor self-esteem, decreases in externalizing symptoms, and a positive correlation between the two across nearly all activity groups. We also identified a relatively constant proportion of those with high levels of both in every group. Increases in poor self-esteem were most pronounced for female adolescents with low levels of socializing, among whom externalizing symptoms also increased. CONCLUSIONS:Rising trends in poor self-esteem are consistent across time use groups, as is the existence of a group facing poor self-esteem and externalizing symptoms. Effective interventions for adolescents' poor self-esteem/co-occurring symptoms are needed broadly, but especially among female adolescents with low peer socialization.

The association between recent release from incarceration and dramatically increased risk of fatal overdose is well-established at the individual level. Fatal overdose and. arrest/release are spatially clustered, suggesting that this association may persist at the neighborhood level. We analyzed multicomponent data from Rhode Island, 2016-2020, and observed a modest association at the census tract level between rates of release per 1000 population and fatal overdose per 100,000 person-years, adjusting for spatial autocorrelation in both the exposure and outcome. Our results suggest that for each additional person released to a given census tract per 1000 population, there is a corresponding increase in the rate of fatal overdose by 2 per 100,000 person years. This association is more pronounced in suburban tracts, where each additional release awaiting trial is associated with an increase in the rate of fatal overdose of 4 per 100,000 person-years and 6 per 100,000 person-years for each additional release following sentence expiration. This association is not modified by the presence or absence of a licensed medication for opioid use disorder (MOUD) treatment provider in the same or surrounding tracts. Our results suggest that neighborhood-level release rates are moderately informative as to tract-level rates of fatal overdose and underscore the importance of expanding pre-release MOUD access in correctional settings. Future research should explore risk and resource environments particularly in suburban and rural areas and their impacts on overdose risk among individuals returning to the community.

IMPORTANCE:Cannabis use disorder (CUD) is increasing among US adults. Few national studies have addressed the role of medical cannabis laws (MCLs) and recreational cannabis laws (RCLs) in these increases, particularly in patient populations with high rates of CUD risk factors. OBJECTIVE:To quantify the role of MCL and RCL enactment in the increases in diagnosed CUD prevalence among Veterans Health Administration (VHA) patients from 2005 to 2019. DESIGN, SETTING, AND PARTICIPANTS:Staggered-adoption difference-in-difference analyses were used to estimate the role of MCL and RCL in the increases in prevalence of CUD diagnoses, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, and patient age group, sex, and race and ethnicity. Patients aged 18 to 75 years with 1 or more VHA primary care, emergency department, or mental health visit and no hospice/palliative care within a given calendar year were included. Time-varying yearly state control covariates were state/year rates from American Community Survey data: percentage male, Black, Hispanic, White, 18 years or older, unemployed, income below poverty threshold, and yearly median household income. Analysis took place between February to December 2022. MAIN OUTCOMES AND MEASURES:As preplanned, International Classification of Diseases, Clinical Modification, ninth and tenth revisions, CUD diagnoses from electronic health records were analyzed. RESULTS:The number of individuals analyzed ranged from 3 234 382 in 2005 to 4 579 994 in 2019. Patients were largely male (94.1% in 2005 and 89.0% in 2019) and White (75.0% in 2005 and 66.6% in 2019), with a mean (SD) age of 57.0 [14.4] years. From 2005 to 2019, adjusted CUD prevalences increased from 1.38% to 2.25% in states with no cannabis laws (no CLs), 1.38% to 2.54% in MCL-only enacting states, and 1.39% to 2.56% in RCL-enacting states. Difference-in-difference results indicated that MCL-only enactment was associated with a 0.05% (0.05-0.06) absolute increase in CUD prevalence, ie, that 4.7% of the total increase in CUD prevalence in MCL-only enacting states could be attributed to MCLs, while RCL enactment was associated with a 1.12% (95% CI, 0.10-0.13) absolute increase in CUD prevalence, ie, that 9.8% of the total increase in CUD prevalence in RCL-enacting states could be attributed to RCLs. The role of RCL in the increases in CUD prevalence was greatest in patients aged 65 to 75 years, with an absolute increase of 0.15% (95% CI, 0.13-0.17) in CUD prevalence associated with RCLs, ie, 18.6% of the total increase in CUD prevalence in that age group. CONCLUSIONS AND RELEVANCE:In this study of VHA patients, MCL and RCL enactment played a significant role in the overall increases in CUD prevalence, particularly in older patients. However, consistent with general population studies, effect sizes were relatively small, suggesting that cumulatively, laws affected cannabis attitudes diffusely across the country or that other factors played a larger role in the overall increases in adult CUD. Results underscore the need to screen for cannabis use and CUD and to treat CUD when it is present.

Policy Points People are dying at record numbers from overdose in the United States. Concerted action has led to a number of successes, including reduced inappropriate opioid prescribing and increased availability of opioid use disorder treatment and harm-reduction efforts, yet ongoing challenges include criminalization of drug use and regulatory and stigma barriers to expansion of treatment and harm-reduction services. Priorities for action include investing in evidence-based and compassionate policies and programs that address sources of opioid demand, decriminalizing drug use and drug paraphernalia, enacting policies to make medication for opioid use disorder more accessible, and promoting drug checking and safe drug supply.

BACKGROUND:Naloxone distribution is central to ongoing efforts to address the opioid overdose crisis. Some critics contend that naloxone expansion may inadvertently promote high-risk substance use behaviors among adolescents, but this question has not been directly investigated. METHODS:We examined relationships between naloxone access laws and pharmacy naloxone distribution with lifetime heroin and injection drug use (IDU), 2007-2019. Models generating adjusted odds ratios (aOR) and 95% confidence intervals (CI) included year and state fixed effects, controlled for demographics and sources of variation in opioid environments (e.g., fentanyl penetration), as well as additional policies expected to impact substance use (e.g., prescription drug monitoring). Exploratory and sensitivity analyses further examined naloxone law provisions (e.g., third-party prescribing) and applied e-value testing to assess vulnerability to unmeasured confounding. RESULTS:Adoption of any naloxone law was not associated with changes in adolescent lifetime heroin or IDU. For pharmacy dispensing, we observed a small decrease in heroin use (aOR: 0.95 [CI: 0.92, 0.99]) and a small increase in IDU (aOR: 1.07 [CI: 1.02, 1.11]). Exploratory analyses of law provisions suggested that third-party prescribing (aOR: 0.80, [CI: 0.66, 0.96]) and non-patient-specific dispensing models (aOR: 0.78, [CI: 0.61, 0.99]) were associated with decreased heroin use but not decreased IDU. Small e-values associated with the pharmacy dispensing and provision estimates indicate that unmeasured confounding may explain observed findings. CONCLUSION:Naloxone access laws and pharmacy naloxone distribution were more consistently associated with decreases rather than increases in lifetime heroin and IDU among adolescents. Our findings therefore do not support concerns that naloxone access promotes high-risk adolescent substance use behaviors. As of 2019, all US states have adopted legislation to improve naloxone access and facilitate use. However, further removal of adolescent naloxone access barriers is an important priority given that the opioid epidemic continues to affect people of all ages.

PURPOSE/OBJECTIVE:Adolescent internalizing symptoms are increasing in the United States. Changes in parenting practices, including monitoring and communication, have been hypothesized to contribute to these increases. We aimed to estimate trends in parenting practices and understand whether shifts in such practices explain increases in internalizing symptoms. METHODS:Using 1991-2019 Monitoring the Future data (N = 933,645), we examined trends in five parental practices (i.e., knowledge [three combined indicators], monitoring [four combined indicators], communication, weekend curfew, social permission) with ordinal regressions. We tested associations between parental practices and indicators of being in the top decile of depressive affect, low self-esteem, and self-derogation using survey-weighted logistic regressions, adjusted for gender, race/ethnicity, grade, and parental education. RESULTS:The prevalences of parental practices have not changed over time, with the exception of increases in parental knowledge, specifically parents knowing where an adolescent is after school (1999-2019 mean increase: 4.34 to 4.61 out of 5) and knowing an adolescent's location (4.16-4.49) and company at night (4.26-4.51). Higher levels of each practice were associated with lower internalizing symptoms (e.g., adjusted odds ratio for a high depressive affect based on a one-unit increase in parental knowledge: 0.89, 95% confidence interval: 0.88, 0.90). Patterns were consistent across internalizing outcomes and decade. DISCUSSION/CONCLUSIONS:Parental knowledge, monitoring, and other practices are stable protective factors for adolescent mental health. These factors are not changing in a manner that would plausibly underlie increases in internalizing symptoms. Future interventions should provide resources that support these parental practices which are tied to adolescent internalizing symptoms.