Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies.

BACKGROUND: Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery. METHODS: We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors. RESULTS: There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87). CONCLUSIONS: These methods will be useful for evaluating intervention packages in studies with network features.

Assessing Direct and Spillover Effects of Intervention Packages in Network-Randomized Studies.

Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component in the overall package effectiveness can improve intervention delivery. We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed themselves under intervention in the network versus no intervention in a control network. We estimated effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using Marginal Structural Models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors. There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant-visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (Rate Ratio = 0.61; 95% confidence interval= 0.43, 0.87). These methods will be useful to evaluate intervention packages in studies with network features.

Development of a new measure of encounters with health care barriers: The Commonly Experienced Health Care Barriers Index.

Common barriers to health care, such as lack of insurance or transportation, hold a key theoretical role in many models attempting to explain problems with health care utilization (not seeking needed health care). However, the assessment of barriers is often post hoc, with no existing scales appropriate for a general population. This study developed and tested a new measure of commonly experienced health care barriers across three studies (Study 1, N = 194; Study 2, N = 206; Study 3, N = 741). Items were developed in line with recommendations for causal indicator models, emphasizing content validity. The measure showed preliminary test-retest reliability, sensitivity to health care inequities between Black and White individuals (beyond socioeconomic status and including association with health care discrimination), expected associations with health care utilization problems and other health experiences and life stressors, and unique associations with health care utilization problems accounting for health experiences and life stressors. The new measure has the potential to identify modifiable factors related to health care inequities and common problems with health care utilization. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Modified-Weight Healthy Eating Index-2015 Scores Are More Strongly Associated With Mortality Risk Than Standard Scores.

BACKGROUND: Various diet quality scores are consistently and similarly associated with mortality risk. Emerging evidence suggests that individual diet quality components are differentially associated with mortality risk, but it is unclear whether or not modified weights reflective of relative component differences would strengthen mortality associations. OBJECTIVE: This study examined whether Healthy Eating Index 2015 (HEI-2015) scores with modified (vs standard) component weights are differentially associated with mortality risk. DESIGN: This was a longitudinal analysis of the National Health and Nutrition Examination Survey III (1988-94) with 23 years of mortality follow-up. The HEI-2015 and modified-weight scores were calculated from one 24-hour recall. The a priori Key Facets HEI was a subset score equivalently weighting fruits, vegetables, whole grains, and seafood and plant proteins. In the least absolute shrinkage and selection operator regression-weighted HEI, components were assigned weights reflecting relative mortality risk associations. PARTICIPANTS/SETTING: Analyses included 10,789 US adults (aged 20 years and older) who were not pregnant and without prior diabetes, cancer, cardiovascular disease, or chronic kidney disease diagnoses. MAIN OUTCOME MEASURES: All-cause and cardiovascular disease mortality risk were the primary outcomes examined. STATISTICAL ANALYSES PERFORMED: Three energy-adjusted HEI scores were assigned to quintiles; covariate-adjusted sex-stratified Cox models with age as the timescale assessed associations between and trends across quintiles of HEI scores and all-cause and cardiovascular disease mortality risk. RESULTS: Modified-weight HEI scores were associated with 23% to 38% reduced all-cause mortality risk in the highest vs lowest quintile, whereas comparisons were only significant for women (Key Facets P = 0.02 and least absolute shrinkage and selection operator regression-weighted P = 0.001; for men P = 0.06 on both scores), trends across quintiles of modified-weight scores were significant for men and women. The HEI-2015 was not significantly associated with all-cause mortality risk, and none of the scores were associated with cardiovascular disease mortality risk. CONCLUSIONS: Only modified-weight HEI scores were associated with reduced all-cause mortality risk. Findings suggest modified diet quality weighting schemes warrant further examination to determine their replicability.

Overall, Direct, Spillover, and Composite Effects of Components of a Peer-Driven Intervention Package on Injection Risk Behavior Among People Who Inject Drugs in the HPTN 037 Study.

We sought to disentangle effects of the components of a peer-education intervention on self-reported injection risk behaviors among people who inject drugs (n = 560) in Philadelphia, US. We examined 226 egocentric groups/networks randomized to receive (or not) the intervention. Peer-education training consisted of two components delivered to the intervention network index individual only: (1) an initial training and (2) "booster" training sessions during 6- and 12-month follow up visits. In this secondary data analysis, using inverse-probability-weighted log-binomial mixed effects models, we estimated the effects of the components of the network-level peer-education intervention upon subsequent risk behaviors. This included contrasting outcome rates if a participant is a network member [non-index] under the network exposure versus under the network control condition (i.e., spillover effects). We found that compared to control networks, among intervention networks, the overall rates of injection risk behaviors were lower in both those recently exposed (i.e., at the prior visit) to a booster (rate ratio [95% confidence interval]: 0.61 [0.46-0.82]) and those not recently exposed to it (0.81 [0.67-0.98]). Only the boosters had statistically significant spillover effects (e.g., 0.59 [0.41-0.86] for recent exposure). Thus, both intervention components reduced injection risk behaviors with evidence of spillover effects for the boosters. Spillover should be assessed for an intervention that has an observable behavioral measure. Efforts to fully understand the impact of peer education should include routine evaluation of spillover effects. To maximize impact, boosters can be provided along with strategies to recruit especially committed peer educators and to increase attendance at trainings. Clinical Trials Registration Clinicaltrials.gov NCT00038688 June 5, 2002.

RESUMEN: Intentamos desenmarañar los efectos de los componentes de una intervención de educación entre pares sobre los comportamientos de inyección de riesgo autorreportados entre personas que se inyectan drogas (n = 560; 226 grupos/redes egocéntricos(as)) aleatorizados(as) a recibir (o no) la intervención en Filadelfia, EUA. Dos componentes fueron administrados a índices de redes de intervención: una capacitación inicial y sesiones de "refuerzo" durante visitas de seguimiento. Usando modelos log-binomial de efectos mixtos ponderados por probabilidad inversa, estimamos los efectos de dichos componentes sobre los comportamientos de riesgo posteriores. Encontramos que en comparación con las redes control, en las redes de intervención, las tasas generales de comportamientos de inyección de riesgo fueron más bajas en ambas aquellas expuestas recientemente a un refuerzo (razón de tasas [intervalo de confianza del 95%]: 0.61 [0.46­0.82]) y aquellas no expuestas recientemente (0.81 [0.67­0.98]). Solamente los refuerzos tuvieron efectos derrame (i.e., contraste de las tasas de resultados si es miembro [no índice] de una red en una red con exposición reciente versus bajo la condición control) significativos (p. ej., 0.59 [0.41­0.86] para la exposición reciente).

A mixed-methods study to inform development of a caregiver-specific problem list for cancer distress screening.

OBJECTIVE: Oncology guidelines for distress management recommend use of the single-item distress thermometer (DT) and accompanying Problem List (PL) to identify patients with high distress levels and their potential sources of distress. However, oncology practices have yet to establish standardized protocols to screen and triage caregivers with high distress levels. With an eye toward integrating caregiver-centered support services into cancer care, this mixed-methods study sought to assess caregiver distress and challenges that may contribute to their distress. METHODS: Nineteen caregivers of metastatic breast cancer patients (60% female, 47% ethnic/racial minority) completed an interview and a survey comprised of the DT, the original 39-item PL, and five additional caregiver-specific PL items. RESULTS: Caregivers reported moderate distress levels and more than half exceeded the National Comprehensive Cancer Network (NCCN) cut-off, denoting significant distress. There was no association between caregiver distress and the number of items endorsed on the original PL. Qualitative analysis identified nine problem domains as areas of caregiver unmet need needs (i.e., practical challenges, caregiving responsibilities, social/relationship issues, caregiver and patient emotional well-being, caregiver and patient physical well-being, spiritual well-being, and communication). Two of the problem domains (caregiving responsibilities and communication) were not captured in any way by the original PL. CONCLUSION: With further research and development, the identified domains could serve as the basis for a caregiver-specific PL to facilitate triage and referral when incorporated as part of routine distress screening.

Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs.

Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant's exposure affects another participant's outcome. PWUD are often members of networks defined by social, sexual, and drug-use partnerships and their receipt of interventions can affect other members in their network. For example, HIV interventions with possible spillover include educational training about HIV risk reduction, pre-exposure prophylaxis, or treatment as prevention. In turn, intervention effects frequently depend on the network structure, and intervention coverage levels and spillover can occur even if not measured in a study, possibly resulting in an underestimation of intervention effects. Recent methodological approaches were developed to assess spillover in the context of network-based studies. This tutorial provides an overview of different study designs for network-based studies and related methodological approaches for assessing spillover in each design. We also provide an overview of other important methodological issues in network studies, including causal influence in networks and missing data. Finally, we highlight applications of different designs and methods from studies of PWUD and conclude with an illustrative example from the Transmission Reduction Intervention Project (TRIP) in Athens, Greece.

Evaluation of the association between health insurance status and healthcare utilization and expenditures among adult cancer survivors in the United States.

BACKGROUND: Health care expenditures for cancer care has increased significantly over the past decade and is further projected to rise. This study examined the associations between health insurance status and total direct health care expenditures and health care utilization among cancer survivors living in the United States. METHODS: A cross-sectional study of cancer survivors aged ≥18 years, identified from the Medical Expenditures Panel Survey (MEPS) during 2017 using International Classification of Diseases, Tenth Revision codes specific for cancer. Health insurance was categorized into Private, Medicare, Medicaid, and uninsured. Multivariable ordinary least squares regression was used to examine the association between log expenditures and health insurance. Negative binomial regression with log link was used to obtain adjusted incident rate ratios (AIRR) for health care utilization. Survey weights were used to produce nationally representative estimates of the US population. RESULTS: A total of 1140 (weighted = 13.9 million) cancer survivors were identified. Compared to the adjusted mean annual health care expenditures for the private group ($14,265; 95% confidence interval (CI): $12,645 to $16,092), the adjusted mean annual health care expenditures for the Medicare group were higher ($15,112; 95%CI: $13,361 to $17,092). As compared to the private group, the average annual expenditures for uninsured cancer survivors ($2315; 95%CI:1038 to $3501) was significantly lower and so was their health care utilization. Adjusted rates of ER visits for Medicaid were twice (AIRR:2.04; SE:0.28; p = 0.001) as compared to privately insured. CONCLUSIONS: A difference in the average total direct expenditures between uninsured and privately insured patients was found. Uninsured had the lowest health care utilization while Medicaid reported significantly higher number of ER visits. Despite differences in program structures, health care expenditures across insurance types were similar. Lower utilization of health care services among uninsured suggests cost maybe a barrier to accessing care.

Finding influential subjects in a network using a causal framework.

Researchers across a wide array of disciplines are interested in finding the most influential subjects in a network. In a network setting, intervention effects and health outcomes can spill over from one node to another through network ties, and influential subjects are expected to have a greater impact than others. For this reason, network research in public health has attempted to maximize health and behavioral changes by intervening on a subset of influential subjects. Although influence is often defined only implicitly in most of the literature, the operative notion of influence is inherently causal in many cases: influential subjects are those we should intervene on to achieve the greatest overall effect across the entire network. In this work, we define a causal notion of influence using potential outcomes. We review existing influence measures, such as node centrality, that largely rely on the particular features of the network structure and/or on certain diffusion models that predict the pattern of information or diseases spreads through network ties. We provide simulation studies to demonstrate when popular centrality measures can agree with our causal measure of influence. As an illustrative example, we apply several popular centrality measures to the HIV risk network in the Transmission Reduction Intervention Project and demonstrate the assumptions under which each centrality can represent the causal influence of each participant in the study.

Contingency Management and Pre-Exposure Prophylaxis Adherence Support Services (CoMPASS): A hybrid type 1 effectiveness-implementation study to promote HIV risk reduction among people who inject drugs.

BACKGROUND: HIV disproportionally affects persons who inject drugs (PWID), but engagement with HIV pre-exposure prophylaxis (PrEP) is low. We describe the rationale and study design for a new study, "Contingency Management and Pre-Exposure Prophylaxis (PrEP) Adherence Support Services (CoMPASS)," a hybrid type 1 effectiveness-implementation trial to promote HIV risk reduction among PWID. METHODS: In four community-based programs in the northeastern United States, PrEP-eligible PWID (target n = 526) are randomized to treatment as usual or Contingency Management (CM) and, as indicated, stepped up to PrEP Adherence Support Services (CoMPASS) over 24 weeks. During CM sessions, participants receive timely tangible rewards for verifiable activities demonstrating 1) PrEP initiation and adherence, and 2) engagement with medications for opioid use disorder (MOUD) and other OUD-related care. Participants who do not have high levels of biomarker-confirmed PrEP adherence at week 12 will be stepped up to receive PrEP Adherence Support Services (PASS) consisting of strengths-based case management over 12 weeks. Interventions are delivered by trained PrEP navigators, staff embedded within the respective sites. The primary outcome is sustained PrEP adherence by dried blood spot testing at 24 weeks. To inform future implementation, we are conducting implementation-focused process evaluations throughout the clinical trial. CONCLUSIONS: Results from this protocol are anticipated to yield novel findings regarding the impact and scalability of CoMPASS to promote HIV prevention among PWID in partnership with community-based organizations. http://ClinicalTrials.gov identifier: NCT04738825.

The effect of antiretroviral therapy with high central nervous system penetration on HIV-related cognitive impairment: a systematic review and meta-analysis.

Chronic complications are a significant concern for people living with HIV/AIDS (PLWHA) infection. HIV-associated neurocognitive disorders (HAND) are prevalent in PLWHA. Yet, the efficacy of medications that penetrate the central nervous system (CNS) at preventing or slowing the progression of HAND remains largely unknown. The objective of this study was to determine whether high CNS penetration effectiveness (CPE) regimens improve neurocognitive test scores in PLWHA on combined antiretroviral therapy (cART). Primary literature evaluating cognitive outcomes based on CPE score of cART regimens in PLWHA was assembled from PubMed/Medline and EMBASE. Both randomized controlled trials and observational studies with at least 12 weeks of follow-up were included. A meta-analysis was conducted to calculate the standardized mean difference. Eight trials including a total of 3,303 patients with 13,103 person-years of follow-up were included in the systematic review. Four trials (n = 366 patients) met our inclusion criteria and were included in the meta-analysis. In the meta-analysis, HIV regimens with a high CPE score did not affect NPZ-4 or GDS scores (standardized mean difference (SMD) 0.10, 95% CI -0.19, 0.38; I2 = 26%). Future studies with larger sample sizes are warranted to prospectively evaluate the relationship between CPE and progression of HAND.

Evaluating the Mediating Role of Recall of Intervention Knowledge in the Relationship Between a Peer-Driven Intervention and HIV Risk Behaviors Among People Who Inject Drugs.

Peer-driven interventions can be effective in reducing HIV injection risk behaviors among people who inject drugs (PWID). We employed a causal mediation framework to examine the mediating role of recall of intervention knowledge in the relationship between a peer-driven intervention and subsequent self-reported HIV injection-related risk behavior among PWID in the HIV Prevention Trials Network (HPTN) 037 study. For each intervention network, the index participant received training at baseline to become a peer educator, while non-index participants and all participants in the control networks received only HIV testing and counseling; recall of intervention knowledge was measured at the 6-month visit for each participant, and each participant was followed to ascertain HIV injection-related risk behaviors at the 12-month visit. We used inverse probability weighting to fit marginal structural models to estimate the total effect (TE) and controlled direct effect (CDE) of the intervention on the outcome. The proportion eliminated (PE) by intervening to remove mediation by the recall of intervention knowledge was computed. There were 385 participants (47% in intervention networks) included in the analysis. The TE and CDE risk ratios for the intervention were 0.47 [95% confidence interval (CI): 0.28, 0.78] and 0.73 (95% CI: 0.26, 2.06) and the PE was 49%. Compared to participants in the control networks, the peer-driven intervention reduced the risk of HIV injection-related risk behavior by 53%. The mediating role of recall of intervention knowledge accounted for less than 50% of the total effect of the intervention, suggesting that other potential causal pathways between the intervention and the outcome, such as motivation and skill, self-efficacy, social norms and behavior modeling, should be considered in future studies.

Estimating Causal Effects of HIV Prevention Interventions with Interference in Network-based Studies among People Who Inject Drugs.

Evaluating causal effects in the presence of interference is challenging in network-based studies of hard-to-reach populations. Like many such populations, people who inject drugs (PWID) are embedded in social networks and often exert influence on others in their network. In our setting, the study design is observational with a non-randomized network-based HIV prevention intervention. Information is available on each participant and their connections that confer possible HIV risk through injection and sexual behaviors. We considered two inverse probability weighted (IPW) estimators to quantify the population-level spillover effects of non-randomized interventions on subsequent health outcomes. We demonstrated that these two IPW estimators are consistent, asymptotically normal, and derived a closed-form estimator for the asymptotic variance, while allowing for overlapping interference sets (groups of individuals in which the interference is assumed possible). A simulation study was conducted to evaluate the finite-sample performance of the estimators. We analyzed data from the Transmission Reduction Intervention Project, which ascertained a network of PWID and their contacts in Athens, Greece, from 2013 to 2015. We evaluated the effects of community alerts on subsequent HIV risk behavior in this observed network, where the connections or links between participants were defined by using substances or having unprotected sex together. In the study, community alerts were distributed to inform people of recent HIV infections among individuals in close proximity in the observed network. The estimates of the risk differences for spillover using either IPW estimator demonstrated a protective effect. The results suggest that HIV risk behavior could be mitigated by exposure to a community alert when an increased risk of HIV is detected in the network.

Spillover benefit of pre-exposure prophylaxis for HIV prevention: evaluating the importance of effect modification using an agent-based model.

We developed an agent-based model using a trial emulation approach to quantify effect measure modification of spillover effects of pre-exposure prophylaxis (PrEP) for HIV among men who have sex with men (MSM) in the Atlanta-Sandy Springs-Roswell metropolitan area, Georgia. PrEP may impact not only the individual prescribed, but also their partners and beyond, known as spillover. We simulated a two-stage randomised trial with eligible components (≥3 agents with ≥1 HIV+ agent) first randomised to intervention or control (no PrEP). Within intervention components, agents were randomised to PrEP with coverage of 70%, providing insight into a high PrEP coverage strategy. We evaluated effect modification by component-level characteristics and estimated spillover effects on HIV incidence using an extension of randomisation-based estimators. We observed an attenuation of the spillover effect when agents were in components with a higher prevalence of either drug use or bridging potential (if an agent acts as a mediator between ≥2 connected groups of agents). The estimated spillover effects were larger in magnitude among components with either higher HIV prevalence or greater density (number of existing partnerships compared to all possible partnerships). Consideration of effect modification is important when evaluating the spillover of PrEP among MSM.

Generalizing trial evidence to target populations in non-nested designs: Applications to AIDS clinical trials.

Comparative effectiveness evidence from randomized trials may not be directly generalizable to a target population of substantive interest when, as in most cases, trial participants are not randomly sampled from the target population. Motivated by the need to generalize evidence from two trials conducted in the AIDS Clinical Trials Group (ACTG), we consider weighting, regression and doubly robust estimators to estimate the causal effects of HIV interventions in a specified population of people living with HIV in the USA. We focus on a non-nested trial design and discuss strategies for both point and variance estimation of the target population average treatment effect. Specifically in the generalizability context, we demonstrate both analytically and empirically that estimating the known propensity score in trials does not increase the variance for each of the weighting, regression and doubly robust estimators. We apply these methods to generalize the average treatment effects from two ACTG trials to specified target populations and operationalize key practical considerations. Finally, we report on a simulation study that investigates the finite-sample operating characteristics of the generalizability estimators and their sandwich variance estimators.

Network-based Analysis of Prescription Opioids Dispensing Using Exponential Random Graph Models (ERGMs).

The United States has been experiencing an unprecedented level of opioid overdose-related mortality due in part to excessive use of prescription opioids. Peer-driven network interventions may be beneficial. A key assumption of social network interventions is that of some members of the network act as key players and can influence the behavior of others in the network. We used opioid prescription records to create a social network of patients who use prescription opioid in the state of Rhode Island. The study population was restricted to patients on stable opioid regimens who used one source of payment and received the same opioid medication from ≥ 3 prescribers and pharmacies. An exponential random graph model (ERGM) was employed to examine the relationship between patient attributes and the likelihood of tie formation and modularity was used to assess for homophily (the tendency of individuals to associate with similar people). We used multivariable logistic regression to assess predictors of high betweenness centrality, a measure of influence within the network. 372 patients were included in the analysis; average age was 51 years; 53% were female; 57% were prescribed oxycodone, 34% were prescribed hydrocodone and 9% were prescribed buprenorphine/naloxone. After controlling for the main effects in the ERGM model, homophily was associated with age group, method of payment, number and type of opioid prescriptions filled, mean daily dose, and number of providers seen. Type of opioid and number of prescribers were identified as significant predictors of high betweenness centrality. We conclude that patients who use multiple prescribers or have a diagnosis of opioid use disorder may help promote positive health behaviors or disrupt harmful behaviors in an opioid prescription network.

Toward evaluation of disseminated effects of medications for opioid use disorder within provider-based clusters using routinely-collected health data.

Routinely-collected health data can be employed to emulate a target trial when randomized trial data are not available. Patients within provider-based clusters likely exert and share influence on each other's treatment preferences and subsequent health outcomes and this is known as dissemination or spillover. Extending a framework to replicate an idealized two-stage randomized trial using routinely-collected health data, an evaluation of disseminated effects within provider-based clusters is possible. In this article, we propose a novel application of causal inference methods for dissemination to retrospective cohort studies in administrative claims data and evaluate the impact of the normality of the random effects distribution for the cluster-level propensity score on estimation of the causal parameters. An extensive simulation study was conducted to study the robustness of the methods under different distributions of the random effects. We applied these methods to evaluate baseline prescription for medications for opioid use disorder among a cohort of patients diagnosed with opioid use disorder and adjust for baseline confounders using information obtained from an administrative claims database. We discuss future research directions in this setting to better address unmeasured confounding in the presence of disseminated effects.

A Comparison of National, State, and Local Drug Use Surveys: The Youth Risk Behavior Survey and the Rx for Addiction and Medication Safety Program.

OBJECTIVE: To understand adolescent substance use and its known risk factors at the local and state level; to inform the development of future programs to reduce substance misuse among adolescents. METHODS: Survey data collected from a convenience sample of Rhode Island 9th-grade students prior to administration of the RAMS curriculum in 2016 and 2017 was compared to 2017 Rhode Island and National Youth Risk Behavior Survey Data. RESULTS: Seventeen percent (2016 RAMS), 10% (2017 RAMS), 6% (RIYRBS) and 11% (NYRBS) of students reported ever using prescription pain reliever without a physician prescription. One percent (2016 RAMS, 2017 RAMS), 3% (RIYRBS), and 2% (NYRBS) reported ever using heroin. Seven percent (2016 RAMS, 2017 RAMS), and 12% (RIYRBS, NYRBS) reported using cannabis in previous 30 days. CONCLUSION: These findings highlight a unique need for targeted education based on school and community risk and protective factors and misuse differences.

Assessing Attitudes Toward COVID-19 Prevention: Defining Two Attitudes Crucial for Understanding Systemic and Social Variables Associated with Disparities.

This study tested a conceptual model identifying two distinct types of attitudes people may have toward following recommendations to prevent COVID-19. These attitudes were expected to be important for understanding types of systemic and social variables associated with health disparities such as racial discrimination, residential environment, lack of healthcare access, and negative healthcare experiences. The conceptual model was drawn from previous work examining adherence to medical recommendations that identified two distinct and consequential attitudes that influence behavior: perceived benefit (believing recommendations are effective and necessary) and perceived burden (experiencing recommendations as unpleasant or difficult). Approximately equal proportions of Black and White individuals living in the USA (N = 194) were recruited to complete an online survey. A psychometric analysis indicated that perceived benefit and burden attitudes were two distinct and meaningful dimensions that could be assessed with high validity, and scales demonstrated measurement invariance across Black and White groups. In correlation analyses, benefit and burden attitudes were robustly associated with neighborhood violence, healthcare access, and healthcare experiences (but not with experiences of discrimination), and all these associations remained significant after accounting for subjective stress and political affiliation. These findings have implications for increasing compliance to public health recommendations and addressing health disparities.

Early buprenorphine-naloxone initiation for opioid use disorder reduces opioid overdose, emergency room visits, and healthcare cost compared to late initiation.

Background: Although the effectiveness of buprenorphine-naloxone (BUP-NX) has been established, real-world evidence on the benefits of early treatment initiation is limited.Objective: To evaluate the association between early BUP-NX initiation and health-related outcomes among insured adults with opioid use disorder (OUD).Methods: We conducted a cross-sectional analysis using the Optum's de-identified Clinformatics® Data Mart Database from 2010 to 2018. Patients who initiated BUP-NX within 30 days of OUD diagnosis were classified as early initiators. Patients who initiated BUP-NX later, but within the one-year follow-up, were defined as late initiators. Outcomes included opioid overdose, opioid overdose-related emergency department (ED) visits, and all-cause healthcare cost during the year after OUD diagnosis. We employed generalized linear models to compare outcomes between early and late initiators, adjusting for baseline covariates and accounting for missing information for covariates using multiple imputation.Results: A total of 8,388 patients with OUD were identified; mean age was 39.9 years; 36% were female; and 67.6% were early initiators. Early initiators had an estimated 42% lower rate of opioid overdose (adjusted rate ratio (aRR) = 0.58; 95% confidence interval (CI): 0.52, 0.64); 51% lower rate of opioid overdose-related ED visits (aRR = 0.49; 95% CI: 0.44, 0.55); and 31% lower total healthcare cost (adjusted cost ratio = 0.69; 95% CI: 0.66, 0.72), compared to late initiators.Conclusion: Compared to late BUP-NX initiation, early initiation was associated with a lower risk of opioid overdose and opioid overdose-related ED visits, and reduced total healthcare cost among insured adult patients with OUD.