Experiential suicide prevention training for substance use treatment intensive outpatient program counselors: Stepped wedge cluster-randomized training study.

INTRODUCTION: The goal of this study was to evaluate changes in knowledge, attitudes, and other key suicide prevention issues for substance use disorder (SUD) counselors trained to administer the Preventing Addiction Related Suicide (PARS) module as part of a large-scale clinical trial. The PARS is a 3-hour, PowerPoint based intervention designed with and for community SUD agencies for their Intensive Outpatient (IOP) group therapy programs. A previous randomized study of 906 patients from 15 community SUD sites showed positive changes in patients' suicide prevention knowledge, attitudes, and help seeking. METHODS: Counselor participants completed measures of knowledge and attitudes about suicide and their confidence treating suicidal patients at each step of a large, stepped wedge cluster randomized trial of PARS, including after the final step. Data analysis compared scores in steps prior to counselors' training in PARS with scores in the steps following counselors' PARS training. RESULTS: A total of 126 counselors participated in the study (89 % of those approached; 89-92 % retention across follow-up). Evaluation of both PARS efficacy and the PARS training by SUD counselors was highly rated. Counselor scores after receiving PARS training (vs. scores prior to PARS training) showed greater suicide knowledge, less maladaptive attitudes about suicide, and greater confidence in working with suicidal patients. CONCLUSIONS: Based on this rigorous test of PARS training for SUD counselors working in community SUD intensive outpatient programs, PARS training, as well as doing the PARS intervention, was rated as highly effective and acceptable. PARS offers an integrated, brief, engaging, and effective training method to improve suicide care for both SUD counselors and SUD clients.

The selection of statistical models for reporting count outcomes and intervention effects in brief alcohol intervention trials: A review and recommendations.

Understanding the efficacy and relative effectiveness of a brief alcohol intervention (BAI) relies on obtaining a credible intervention effect estimate. Outcomes in BAI trials are often count variables, such as the number of drinks consumed, which may be overdispersed (i.e., greater variability than expected based on a given model) and zero-inflated (i.e., greater probability of zeros than expected based on a given model). Ignoring such distribution characteristics can lead to biased estimates and invalid statistical conclusions. In this critical review, we identified and reviewed 64 articles that reported count outcomes from a systematic review of BAI trials for adolescents and young adults from 2013 to 2018. Given many statistical models to choose from when analyzing count outcomes, we reviewed the models used and reporting practices in the BAI trial literature. A majority (61.3%) of analyses with count outcomes used linear models despite violations of normality assumptions; 75.6% of outcome variables demonstrated clear overdispersion. We provide an overview of available count models (Poisson, negative binomial, zero-inflated or hurdle, and marginalized zero-inflated Poisson regression) and formulate practical guidelines for reporting outcomes of BAIs. We provide a visual step-by-step decision guide for selecting appropriate statistical models and reporting results for count outcomes. We list accessible resources to help researchers select an appropriate model with which to analyze their data. Recent advances in count distribution-based models hold promise for evaluating count outcomes to gauge the efficacy and effectiveness of BAIs and identify critical covariates in alcohol epidemiologic research. We recommend that researchers report the distributional properties of count outcomes, such as the proportion of zero counts, and select an appropriate statistical analysis for count outcomes using the provided decision tree. By following these recommendations, future research may yield more accurate, transparent, and reproducible results.

Unsettling Settler Colonialism in Research: Strategies Centering Native American Experience and Expertise in Responding to Substance Misuse and Co-occurring Sexual Risk-Taking, Alcohol-Exposed Pregnancy, and Suicide Prevention Among Young People.

Native American (NA) populations in the USA (i.e., those native to the USA which include Alaska Natives, American Indians, and Native Hawaiians) have confronted unique historical, sociopolitical, and environmental stressors born of settler colonialism. Contexts with persistent social and economic disadvantage are critical determinants of substance misuse and co-occurring sexual risk-taking and suicide outcomes, as well as alcohol exposed pregnancy among NA young people (i.e., adolescents and young adults). Despite intergenerational transmission of resistance and resiliencies, NA young people face continued disparities in substance misuse and co-occurring outcomes when compared to other racial and ethnic groups in the USA. The failure in progress to address these inequities is the result of a complex set of factors; many of which are structural and rooted in settler colonialism. One of these structural factors includes barriers evident in health equity research intended to guide solutions to address these disparities yet involving maintenance of a research status quo that has proven ineffective to developing these solutions. Explicitly or implicitly biased values, perspectives, and practices are deeply rooted in current research design, methodology, analysis, and dissemination and implementation efforts. This status quo has been supported, intentionally and unintentionally, by researchers and research institutions with limited experience or knowledge in the historical, social, and cultural contexts of NA communities. We present a conceptual framework illustrating the impact of settler colonialism on current research methods and opportunities to unsettle its influence. Moreover, our framework illustrates opportunities to resist settler colonialism in research. We then focus on case examples of studies from the Intervention Research to Improve Native American Health program, funded by the NIH, that impact substance use and co-occurring health conditions among NA young people.

Do brief motivational interventions increase motivation for change in drinking among college students? A two-step meta-analysis of individual participant data.

BACKGROUND: Brief motivational interventions (BMIs) are one of the most effective individually focused alcohol intervention strategies for college students. Despite the central theoretical role of motivation for change in BMIs, it is unclear whether BMIs increase motivation to change drinking behavior. We conducted a two-step meta-analysis of individual participant data (IPD) to examine whether BMIs increase motivation for change. N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). METHODS: We included 15 trials of BMI (N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually-delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). Different measures and responses used in the original trials were harmonized. Effect size estimates were derived from a model that adjusted for baseline motivation and demographic variables for each trial (step 1) and subsequently combined in a random-effects meta-analysis (step 2). RESULTS: The overall intervention effect of BMIs on motivation for change was not statistically significant (standard mean difference [SMD]: 0.026, 95% CI: [-0.001, 0.053], p = 0.06, k = 19 comparisons). Of the three subtypes of BMIs, GMI, which tended to provide motivation-targeted content, had a statistically significant intervention effect on motivation, compared with controls (SMD: 0.055, 95% CI: [0.007, 0.103], p = 0.025, k = 5). By contrast, there was no evidence that MI + PF (SMD = 0.04, 95% CI: [-0.02, 0.10], k = 6, p = 0.20) nor PF increased motivation (SMD = 0.005, 95% CI: [-0.028, 0.039], k = 8, p = 0.75), compared with controls. Post hoc meta-regression analysis suggested that motivation sharply decreased each month within the first 3 months postintervention (b = -0.050, z = -2.80, p = 0.005 for k = 14). CONCLUSIONS: Although BMIs provide motivational content and normative feedback and are assumed to motivate behavior change, the results do not wholly support the hypothesis that BMIs improve motivation for change. Changing motivation is difficult to assess during and following interventions, but it is still a theoretically important clinical endpoint. Further, the evidence cautiously suggests that changing motivation may be achievable, especially if motivation-targeted content components are provided.

Prevalence of Mental Health Disorders and Treatment Utilization among Urban Lesbian, Gay, Bisexual, and Transgender American Indians and Alaska Natives.

We examined prevalence of mental health treatment utilization among 447 lesbian, gay, bisexual, transgender, and Two-Spirit (LGBTT-S) American Indian/Alaska Native (AI/AN) adults and the association of mental health treatment utilization with socio-demographic factors, social support, and mental health diagnoses. We derived data from the HONOR Project, a multi-site cross-sectional survey of Native LGBTT-S adults from seven U.S. metropolitan cities. Rates of lifetime mental health treatment utilization were higher for women (87%), those who were college educated (84%), and homeowners (92%). Cisgender women and transgender AI/AN adults had a higher prevalence than cisgender men of major depression, generalized anxiety, and panic disorder. Rates of subthreshold and threshold posttraumatic stress disorder were significantly higher for transgender adults. Lower positive social support and higher emotional social support were associated with greater odds of mental health treatment utilization. Mental health diagnoses and lifetime mental health treatment utilization was positively associated.

A Community Engaged Approach in Adapting Motivational Interviewing and Skills Training for Native Americans With Experiences of Substance Misuse.

OBJECTIVE: American Indian and Alaskan Natives (AIAN) are regenerating cultural knowledge and practices to adapt westernized evidence-based interventions to address health concerns such as substance use. This study describes the process of selecting, adapting, and implementing motivational interviewing plus cognitive behavior therapy (motivational interviewing + Skills Training; MIST) for use in a combined substance use intervention with a rural, Northwest tribal community. METHODS: An established community and academic partnership worked together to make culturally mindful changes to MIST. The partnership incorporated community leaders/Elders (n = 7), providers (n = 9), and participants (n = 50) to implement an iterative process of adapting and implementing the adapted form of MIST. RESULTS: Key adaptations included presenting concepts grounded in tribal values, providing examples from the community perspective, and incorporating cultural customs and traditions. Overall, the MIST adaptation was favorably received by participants, and the adaptation appeared feasible. CONCLUSIONS: Adapted MIST appeared to be an acceptable intervention for this Native American community. Future research should evaluate the interventions efficacy in reducing substance use among this and other Native American communities. Future clinical research should consider strategies outlined in this adaptation as a potential process for working with Native American communities to implement culturally appropriate interventions.

Which is Better for Individual Participant Data Meta-Analysis of Zero-Inflated Count Outcomes, One-Step or Two-Step Analysis? A Simulation Study.

Meta-analysis using individual participant data (IPD) is an important methodology in intervention research because it (a) increases accuracy and precision of estimates, (b) allows researchers to investigate mediators and moderators of treatment effects, and (c) makes use of extant data. IPD meta-analysis can be conducted either via a one-step approach that uses data from all studies simultaneously, or a two-step approach, which aggregates data for each study and then combines them in a traditional meta-analysis model. Unfortunately, there are no evidence-based guidelines for how best to approach IPD meta-analysis for count outcomes with many zeroes, such as alcohol use. We used simulation to compare the performance of four hurdle models (3 one-step and 1 two-step models) for zero-inflated count IPD, under realistic data conditions. Overall, all models yielded adequate coverage and bias for the treatment effect in the count portion of the model, across all data conditions. However, in the zero portion, the treatment effect was underestimated in most models and data conditions, especially when there were fewer studies. The performance of both one- and two-step approaches depended on the formulation of the treatment effects, suggesting a need to carefully consider model assumptions and specifications when using IPD.

A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses.

In research applications, mental health problems such as alcohol-related problems and depression are commonly assessed and evaluated using scale scores or latent trait scores derived from factor analysis or item response theory models. This tutorial paper demonstrates the use of cognitive diagnosis models (CDMs) as an alternative approach to characterizing mental health problems of young adults when item-level data are available. Existing measurement approaches focus on estimating the general severity of a given mental health problem at the scale level as a unidimensional construct without accounting for other symptoms of related mental health problems. The prevailing approaches may ignore clinically meaningful presentations of related symptoms at the item level. The current study illustrates CDMs using item-level data from college students (40 items from 719 respondents; 34.6% men, 83.9% White, and 16.3% first-year students). Specifically, we evaluated the constellation of four postulated domains (i.e., alcohol-related problems, anxiety, hostility, and depression) as a set of attribute profiles using CDMs. After accounting for the impact of each attribute (i.e., postulated domain) on the estimates of attribute profiles, the results demonstrated that when items or attributes have limited information, CDMs can utilize item-level information in the associated attributes to generate potentially meaningful estimates and profiles, compared to analyzing each attribute independently. We introduce a novel visual inspection aid, the lens plot, for quantifying this gain. CDMs may be a useful analytical tool to capture respondents' risk and resilience for prevention research.

Brief Alcohol Interventions are Effective through 6 Months: Findings from Marginalized Zero-inflated Poisson and Negative Binomial Models in a Two-step IPD Meta-analysis.

To evaluate and optimize brief alcohol interventions (BAIs), it is critical to have a credible overall effect size estimate as a benchmark. Estimating such an effect size has been challenging because alcohol outcomes often represent responses from a mixture of individuals: those at high risk for alcohol misuse, occasional nondrinkers, and abstainers. Moreover, some BAIs exclusively focus on heavy drinkers, whereas others take a universal prevention approach. Depending on sample characteristics, the outcome distribution might have many zeros or very few zeros and overdispersion; consequently, the most appropriate statistical model may differ across studies. We synthesized individual participant data (IPD) from 19 studies in Project INTEGRATE (Mun et al., 2015b) that randomly allocated participants to intervention and control groups (N = 7,704 participants, 38.4% men, 74.7% White, 58.5% first-year students). We sequentially estimated marginalized zero-inflated Poisson (Long et al., 2014) or negative binomial regression models to obtain covariate-adjusted, study-specific intervention effect estimates in the first step, which were subsequently combined in a random-effects meta-analysis model in the second step. BAIs produced a statistically significant 8% advantage in the mean number of drinks at both 1-3 months (RR = 0.92, 95% CI = [0.85, 0.98]) and 6 months (RR = 0.92, 95% CI = [0.85, 0.99]) compared to controls. At 9-12 months, there was no statistically significant difference in the mean number of drinks between BAIs and controls. In conclusion, BAIs are effective at reducing the mean number of drinks through at least 6 months post intervention. IPD can play a critical role in deriving findings that could not be obtained in original individual studies or standard aggregate data meta-analyses.

Changes in high-risk sexual behavior, HIV and other STI testing, and PrEP use during the COVID-19 pandemic in a longitudinal cohort of adolescent men who have sex with men 13 to 18 years old in the United States.

The COVID-19 pandemic has disrupted sexual health services among those most vulnerable to HIV acquisition, such as adolescent men who have sex with men (AMSM). We sought to characterize the changes in sexual-risk behaviors, HIV and other STI testing, and pre-exposure prophylaxis (PrEP) use among a longitudinal cohort of AMSM aged 13 to 18 years before and during the COVID-19 pandemic. We observed a significant decline in HIV testing and a marginal decrease in other STI testing since the pandemic began in March 2020. Outreach efforts and innovative remote delivery of sexual health services are needed to support access to healthcare services among AMSM as the pandemic persists.

RESUMEN: La pandemia de COVID-19 ha afectado la prestación de servicios de salud sexual para los más vulnerables, tales como los hombres adolescentes que tienen relaciones sexuales con hombres (AMSM; por sus siglas en ingles). En una cohorte longitudinal de AMSM de 13 a 18 años, examinamos los cambios en comportamientos sexuales de alto riesgo, la prueba de VIH, las pruebas de otras enfermedades de transmisión sexual, y el uso de Profilaxis Preexposición (PrEP) para el VIH antes y durante la pandemia. Desde el inicio de la pandemia en marzo de 2020, observamos una disminución significativa en la frecuencia de pruebas de VIH y una disminución marginal en la frecuencia de pruebas de otras enfermedades de transmisión sexual. Mientras persista la pandemia, serán necesarios más esfuerzos de divulgación e innovaciones en la prestación remota de servicios de salud sexual para apoyar el acceso a dichos servicios por parte de AMSM.

Does abstaining from alcohol in high school moderate intervention effects for college students? Implications for tiered intervention strategies.

Brief motivational intervention (BMI) and personalized feedback intervention (PFI) are individual-focused brief alcohol intervention approaches that have been proven efficacious for reducing alcohol use among college students and young adults. Although the efficacy of these two intervention approaches has been well established, little is known about the factors that may modify their effects on alcohol outcomes. In particular, high school drinking may be a risk factor for continued and heightened use of alcohol in college, and thus may influence the outcomes of BMI and PFI. The purpose of this study was to investigate whether high school drinking was associated with different intervention outcomes among students who received PFI compared to those who received BMI. We conducted moderation analyses examining 348 mandated students (60.1% male; 73.3% White; and 61.5% first-year student) who were randomly assigned to either a BMI or a PFI and whose alcohol consumption was assessed at 4-month and 15-month follow-ups. Results from marginalized zero-inflated Poisson models showed that high school drinking moderated the effects of PFI and BMI at the 4-month follow-up but not at the 15-month follow-up. Specifically, students who reported no drinking in their senior year of high school consumed a 49% higher mean number of drinks after receiving BMI than PFI at the 4-month follow-up. The results suggest that alcohol consumption in high school may be informative when screening and allocating students to appropriate alcohol interventions to meet their different needs.

Examining Employment Conditions During the COVID-19 Pandemic in Pasifika Communities.

Introduction: Pasifika (Native Hawaiian and Pacific Islander) people living in the United States experience health, economic, and social inequities, and a disproportionate burden of COVID-19 cases and deaths. This study examines employment among Pasifika living in the 10 US states with the largest Pasifika populations during the COVID-19 pandemic. Methods: We use the Current Population Survey to examine racial differences in employment status, paid work from home (PWFH), and industry telework friendliness. We use data from the Washington Office of Fiscal Management and the Washington State (WA) Employment Security Department to examine county-level unemployment claims. Results: Nationally, Pasifika did not self-report unemployment significantly more than Black, Latino, Asian, and American Indian/Alaska Native respondents, but in WA counties with high Pasifika concentrations, unemployment insurance claim rates were higher compared with all other racial groups, particularly Whites and Asians. Surprisingly, Pasifika had more PWFH opportunities, but worked in less telework-friendly industries nationally. Discussion: This study demonstrates the complexity of employment among Pasifika during the COVID-19 pandemic. The findings correspond with national reports of racialized communities impacted by unemployment, including Pasifika. Marginally significant differences in unemployment nationally may be due to Pasifika working largely in essential industries requiring workplace attendance. Health Equity Implications: Although overlooked or overshadowed by size, our findings highlight the need for continued advocacy to support data disaggregation and Pasifika data sovereignty. This can be achieved through collaborations between researchers as well as local and community organizations to address data needs of Pasifika communities.

Adapting narrative exposure therapy with a tribal community: A community-based approach.

OBJECTIVE: American Indian (AI) individuals are at increased risk for present-day trauma exposure and associated negative outcomes, as well as ongoing effects of intergenerational trauma exposure and adversity. However, few empirically supported treatments exist that are specifically tailored and/or tested with AI communities. This study describes the process of selecting, adapting, and implementing narrative exposure therapy (NET) with an AI community. METHODS: A community and academic partnership was formed and worked together to make culturally mindful changes to NET to best fit the needs of the community. The partnership incorporated community leaders/Elders (n = 7), providers (n = 11), and participants seeking treatment (n = 50) to implement an iterative process of adapting and implementing the adapted form of NET. RESULTS: Key adaptions included addressing historical and intergenerational trauma, greater protections for confidentiality in a small community, and incorporation of cultural customs and traditions. Overall, the adapted form of NET was favorably received by the participants, and the implementation appeared to be feasible, with improved retention over past trials of adapted trauma-focused treatments with this community and with highly positive satisfaction ratings and feedback. CONCLUSIONS: NET was shown to be an appropriate approach for this AI community and should be considered as a treatment option for other AI communities. Future work should consider strategies outlined in this adaption as well as following a similar process for working with AI communities to implement culturally appropriate interventions for trauma-related symptoms.

Effectiveness of a Suicide Prevention Module for Adults in Substance Use Disorder Treatment: A Stepped-Wedge Cluster-Randomized Clinical Trial.

Importance: Individuals with substance use disorders (SUDs) are at high risk for suicide. The Preventing Addiction Related Suicide (PARS) module is the first suicide prevention module developed in and for community substance use intensive outpatient programs (IOPs). Objective: To evaluate the effectiveness of PARS on suicide-related outcomes (ie, knowledge, attitudes, and help-seeking behavior) compared with usual care. Design, Setting, and Participants: This stepped-wedge cluster-randomized clinical trial was conducted from 2017 to 2020, with follow-up assessments conducted after treatment and at 1, 3, and 6 months. Participants included adult outpatients in SUD treatment at community IOPs across western Washington state. Data were analyzed from July 1, 2020, to January 20, 2022. Interventions: The intervention, PARS, was a 1-session secondary prevention module administered by trained SUD counselors consisting of didactic presentations and group discussions about suicide risk factors, warning signs, and actions to take if suicide risk is observed in self or others. The control group received usual care. Main Outcomes and Measures: Primary outcomes were suicide knowledge, attitudes about suicide, and help-seeking behavior among patients enrolled in an IOP. Results: A total of 906 participants (mean [SD] age, 37.5 [12.0] years; 540 [59.6%] men) were included, with 478 participants receiving usual care and 428 participants receiving PARS. In intent-to-treat analysis from baseline to after treatment, there was a greater improvement in suicide knowledge (d = 0.15; 95% CI, 0.08 to 0.23; P < .001) and a greater reduction in maladaptive attitudes (d = 0.18; 95% CI, 0.14 to 0.25; P < .001) for PARS participants compared with those receiving usual care. Improvements were maintained at follow-up for suicide knowledge (1 month: d = 0.16; 95% CI, 0.07 to 0.22; P < .001; 3 months: d = 0.12; 95% CI, 0.05 to 0.19; P = .001; 6 months: d = 0.13; 95% CI, 0.06 to 0.20; P < .001) and reductions in maladaptive attitudes (1 month: d = 0.20; 95% CI, 0.12 to 0.23; P < .001; 3 months: d = 0.10; 95% CI, 0.05 to 0.16; P < .001; 6 months: d = 0.14; 95% CI, 0.09 to 0.19; P < .001), with 788 participants (87.0%) of the sample responding across time points. From baseline to 6 months, there was a greater improvement in help-seeking in the PARS group vs usual care (d = 0.16; 95% CI, 0.01 to 0.32; P = .04). Conclusions and Relevance: This stepped-wedge cluster-randomized clinical trial found that PARS was superior to usual care in improving suicide knowledge, maladaptive attitudes, and help-seeking in adults undergoing community addiction treatment. As a 1-session IOP module developed in partnership with community addiction agencies, PARS has the potential for wide impact in the national suicide prevention strategy. Trial Registration: ClinicalTrials.gov Identifier: NCT03166709.

A Structural Equation Modeling Approach to Meta-analytic Mediation Analysis Using Individual Participant Data: Testing Protective Behavioral Strategies as a Mediator of Brief Motivational Intervention Effects on Alcohol-Related Problems.

This paper introduces a meta-analytic mediation analysis approach for individual participant data (IPD) from multiple studies. Mediation analysis evaluates whether the effectiveness of an intervention on health outcomes occurs because of change in a key behavior targeted by the intervention. However, individual trials are often statistically underpowered to test mediation hypotheses. Existing approaches for evaluating mediation in the meta-analytic context are limited by their reliance on aggregate data; thus, findings may be confounded with study-level differences unrelated to the pathway of interest. To overcome the limitations of existing meta-analytic mediation approaches, we used a one-stage estimation approach using structural equation modeling (SEM) to combine IPD from multiple studies for mediation analysis. This approach (1) accounts for the clustering of participants within studies, (2) accommodates missing data via multiple imputation, and (3) allows valid inferences about the indirect (i.e., mediated) effects via bootstrapped confidence intervals. We used data (N = 3691 from 10 studies) from Project INTEGRATE (Mun et al. Psychology of Addictive Behaviors, 29, 34-48, 2015) to illustrate the SEM approach to meta-analytic mediation analysis by testing whether improvements in the use of protective behavioral strategies mediate the effectiveness of brief motivational interventions for alcohol-related problems among college students. To facilitate the application of the methodology, we provide annotated computer code in R and data for replication. At a substantive level, stand-alone personalized feedback interventions reduced alcohol-related problems via greater use of protective behavioral strategies; however, the net-mediated effect across strategies was small in size, on average.

Do Brief Alcohol Interventions Reduce Driving After Drinking Among College Students? A Two-step Meta-analysis of Individual Participant Data.

AIMS: College students who drink are at an increased risk of driving after drinking and alcohol-involved traffic accidents and deaths. Furthermore, the persistence of driving after drinking over time underscores a need for effective interventions to prevent future drunk driving in adulthood. The present study examined whether brief alcohol interventions (BAIs) for college students reduce driving after drinking. METHODS: A two-step meta-analysis of individual participant data (IPD) was conducted using a combined sample of 6801 college students from 15 randomized controlled trials (38% male, 72% White and 58% first-year students). BAIs included individually delivered Motivational Interviewing with Personalized Feedback (MI + PF), Group Motivational Interviewing (GMI), and stand-alone Personalized Feedback (PF) interventions. Two outcome variables, driving after two+/three+ drinks and driving after four+/five+ drinks, were checked, harmonized and analyzed separately for each study and then combined for meta-analysis and meta-regression analysis. RESULTS: BAIs lowered the risk of driving after four+/five+ drinks (19% difference in the odds of driving after drinking favoring BAIs vs. control), but not the risk of driving after two+/three+ drinks (9% difference). Subsequent subgroup analysis indicated that the MI + PF intervention was comparatively better than PF or GMI. CONCLUSIONS: BAIs provide a harm reduction approach to college drinking. Hence, it is encouraging that BAIs reduce the risk of driving after heavy drinking among college students. However, there may be opportunities to enhance the intervention content and timing to be more relevant for driving after drinking and improve the outcome assessment and reporting to demonstrate its effect.

A bias correction method in meta-analysis of randomized clinical trials with no adjustments for zero-inflated outcomes.

Many clinical endpoint measures, such as the number of standard drinks consumed per week or the number of days that patients stayed in the hospital, are count data with excessive zeros. However, the zero-inflated nature of such outcomes is sometimes ignored in analyses of clinical trials. This leads to biased estimates of study-level intervention effect and, consequently, a biased estimate of the overall intervention effect in a meta-analysis. The current study proposes a novel statistical approach, the Zero-inflation Bias Correction (ZIBC) method, that can account for the bias introduced when using the Poisson regression model, despite a high rate of inflated zeros in the outcome distribution of a randomized clinical trial. This correction method only requires summary information from individual studies to correct intervention effect estimates as if they were appropriately estimated using the zero-inflated Poisson regression model, thus it is attractive for meta-analysis when individual participant-level data are not available in some studies. Simulation studies and real data analyses showed that the ZIBC method performed well in correcting zero-inflation bias in most situations.

A comparison of Bayesian to maximum likelihood estimation for latent growth models in the presence of a binary outcome.

Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in studies with modest samples. Bayesian estimation is a logical alternative to ML for LGMs, but there is a lack of research providing guidance on when Bayesian estimation may be preferable to ML or vice versa. This study compared the performance of Bayesian versus ML estimators for LGMs by evaluating their accuracy via Monte Carlo (MC) simulations. For the MC study, longitudinal data sets were generated and estimated using LGM via both ML and Bayesian estimation with three different priors, and parameter recovery across the two estimators was evaluated to determine their relative performance. The findings suggest that ML estimation is a reasonable choice for most LGMs, unless it fails to converge, which can occur with limiting data situations (i.e., just a few time points, no covariate or outcome, modest sample sizes). When models do not converge using ML, we recommend Bayesian estimation with one caveat that the influence of the priors on estimation may have to be carefully examined, per recent recommendations on Bayesian modeling for applied researchers.

Exploring HIV-Related Stigma as a Determinant of Engagement in HIV Care by African American Women.

Engagement in HIV care reduces HIV-related health disparities that persist across racial/ethnic and gender lines; yet, African American (AA) women face multiple challenges to remaining engaged in care, including HIV-related stigma. We analyzed longitudinal data from 239 participants in the Unity Health Study to estimate associations between HIV-related stigma and engagement in care among AA women linked to HIV care. In adjusted Poisson regression analyses, engagement in care was not associated with HIV-related stigma but was associated with older age (incidence rate ratio [IRR] = 1.01, 95% confidence interval [CI] = [1.00-1.01], p = .01), higher levels of education (IRR = 1.18, 95% CI = [1.02-1.35], p = .03), and higher levels of social support (IRR = 1.05, 95% CI = [1.01-1.09], p = .04). Our findings suggest the need for targeted interventions to enhance engagement in care and to incorporate social support into health promotion programming for AA women living with HIV.

HIV stigma and viral load among African-American women receiving treatment for HIV.

OBJECTIVE: African-American women are more likely than other women in the United States to experience poor HIV-related health; HIV stigma may contribute to these outcomes. This study assessed the relationship between HIV stigma and viral load, over time, among a sample of African-American women receiving treatment for HIV, and explored social support and depressive symptoms as mediators. DESIGN: Secondary analysis of longitudinal data. METHODS: Data came from a randomized trial of an intervention to reduce HIV stigma among African-American women in HIV care in Chicago, Illinois and Birmingham, Alabama. Sociodemographic and psychosocial data were collected at up to six study visits over 14 months. Viral loads were extracted from medical records during the study period. Generalized linear mixed effects models were used to estimate associations among overall, internalized, and enacted HIV stigma and viral load over time. Mediation analyses were used to estimate indirect effects via social support and depressive symptoms. RESULTS: Data from 234 women were analyzed. Overall HIV stigma was significantly associated with subsequent viral load (adjusted ß = 0.24, P = 0.005). Both between-subject (adjusted ß = 0.74, P < 0.001) and within-subject (adjusted ß = 0.34, P = 0.005) differences in enacted stigma were associated with viral load. Neither social support nor depressive symptoms were statistically significant mediators. CONCLUSION: Ongoing experiences of HIV stigmatization may contribute to increased viral load among African-American women in primary HIV care. Interventions should aim to alleviate the consequences of stigma experienced by patients and prevent future stigmatization.