Community-Based Cluster-Randomized Trial to Reduce Opioid Overdose Deaths.

BACKGROUND: Evidence-based practices for reducing opioid-related overdose deaths include overdose education and naloxone distribution, the use of medications for the treatment of opioid use disorder, and prescription opioid safety. Data are needed on the effectiveness of a community-engaged intervention to reduce opioid-related overdose deaths through enhanced uptake of these practices. METHODS: In this community-level, cluster-randomized trial, we randomly assigned 67 communities in Kentucky, Massachusetts, New York, and Ohio to receive the intervention (34 communities) or a wait-list control (33 communities), stratified according to state. The trial was conducted within the context of both the coronavirus disease 2019 (Covid-19) pandemic and a national surge in the number of fentanyl-related overdose deaths. The trial groups were balanced within states according to urban or rural classification, previous overdose rate, and community population. The primary outcome was the number of opioid-related overdose deaths among community adults. RESULTS: During the comparison period from July 2021 through June 2022, the population-averaged rates of opioid-related overdose deaths were similar in the intervention group and the control group (47.2 deaths per 100,000 population vs. 51.7 per 100,000 population), for an adjusted rate ratio of 0.91 (95% confidence interval, 0.76 to 1.09; P = 0.30). The effect of the intervention on the rate of opioid-related overdose deaths did not differ appreciably according to state, urban or rural category, age, sex, or race or ethnic group. Intervention communities implemented 615 evidence-based practice strategies from the 806 strategies selected by communities (254 involving overdose education and naloxone distribution, 256 involving the use of medications for opioid use disorder, and 105 involving prescription opioid safety). Of these evidence-based practice strategies, only 235 (38%) had been initiated by the start of the comparison year. CONCLUSIONS: In this 12-month multimodal intervention trial involving community coalitions in the deployment of evidence-based practices to reduce opioid overdose deaths, death rates were similar in the intervention group and the control group in the context of the Covid-19 pandemic and the fentanyl-related overdose epidemic. (Funded by the National Institutes of Health; HCS ClinicalTrials.gov number, NCT04111939.).

Simulating the Simultaneous Impact of Medication for Opioid Use Disorder and Naloxone on Opioid Overdose Death in Eight New York Counties.

BACKGROUND: The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, and nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, Simulation of Community-Level Overdose Prevention Strategy, we simulated increases in buprenorphine initiation and retention and naloxone distribution aimed at reducing overdose deaths by 40% in New York Counties. METHODS: Our simulations covered 2020-2022. The eight counties contrasted urban or rural and high and low baseline rates of opioid use disorder treatment. The model calibrated agent characteristics for opioid use and use disorder, treatments and treatment access, and fatal and nonfatal overdose. Modeled interventions included increased buprenorphine initiation and retention, and naloxone distribution. We predicted a decrease in the rate of fatal opioid overdose 1 year after intervention, given various modeled intervention scenarios. RESULTS: Counties required unique combinations of modeled interventions to achieve a 40% reduction in overdose deaths. Assuming a 200% increase in naloxone from current levels, high baseline treatment counties achieved a 40% reduction in overdose deaths with a simultaneous 150% increase in buprenorphine initiation. In comparison, low baseline treatment counties required 250-300% increases in buprenorphine initiation coupled with 200-1000% increases in naloxone, depending on the county. CONCLUSIONS: Results demonstrate the need for tailored county-level interventions to increase service utilization and reduce overdose deaths, as the modeled impact of interventions depended on the county's experience with past and current interventions.

Effect of the Communities That HEAL Intervention on Overdose Education and Naloxone Distribution: A Cluster-Randomized, Wait-List Controlled Trial.

Objectives. To determine whether the Communities That HEAL (CTH) intervention is effective in increasing naloxone distribution compared with usual care. Methods. The HEALing (Helping to End Addiction Long-Term) Communities Study (HCS) is a cluster-randomized, parallel-arm, wait-list controlled implementation science trial testing the impact of the CTH intervention on increasing the use of evidence-based practices to lower opioid-related overdose deaths. Communities (n = 67) highly impacted by opioid overdose in Kentucky, Massachusetts, New York, and Ohio were allocated to CTH intervention (n = 34) or wait-list comparison (usual care; n = 33) arms. The primary outcome for this study was the number of naloxone units distributed in HCS communities during the comparison period (July 1, 2021‒June 30, 2022), examined using an intent-to-treat negative binomial regression model. Results. Naloxone distribution was 79% higher in the CTH intervention versus usual care arm (adjusted relative rate = 1.79; 95% confidence interval = 1.28, 2.51; P = .001; adjusted rates of naloxone distribution 3378 vs 1884 naloxone units per 100 000 residents), when controlling for urban‒rural status, state, baseline opioid-related overdose death rate, and baseline naloxone distribution rate. Conclusions. The CTH intervention increased naloxone distribution compared with usual care in communities highly impacted by the opioid crisis. Trial Registration. ClinicalTrials.gov identifier: NCT04111939. (Am J Public Health. Published online ahead of print October 10, 2024:e1-e12. https://doi.org/10.2105/AJPH.2024.307845).

Psychosocial Factors Linked to Uncontrolled Infection and Mortality among People Living with HIV Who Use Substances: A Latent Class Analysis.

To determine whether endorsement patterns of psychosocial symptoms revealed distinct subgroups, or latent classes, of people living with HIV who use substances (PLWH-SU), and to assess whether these classes demonstrated differential health outcomes over time. This study uses data from 801 PLWH-SU initially enrolled across 11 US hospitals during 2012-2014 and followed up in 2017. Latent class analysis included 28 psychosocial items. Regression analysis examined class membership as a predictor of viral suppression. Survival analysis examined class as a predictor of all-cause mortality. The selected model identified five unique classes. Individuals in classes characterized by more severe and more numerous psychosocial symptoms at baseline had lower likelihoods of viral suppression and survival. The study demonstrated the importance of considering patterns of overlapping psychosocial symptoms to identify subgroups of PLWH-SU and reveal their risks for adverse outcomes. Integration of primary, mental health, and substance use care is essential to address the needs of this population.

Disadvantaged groups have greater spatial access to pharmacies in New York state.

BACKGROUND: The accessibility of pharmacies has been associated with overall health and wellbeing. Past studies have suggested that low income and racial minority communities are underserved by pharmacies. However, the literature is inconsistent in finding links between area-level income or racial and ethnic composition and access to pharmacies. Here we aim to assess area-level spatial access to pharmacies across New York State (NYS), hypothesizing that Census Tracts with higher poverty rates and higher percentages of Black and Hispanic residents would have lower spatial access. METHODS: The population weighted mean shortest road network distance (PWMSD) to a pharmacy in 2018 was calculated for each Census Tract in NYS. This statistic was calculated from the shortest road network distance to a pharmacy from the centroid of each Census block within a tract, with the mean across census blocks weighted by the population of the census block. Cross-sectional analyses were conducted to assess links between Tract-level socio demographic characteristics and Tract-level PWMSD to a pharmacy. RESULTS: Overall the mean PWMSD to a pharmacy across Census tracts in NYS was 2.07 Km (SD = 3.35, median 0.85 Km). Shorter PWMSD to a pharmacy were associated with higher Tract-level % poverty, % Black/African American (AA) residents, and % Hispanic/Latino residents and with lower Tract-level % of residents with a college degree. Compared to tracts in the lowest quartile of % Black/AA residents, tracts in the highest quartile had a 70.7% (95% CI 68.3-72.9%) shorter PWMSD to a pharmacy. Similarly, tracts in the highest quartile of % poverty had a 61.3% (95% CI 58.0-64.4%) shorter PWMSD to a pharmacy than tracts in the lowest quartile. CONCLUSION: The analyses show that tracts in NYS with higher racial and ethnic minority populations and higher poverty rates have higher spatial access to pharmacies.

Strategies of Managing Repeated Measures: Using Synthetic Random Forest to Predict HIV Viral Suppression Status Among Hospitalized Persons with HIV.

The HIV/AIDS epidemic remains a major public health concern since the 1980s; untreated HIV infection has numerous consequences on quality of life. To optimize patients' health outcomes and to reduce HIV transmission, this study focused on vulnerable populations of people living with HIV (PLWH) and compared different predictive strategies for viral suppression using longitudinal or repeated measures. The four methods of predicting viral suppression are (1) including the repeated measures of each feature as predictors, (2) utilizing only the initial (baseline) value of the feature as predictor, (3) using the last observed value as the predictors and (4) using a growth curve estimated from the features to create individual-specific prediction of growth curves as features. This study suggested the individual-specific prediction of the growth curve performed the best in terms of lowest error rate on an independent set of test data.

Functions of Resiliency Traits and Processes in Differential Effects of CBSM on Quality of Life in Breast Cancer Survivors: A Moderated Mediation Model.

BACKGROUND: Although there is evidence that cognitive behavioral therapy (CBT)-based group interventions can improve quality of life (QoL) in women undergoing treatment for breast cancer (BC) little is known about factors that mediate and moderate these effects. We examined a) the mediating role of benefit finding on QoL changes after a Cognitive Behavioral Stress Management (CBSM) intervention, and b) whether this mediation effect differed based on baseline optimism in the first year following surgery for BC. METHODS: We used data from a prior CBSM trial in 240 women with stage 0-3 BC who completed measures of benefit finding (Benefit Finding Scale, BFS), QoL (Functional Assessment of Cancer Treatment, FACT-G), and optimism (Life Orientation Test-Revised) at baseline (2 - 10 weeks post-surgery), 6-months and 12-months after randomization. CBSM-related changes and mediation and moderation effects were assessed using latent growth curve models. RESULTS: We found CBSM increased benefit finding (b = 2.65, p < 0.01), emotional (b = 0.53, p < 0.01), and functional QoL (b = 0.71, p < 0.05) over time. CBSM-related changes in emotional QoL were mediated by increased benefit finding (indirect effect = 0.68, 95% bootstrapped CI: 0.17, 1.56) but only among participants with low to moderate optimism at baseline. CONCLUSION: CBSM intervention improved emotional QoL over the first year of breast cancer treatment by increasing benefit finding among women who reported low trait optimism suggesting those who will most likely benefit from improving benefit finding during this stressful period.

Neighborhood Characteristics, Intersectional Discrimination, Mental Health, and HIV Outcomes Among Black Women Living With HIV, Southeastern United States, 2019‒2020.

Objectives. To examine the effects of within-neighborhood and neighboring characteristics on discrimination, stigma, mental health, and HIV outcomes among Black women living with HIV (BWLWH). Methods. A total of 151 BWLWH in a southeastern US city provided baseline data (October 2019‒January 2020) on experienced microaggressions and discrimination (race-, gender-, sexual orientation-, or HIV-related), mental health (e.g., depression, posttraumatic stress disorder), and HIV outcomes (e.g., viral load, antiretroviral therapy adherence). Neighborhood characteristics by census tract were gathered from the American Community Survey and the National Center for Charitable Statistics. Spatial econometrics guided the identification strategy, and we used the maximum likelihood technique to estimate relationships between a number of predictors and outcomes. Results. Within-neighborhood and neighboring characteristics (employment, education, crime, income, number of religious organizations, and low-income housing) were significantly related to intersectional stigma, discrimination, mental health, HIV viral load, and medication adherence. Conclusions. Policy, research, and interventions for BWLWH need to address the role of neighborhood characteristics to improve quality of life and HIV outcomes. (Am J Public Health. 2022;112(S4):S433-S443. https://doi.org/10.2105/AJPH.2021.306675).

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model.

BACKGROUND/AIMS: This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. METHODS: Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. RESULTS: The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. CONCLUSION: Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.

Impact of COVID-19 on HIV service delivery in Miami-Dade County: a mixed methods study.

BACKGROUND: Facilitating access to HIV prevention and treatment is imperative in Miami-Dade County (MDC), a U.S. HIV epicenter. With COVID-19, disruptions to these services have occurred, leading HIV organizations to innovate and demonstrate resilience. This study documented COVID-19 related disruptions and resilient innovations in HIV services within MDC. METHODS: This mixed methods cross-sectional study included HIV test counselors in MDC. In the quantitative component (N=106), participants reported COVID-19 impacts on HIV service delivery. Data visualization examined patterns within organizations and throughout the study period. Generalized estimating equation modeling examined differences in service disruptions and innovations. In the qualitative component, participants (N=20) completed interviews regarding COVID-19 impacts on HIV services. Rapid qualitative analysis was employed to analyze interviews. RESULTS: Quantitative data showed that innovations generally matched or outpaced disruptions, demonstrating resilience on HIV service delivery during COVID-19. HIV testing (36%, 95%CI[28%, 46%]) and STI testing (42%, 95%CI[33%, 52%]) were most likely to be disrupted. Sexual/reproductive health (45%, 95%CI[35%, 55%]), HIV testing (57%, 95%CI[47%,66%]), HIV case management (51%, 95%CI[41%, 60%]), PrEP initiation (47%, 95%CI[37%,57%]), and STI testing (47%, 95%CI[37%, 57%]) were most likely to be innovated. Qualitative analysis revealed three orthogonal themes related to 1) disruptions (with five sub-components), 2) resilient innovations (with four sub-components), and 3) emerging and ongoing health disparities. CONCLUSIONS: HIV organizations faced service disruptions during COVID-19 while also meaningfully innovating. Our findings point to potential changes in policy and practice that could be maintained beyond the immediate impacts of COVID-19 to enhance the resilience of HIV services. Aligning with the US Ending the HIV Epidemic Plan and the National Strategy for HIV/AIDS, capitalizing on the observed innovations would facilitate improved HIV-related health services for people living in MDC and beyond.

Efficacy of a Family-Based Intervention for HIV Prevention with Hispanic Adolescents with Same Gender Sexual Behaviors.

Despite the availability of efficacious and effective family-based interventions, such interventions are scarce for sexual minority adolescents, particularly among ethnic/racial minorities. Prior to creating an entirely new intervention, a prudent first step may be to determine if existing interventions are efficacious in reducing risk behaviors in sexual minority adolescents. This study assesses the relative efficacy of a general, family-based intervention (Familias Unidas) on improving substance and condom use outcomes among Hispanic adolescents with same gender sexual behaviors (HASGB). Data across five distinct trials of Familias Unidas were synthesized. HASGB were randomized either to an intervention (n = 94) or control condition (n = 100). Mediation analyses tested for intervention efficacy on past 90-day substance (cigarette/alcohol/illicit drug) use and condomless sex at last intercourse in HASGB participants and whether family functioning indicators-parent-adolescent communication, positive parenting, and parental monitoring of peers-mediated the effects. Post hoc analyses explored the moderating role of study target population based on prior risk. Familias Unidas did not impact substance use but significantly reduced condomless sex postintervention relative to the control condition. Hypothesized mediators did not explain this effect. Post hoc analyses indicated that the effect was significant in studies that recruited based on prior risk but not studies that recruited universal samples. Our results suggest that a general, family-based intervention may have positive effects on condom use in HASGB, particularly those with prior indicated risk. Identifying intervention components that drive this effect in addition to developing tailored content for HASGB is needed.

Latent class analysis of loneliness and connectedness in US young adults during COVID-19.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic in the United States has exacerbated a number of mental health conditions and problems related to prolonged social isolation. While COVID-19 has led to greater loneliness and a lack of social connectedness, little is known about who are the most affected and how they are impacted. Therefore, we performed a Latent Class Analysis using items from two scales - the UCLA Loneliness Scale and the Social Connectedness Scale - to characterize different experiences of loneliness and connectedness, examine their relationship with mental health and substance use symptoms, including depression, anxiety, drinking, and drug use. METHODS: Data were drawn from an anonymous one-time online survey examining the mental health of 1008 young adults (18-35 years old) during COVID-19. A latent class analysis (LCA) was conducted to observe and identify classes based on responses to loneliness and connectedness scale items, and to examine the existence of subgroups among this young adult population. RESULTS: We identified a 4-class model of loneliness and connectedness: (1) Lonely and Disconnected - highest probabilities in items of loneliness and disconnectedness, (2) Moderately Lonely and Disconnected - adaptive levels of some isolation and disconnection during COVID-19, (3) Ambivalent Feelings - displaying negative responses in particular to negatively-worded items while simultaneously affirming positively worded items, and (4) Connected and Not Lonely - lowest probabilities in items of loneliness and disconnectedness. CONCLUSION: Key findings include (1) the delineation of classes by levels of loneliness and connectedness showcasing differential mental health and substance use symptoms, (2) the utility of item-level evaluation with LCA in determining specific classes of people in need of outreach and intervention, and (3) the promise of social connection to bolster resilience in young adults.

Initiation of Antiretroviral Therapy in the Hospital Is Associated With Linkage to Human Immunodeficiency Virus (HIV) Care for Persons Living With HIV and Substance Use Disorder.

BACKGROUND: Studies have demonstrated benefits of antiretroviral therapy (ART) initiation on the day of human immunodeficiency virus (HIV) testing or at first clinical visit. The hospital setting is understudied for immediate ART initiation. METHODS: CTN0049, a linkage-to-care randomized clinical trial, enrolled 801 persons living with HIV (PLWH) and substance use disorder (SUD) from 11 hospitals across the United States. This secondary analysis examined factors related to initiating (including reinitiating) ART in the hospital and its association with linkage to HIV care, frequency of outpatient care visits, retention, and viral suppression. RESULTS: Of 801 participants, 124 (15%) initiated ART in the hospital, with more than two-thirds of these participants (80/124) initiating ART for the first time. Time to first HIV care visit among those who initiated ART in the hospital and those who did not was 29 and 54 days, respectively (P = .0145). Hospital initiation of ART was associated with increased frequency of HIV outpatient care visits at 6 and 12 months. There was no association with ART initiation in the hospital and retention and viral suppression over a 12-month period. Participants recruited in Southern hospitals were less likely to initiate ART in the hospital (P < .001). CONCLUSIONS: Previous research demonstrated benefits of immediate ART initiation, yet this approach is not widely implemented. Research findings suggest that starting ART in the hospital is beneficial for increasing linkage to HIV care and frequency of visits for PLWH and SUD. Implementation research should address barriers to early ART initiation in the hospital.

The Potential Epidemiological Impact of Coronavirus Disease 2019 (COVID-19) on the Human Immunodeficiency Virus (HIV) Epidemic and the Cost-effectiveness of Linked, Opt-out HIV Testing: A Modeling Study in 6 US Cities.

BACKGROUND: Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities. METHODS: Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years. RESULTS: In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city. CONCLUSIONS: A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.

Tryptophan depletion predicts lower positive affect in sexual minority men living with HIV who use methamphetamine.

This longitudinal study with 76 sexual minority men living with HIV who use methamphetamine examined whether dysregulation of essential amino acid precursors for neurotransmitters at baseline predicted positive and negative affect at 15 months. After controlling for covariates including baseline positive affect, a higher baseline kynurenine/tryptophan (K/T) ratio independently predicted lower positive affect at 15 months (ß = - 18.31; 95% CI = - 35.35, - 1.27; p = 0.036). Future clinical research should examine whether bio-behavioral interventions targeting tryptophan degradation could optimize treatments for people living with co-occurring HIV and stimulant use disorders.

Disparities in Opioid Overdose Death Trends by Race/Ethnicity, 2018-2019, From the HEALing Communities Study.

Objectives. To examine trends in opioid overdose deaths by race/ethnicity from 2018 to 2019 across 67 HEALing Communities Study (HCS) communities in Kentucky, New York, Massachusetts, and Ohio. Methods. We used state death certificate records to calculate opioid overdose death rates per 100 000 adult residents of the 67 HCS communities for 2018 and 2019. We used Poisson regression to calculate the ratio of 2019 to 2018 rates. We compared changes by race/ethnicity by calculating a ratio of rate ratios (RRR) for each racial/ethnic group compared with non-Hispanic White individuals. Results. Opioid overdose death rates were 38.3 and 39.5 per 100 000 for 2018 and 2019, respectively, without a significant change from 2018 to 2019 (rate ratio = 1.03; 95% confidence interval [CI] = 0.98, 1.08). We estimated a 40% increase in opioid overdose death rate for non-Hispanic Black individuals (RRR = 1.40; 95% CI = 1.22, 1.62) relative to non-Hispanic White individuals but no change among other race/ethnicities. Conclusions. Overall opioid overdose death rates have leveled off but have increased among non-Hispanic Black individuals. Public Health Implications. An antiracist public health approach is needed to address the crisis of opioid-related harms. (Am J Public Health. 2021;111(10):1851-1854. https://doi.org/10.2105/AJPH.2021.306431).

Understanding Willingness to Participate in HIV Biomedical Research: A Mixed Methods Investigation.

Biomedical research often enrolls people living with HIV (PLWH) receiving effective treatment to complete invasive procedures. This mixed methods study characterized determinants of willingness to undergo specific biomedical procedures among PLWH. In 2017, 61 participants (77% Black) from Miami completed a quantitative assessment examining willingness to participate. A subset of 19 participants completed an in-depth qualitative interview. Across all procedures, there was greater willingness to participate if asked by a primary care provider and if experimental results were shared. However, half of participants reported that they would experience undue influence (i.e., excessive persuasion) to participate from their primary care provider. In thematic analyses, altruism and personal benefit were identified as facilitators while medication changes, confidentiality, and perceived stigma were identified as barriers to participation in HIV biomedical research. Addressing participants' expectations and mitigating potential undue influence from primary care providers could optimize the ethical conduct of HIV biomedical studies.

Daily Microaggressions and Related Distress among Black Women Living with HIV during the Onset of the COVID-19 Pandemic and Black Lives Matter Protests.

Black women living with HIV (BWLWH) in the U.S. face microaggressions based on race, gender, HIV-status, and sexual orientation. We examined changes in daily microaggressions and related distress among 143 BWLWH in Miami, FL. Microaggression-related distress increased from 52% at baseline/October, peaked at 70% during the holidays (November/December), declined to 55% in March when COVID-19 social distancing began, and peaked to 83% in June/July 2020 during widespread Black Lives Matters protests. Baseline viral suppression was associated with lower microaggressions across the 9-months. Microaggression-related distress may change due to social context and research is needed on microaggressions and viral load overtime.

RESUMEN: Las mujeres de raza negra que viven con el VIH (MNVV) en los EE. UU. enfrentan microagresiones basadas en la raza, el género, el estado serológico del VIH y la orientación sexual. Examinamos los cambios en las microagresiones diarias y el estrés relacionado entre 143 MNVV en Miami, FL. El estrés relacionado con la microagresión aumentó del 52% en la línea de base/octubre, alcanzó un máximo del 70% durante las vacaciones (noviembre/diciembre), disminuyó al 55% en marzo cuando comenzó el distanciamiento social por el COVID-19 y alcanzó un máximo del 83% en junio/julio de 2020 durante las protestas generalizadas de Black Lives Matters. La supresión viral inicial se asoció con menores microagresiones durante los 9 meses. El estrés relacionada con la microagresión puede cambiar debido al contexto social y se necesitan investigaciones sobre las microagresiones y la carga viral con el tiempo.

The Disaggregated Repeated Measures Design: A Novel Approach to Assess Sexual Risk Behaviors.

Although numerous studies have examined sexual and substance use behaviors that put people at risk for sexually transmitted infections including HIV, most focus on an overall measure of aggregate risk or a few simple and particular subtypes of sexual acts assessed in separate analyses. In this article, we introduce a more sensitive approach to assess how the relative characteristics of sex acts may determine the level of risk in which an individual chooses to engage. Project AWARE, a randomized clinical trial conducted among 5012 patients in nine STD clinics across the U.S., is used to illustrate the approach. Our study was guided by two aims: (1) describe a new approach to examine the count of sexual acts using a disaggregated repeated measures design and (2) show how this new approach can be used to evaluate interactions among different categories of sexual risk behaviors and other predictors of interest (such as gender/sexual orientation). Profiles of different subtypes of sexual acts in the past 6 months were assessed. Potential interactions of the characteristics associated with each subtype which resulted in up to 48 distinct subtypes of sexual risk behaviors-sex with a primary/non-primary partner; partner's HIV status; vaginal/anal sex; condom use; and substance use before or during sex act-can be examined. Specifically, we chose condom use and primary and non-primary status of partner as an application in this paper to illustrate our method. There were significantly more condomless sex acts (M = 23, SE = 0.9) and sex acts with primary partners (M = 27.1, SE = 0.9) compared to sex acts with condoms (M = 10.9, SE = 0.4, IRR = 2.10, 95% CI 1.91-2.32, p < .001) and sex acts with non-primary partner (M = 10.9, SE = 0.5, IRR = 2.5, 95% CI 2.33-2.78, p < .001). In addition, there were significant differences for the count of sexual risk behaviors among women who have sex with men (WSM), men who have sex with women (MSW) and men who have sex with men (MSM) for sex acts with and without condom use, primary and non-primary partner, and their interaction (ps = .03, < .0001, and .001, respectively). This approach extends our understanding of how people make choices among sexual behaviors and may be useful in future research on disaggregated characteristics of sex acts.

Trauma exposure, PTSD, and suboptimal HIV medication adherence among marginalized individuals connected to public HIV care in Miami.

Individuals living with HIV report disproportionately high levels of trauma exposure and PTSD symptoms, both which have been associated with suboptimal ART adherence. Often conflated, the question arises as to which construct is driving subsequent HIV self-care behavior. Given the HIV disparities among Black and Hispanic/Latinx individuals, and that Miami is a geographic region with a high racial/ethnic minority make up and a unique socioeconomic environment, it is important to explore factors related to HIV outcomes in Miami to mitigate its uncontrolled epidemic. This study aimed to examine the association of trauma exposure, PTSD symptoms, and relevant additional key factors with adherence to ART among a sample of majority Black and Hispanic/Latinx individuals who are economically marginalized receiving public HIV care in Miami, FL (N = 1237) via a cross-sectional survey. Sequential linear regression was used to examine the study aim in four blocks: (1) trauma, (2) PTSD symptoms, and key covariates of ART adherence including (3) depression and substance use (potential psychological covariates), and (4) indicators of socioeconomic status (potential structural covariates). In the first block, trauma exposure was associated with worse adherence. However, in the second block, the association with trauma dropped and PTSD was significantly associated with worse adherence. Of note, for those experiencing high levels of trauma exposure, adherence was negatively impacted regardless of PTSD. When other key factors associated with adherence were entered in the third and fourth blocks, neither trauma exposure nor PTSD were uniquely significant. In this final model, depression, substance use, and unstable housing were uniquely associated with worse adherence. Trauma-informed models of HIV care that holistically address co-occurring factors are warranted to cater to communities with HIV health disparities and keep them from falling off the HIV care continuum.