Amanda D. Castel

Background: Internalized HIV-related stigma can have a negative impact on health outcomes among people with HIV (PWH). A multilevel model, informed by an intersectional framework, is needed to evaluate the interactions between various aspects of one’s identity and their impact on internalized HIV-related stigma. Therefore, we used a Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate internalized stigma among PWH. Methods: We evaluated a subset of participants in the DC Cohort longitudinal study on PWH who completed a patient reported outcomes (PROs) survey. Participants were sorted into 24 strata of race/ethnicity, gender, sexual orientation, and age. Stigma was evaluated using a self-reported 4-item instrument. We evaluated the individual and strata level impacts of these variables on internalized stigma using MAIHDA. Results: We evaluated 1,540 DC Cohort participants with complete strata information, most of which were non-Hispanic Black (80.3%), male (73.1%), gay/lesbian/bisexual (52.1%), and had a mean age of 52.3 years old. Based on the null model, the strata explain 6.96% of the total variance in stigma. This variance was reduced to 1.67% after adjusting for the individual effects of race/ethnicity, gender, sexual orientation, and age. This shows that the main effects of these covariates jointly account for 77.27% of the between-strata stigma variance, while the remaining 22.73% of the between-strata variance is potentially due to the intersectional effects between the covariates. Conclusion: Although the individual effects of race/ethnicity, gender, sexual orientation, and age did not explain a large portion of the variance in stigma, nearly a quarter of the between-strata variance in stigma is potentially attributable to the interaction between these covariates.

Background: Adolescents and young adults account for a disproportionate number of new HIV diagnoses in the United States due to missed opportunities for education, testing, and prevention. Objective: We tested the efficacy of an interactive life-simulation gaming intervention to provide HIV education and improve HIV testing uptake and preventive services among youths ages 13‐24 years in the Washington, DC area. Methods: We conducted a parallel randomized controlled trial testing the efficacy of an HIV-focused gaming intervention app to a control app in increasing HIV testing uptake. Participants were recruited via social media and peer referral. Eligible participants were randomized 1:1 by age (13‐17 vs 18‐24 years) and sexual orientation (lesbian, gay, bisexual, or “other” vs heterosexual). Participants accessed their assigned app for 3 months and completed baseline, 1-, 3-, and 6-month surveys. The primary outcome was self-reported HIV testing within 6 months after enrollment; secondary outcomes included intent to test for HIV, HIV knowledge, and intention to start pre-exposure prophylaxis (PrEP). Analyses were conducted as intent-to-treat and stratified by sexual orientation. Results: From November 2023 to May 2024, we randomized 309 participants (intervention: n=156; control: n=153) with 80% and 88% retention at 6 months, respectively. Among the analyzed participants (intervention: n=150; control: n=149), the mean age was 20.7 (SD 1.84) years, 49% (145/299) were women, and 34% (103/299) were non-Hispanic White. Overall, 53% (158/299) self-reported as gay, lesbian, bisexual, or “other” sexual orientation. A total of 48% (144/299) had previously tested for HIV. Compared to the control app, game participants were 32% less likely to test for HIV within 6 months (relative risk 0.68, 95% CI 0.47‐0.98). The two groups showed no statistically significant differences regarding their intention to get tested for HIV or to start PrEP. A significantly higher difference in mean HIV knowledge scores at 3 months (0.99, 95% CI 0.33‐1.65; P <.01) and 6 months (0.81, 95% CI 0.14‐1.48; P =.02) was observed in the game arm compared to the control arm. Additionally, heterosexual participants in the game arm had statistically significant increases in PrEP intention (0.53, 95% CI 0.05‐1.00; P =.03) across all time points compared to controls. Conclusions: Our interactive gaming app was less effective than an information control app in increasing HIV testing and changing testing and prevention intentions among adolescents and young adults. In the game arm, we did observe increased HIV knowledge and increased PrEP intention among heterosexual adolescents and young adults. Few life-simulation apps integrating HIV testing and prevention features have been rigorously tested among adolescents and young adults. Our efficacy findings suggest that while these interventions are feasible and acceptable to adolescents and young adults, they require additional tailoring to improve their reach, use, and potential effectiveness in real-world settings.

Background: We examined factors related to being out of care (OOC) or reentering care after clinic transfer among people with HIV in Washington, DC using clinical and linked surveillance data from the DC Department of Health (DC Health). Methods: Using DC Cohort HIV care encounters and laboratory results, linked surveillance data, and chart review, we determined if participants were (1) engaged in care; (2) OOC; (3) died; (4) withdrew; (5) clinic-reported transfer; (6) surveillance-based transfer (using DC Health data); and (7) undetermined. Of the clinic-reported transfers, we used surveillance data to determine whether participants reentered care after transfer. We evaluated associations between participant characteristics, being OOC, and reentering care using logistic regression. Results: We evaluated 12,563 DC Cohort participants, 6557 (52.5%) were engaged in care, 748 (6.0%) OOC, 1893 (15.0%) clinic-reported transfers, 1692 (13.5%) surveillance-based transfers, 1418 (11.0%) died, 41 (0.3%) withdrew, and 214 (1.7%) were undetermined. Of clinic-reported transfers, 832 (44.0%) reentered care, with 80.9% achieving viral suppression (<200 copies/mL). In the adjusted analysis, females, older age, non-Hispanic Black race, longer time since HIV diagnosis, CD4 ≥ 500 cells/µL, former or never smoking, and public insurance were associated with being engaged in care. Similarly, non-Hispanic Black race, non-Hispanic White race, nonviral suppression, Ryan White clinic, former alcohol abuse, and temporary/unstable housing were associated with reentering care among the clinic-reported transfers, after adjusting for covariates. Conclusions: Individual, clinical, and structural factors were associated with being OOC or care reentry. Targeted interventions addressing these factors may improve sustained HIV care and reduce transmission.

Background: Evaluating implementation of digital health interventions (DHIs) in practice settings is complex, involving diverse users and multistep processes. Proactive planning can ensure implementation determinants and outcomes are captured for hybrid studies, but operational guidance for designing or planning hybrid DHI studies is limited. Objective: This study aimed to proactively define, prioritize, and operationalize measurement of implementation outcomes and determinants for a DHI hybrid effectiveness-implementation trial. We describe unique advantages and limitations of planning the trial implementation evaluation among a large-scale cohort study population and share results of a pretrial organizational readiness assessment. Methods: We planned a cluster-randomized, type II hybrid effectiveness-implementation trial testing PositiveLinks , a smartphone app for HIV care, compared to usual care (n=6 sites per arm), among HIV outpatient sites in the DC Cohort Longitudinal HIV Study in Washington, DC. We (1) defined components of the DHI and associated implementation strategy; (2) selected implementation science frameworks to accomplish evaluation aims; (3) mapped framework dimensions, domains, and constructs to implementation strategy steps; (4) modified or created instruments to collect data for implementation outcome measures and determinants; and (5) developed a compatible implementation science data collection and management plan. Provider baseline surveys administered at intervention sites probed usage of digital tools and assessed provider readiness for implementation with the Organizational Readiness to Implement Change tool. Results: We specified DHI and implementation strategy toward planning measurement of DHI and broader program reach and adoption. Mapping of implementation strategy steps to the Reach Effectiveness Adoption Implementation Maintenance framework prompted considerations for how to capture understudied aspects of each dimension: denominators and demographic representativeness within reach or adoption, and provider or organization-level adaptations, dose, and fidelity within the implementation dimension. Our process also prompted the creation of tools to obtain detailed determinants across domains and constructs of the Consolidated Framework for Implementation Research within a large sample at multiple time points. Some aspects of real-world PositiveLinks implementation were not reflected within the planned hybrid trial (eg, research assistants selected as de facto site implementation leads) or were modified to preserve internal validity of effectiveness measurement (eg, “Community of Practice”). Providers and research assistants (n=17) at intervention sites self-reported high baseline use of digital tools to communicate with patients. Readiness assessment revealed high median (48, IQR 45‐54) total Organizational Readiness to Implement Change scores, with research assistants scoring higher than physicians (52.5, IQR 44-55 vs 48.0, IQR 46-49). Conclusions: Key takeaways, challenges, and opportunities arose in planning the implementation evaluation within a hybrid DHI trial among a cohort population. Prospective trial planning must balance generalizability of implementation processes to “real world” conditions with rigorous procedures to measure intervention effectiveness. Rapid, scalable tools require further study to enable evaluations within large multisite hybrid studies.

Background: People of Asian ethnicity represent one of the fastest-growing populations in the United States and may experience unique social and cultural challenges to accessing sexual healthcare. This analysis explores disparities in annual sexually transmitted infection screening and diagnosis rates per person-year between Asian and non-Asian people with human immunodeficiency virus in Washington, District of Columbia (DC). Methods: Using District Columbia cohort data, a longitudinal study of people living with human immunodeficiency virus receiving care in Washington, DC, we analyzed people with human immunodeficiency virus aged 18 or older with at least 1 year of follow-up between 2018 and 2023. Logistic regression was used to examine differences in sexually transmitted infection screening and diagnoses between Asian and non-Asian participants, while linear trend analyses were used to assess changes in the number of screenings and diagnoses between Asian and non-Asian participants. Results: Among 8679 eligible participants, 0.88% (n = 76) were Asian. No significant differences in total sexually transmitted infection screenings or diagnoses were observed. However, Asian participants had higher screening rates per person-year for pharyngeal and urogenital gonorrhea, pharyngeal chlamydia, and syphilis. Chlamydia incidence was higher among Asian than non-Asian participants. Over 30% of both groups met the annual screening recommendation during the study period. Conclusions: Asians had comparable screening rates to non-Asians, but the small sample size limited the generalizability of our findings. Nonetheless, this study helps address an existing gap in the literature on Asian sexual health. Larger studies with detailed ethnic and social data are needed to deepen our understanding of sexual health service use within Asian communities.

Latina/o/x (Latino) populations are disproportionately affected by HIV, with intersecting social and structural factors shaping outcomes. To capture these complex intersections, we applied a decision tree approach, Chi-squared Automatic Interaction Detector (CHAID), to examine engagement in care and viral suppression among adult Latinos enrolled in the DC Cohort, a longitudinal electronic health record-based cohort of people with HIV across 15 Washington, DC, clinics (2011-2019). Socio-structural variables included age, gender identity, HIV risk category, country of birth, mental health diagnosis, substance use, housing, employment, and insurance. Engagement in care was defined as ≥ 2 visits ≥ 90 days apart with laboratory work in the prior year; viral suppression as < 200 copies/mL. Analyses included chi-square tests and CHAID decision trees. Among 541 participants, most were cisgender male (85%) with a median age of 47 years; 48% were foreign-born, 31% had substance use disorder, and 49% a mental health diagnosis. Overall, 80% were engaged in care, and 88% were virally suppressed. CHAID identified site of care (academic vs. community clinic) as the strongest predictor of engagement, with higher engagement in community clinics. Within community sites, employment, housing stability, and age further differentiated outcomes. For viral suppression, housing was the most important predictor, followed by HIV transmission risk, substance use, and age. Decision tree analysis enabled an intersectional, non-additive approach to HIV outcomes. Housing emerged as the most significant factor, interacting with employment, substance use, and age. Findings highlight the utility of CHAID for identifying at-risk subgroups and guiding targeted support for Latinos with HIV.

The COVID-19 pandemic created interruptions in healthcare for many people with chronic illnesses, including people with HIV (PWH). Our objective was to ass

Objectives: There is a high prevalence of internalized stigma among people with HIV (PWH) and it is possible that factors associated with stigma differ by gender. Therefore, we evaluated whether gender is an effect modifier of the association between covariates and internalized stigma among 694 PWH. Methods: Linear regression with interaction terms between covariates and gender was used to evaluate significant associations and test for interactions. Results: We found a 10-year increase in age was associated with lower stigma among women (β (95% CI): −0.20 (−0.30, −0.10)) but not among men (β = 0). Generalized anxiety disorder (GAD) was associated with higher stigma (GAD & GAD-squared β (95% CI): 0.12 (0.08, 0.187), −0.004 (−0.006, −0.001)) and an increased time since HIV diagnosis was associated with lower stigma (β (95% CI): −0.20 (−0.30, −0.10)). Conclusions: Gender-specific interventions should be developed to account for the differences in the association between age and stigma across genders.

The DC Cohort is a longitudinal HIV cohort study of people with HIV receiving care at 14 clinical sites in Washington, DC, led by George Washington University. Data are routinely linked to the DC Department of Health (DC Health) HIV surveillance databases to increase data completeness and accuracy and to help identify people with HIV enrolled at multiple sites. The ATra Black Box (Black Box henceforth) is a novel privacy technology developed by Georgetown University, which is currently deployed in 40 public health jurisdictions. The Black Box provides a secure mechanism to link private health information across data systems. The Black Box was modified for the purposes of linking data from the DC Cohort to DC Health surveillance data and increasing the ease, feasibility, accuracy, and timeliness of future linkages. These modifications included providing deidentified data to George Washington University and developing analytic code to compare data between the DC Cohort and DC Health to report on data discrepancies. This paper reports on the results of the initial linkage using the Black Box. DC Cohort data on all consented participants from January 2011 through September 2022 were submitted to the Black Box. Simultaneously, all DC Health HIV surveillance data were also submitted to the Black Box. The data were matched using a predetermined algorithm, match-level scores were assigned, and matches were manually verified. The new Black Box graphical user interface allows users to check files for errors and easily track the Black Box processes and provides analytic plugins for running SAS code. A total of 9744 records of DC Cohort participants were submitted for matching to DC Health. Of these, 9060 participants (93.0%) matched to surveillance data and were validated through manual review. Match-level scores ranged from 20 to 100, and the validation found that scores of 61 and above were true matches. The SAS output files provided information on missing or conflicting data, including lab records, date of HIV diagnosis, and other key demographics. The linkage resulted in the addition of 48,970 CD4 T-lymphocyte counts, 33,413 viral load lab records, and 767 previously unrecognized deaths. Among the DC Cohort participants, 470 were enrolled at more than one site and 17 at more than two sites. The implementation of the Black Box for sharing DC Cohort and DC Health data resulted in better capture of HIV lab records, improved vital status information, and enhanced characterization of care patterns for people with HIV enrolled in the DC Cohort. Future linkages will include DC Health data on diagnoses of sexually transmitted infections, hepatitis, and tuberculosis.

Aim Patient-reported outcomes (PROs) can help to evaluate gaps and areas for improvement along the HIV care continuum. We sought to describe the methodology and processes of a PROs study within the DC Cohort study population, describe the PROs results to date, report on lessons learned, and describe future directions of the research. Subject and methods Each study site recruited participants from the DC Cohort, a longitudinal study on people with HIV, to complete the electronic PROs baseline and annual follow-up surveys, which consisted of previously validated measures of social determinants of health, mental health, substance use, medication adherence, and other related measures. The recruitment, enrollment, and data linkage process strengths and limitations were described. Participants’ PROs survey responses were linked to their DC Cohort data to better understand participant’s health overall. Results There have been 1739 baseline, 610 first annual, and 142 second annual completed surveys between May 2021 and May 2024. Among PROs participants, the most common reported unmet need was food insecurity (33.5%) and the most common mental health condition was generalized anxiety disorder (39.5%). A majority (59.7%) of participants reported being sexually active, but at least half did not use barrier protection. Conclusion PROs surveys complement electronic health record data collected in the DC Cohort study, allowing for examination of health outcomes and factors collected in a longitudinal manner. PROs results could be integrated into near-real time dashboards for use by clinicians and incorporated into routine clinical care to provide a more holistic understanding of the patient.