Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: J Behav Med. 2020 Oct 24;44(2):147–158. doi: 10.1007/s10865-020-00191-w

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

Tiffany R Glynn 1, Noelle A Mendez 1, Deborah L Jones 3, Sannisha K Dale 1, Adam W Carrico 2, Daniel J Feaster 2, Allan E Rodriguez 4, Steven A Safren 1
PMCID: PMC7965249  NIHMSID: NIHMS1640771  PMID: 33098541

Abstract

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=1,237) 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.

Keywords: trauma, PTSD, HIV, antiretroviral therapy, adherence

Introduction

The most recent data from the CDC reported that the overall HIV incidence in the United States (US) remained stable in 2018 (Centers for Disease Control and Prevention, 2020a), yet some geographic regions and subgroups of people continue to be disproportionately impacted. Specifically, Miami, FL continues to see increasing rates of new HIV infections and ranks first as the US city with the highest HIV incidence in the country (Centers for Disease Control and Prevention, 2020b). Contextualizing this HIV epidemic, Miami has high racial/ethnic diversity (Miami Matters, 2020a), an important consideration given the disparities in HIV infection and care among Black and Hispanic/Latinx individuals. Across the US, 70% of new infections in 2018 were among Black individuals (42%) and Hispanic/Latinx individuals (28%)(Centers for Disease Control and Prevention, 2020a). Specifically, in Miami, 93% of new infections were among people of color, specifically, 43% Black, 49% Hispanic/Latinx, and 1% other (Florida Department of Health Bureau of Communicable Diseases, 2019a). Further, Black and Hispanic/Latinx individuals have less linkage to HIV medical care and lower proportion of viral suppression compared to White counterparts across the US (Centers for Disease Control and Prevention, 2020c). Notably, in Miami, only 61% of Black individuals and 69% of Hispanic/Latinx individuals living with HIV were retained in HIV care and only 53% of Black individuals and 66% of Hispanic/Latinx individuals are virally suppressed (Florida Department of Health Bureau of Communicable Diseases, 2019a, 2019b).

Such disparities among Black and Hispanic/Latinx communities are rooted in social and structural marginalization, such as racism and low access to resources, which then affect individual level issues like mental health, substance use, and health behaviors (e.g., medication adherence)(Kennedy, 2009; Pellowski et al., 2013; Whittle et al., 2020). This is especially pertinent in Miami which has a unique socioeconomic context including high immigration, high economic inequities, politically mixed population, and relatively low resources compared to the rest of the country (American Immigration Council, 2020; Miami Matters, 2020b; Miami Urban Future Initiative, 2019; Miami-Dade County Elections Department, 2020). Further, when an individual has multiple marginalized identities, like being a person of color living with HIV, this intersection of marginalization can exacerbate disparities in connection to HIV care, and HIV disease progression (Logie et al., 2019; Turan et al., 2017). 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 sociopolitical environment, it is important to explore factors related to HIV outcomes in Miami to mitigate its uncontrolled epidemic.

Individuals living with HIV report disproportionately high levels of exposure to traumatic events compared to their HIV-uninfected counterparts (Brezing et al., 2015; Brief et al., 2004; Machtinger et al., 2012). The types of trauma experienced at higher rates than the general population are across both childhood and adulthood and include emotional, verbal, physical, and sexual abuse/violence (LeGrand et al., 2015). Compounding this for people of color living with HIV, Black and Hispanic/Latinx individuals experience greater exposure to some types of trauma compared to their White counterparts (McLaughlin et al., 2019; Roberts et al., 2011). Exposure to trauma has been associated with worse physical health outcomes in the general population (D’Andrea et al., 2011; Schnurr & Green, 2004; Spitzer et al., 2009). Considering the significantly higher rates of trauma in individuals living with HIV, and especially among Black and Hispanic/Latinx individuals living with HIV, several studies have examined the sequelae of trauma including HIV health outcomes. Exposure to trauma has been associated with poorer physical functioning, greater HIV symptomology, and AIDS mortality among individuals with HIV (Anderson et al., 2018; Brief et al., 2004; LeGrand et al., 2015; Leserman, 2008; Mugavero et al., 2007; Pence, 2009).

Pathways from trauma to HIV health outcomes are complex and operate via physiological, psychological, and behavioral mechanisms (Glynn, Llabre, et al., 2019; LeGrand et al., 2015; Neigh et al., 2016). Given that many individuals living with HIV achieve viral suppression through antiretroviral treatment (ART), and viral suppression is associated with better health outcomes (Lundgren et al., 2015; Teeraananchai et al., 2017), adherence to ART continues to be an important behavioral factor to consider in the trauma to HIV health outcomes relationship. Indeed, individuals living with HIV/AIDS with trauma histories show higher likelihood of ART nonadherence (Brezing et al., 2015; Mugavero et al., 2006; Mugavero et al., 2007; Mugavero et al., 2009; Pence, 2009).

Post-traumatic stress disorder (PTSD) is a psychological disorder resulting from trauma characterized by enduring alterations in the physiological, psychological, and behavioral stress response. Compared to the estimated 4.7% (past year) and 6.1% (lifetime) prevalence of PTSD in the general population in the United States (Goldstein et al., 2016), people living with HIV have higher rates of PTSD, with an estimated 38% global prevalence (Tang et al., 2020). For example, a meta-analysis found that 30% of women with HIV in the studies reviewed met criteria for PTSD, five times the rate of HIV-uninfected counterparts (Machtinger et al., 2012). Additionally, Black and Hispanic/Latinx individuals develop PTSD at higher rates and experience more severe symptoms than White individuals (Sibrava et al., 2019). Belonging to both groups (i.e., being Black and/or Hispanic/Latinx living with HIV) significantly increases risk of developing PTSD. Indeed, recent research found that Black women living with HIV had 3-fold higher prevalence of lifetime PTSD and 11-fold higher prevalence of current PTSD compared to the general population (Hutton et al., 2020). PTSD is important to consider as it has been associated with suboptimal ART adherence, HIV disease progression, greater symptomology, higher viral load, and lower CD4+ T-cell count (Delahanty et al., 2004; Leserman, 2008; Leserman et al., 2005; Reilly et al., 2009; Taggart Wasson et al., 2018; Vranceanu et al., 2008).

Although often conflated, trauma exposure and PTSD are separate constructs with PTSD being a potential result of trauma. However, not all individuals exposed to trauma develop PTSD. Studies have found a wide range in the prevalence of exposure to traumatic events in the United States, reaching percentages as high as 90% (Kilpatrick et al., 2013), yet the prevalence of PTSD still remains below 7% (Goldstein et al., 2016). Given that trauma exposure is associated with suboptimal ART adherence (and subsequent HIV disease progression) and that PTSD is also associated with these outcomes, the question arises as to which construct is driving the implications for self-care/adherence: trauma exposure or symptoms meeting diagnostic criteria for PTSD? Studies examining both constructs together, which would aid in parsing out these relationships, are not yet integrated into the literature as these constructs are often conflated or used interchangeably.

In addition to trauma exposure and PTSD showing a predictive relationship with suboptimal ART adherence, there are other factors that have been shown to have a similar relationship. Specifically, suboptimal adherence has been associated with depression (J. S. Gonzalez et al., 2011; Langebeek et al., 2014), substance use (A. Gonzalez et al., 2011; Langebeek et al., 2014; Zhang et al., 2018), and socioeconomic marginalization (unstable housing [Milloy et al., 2012; Smith & Cook, 2019], low education [Golin et al., 2002; Peltzer & Pengpid, 2013], and unemployment [Nachega et al., 2015; Smith & Cook, 2019]). Of note, due to social and structural marginalization, Black and Hispanic/Latinx individuals often experience depression, substance use, and socioeconomic marginalization (Bailey et al., 2017). Thus, not only do these factors influence ART adherence among individuals living with HIV, but the intersection of marginalized identities, being a Black and/or Hispanic/Latinx individual living with HIV, also bolsters these associations. Of note, although both depression and PTSD have been consistently associated with adherence as discussed, research has been mixed when considering these two predictors together. Some studies have shown that, while controlling for each other, depression, and not PTSD, was associated with poor ART adherence (Sledjeski et al., 2005; Vranceanu et al., 2008) while at least one study has found the opposite (Ebrahimzadeh et al., 2019). Additionally, it is unclear the effect of substance use and socioeconomic status on ART adherence when also controlling for PTSD/trauma given the paucity in the literature examining these constructs in one model. Not only are these additional factors associated with suboptimal ART adherence, the sequelae of trauma often includes depression, substance use, and socioeconomic marginalization alongside PTSD (Afzali et al., 2017; Chilcoat & Breslau, 1998; Leeies et al., 2010; María-Ríos & Morrow, 2020; Stander et al., 2014). Thus, the aim of the current study was to examine if PTSD symptoms and trauma exposure are associated with ART adherence, a supported mechanism of HIV health outcomes, while controlling for each other and the additional key factors that have been shown to affect adherence and are a part of the sequelae of trauma. Additionally, given the racial/ethnic disparities in HIV and related factors and the uncontrolled HIV epidemic particularly impacting Black and Hispanic/Latinx individuals in Miami, a geographic location with both high racial/ethnic and economic diversity, the study examines this aim within the context of individuals receiving care at the public HIV clinic in Miami.

Methods

Participants

From April 2017 through February 2020, 1,237 persons living with HIV/AIDS in a public, non-profit tertiary care hospital in downtown Miami completed a one-time interviewer-administered psychosocial assessment in either English (n = 964, 78%), Spanish (n = 264, 21%), or Haitian Creole (n = 9, 1%). All measures were forward and back translated by certified translators for this study. This clinic is an urban safety-net clinic serving the socially marginalized and underserved individuals not consistently connected to care (Glynn, Safren, et al., 2019; Wawrzyniak et al., 2015). Inclusion criteria included: (a) clinic patient receiving HIV care, (b) able to give consent, (c) 18 years of age or older, and (d) able to speak and understand either English, Spanish, or Haitian Creole. Trained study staff allowed time for participant to read consent form and then discussed the form with the participant. All study procedures received approval from the University of Miami Institutional Review Board prior to study onset.

Measures

ART adherence.

Wilson et al.’s validated 3-item adherence measure (Wilson et al., 2016) was used to assess level of ART adherence. For the past 30 days, items assess: 1) number of missed medication days; 2) how “good of a job” one did at taking medications as prescribed on 6-point Likert-scale from 0 (very poor) to 5 (excellent); and 3) frequency of taking medications as prescribed on a 6-point scale from 0 (never) to 5 (always). Per original scale validation, given that the three items are measured on different scales, each item was linearly transformed to be on a scale from 0 (worst adherence) to 100 (perfect adherence). A mean score was calculated from the 3 items. Adherence was then reversed scored (due to left skew) and a log10 transformation was done which allowed variable to meet assumptions for linear regression. Due to transformation, adherence interpretation changes from originally scaled variable – higher scores indicate worse ART adherence.

Trauma exposure.

The Brief Trauma Questionnaire (BTQ; Schnurr et al., 1999) assessed lifetime trauma exposure. The BTQ is a 10-item scale that asks about exposure (yes/no) to traumatic events that would meet Criterion A for PTSD (person was exposed to death, threatened death, actual or threatened serious injury, or actual or threatened sexual violence; i.e., trauma) according to the Diagnostic and Statistical Manual of Mental Disorders (DSM–V)(American Psychiatric Association, 2013). A dichotomous dummy variable was created representing whether or not they endorsed any of these Criterion A traumas.

PTSD.

The 4-item Primary Care PTSD Screen was used to assess past month PTSD symptoms (PC-PTSD; Prins et al., 2003). According to the validated clinical cut-off, patients who met Criterion A from BTQ (i.e., trauma exposure) and endorsed at least 3 out of the 4 symptoms were considered screening in for PTSD symptoms.

Depression.

The 9-item Patient Health Questionnaire (Kroenke et al., 2001) was used to assess past 2 week symptoms of depression per the DSM-V criteria. Each item is on a 4-point frequency scale from 0 (not at all) to 3 (nearly every day). A total score is derived by summing items with higher scores representing more severe depression (range 0 to 27). Validated clinical cut-offs for interpretation include: 0 to 4 (minimal depression), 5 to 9 (mild depression), 10 to 14 (moderate depression), 15 to 19 (moderately severe depression), and 20+ (severe depression). A dichotomous dummy variable was created representing moderate depression or higher. This measure has been validated in both Spanish speaking and Haitian Creole speaking samples (Diez-Quevedo et al., 2001; Marc et al., 2014).

Substance use.

Substance use was assessed using a measure adapted from the Addiction Severity Index – Lite (McLellan et al., 1980). Frequency of use in the past 30 days was assessed for marijuana, crack, cocaine, heroin, other opioids, amphetamines, hallucinogens, ecstasy/MDMA, sedatives/tranquilizers, and other drugs. Although research has shown marijuana acts as an anti-inflammatory and could potentially be beneficial to physical health among people living with HIV (Manuzak et al., 2018), other research has shown that marijuana use negatively impacts ART adherence (Bonn-Miller et al., 2014; Montgomery et al., 2019). Thus, a dichotomous variable representing those reporting any drug use, including marijuana, in the past 30 days was created.

Demographics.

Age, race/ethnicity, sex assigned at birth, gender identity, sexual orientation, education level, housing status, and employment status were assessed. Individuals endorsing homelessness or temporary/transitional housing in the past 12 months were considered unstably housed.

Data Analysis

Statistical analyses were conducted using SAS Studio 9.4 (SAS Institute, 2014). Descriptive statistics were obtained for all variables included in the analyses and tests for normality indicated outcome of adherence did not meet assumptions. Adherence was reversed scored (due to left skew) and a log10 transformation was done which allowed variable to meet assumptions for linear regression. Due to transformation, adherence interpretation changes from originally scaled variable – higher scores indicate worse ART adherence. Initially, bivariate associations between all variables were examined (Pearson, point-biserial, and phi). Next, sequential linear regression was used to test the association between predictors and ART adherence. This allows for evaluating predictors of ART adherence above and beyond previously entered predictors. Variables were entered in four blocks. First, trauma was entered to examine any independent association with adherence. Second, PTSD was added to the model to examine the association with adherence while controlling for trauma. Third, mental health constructs that are supported as key influencers of ART adherence, depression and substance use, were entered to examine the role of PTSD on adherence while controlling for such important covariates. Fourth, indicators of socioeconomic status (unemployment, unstable housing, low education [less than high school]) were entered to examine the effects of PTSD and mental health constructs in the context of supported structural influencers of ART adherence. Additionally, in this fourth block, race/ethnicity was added to account for supported disparities. Given that separating out all minority identities would result in numerous categories with less than 1% frequency, a dummy variable for identifying as a person of color (referent = White, Non-Hispanic/Latinx) was entered. Collinearity diagnostics were examined for all models which indicated no issues. Alpha was set to .05.

Results

Patient characteristics are presented in Table 1. Overall, the sample was 50 years old (SD = 12), a person of color (95%, n = 1,173) with the majority being Black, non-Hispanic/Latinx (60%, n = 737), cisgender male (59%, n = 727), and heterosexual (74%, n = 920). Additionally, 43% (n = 526) screened in for at least mild depression, 19% (n = 228) for at least moderate depression, 77% reported trauma exposure (n = 943), 21% (n = 256) screening in for current PTSD, and 27% (n = 332) reported past 30-day substance use. The sample also reported high socioeconomic marginalization including unstable housing (n = 278, 23%), less than a high school education (n = 436, 35%), and unemployment (n = 830, 67%). In examining bivariate associations, almost all constructs were significantly associated with one another and with ART adherence (see Table 2).

Table 1.

Patient characteristics (N = 1,237)

M or n (SD or %)
Age 49.80 (11.91)
Race/ethnicity
 Black, non-Hispanic/Latinx 737 (59.68%)
 Black, Hispanic/Latinx 56 (4.53%)
 White, non-Hispanic/Latinx 62 (5.02%)
 White, Hispanic/Latinx 327 (26.48%)
 Asian, non-Hispanic/Latinx 4 (0.32%)
 Asian, Hispanic/Latinx 1 (0.08%)
 Native Hawaiian/Pacific Islander, non-Hispanic/Latinx 2 (0.16%)
 Native Hawaiian/Pacific Islander, Hispanic/Latinx 1 (0.08%)
 Indigenous, non-Hispanic/Latinx 1 (0.08%)
 Indigenous, Hispanic/Latinx 2 (0.16%)
 multi-racial, non-Hispanic/Latinx 4 (0.32%)
 multi-racial, Hispanic/Latinx 17 (1.38%)
 another race not listed, non-Hispanic/Latinx 3 (0.24%)
 another race not listed, Hispanic/Latinx 18 (1.46%)
 declined to answer 2 (0.16%)
Gender
 cisgender male 727 (58.82%)
 cisgender female 494 (39.97%)
 transgender male 2 (0.16%)
 transgender female 13 (1.05%)
 non-binary 1 (0.08%)
Sexual orientation
 straight/heterosexual 920 (74.37%)
 gay/lesbian/homosexual 202 (16.33%)
 bisexual 100 (8.08%)
 different identity 8 (0.65%)
 don’t know 5 (0.40%)
 declined to answer 2 (0.16%)
ART adherence1 88.69 (21.71)
Screened positive for PTSD 256 (20.76%)
Trauma 943 (76.54%)
Moderate depression or higher 228 (18.55%)
Substance use 332 (26.84%)
Unstable housing 278 (22.53%)
Less than a high school education 436 (35.25%)
Unemployed 830 (67.26%)
Being a person of color 1173 (94.98%)
Open in a new tab

Notes.

1

Scale from 0 (worst) to 100 (perfect)

Table 2.

Bivariate correlations between all study variables

1 2 3 4 5 6 7 8
1 log10 ART adherence1 -
2 PTSD symptoms 0.09*** -
3 Trauma 0.08** 0.28**** -
4 Depression 0.17**** 0.33**** 0.15**** -
5 Substance use 0.24**** 0.13**** 0.12**** 0.18**** -
6 Unstable housing 0.19**** 0.25**** 0.16**** 0.20**** 0.23**** -
7 Less than a high school education 0.06* 0.03 0.02 0.08** 0.04 0.06* -
8 Unemployed −0.004 0.13**** 0.04 0.13**** 0.06* 0.12**** 0.15**** -
9 Being a person of color −0.01 −0.01 −0.04 −0.06 −0.12**** −0.12**** 0.12**** −0.03
Open in a new tab

Notes.

*

p < .05

**

p < .01

***

p < .001

****

p < .0001; for correlations between two binary variables, phi coefficient was used; for correlations between two continuous variables, Pearson’s r was used; for correlations between continuous and binary variable, point-biserial correlation was used

1

due to transformation, interpretation is reversed from raw scale – higher scores indicate worse adherence

In examining the first block of the sequential linear regression (see Table 3), trauma was significantly associated with worse ART adherence (β = 0.08, p = .007). However, when screening in for PTSD symptoms was entered in the second block, the association with trauma dropped in size by about 1/3 and became nonsignificant (p = .074). Notably, PTSD, while controlling for trauma, was significantly associated with worse ART adherence (β = 0.08, p = .005).

Table 3.

Sequential regression predicting log10 ART adherence1

Block 1 Block 2 Block 3 Block 4
F(1, 1230) = 7.27, p = .007 F(2, 1229) = 7.65, p = .001 F(4, 1222) = 24.78, p < .0001 F(8, 1213) = 15.37, p > .0001
R2 = .006 R2 = .012 R2 = .075 R2 = .095
b SE β p b SE β p b SE β p b SE β p
Intercept 0.45 0.04 0.00 < .0001 0.45 0.04 0.00 < .0001 0.37 0.04 0.00 < .0001 0.31 0.10 0.00 .0013
Trauma 0.12 0.05 0.08 .007 0.08 0.04 0.05 .074 0.04 0.05 0.03 .368 0.03 0.05 0.02 .461
PTSD symptoms 0.14 0.05 0.08 .005 0.04 0.05 0.03 .381 0.01 0.05 0.01 .831
Depression 0.20 0.05 0.11 .0001 0.19 0.05 0.11 .0002
Substance use 0.33 0.04 0.21 < .0001 0.30 0.04 0.20 < .0001
Unstable housing 0.20 0.05 0.12 < .0001
< High school education 0.06 0.04 0.04 .149
Unemployed −0.07 0.04 −0.05 .101
Being a person of color 0.07 0.09 0.02 .434
Open in a new tab

Notes.

1

due to transformation, interpretation is reversed from raw scale – higher scores indicate worse adherence

When depression and substance use, additional key factors potentially associated with adherence, were entered in the third block, PTSD was no longer significant (p = .381). However, depression (β = 0.11, p = .0001) and substance use (β = 0.21, p <.0001) were significantly associated with worse ART adherence. In the final fourth block adding indicators of socioeconomic status [low education, unemployment, unstable housing]) and race/ethnicity, trauma and PTSD remained nonsignificant. In this final model, unstable housing (β = 0.12, p < .0001), depression (β = 0.11, p = .0002), and substance use (β = 0.20, p < .0001) were significantly associated with worse adherence.

Post-hoc Sensitivity Analysis

Given that the trauma measure used assessed number of trauma domains experienced (vs. actual number of traumas experienced; e.g., an individual could experience the same type of trauma multiple times), the primary analysis collapsed trauma into the dichotomous variable representing screening positive for DSM-V diagnostic criteria for trauma exposure. However, some research indicates that individuals living with HIV not only experience higher prevalence of trauma, but also experience multiple traumas (Koehn et al., 2019; Reif et al., 2011). Although not able to speak to number of traumas, the current sample experienced an average of about two trauma domains (M = 1.9; SD = 1.7; range = 0 – 9). To explore if experiencing a certain number of trauma domains (vs. the dichotomous trauma or not) would be predictive of suboptimal ART adherence when controlling for PTSD, a post-hoc sensitivity analysis was done. The count variable representing number of trauma domains experienced was collapsed into five categorical dummy codes indicating having experienced one (n = 310, 25.2%), two (n = 258, 20.9%), three (n = 170, 13.8%), four (n = 98, 8.0%), and five or more (n = 107, 8.7%) types of trauma. Individuals experiencing five to nine trauma domains were collapsed into one category due to the lower frequency in the upper tail of number of trauma domains experienced (five n = 63, 5.1%; six n = 28, 2.3%; seven n = 7, 0.6%; eight n = 8, 0.7%; nine n = 1, 0.1%).

These five categorical dummy codes were entered (referent = those experiencing no trauma) into the same sequential models of the primary analysis (see Table 4). Unlike the first set of analyses, when trauma and PTSD were entered into the same model (see Step 2 in Table 4) results showed that even when controlling for screening positive for PTSD, experiencing five or more trauma exposures was significantly associated with worse ART adherence compared to those experiencing no trauma (β = 0.10, p = .003). Additionally, within this model, and parallel to the primary analysis, having screened positive for PTSD was a significant predictor of worse ART adherence (β = 0.07, p = .030), but in this case, along with five or more trauma exposures as a significant predictor. Also paralleling the primary analysis, when depression and substance use were entered in the third block, PTSD and trauma exposure were not significant but depression (β = 0.11, p = .0002) and substance use (β = 0.21, p <.0001) were significantly associated with worse ART adherence. In the final fourth block adding indicators of socioeconomic status, results also paralleled the primary analysis such that trauma and PTSD remained nonsignificant and unstable housing (β = 0.12, p < .0001), depression (β = 0.10, p = .0004), and substance use (β = 0.20, p < .0001) were significantly associated with worse adherence.

Table 4.

Post-hoc analysis - sequential regression predicting log10 ART adherence1

Block 1 Block 2 Block 3 Block 4
F(5, 1226) = 3.61 , p = .003 F(6, 1225) = 3.80, p = .001 F(8, 1218) = 13.11, p < .0001 F(12, 1209) = 11.13, p < .0001
R2 = .01 R2 = .02 R2 = .08 R2 = .10
b SE β p b SE β p b SE β p b SE β p
Intercept 0.45 0.04 0.00 <.00010 0.45 0.04 0.00 <.0001 0.38 0.04 0.00 <.0001 0.30 0.10 0.00 .001
Trauma (REF = 0)
1 0.09 0.05 0.06 .111 0.07 0.06 0.05 .178 0.03 0.05 0.02 .577 0.03 0.05 0.02 .634
2 0.13 0.06 0.08 .027 0.10 0.06 0.06 .074 0.08 0.06 0.05 .146 0.08 0.06 0.05 .161
3 0.06 0.06 0.03 .353 0.02 0.07 0.01 .768 −0.03 0.07 −0.01 .693 −0.04 0.07 −0.02 .529
4 0.12 0.08 0.05 .136 0.07 0.08 0.03 .413 0.01 0.08 0.003 .916 −0.01 0.08 −0.004 .884
5+ 0.31 0.08 0.13 <.0001 0.24 0.08 0.10 .003 0.14 0.08 0.06 .081 0.13 0.08 0.05 .110
PTSD symptoms 0.11 0.05 0.07 .030 0.04 0.05 0.02 .500 0.01 0.05 0.004 .895
Depression 0.19 0.05 0.11 .0002 0.18 0.05 0.10 .0004
Substance use 0.33 0.04 0.21 <.0001 0.30 0.04 0.20 <.0001
Unstable housing 0.20 0.05 0.12 <.0001
< High school education 0.06 0.04 0.04 .109
Unemployed −0.07 0.04 −0.05 .081
Being a person of color 0.07 0.09 0.02 .407
Open in a new tab

Notes.

1

due to transformation, interpretation is reversed from raw scale – higher scores indicate worse adherence; REF = reference group; trauma represents number of trauma domains experienced

Discussion

The findings from the current study contributes to the literature by examining the impact of both trauma exposure and PTSD on ART adherence to parse out the effects of each while also examining the role of previously established key factors in adherence. Additionally, the study examined this within the context of a racially and ethnically diverse sample of individuals most at risk for falling off the care cascade amid an uncontrolled HIV epidemic. In other words, this sample from the public HIV clinic in Miami is representative of Black and Hispanic/Latinx individuals and those economically marginalized – groups, often intersecting, that have significant disparities in HIV health outcomes due to structural and social discrimination. The sample aligned with past studies in that there was high prevalence of trauma (77%) and screening positive for PTSD (21%). Although individuals living with HIV/AIDS have increased exposure to trauma, findings suggest that, of these two psychosocial problems, developing PTSD may be the construct driving implications for self-care (adherence) versus exposure to trauma itself. However, the post-hoc analysis revealed that for those experiencing multiple trauma domains, specifically five or more, trauma exposure was associated with worse ART adherence over and above PTSD. In other words, for those experiencing high levels of multiple traumas, self-care (e.g. adherence) is impacted regardless of development of PTSD symptoms. This finding is especially important given that Black and Hispanic/Latinx individuals have high rates of experiencing multiple types of traumas (Graham et al., 2017) and higher rates of HIV (Centers for Disease Control and Prevention, 2020a). Findings indicate a need to regularly screen for trauma exposure within HIV care serving Black and Hispanic/Latinx and other marginalized individuals.

The finding that PTSD is important to consider in HIV care over and above trauma exposure at certain levels has several important clinical implications. Clinics caring for individuals living with HIV/AIDS should not only assess for trauma, but also PTSD to preemptively address potential medication adherence issues. Additionally, improving upon interventions to facilitate resilience and coping post-trauma within HIV care may mitigate disease progression through better medication adherence. Indeed, scholars and clinicians have advocated for a trauma-informed model of HIV care (Brezing et al., 2015; Brief et al., 2004). However, the majority of interventions tested in the literature focus on trauma-informed primary HIV prevention with limited studies examining such interventions for those already infected and their unique care needs (Cuca et al., 2019; Sales et al., 2016; Seedat, 2012; Verhey et al., 2016). Although, recently, initial steps were completed for adapting an evidence-based trauma treatment, Cognitive Processing Therapy, for individuals living with HIV (López et al., 2019) and Prolonged Exposure, another evidenced-based trauma treatment, has shown initial results for decreasing PTSD symptoms among individuals living with HIV (Junglen et al., 2017).

The relationship between PTSD and HIV outcomes is more complex for individuals with multiple and intersecting marginalized identities, like being a Black and/or Hispanic/Latinx individual living with HIV. For example, discrimination has been found to mediate the relationship between PTSD and poor ART adherence among Black men living with HIV (Wagner et al., 2012). Mechanisms of ART adherence, like discrimination, need to be considered when addressing PTSD among Black and Hispanic/Latinx individuals and other marginalized individuals living with HIV. For example, a promising cognitive-behavioral intervention for Black women living with HIV who have trauma histories showed increased medication adherence. The intervention targeted not only trauma and HIV care, but also resilient coping for HIV- and race-based discrimination (Dale & Safren, 2018). Although important steps in the field, much more work is needed for development and testing of trauma-informed HIV care, especially among subgroups of individuals living with HIV that experience significant prevalence of trauma and social and structural inequities (e.g., Black women [Dale & Safren, 2018], transgender women [Empson et al., 2017]).

The findings that trauma and PTSD symptoms were associated with suboptimal ART adherence, however, are contextualized by the further findings that additional key factors previously associated with ART adherence made PTSD symptoms no longer significant both in the primary analysis and the post-hoc analysis. Specifically, substance use, depression, and unstable housing were associated with worse adherence. Interpreting this finding becomes complex given that these constructs have bivariate and bidirectional associations with PTSD symptoms. For example, substance use is often a subsequent behavior after experiencing symptoms of PTSD (Chilcoat & Breslau, 1998; Leeies et al., 2010; María-Ríos & Morrow, 2020). Additionally, PTSD has overlapping symptoms with depression (Afzali et al., 2017) and/or may lead to subsequent comorbid depression (Stander et al., 2014). Further, PTSD symptoms have been shown to precede unstable housing (Martijn & Sharpe, 2006) likely due to functional impairment (e.g., unable to retain employment; Rodriguez et al., 2012), yet, being unstably housed is traumatic in itself (Deck & Platt, 2015; Taylor & Sharpe, 2008) which could lead to the onset or exacerbation of PTSD symptoms. Overall, the causal pathways to suboptimal ART adherence involving these constructs are complex and need clarification via longitudinal research. Regardless of temporality, development of trauma-informed models of HIV care are needed and should consider the role of depression, substance use, and unstable housing.

Although the relationships between PTSD, depression, substance use, unstable housing, and ART adherence are complex in general, the complexity is exacerbated for those with intersectional marginalized identities, like people of color living with HIV. According to recent frameworks addressing HIV health disparities (Logie et al., 2019; Turan et al., 2017), experiencing structural stigma (i.e., macro level attitudes, laws, policies, services, etc. that facilitate disadvantage for minorities) and intersectional stigma (e.g., based on HIV-status, race, class, gender, sexual orientation, and other marginalized identities) lead to mental health and substance use issues which in turn lead to suboptimal ART adherence. Indeed, the current sample, which is made up of economically marginalized Black and Hispanic/Latinx individuals living with HIV, had comorbidity between PTSD symptoms and substance use (38% of those screening in for PTSD also endorsed past 30-day substance use; significant phi coefficient = 0.13), PTSD symptoms and depression (44% of those screening positive of PTSD met criteria at least moderate depression; significant phi coefficient = 0.33), and PTSD symptoms and unstable housing (43% of those screening positive for PTSD endorsed unstable housing; significant phi coefficient = 0.25). These comorbidities are indicative of the interconnecting nature of these factors among communities with HIV health disparities. Trauma-informed HIV care should not only consider this synergy, but also needs to address the intersectional stigma and discrimination faced by those most at risk for falling off the HIV treatment care cascade.

Although this study is among the first to examine how the experience of trauma vs. PTSD impact ART adherence, especially in the context of key factors that influence adherence among marginalized individuals in an HIV epidemic, there are several limitations to consider. Measures were self-report, including medication adherence, which can be inflated based on social desirability bias or inaccurate reporting. Also, PTSD was not measured by a clinical diagnostic tool, but rather self-report, which introduces error in detection of those screening in for PTSD. The measure used to assess for trauma assesses trauma domains experienced (i.e., types of trauma) and does not take into account individuals experiencing the same trauma multiple times; thus, estimates of the prevalence of trauma may be underestimated, especially in individuals living with HIV who have been shown to experience a chronic cycle of trauma. Future research is needed to explore a potential dose-response relationship with ART adherence. The majority of measures are not validated in Spanish and Haitian Creole samples; thus, measure validity and reliability may be affected when not delivered in English. In order to adequately measure and address HIV disparities, psychometric work needs to be done. Further, this is a cross-sectional study, which limits the conclusions of temporality. Generalizability is limited given that participants were patients receiving care and may not reflect those not connected to HIV care. Limitations in the field should also be noted when considering the limited extant evidence for trauma-informed HIV care. There may be such programs that are being done in the community, but since they have not been tested for efficacy or effectiveness, they have not been integrated into the literature nor considered evidence-based practice limiting dissemination. For example, Tavakkoli and colleagues (2014) developed a curriculum for HIV clinicians to be able to integrate assessment of trauma, diagnose PTSD, and formulate treatment approaches to bolster medication adherence and HIV disease outcomes among patients with PTSD; however, this curriculum has not been evaluated. Researchers should consider rigorously evaluating current community programs to add them to the body of evidence.

Conclusions

Although a history of trauma has previously been shown to predict lower HIV medication adherence (Brezing et al., 2015; Mugavero et al., 2006; Mugavero et al., 2007; Mugavero et al., 2009; Pence, 2009), findings indicate that the development of PTSD might be a critical factor that determines suboptimal adherence. While individuals who experienced trauma may be at higher risk for suboptimal medication adherence, the prevention or treatment of subsequent PTSD might be most important in order to improve HIV health outcomes. However, for those experiencing high levels of multiple traumas, self-care (such as ART adherence) is impacted regardless of development of PTSD symptoms. It is also important to implement a trauma-informed model of care that considers depression, substance use, and unstable housing. Of note, bivariate associations indicated that almost every construct of mental health, substance use, and socioeconomic status were associated with each other and with ART adherence indicating the significant complexity in optimizing HIV care.

It is important to consider these findings and implications in the context of the sample, which is representative of Black and Hispanic/Latinx individuals and those economically marginalized – groups, often intersecting, that have significant disparities in HIV health outcomes due to structural and social discrimination. Additionally, this research takes place in a geographic area with an uncontrolled HIV epidemic, likely influenced by its unique social and structural context such as having high immigration, high wealth disparities, and low resources compared to the rest of the country. Taken together, the onus for improving ART adherence should first be placed on macro-level interventions (e.g., changing of laws, policies, public services) to address these structural and social issues, like discrimination and accessibility of resources, that influence HIV self-care. However, given the complexity and length of time macro-level interventions take to implement, individual-level interventions are needed to immediately support and empower individuals to achieve optimal HIV self-care. Research is needed to identify resiliency mechanisms in order to begin to extend evidence-based cognitive-behavioral and stress-coping interventions that can promote such resiliency factors. Efforts to holistically address the multilevel factors impacting individuals living with HIV across systemic, organizational, community, and intrapersonal levels are needed in order to cater to communities with HIV epidemics and disparities and keep them from falling off the HIV care continuum.

Acknowledgments

Funding: The project described was supported by the University of Miami Developmental HIV/AIDS Mental Health Research Center (D-ARC) funded by P30MH116867 (Safren), the Miami Center for AIDS Research (CFAR) at the University of Miami Miller School of Medicine funded by P30AI073961 (Rodriguez [Behavioral, Social Sciences and Community Outreach Core]; Pahwa overall director), the Department of Psychology at the University of Miami, and from K24DA040489 (Safren). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or any of the other funders.

Footnotes

Declarations

Conflict of interest: The authors declare that they have no conflict of interest.

Ethics approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee (University of Miami Institutional Review Board) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Consent to participate: Informed consent was obtained from all individual participants included in the study.

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

References Cited

  1. Afzali MH, Sunderland M, Teesson M, Carragher N, Mills K, & Slade T. (2017). A network approach to the comorbidity between posttraumatic stress disorder and major depressive disorder: The role of overlapping symptoms. Journal of Affective Disorders, 208, 490–496. 10.1016/j.jad.2016.10.037 [DOI] [PubMed] [Google Scholar]
  2. American Immigration Council. (2020). Immigrants in Florida. Accessed on 09/21/2020 at https://www.americanimmigrationcouncil.org/research/immigrants-florida.
  3. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5). American Psychiatric Association. [Google Scholar]
  4. Anderson JC, Campbell JC, Glass NE, Decker MR, Perrin N, & Farley J. (2018). Impact of intimate partner violence on clinic attendance, viral suppression and CD4 cell count of women living with HIV in an urban clinic setting. AIDS Care, 30(4), 399–408. 10.1080/09540121.2018.1428725 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, & Bassett MT (2017). Structural racism and health inequities in the USA: Evidence and interventions. The Lancet, 389(10077), 1453–1463. 10.1016/S0140-6736(17)30569-X [DOI] [PubMed] [Google Scholar]
  6. Bonn-Miller MO, Oser ML, Bucossi MM, & Trafton JA (2014). Cannabis use and HIV antiretroviral therapy adherence and HIV-related symptoms. Journal of Behavioral Medicine, 37(1), 1–10. 10.1007/s10865-012-9458-5 [DOI] [PubMed] [Google Scholar]
  7. Brezing C, Ferrara M, & Freudenreich O. (2015). The syndemic illness of HIV and trauma: Implications for a trauma-informed model of care. Psychosomatics, 56(2), 107–118. 10.1016/j.psym.2014.10.006 [DOI] [PubMed] [Google Scholar]
  8. Brief DJ, Bollinger AR, Vielhauer MJ, Berger-Greenstein JA, Morgan EE, Brady SM, Buondonno LM, Keane TM, & For the HIV/AIDS Treatment Adherence Health Outcomes Cost Study Group. (2004). Understanding the interface of HIV, trauma, post-traumatic stress disorder, and substance use and its implications for health outcomes. AIDS Care, 16(Sup1), 97–120. 10.1080/09540120412301315259 [DOI] [PubMed] [Google Scholar]
  9. Centers for Disease Control and Prevention. (2020a). Estimated HIV incidence and prevalence in the United States 2014–2018. HIV Surveillance Supplemental Report 2020;25(No. 1), Accessed on 09/21/2020 at http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html. [Google Scholar]
  10. Centers for Disease Control and Prevention. (2020b). HIV surveillance report, 2018 (updated); vol. 31. Accessed on 09/21/2020 at http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html. [Google Scholar]
  11. Centers for Disease Control and Prevention. (2020c). Monitoring selected HIV prevention and care objectives using surveillance data, United States and 6 dependent areas, 2018. HIV Surveillance Supplemental Report 2020;25(No. 1), Accessed on 09/21/2020 at http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html. [Google Scholar]
  12. Chilcoat HD, & Breslau N. (1998). Investigations of causal pathways between ptsd and drug use disorders. Addictive Behaviors, 23(6), 827–840. 10.1016/S0306-4603(98)00069-0 [DOI] [PubMed] [Google Scholar]
  13. Cuca YP, Shumway M, Machtinger EL, Davis K, Khanna N, Cocohoba J, & Dawson-Rose C. (2019). The association of trauma with the physical, behavioral, and social health of women living with HIV: Pathways to guide trauma-informed health care interventions. Women’s Health Issues, 29(5), 376–384. 10.1016/j.whi.2019.06.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. D’Andrea W, Sharma R, Zelechoski AD, & Spinazzola J. (2011). Physical health problems after single trauma exposure: When stress takes root in the body. Journal of the American Psychiatric Nurses Association, 17(6), 378–392. 10.1177/1078390311425187 [DOI] [PubMed] [Google Scholar]
  15. Dale SK, & Safren SA (2018). Striving towards empowerment and medication adherence (STEP-AD): A tailored cognitive behavioral treatment approach for Black women living with HIV. Cognitive and Behavioral Practice, 25(3), 361–376. 10.1016/j.cbpra.2017.10.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Deck SM, & Platt PA (2015). Homelessness is traumatic: Abuse, victimization, and trauma histories of homeless men. Journal of Aggression, Maltreatment & Trauma, 24(9), 1022–1043. 10.1080/10926771.2015.1074134 [DOI] [Google Scholar]
  17. Delahanty DL, Bogart LM, & Figler JL (2004). Posttraumatic stress disorder symptoms, salivary cortisol, medication adherence, and CD4 levels in HIV-positive individuals. AIDS Care, 16(2), 247–260. 10.1080/09540120410001641084 [DOI] [PubMed] [Google Scholar]
  18. Diez-Quevedo C, Rangil T, Sanchez-Planell L, Kroenke K, & Spitzer RL (2001). Validation and utility of the patient health questionnaire in diagnosing mental disorders in 1003 general hospital spanish inpatients. Psychosom Med, 63(4), 679–686. 10.1097/00006842-200107000-00021 [DOI] [PubMed] [Google Scholar]
  19. Ebrahimzadeh Z, Goodarzi MA, & Joulaei H. (2019). Predicting the antiretroviral medication adherence and CD4 measure in patients with HIV/AIDS based on the post traumatic stress disorder and depression. Iranian Journal of Public Health, 48(1), 139–146. [PMC free article] [PubMed] [Google Scholar]
  20. Empson S, Cuca YP, Cocohoba J, Dawson-Rose C, Davis K, & Machtinger EL (2017). Seeking safety group therapy for co-occurring substance use disorder and PTSD among transgender women living with HIV: A pilot study. Journal of Psychoactive Drugs, 49(4), 344–351. 10.1080/02791072.2017.1320733 [DOI] [PubMed] [Google Scholar]
  21. Florida Department of Health Bureau of Communicable Diseases. (2019a). Blacks living with diagnosed HIV infection in Miami-Dade County, 2018. Accessed on 09/21/2020 at http://miamidade.floridahealth.gov/programs-and-services/infectious-disease-services/hiv-aids-services/hiv-fact-sheet.html.
  22. Florida Department of Health Bureau of Communicable Diseases. (2019b). Hispanics living with diagnosed HIV infection in Miami-Dade County, 2018. Accessed on 09/21/2020 at http://miamidade.floridahealth.gov/programs-and-services/infectious-disease-services/hiv-aids-services/_documents/2019/_documents/2018-FS-Hispanics-English.pdf.
  23. Glynn TR, Llabre MM, Lee JS, Bedoya CA, Pinkston MM, O’Cleirigh C, & Safren SA (2019). Pathways to health: An examination of HIV-related stigma, life stressors, depression, and substance use. International Journal of Behavioral Medicine, 26(3), 286–296. 10.1007/s12529-019-09786-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Glynn TR, Safren SA, Carrico AW, Mendez NA, Duthely LM, Dale SK, Jones DL, Feaster DJ, & Rodriguez AE (2019). High levels of syndemics and their association with adherence, viral non-suppression, and biobehavioral transmission risk in miami, a U.S. City with an HIV/AIDS epidemic. AIDS and Behavior, 23(11), 2956–2965. 10.1007/s10461-019-02619-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Goldstein RB, Smith SM, Chou SP, Saha TD, Jung J, Zhang H, Pickering RP, Ruan WJ, Huang B, & Grant BF (2016). The epidemiology of DSM-5 posttraumatic stress disorder in the United States: Results from the National Epidemiologic Survey on Alcohol and Related Conditions-III. Social Psychiatry and Psychiatric Epidemiology, 51(8), 1137–1148. 10.1007/s00127-016-1208-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Golin CE, Liu H, Hays RD, Miller LG, Beck CK, Ickovics J, Kaplan AH, & Wenger NS (2002). A prospective study of predictors of adherence to combination antiretroviral medication. Journal of General Internal Medicine, 17(10), 756–765. 10.1046/j.1525-1497.2002.11214.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Gonzalez A, Barinas J, & O’Cleirigh C. (2011). Substance use: Impact on adherence and HIV medical treatment. Current HIV/AIDS Reports, 8(4), 223. 10.1007/s11904-011-0093-5 [DOI] [PubMed] [Google Scholar]
  28. Gonzalez JS, Batchelder AW, Psaros C, & Safren SA (2011). Depression and HIV/AIDS treatment nonadherence: A review and meta-analysis. Journal of Acquired Immune Deficiency Syndromes, 58(2), 181–187. 10.1097/QAI.0b013e31822d490a [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Graham PW, Yaros A, Lowe A, & McDaniel MS (2017). Nurturing environments for boys and men of color with trauma exposure. Clinical Child and Family Psychology Review, 20(2), 105–116. 10.1007/s10567-017-0241-6 [DOI] [PubMed] [Google Scholar]
  30. Hutton HE, Cardin N, Ereme K, Chander G, Xu X, & McCaul ME (2020). Psychiatric disorders and substance use among African American women in HIV care. AIDS and Behavior. 10.1007/s10461-020-02858-6 [DOI] [PubMed] [Google Scholar]
  31. Junglen AG, Smith BC, Coleman JA, Pacella ML, Boarts JM, Jones T, Feeny NC, Ciesla JA, & Delahanty DL (2017). A multi-level modeling approach examining PTSD symptom reduction during prolonged exposure therapy: Moderating effects of number of trauma types experienced, having an HIV-related index trauma, and years since HIV diagnosis among HIV-positive adults. AIDS Care, 29(11), 1391–1398. 10.1080/09540121.2017.1300625 [DOI] [PubMed] [Google Scholar]
  32. Kennedy BR (2009). Psychosocial model: Racism as a predictor of adherence and compliance to treatment and health outcomes among African Americans. Journal of Theory Construction & Testing, 13(1), 20. [Google Scholar]
  33. Kilpatrick DG, Resnick HS, Milanak ME, Miller MW, Keyes KM, & Friedman MJ (2013). National estimates of exposure to traumatic events and PTSD prevalence using DSM-IV and DSM-5 criteria. Journal of Traumatic Stress, 26(5), 537–547. 10.1002/jts.21848 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Koehn K, Collins AB, Burgess H, Von Bischoffshausen O, Marziali M, Salters KA, Hogg RS, & Parashar S. (2019). Understanding the pervasiveness of trauma within a housing facility for people living with HIV. Housing Studies, 1–15. 10.1080/02673037.2019.1648773 [DOI] [Google Scholar]
  35. Kroenke K, Spitzer RL, & Williams JB (2001). The phq-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. 10.1046/j.1525-1497.2001.016009606.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Langebeek N, Gisolf EH, Reiss P, Vervoort SC, Hafsteinsdóttir TB, Richter C, Sprangers MAG, & Nieuwkerk PT (2014). Predictors and correlates of adherence to combination antiretroviral therapy (ART) for chronic HIV infection: A meta-analysis. BMC Medicine, 12(1), 142. 10.1186/s12916-014-0142-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Leeies M, Pagura J, Sareen J, & Bolton JM (2010). The use of alcohol and drugs to selfmedicate symptoms of posttraumatic stress disorder. Depression and Anxiety, 27(8), 731–736. 10.1002/da.20677 [DOI] [PubMed] [Google Scholar]
  38. LeGrand S, Reif S, Sullivan K, Murray K, Barlow ML, & Whetten K. (2015). A review of recent literature on trauma among individuals living with HIV. Current HIV/AIDS Reports, 12(4), 397–405. 10.1007/s11904-015-0288-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Leserman J. (2008). Role of depression, stress, and trauma in HIV disease progression. Psychosomatic Medicine, 70(5), 539–545. 10.1097/PSY.0b013e3181777a5f [DOI] [PubMed] [Google Scholar]
  40. Leserman J, Whetten K, Lowe K, Stangl D, Swartz MS, & Thielman NM (2005). How trauma, recent stressful events, and PTSD affect functional health status and health utilization in HIV-infected patients in the south. Psychosomatic Medicine, 67(3), 500–507. 10.1097/01.psy.0000160459.78182.d9 [DOI] [PubMed] [Google Scholar]
  41. Logie CH, Williams CC, Wang Y, Marcus N, Kazemi M, Cioppa L, Kaida A, Webster K, Beaver K, de Pokomandy A, & Loutfy M. (2019). Adapting stigma mechanism frameworks to explore complex pathways between intersectional stigma and HIV-related health outcomes among women living with HIV in Canada. Soc Sci Med, 232, 129–138. 10.1016/j.socscimed.2019.04.044 [DOI] [PubMed] [Google Scholar]
  42. López CM, Hahn CK, Gilmore AK, & Danielson CK (2019). Tailoring cognitive behavioral therapy for trauma-exposed persons living with HIV. Cognitive and Behavioral Practice. 10.1016/j.cbpra.2019.02.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Lundgren JD, Babiker AG, Gordin F, Emery S, Grund B, Sharma S, Avihingsanon A, Cooper DA, Fatkenheuer G, Llibre JM, Molina JM, Munderi P, Schechter M, Wood R, Klingman KL, Collins S, Lane HC, Phillips AN, & Neaton JD (2015). Initiation of antiretroviral therapy in early asymptomatic HIV infection. New England Journal of Medicine, 373(9), 795–807. 10.1056/NEJMoa1506816 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Machtinger EL, Wilson TC, Haberer JE, & Weiss DS (2012). Psychological trauma and PTSD in HIV-positive women: A meta-analysis. AIDS and Behavior, 16(8), 2091–2100. 10.1007/s10461-011-0127-4 [DOI] [PubMed] [Google Scholar]
  45. Manuzak JA, Gott TM, Kirkwood JS, Coronado E, Hensley-McBain T, Miller C, Cheu RK, Collier AC, Funderburg NT, Martin JN, Wu MC, Isoherranen N, Hunt PW, & Klatt NR (2018). Heavy cannabis use associated with reduction in activated and inflammatory immune cell frequencies in antiretroviral therapy-treated human immunodeficiency virus-infected individuals. Clinical Infectious Diseases, 66(12), 1872–1882. 10.1093/cid/cix1116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Marc LG, Henderson WR, Desrosiers A, Testa MA, Jean SE, & Akom EE (2014). Reliability and validity of the haitian creole phq-9. Journal of General Internal Medicine, 29(12), 1679–1686. 10.1007/s11606-014-2951-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. María-Ríos CE, & Morrow JD (2020). Mechanisms of shared vulnerability to post-traumatic stress disorder and substance use disorders. Frontiers in Behavioral Neuroscience, 14, 6. 10.3389/fnbeh.2020.00006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Martijn C, & Sharpe L. (2006). Pathways to youth homelessness. Social Science & Medicine, 62(1), 1–12. 10.1016/j.socscimed.2005.05.007 [DOI] [PubMed] [Google Scholar]
  49. McLaughlin KA, Alvarez K, Fillbrunn M, Green JG, Jackson JS, Kessler RC, Sadikova E, Sampson NA, Vilsaint CL, Williams DR, & Alegría M. (2019). Racial/ethnic variation in trauma-related psychopathology in the United States: A population-based study. Psychological Medicine, 49(13), 2215–2226. 10.1017/S0033291718003082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. McLellan AT, Luborsky L, Woody GE, & O’Brien CP (1980). An improved diagnostic evaluation instrument for substance abuse patients: The Addiction Severity Index. The Journal of Nervous and Mental Disease, 168(1), 26–33. 10.1097/00005053-198001000-00006 [DOI] [PubMed] [Google Scholar]
  51. Miami Matters. (2020a). 2020 Demographics. Accessed on 09/21/2020 at http://www.miamidadematters.org/demographicdata.
  52. Miami Matters. (2020b). Socioneeds index. Accessed on 09/21/2020 at http://www.miamidadematters.org/index.php?module=Indicators&controller=index&action=socioneeds.
  53. Miami Urban Future Initiative. (2019). Toward a more inclusive region: Inequality and poverty in greater miami. Accessed 09/21/2020 at http://www.creativeclass.com/_wp/wp-content/uploads/2019/2004/FIU_Toward_a_More_Inclusive_Region.pdf.
  54. Miami-Dade County Elections Department. (2020). Voter registration statistics. Accessed on 09/21/2020 at https://www.miamidade.gov/global/elections/voter-registration-statistics.page.
  55. Milloy MJ, Marshall BDL, Montaner J, & Wood E. (2012). Housing status and the health of people living with HIV/AIDS. Current HIV/AIDS Reports, 9(4), 364–374. 10.1007/s11904-012-0137-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Montgomery L, Bagot K, Brown JL, & Haeny AM (2019). The association between marijuana use and HIV continuum of care outcomes: A systematic review. Current HIV/AIDS Reports, 16(1), 17–28. 10.1007/s11904-019-00422-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Mugavero M, Ostermann J, Whetten K, Leserman J, Swartz M, Stangl D, & Thielman N. (2006). Barriers to antiretroviral adherence: The importance of depression, abuse, and other traumatic events. AIDS Patient Care and STDs, 20(6), 418–428. 10.1089/apc.2006.20.418 [DOI] [PubMed] [Google Scholar]
  58. Mugavero MJ, Pence BW, Whetten K, Leserman J, Swartz M, Stangl D, & Thielman NM (2007). Predictors of AIDS-related morbidity and mortality in a southern U.S. Cohort. AIDS Patient Care and STDs, 21(9), 681–690. 10.1089/apc.2006.0167 [DOI] [PubMed] [Google Scholar]
  59. Mugavero MJ, Raper JL, Reif S, Whetten K, Leserman J, Thielman NM, & Pence BW (2009). Overload: Impact of incident stressful events on antiretroviral medication adherence and virologic failure in a longitudinal, multisite human immunodeficiency virus cohort study. Psychosomatic Medicine, 71(9), 920–926. 10.1097/PSY.0b013e3181bfe8d2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Nachega JB, Uthman OA, Peltzer K, Richardson LA, Mills EJ, Amekudzi K, & Ouedraogo A. (2015). Association between antiretroviral therapy adherence and employment status: Systematic review and meta-analysis. Bulletin of the World Health Organization, 93(1), 29–41. 10.2471/blt.14.138149 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Neigh GN, Rhodes ST, Valdez A, & Jovanovic T. (2016). PTSD co-morbid with HIV: Separate but equal, or two parts of a whole? Neurobiology of Disease, 92, 116–123. 10.1016/j.nbd.2015.11.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Pellowski JA, Kalichman SC, Matthews KA, & Adler N. (2013). A pandemic of the poor: Social disadvantage and the U.S. HIV epidemic. The American psychologist, 68(4), 197–209. 10.1037/a0032694 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Peltzer K, & Pengpid S. (2013). Socioeconomic factors in adherence to HIV therapy in low- and middle-income countries. Journal of Health, Population, and Nutrition, 31(2), 150–170. 10.3329/jhpn.v31i2.16379 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Pence BW (2009). The impact of mental health and traumatic life experiences on antiretroviral treatment outcomes for people living with HIV/AIDS. Journal of Antimicrobial Chemotherapy, 63(4), 636–640. 10.1093/jac/dkp006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Prins A, Ouimette P, Kimerling R, Cameron RP, Hugelshofer DS, Shaw-Hegwer J, Thrailkill A, Gusman FD, & Sheikh JI (2003). The primary care PTSD screen (PC-PTSD): Development and operating characteristics. Primary Care Psychiatry, 9(1), 9–14. 10.1185/135525703125002360 [DOI] [Google Scholar]
  66. Reif S, Mugavero M, Raper J, Thielman N, Leserman J, Whetten K, & Pence BW (2011). Highly stressed: Stressful and traumatic experiences among individuals with HIV/AIDS in the deep south. AIDS Care, 23(2), 152–162. 10.1080/09540121.2010.498872 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Reilly KH, Clark RA, Schmidt N, Benight CC, & Kissinger P. (2009). The effect of post-traumatic stress disorder on HIV disease progression following hurricane Katrina. AIDS Care, 21(10), 1298–1305. 10.1080/09540120902732027 [DOI] [PubMed] [Google Scholar]
  68. Roberts AL, Gilman SE, Breslau J, Breslau N, & Koenen KC (2011). Race/ethnic differences in exposure to traumatic events, development of post-traumatic stress disorder, and treatment-seeking for post-traumatic stress disorder in the United States. Psychological medicine, 41(1), 71–83. 10.1017/S0033291710000401 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Rodriguez P, Holowka DW, & Marx BP (2012). Assessment of posttraumatic stress disorder-related functional impairment: A review. Journal of Rehabilitation Research & Development, 49(5), 649–665. 10.1682/jrrd.2011.09.0162 [DOI] [PubMed] [Google Scholar]
  70. Sales JM, Swartzendruber A, & Phillips AL (2016). Trauma-informed HIV prevention and treatment. Current HIV/AIDS Reports, 13(6), 374–382. 10.1007/s11904-016-0337-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. SAS Institute. (2014). Sas 9.4 output delivery system: User’s guide. SAS Institute. [Google Scholar]
  72. Schnurr P, Vielhauer M, Weathers F, & Findler M. (1999). The brief trauma questionnaire. National Center for PTSD. [Google Scholar]
  73. Schnurr PP, & Green BL (2004). Understanding relationships among trauma, posttraumatic stress disorder, and health outcomes. In Schnurr PP & Green BL (Eds.), Trauma and health: Physical health consequences of exposure to extreme stress (Vol. 20, pp. 247–275). American Psychological Association. 10.1037/10723-010 [DOI] [Google Scholar]
  74. Seedat S. (2012). Interventions to improve psychological functioning and health outcomes of HIV-infected individuals with a history of trauma or PTSD. Current HIV/AIDS Reports, 9(4), 344–350. 10.1007/s11904-012-0139-3 [DOI] [PubMed] [Google Scholar]
  75. Sibrava NJ, Bjornsson AS, Pérez Benítez ACI, Moitra E, Weisberg RB, & Keller MB (2019). Posttraumatic stress disorder in African American and latinx adults: Clinical course and the role of racial and ethnic discrimination [doi: 10.1037/amp0000339]. American Psychological Association. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Sledjeski EM, Delahanty DL, & Bogart LM (2005). Incidence and impact of posttraumatic stress disorder and comorbid depression on adherence to haart and CD4+ counts in people living with HIV. AIDS Patient Care STDS, 19(11), 728–736. 10.1089/apc.2005.19.728 [DOI] [PubMed] [Google Scholar]
  77. Smith AB, & Cook PF (2019). Comorbid mental health disorders in persons living with HIV: Adherence to antiretroviral therapy. Archives of Psychiatric Nursing, 33(4), 364–370. 10.1016/j.apnu.2019.04.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Spitzer C, Barnow S, Volzke H, John U, Freyberger HJ, & Grabe HJ (2009). Trauma, posttraumatic stress disorder, and physical illness: Findings from the general population. Psychosomatic Medicine, 71(9), 1012–1017. 10.1097/PSY.0b013e3181bc76b5 [DOI] [PubMed] [Google Scholar]
  79. Stander VA, Thomsen CJ, & Highfill-McRoy RM (2014). Etiology of depression comorbidity in combat-related PTSD: A review of the literature. Clinical Psychology Review, 34(2), 87–98. 10.1016/j.cpr.2013.12.002 [DOI] [PubMed] [Google Scholar]
  80. Taggart Wasson L, Shaffer JA, Edmondson D, Bring R, Brondolo E, Falzon L, Konrad B, & Kronish IM (2018). Posttraumatic stress disorder and nonadherence to medications prescribed for chronic medical conditions: A meta-analysis. Journal of Psychiatric Research, 102, 102–109. 10.1016/j.jpsychires.2018.02.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Tang C, Goldsamt L, Meng J, Xiao X, Zhang L, Williams AB, & Wang H. (2020). Global estimate of the prevalence of post-traumatic stress disorder among adults living with HIV: A systematic review and meta-analysis. BMJ Open, 10(4), e032435. 10.1136/bmjopen-2019-032435 [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Tavakkoli M, Cohen MA, Alfonso CA, Batista SM, Tiamson-Kassab MLA, & Meyer P. (2014). Caring for persons with early childhood trauma, PTSD, and HIV: A curriculum for clinicians. Academic Psychiatry, 38(6), 696–700. 10.1007/s40596-014-0186-8 [DOI] [PubMed] [Google Scholar]
  83. Taylor KM, & Sharpe L. (2008). Trauma and post-traumatic stress disorder among homeless adults in Sydney. Australian & New Zealand Journal of Psychiatry, 42(3), 206–213. 10.1080/00048670701827218 [DOI] [PubMed] [Google Scholar]
  84. Teeraananchai S, Kerr SJ, Amin J, Ruxrungtham K, & Law MG (2017). Life expectancy of HIV-positive people after starting combination antiretroviral therapy: A meta-analysis. HIV Medicine, 18(4), 256–266. 10.1111/hiv.12421 [DOI] [PubMed] [Google Scholar]
  85. Turan B, Hatcher AM, Weiser SD, Johnson MO, Rice WS, & Turan JM (2017). Framing mechanisms linking HIV-related stigma, adherence to treatment, and health outcomes. American Journal of Public Health, 107(6), 863–869. 10.2105/AJPH.2017.303744 [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Verhey R, Chibanda D, Brakarsh J, & Seedat S. (2016). Psychological interventions for post-traumatic stress disorder in people living with HIV in resource poor settings: A systematic review. Tropical Medicine & International Health, 21(10), 1198–1208. 10.1111/tmi.12756 [DOI] [PubMed] [Google Scholar]
  87. Vranceanu AM, Safren SA, Lu M, Coady WM, Skolnik PR, Rogers WH, & Wilson IB (2008). The relationship of post-traumatic stress disorder and depression to antiretroviral medication adherence in persons with HIV. AIDS Patient Care and STDs, 22(4), 313–321. 10.1089/apc.2007.0069 [DOI] [PubMed] [Google Scholar]
  88. Wagner GJ, Bogart LM, Galvan FH, Banks D, & Klein DJ (2012). Discrimination as a key mediator of the relationship between posttraumatic stress and HIV treatment adherence among African American men. Journal of Behavioral Medicine, 35(1), 8–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Wawrzyniak AJ, Rodriguez AE, Falcon AE, Chakrabarti A, Parra A, Park J, Mercogliano K, Villamizar K, Kolber MA, Feaster DJ, & Metsch LR (2015). Association of individual and systemic barriers to optimal medical care in people living with HIV/AIDS in Miami-Dade County. Journal of Acquired Immune Deficiency Syndromes, 69 Suppl 1, S63–72. 10.1097/qai.0000000000000572 [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. Whittle HJ, Leddy AM, Shieh J, Tien PC, Ofotokun I, Adimora AA, Turan JM, Frongillo EA, Turan B, & Weiser SD (2020). Precarity and health: Theorizing the intersection of multiple material-need insecurities, stigma, and illness among women in the United States. Social Science & Medicine, 245, 112683. 10.1016/j.socscimed.2019.112683 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Wilson IB, Lee Y, Michaud J, Fowler FJ Jr., & Rogers WH (2016). Validation of a new three-item self-report measure for medication adherence. AIDS and Behavior, 20(11), 2700–2708. 10.1007/s10461-016-1406-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Zhang Y, Wilson TE, Adedimeji A, Merenstein D, Milam J, Cohen J, Cohen M, & Golub ET (2018). The impact of substance use on adherence to antiretroviral therapy among HIV-infected women in the United States. AIDS and Behavior, 22(3), 896–908. 10.1007/s10461-017-1808-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES