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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Womens Health Issues. 2020 Dec 6;31(2):148–156. doi: 10.1016/j.whi.2020.11.002

Resilience among cisgender and transgender women in street-based sex work in Baltimore, Maryland

Saba Rouhani 1,2, Michele R Decker 3, Catherine Tomko 1, Bradley Silberzahn 4, Sean T Allen 1, Ju Nyeong Park 1, Katherine Footer 1, Susan G Sherman 1
PMCID: PMC8005437  NIHMSID: NIHMS1645806  PMID: 33298401

Abstract

Background.

Resilience represents adaptability and empowerment and can buffer against the consequences of traumatic events. Cisgender and transgender women in street-based sex work are at high risk for trauma, yet data on their resilience is sparse. A clearer understanding of resilience and its correlates is useful for informing sex worker-centered interventions.

Methods.

Using the Connor-Davidson 10-item Resilience Scale (range 0–40), we describe resilience among 165 cisgender and 42 transgender street-based women sex workers in Baltimore, Maryland. Longitudinal cohort data were used to examine correlates of resilience in each population. Analyses are conducted using multiple linear regression.

Results.

Mean resilience score was 24.2 (95% CI 23.6, 24.8) among cisgender women sex workers and 32.2 among transgender women sex workers (95% CI 30.8, 32.7). Among cisgender participants, positive correlates of resilience were being Black, Hispanic, or other race (ß=2.7, p=0.004), having housing (ß=1.9, p=0.034), social cohesion score (ß=0.18, p=0.047), and daily drug injection (ß=3.7, p<0.001); negative correlates of resilience were sexual violence (ß=−4.8, p=0.006) and exposure to egregious police acts (ß=−0.6, p=0.015). Among transgender participants, higher education level (ß=8.8, p<0.001), food security (ß=3.5, p=0.005), and housing stability (ß=2.0, p<0.001) were associated with increased resilience, and daily non-injection drug use (excluding marijuana; ß=−3.3, p<0.001) and physical violence (ß=−2.9, p<0.001) were associated with reduced resilience.

Conclusions.

This is the first study to characterize factors that may influence resilience among cisgender and transgender women sex workers. Results highlight tangible intervention targets for promoting mental health and safety among a uniquely vulnerable population of women.

Introduction.

In countries where sex work remains criminalized, street-based women sex workers are uniquely vulnerable to interacting risks, including sexually transmitted infections (STI), substance use, and high rates of interpersonal violence (Deering et al., 2014; Mizock & Lewis, 2008; Shannon et al., 2009). They face broad structural barriers that can further impact health outcomes, such as criminalization and exclusion from the licit economy, and lack of access to mental health resources, medical care, and housing (Footer et al., 2016; Lazarus et al., 2011; Lazarus et al., 2012; Park et al., 2019; Puri et al., 2017). These risks are further magnified among particular sub-groups of sex workers like transgender women, who face elevated rates of violence and homicide, HIV risk, and institutional discrimination and exclusion, relative to their cisgender counterparts (Baral et al., 2013; Bradford et al., 2013; Glick et al., 2018). Rather than exerting independent effects, these health and structural risk factors reinforce one another and produce a uniquely elevated, “syndemic” risk environment (Buttram et al., 2014; Rhodes et al., 1999). At the same time, sex workers comprise diverse populations who persevere in the face of multiple layers of marginalization, violence, and trauma; nonetheless, the majority of research among them remains pathology-based (Burnes et al., 2018), with limited focus on understanding what tools they regularly employ to cope or thrive.

A growing literature studies how individuals and populations respond to adversity and which factors can promote healthy development and empowerment in response to stressors. The term “resilience” is used in research and clinical practice to refer to this trajectory of adaptability, or ability to “bounce back.” Resilience can help explain differential outcomes between individuals with similar exposures, with greater resilience sometimes translating to adoption of protective behaviors (Yuen, 2015) and buffering against long-term mental health consequences of traumatic events. Characterizing resilience among sex workers may therefore be informative for developing better tools to promote risk reduction among them.

Resilience has been characterized in populations ranging from survivors of acute conflicts or disasters (Bonanno et al., 2007; Norris et al., 2009) or childhood trauma (Anderson et al., 2012; Domhardt et al., 2014) to those coping with chronic disease diagnoses (Dale et al., 2014; Seiler & Jenewein, 2019). Given their structural risk environment and the ongoing, recurrent, and multifaceted exposure to trauma they often experience, resilience and the factors that can bolster it are likely to look very different among sex workers. Little is known about how co-occurring exposure to violence, law enforcement, STIs, substance use, housing instability, and other markers of poverty and social exclusion may influence their resilience, particularly among transgender subpopulations; indeed, existing research has highlighted the need to focus on individual, community, and structural elements that influence this construct specifically among sex workers with limited environmental and economic resources at their disposal (Buttram et al., 2014; Herrick et al., 2014; Seccombe, 2002). More broadly, the lack of consensus in the field as to whether resilience is an inherent trait, or a state that can be shaped, has perhaps hindered efforts to identify tangible, material elements that may promote or threaten resilience (Norris et al., 2009; Seccombe, 2002). A clearer understanding of these relationships among hyper-marginalized women with excess burdens of trauma may help to tailor interventions aimed at promoting their resilience, safety, and survival.

The current study describes and compares resilience in a longitudinal cohort of cisgender and transgender women engaged in street-based sex work in Baltimore City. We examine associations between resilience and elements of the supportive or risk environments, such as access to housing, food security, drug use, interpersonal violence, and criminal justice interactions.

Methods.

The Sapphire Study.

For the purposes of this manuscript, the term “sex workers” specifically refers to women sex workers unless otherwise noted. This work is nested within a prospective longitudinal cohort of 250 cisgender and 63 transgender sex workers in Baltimore, Maryland. Recruitment occurred between April 2016 and January 2017. The cohort were assessed at 3-month intervals for one year. The current analysis uses data from baseline, 3-month, and 6-month time points to generate exposure histories and assess their relationship to resilience. Recruitment and data collection methods are discussed elsewhere (Allen et al., 2019); briefly, targeted sampling was used to recruit cisgender sex workers from 14 locations across Baltimore City. Similar methods were used to recruit transgender sex workers; however, they primarily came from a single area. Inclusion criteria were minimum age of 15 years; identifying as a woman; willingness to undergo HIV/STI testing; and selling or trading oral, vaginal, or anal sex for “money, food, drugs or favors” in public spaces at least three times in the past three months. A total of three transgender women and no cisgender women below the age of 18 were recruited into the study; all three of these minors were 16–17 years of age, which is over the age of consent in the state of Maryland. Participants provided informed consent to complete computer-assisted personal interview surveys and HIV/STI testing on the study van. Onsite counseling pertaining to HIV results and referrals to local health and social services were provided. Participants were compensated with a prepaid gift card for $70 USD.

Analytic framework.

Analyses were informed by the syndemic and risk environment frameworks, which theorize that multiple intersecting factors can interact and amplify one another to produce environments characterized by excess burden of disease as well as social and structural barriers to accessing prevention and treatment, thereby compounding negative outcomes (Buttram et al., 2014; Rhodes et al., 1999). We hypothesized possible risk factors to include HIV, drug use characteristics, law enforcement interactions, and interpersonal violence. Based on existing literature, we hypothesized possible resilience-promoting factors to be: educational attainment, housing, food, licit employment, and markers of social, family and community connectedness including relationship status, having living children, positive interactions with police (i.e., police assistance), and self-reported social cohesion (Burnes et al., 2018; Madewell & Ponce-Garcia, 2016).

Measures.

The outcome of interest, resilience, was measured once at the 6-month visit. We used the 10-item Connor-Davidson Resilience Scale (CD-RISC; 0–40 points), which has been validated in multiple settings and populations (Campbell-Sills & Stein, 2007; Connor & Davidson, 2003). Cronbach’s alpha (α) showed high internal consistency for the CD-RISC scale among both cisgender and transgender sex workers (0.88 and 0.84, respectively).

Sociodemographic data (age, race, relationship status) were collected at baseline. Housing, employment, drug use, and frequency of engaging in sex work were measured at baseline (fixed) and again at each follow-up measure (time-varying). Food security was defined as going to bed hungry less than once per week. Data were collapsed to generate lifetime and recent histories of exposures. To address the lack of precision in resilience estimates compared across racial categories with small sample sizes, we analyzed race as a binary variable comparing non-Hispanic White participants to all others (Black, Hispanic, mixed, and other races).

Exposure to violence was measured using an adapted version of the Revised Conflict Tactic Scale (Strauss et al., 1996), previously used with this population (Decker et al., 2014). Physical violence was defined as being hit, punched, slapped, or physically hurt/threatened with a weapon; sexual violence was defined as being forced or forcibly pressured to have vaginal or anal sex. Childhood and perpetrator-specific (client, intimate partner, or police) violence in adulthood were ascertained. Additional questions included age of entry into sex work to derive whether the participant sold or traded sex as a minor (<18 years old), and whether the participant had ever been coerced, forced, threatened, or misled to sell or trade sex.

A thirteen-item scale was adapted (Lippman et al., 2010) to measure social cohesion among sex workers by measuring agreement with a series of statements on a Likert scale (1=strongly agree, 2=agree, 3=disagree, 4=strongly disagree). Statements assessed whether participants felt they could “count on other sex workers” to do things such as lend money, accompany them to doctors or hospitals, warn them about bad dates, help deal with violent clients, or help with housing. The final social cohesion score was calculated as the sum of all responses and analyzed continuously. Cronbach’s α showed high internal consistency of the scale in both cisgender (0.89) and transgender cohorts (0.85).

Three police practice scales were employed to measure three distinct policing exposures: routine law enforcement, egregious police behaviors, and police assistance; a full description of scale validation and development is available elsewhere (Footer et al., 2020). Routine law enforcement behaviors included: asking women to move along; running a warrant check; performing routine stops; searching persons and property; confiscating drugs or paraphernalia, including condoms; and arrest. Egregious police behaviors were defined as: verbal or emotional harassment; sexual harassment or assault; damage of property; physical violence; acceptance or demand of sex, goods, or favors in exchange for no arrest; and paying for sex (police as clients). Police assistance referred to assistance through referrals to social or health services, or helping out (e.g., buying food or drink, giving a ride to safety or services) without expecting anything in return. Responses were categorized by frequency (2 = daily or weekly, 1 = less than weekly, 0 = never) and aggregated to a final score for each scale.

Participant retention and sample size.

Analyses were restricted to participants who completed the 6-month visit and reported all resilience items (n=165 cisgender sex workers, n=42 transgender sex workers). Baseline characteristics (e.g., sociodemographic, mental health, and all putative resilience-promoting and risk factors) of women who were retained versus lost to follow up by this time were compared for both groups. Among cisgender women, those retained at 6 months had been in sex work longer and were more likely to be in a relationship and have stable housing (p<0.05). Among transgender women, a greater proportion with licit employment and fewer women with daily drug use were retained at 6 months (p<0.05).

Statistical analyses.

Mean resilience was compared across strata of interest using bivariate regression with clustered variances to adjust for clustering by geographic recruitment zone. Multivariable models were constructed using variables with bivariate associations at p<0.1 and with a sample size of at least 10 cisgender or 5 transgender women per category. If both lifetime and recent violence were significant, we included the more proximal exposure; however, where this led to small cell sizes, lifetime history was used. When modeling police interactions, the routine policing scale was excluded due to high correlation with the egregious policing scale. We excluded one significant variable (“has living children”) from the multivariable analysis in the trans cohort, due to a small sample size of women with that attribute (n=3).

Due to differences in the demographics, patterns of exposure, and risk profiles between groups, analyses were conducted separately among cisgender and transgender participants. All analyses were conducted in Stata/SE 14.2 (StataCorp: College Station, Texas, USA).

RESULTS

Resilience among cohorts.

Figure 1 shows the distribution of combined resilience scores across both cisgender and transgender sex workers. The mean score was 24.2 (95% CI 23.6, 24.8) among cisgender and 32.2 (95% CI 30.8, 32.7) among transgender participants.

Figure 1.

Figure 1.

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Histogram displaying distribution of scores using a 10-item Conor-Davidson Resilience Scale (CD-RISC 10) among Cisgender (N = 165) and transgender (N = 42) Participants in Baltimore, Maryland. Distribution of resilience score (range 0–40 points) among cisgender and transgender women sex workers in Baltimore, Maryland.

Sociodemographic characteristics.

The mean age of participants at entry into the study was 37 and 30 years old among cisgender and transgender women, respectively, and the majority entered sex work at least 5 years prior to enrollment (cisgender sex workers: 59%; transgender sex workers: 65%). Among cisgender sex workers, 68% were non-Hispanic White, while the remainder were Black, Hispanic, and mixed or other race; conversely, all transgender participants were Black, Hispanic, mixed or other race. Among cisgender sex workers, significantly higher resilience was observed among participants who were Black, Hispanic, and other races (25.9 vs 23.5; p=0.036). Table 1 shows mean resilience by baseline sociodemographic characteristics and structural risk factors.

Table 1:

Mean resilience among women sex workers by sociodemographic characteristics and hypothesized resilience-promoting factors

Cisgender Sex Workers (n=165) Transgender Sex Workers (n=42)
n (col%) Mean Resilience (95% CI) P-value n (col%) Mean Resilience (95% CI) P-value
Sociodemographic characteristics
Age (years) at enrollment
 <35 70 (42.4) 23.8 (22.0,25.6) 30 (69.8) 32 (29.6,34.4)
 ≥35 95 (57.6) 24.6 (22.9,26.4) 0.694 13 (30.2) 31.4 (27.1,35.7) 0.817
Race
 NH White 112 (67.9) 23.5 (22.0,25.1) 0 (0)
 Black, Hispanic, other 53 (32.1) 25.9 (23.6,28.2) 0.036* 43 (100) 31.8 (29.7,33.9) NA
Years in sex work
 ≤5 years 68 (41.2) 24 (22.1,25.8) 15 (34.9) 32.7 (30.0,35.5)
 >5 years 97 (58.8) 24.5 (22.8,26.2) 0.596 28 (65.1) 31.3 (28.5,34.2) 0.443
Resilience-promoting factors
Relationship status at enrollment
 In a relationship or married 64 (38.8) 25.3 (23.5,27.1) 13 (30.2) 29.2 (24.7,33.7)
 Single 101 (61.2) 23.6 (21.9,25.4) 0.138 30 (69.8) 32.9 (30.7, 35.1) <0.001**
Has living children 145 (87.9) 24.3 (22.9, 25.7) 0.465 3 (7.0) 37.7 (34.7, 40.6) <0.001**
Education level at enrollment
 High school/GED or equivalent 77 (46.7) 24.3 (22.4,26.1) 33 (76.7) 33.6 (31.8,35.4)
 Less than grade 12 88 (53.3) 24.3 (22.6,26.1) 0.944 10 (23.3) 26 (20.7,31.3) <0.001**
Employed at enrollment
 No 150 (90.9) 24 (22.7,25.4) 31 (72.1) 31.3 (28.6,34.1)
 Yes 14 (8.5) 27.1 (23.3,31.0) 0.156 12 (27.9) 33.1 (30.8,35.4) 0.593
Food security at enrollment§
 No 86 (52.1) 23.9 (21.9,25.9) 7 (16.3) 26.7 (20.4,33.0)
 Yes 79 (47.9) 24.7 (23.1,26.2) 0.442 36 (83.7) 32.8 (30.8,34.8) <0.001**
Currently has housing
 No 66 (40) 23.1 (20.9,25.2) 8 (18.6) 29.5 (24.9,34.1)
 Yes 99 (60) 25.1 (23.6,26.7) 0.042* 35 (81.4) 32.3 (30.0,34.7) 0.039*
Mean ß (95%CI) p-value Mean ß (95%CI) P-value
Social cohesion 29.8 0.2 (0.0, 0.3) 0.072 31.5 0.2 (−0.2, 0.5) 0.306
Police assistance scale 0.9 −0.6 (0.7, 1.0) 0.613 1.2 −0.4 (0.9, 1.6) 0.362
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P-values derived from bivariate regression with continuous outcome (resilience) and adjusted for clustering by recruitment zone.

§

Food security defined as going to bed hungry fewer than once a week.

*

p<0.05

**

p<0.01

Hypothesized resilience-promoting factors.

Most cisgender sex workers were single (61%) and had living children (88%); 47% had educational achievement of high school or beyond, and 9% had licit employment at baseline. Approximately half reported experiencing food security (48%), and 60% had access to housing at 6 months. Transgender sex workers were also predominantly single (70%) and had higher rates of educational achievement (77% completing high school or beyond), licit employment (28%), housing (81%), and food security (84%). In both groups, having current housing was positively associated with resilience (p=0.042 cisgender sex workers, p=0.039 transgender sex workers). Among transgender sex workers, educational attainment (p<0.001), having children (p<0.001), and food security were also significantly associated with higher resilience (p<0.001). Being in a relationship was associated with reduced resilience among transgender participants (p<0.001).

Hypothesized resilience risk factors.

The prevalence of each characteristic is shown in Table 2. Over half of cisgender sex workers reported recent injection drug use, and 39% reported daily injection. In contrast, no transgender sex workers reported injection, though resilience was significantly lower among the 37% who reported daily non-injection drug use excluding marijuana (29.9 vs 33.0, p<0.001). Thirteen percent of cisgender and 5% of transgender sex workers reported recent overdose. HIV prevalence was high among transgender (47%), compared cisgender sex workers (7%). Interaction with the criminal justice system was common: 21% of cisgender and 14% of transgender sex workers reported recent arrest. Both routine and egregious police interactions were significantly associated with reduced resilience (ß = 1.0, p=0.007; ß = 1.0, p<0.001).

Table 2:

Mean resilience among women sex workers by hypothesized resilience risk factors

Cisgender Sex Workers (n=165) Transgender Sex Workers (n=42)
n (col%) Mean Resilience (95% CI) P-value n (col%) Mean Resilience (95% CI) P-value
Drug use experiences
Injection drug use, past 3 months
 None 75 (45.5) 23.4 (21.5,25.3) Ref 42 (97.7) 31.7 (29.5,33.9) NA
 Less than daily 26 (15.8) 23.7 (20.0,27.5) 0.796 0 (0)
 Daily injection 64 (38.8) 25.6 (23.7,27.5) 0.088 0 (0)
Daily non-injection drug use, past 3 months
 No 39 (23.6) 25 (22.3,27.7) 27 (62.8) 33 (30.3,35.6)
 Yes 126 (76.4) 24.1 (22.6,25.5) 0.484 16 (37.2) 29.9 (26.6,33.2) <0.001**
Overdose, past 3 months
 No 144 (87.3) 24.4 (23.1,25.7) 40 (93.0) 31.8 (29.6,34.0)
 Yes 21 (12.7) 23.4 (19.0,27.9) 0.333 2 (4.7) 32 (27.7,36.3) 0.92
HIV Status
 Negative at 6m follow-up 154 (93.3) 24.7 (23.4, 25.9) Ref 23 (53.5) 32.6 (30.6,34.7)
 Positive, previously diagnosed 8 (4.9) 15.4 (7.6,23.1) 0.063 18 (41.9) 31.7 (27.8,35.6) 0.698
 Positive, diagnosed at current visit 3 (1.8) 29.3 (20.9, 37.8) 0.271 2 (4.7) 23 (14.3,31.7) 0.062
Law enforcement experiences
Arrested, past 6 months
 No 130 (78.8) 24.5 (23.1,25.9) 37 (86.1) 31.9 (29.6,34.2)
 Yes 35 (21.2) 23.5 (20.4,26.5) 0.446 6 (13.9) 31.2 (26.0,36.4) 0.8
Mean ß (95%CI) P-value Mean ß (95%CI) P-value
Egregious policing score, past 6 months 1.7 −1 (1.3, 2.1) <0.001** 1.6 −0.2 (0.7, 2.5) 0.203
Routine policing score, past 6 months 2.5 −1 (2.2, 2.8) 0.007** 2.8 0.1 (2.2, 3.4) 0.873
Childhood violence indicators
Childhood physical or sexual violence 85 (51.5) 23.5 (21.9,25.1) 0.604 19 (44.2) 32.6 (29.7,35.6) 0.001**
 Physical violence 70 (42.4) 23.9 (22.2,25.6) 0.968 9 (20.9) 31.4 (28.3,34.4) 0.841
 Sexual violence 55 (33.3) 23.2 (21.2,25.1) 0.212 15 (34.9) 32.5 (28.8,36.2) 0.431
Minor at entry into sex work 31 (18.8) 23.5 (20.4,26.5) 0.457 24 (55.8) 31.5 (28.5,34.5) 0.173
Forced or coerced into sex work 11 (6.7) 20.1 (15.7,24.4) 0.074 3 (7.0) 27.7 (20.2,35.2) 0.197
Intimate partner violence
Sexual
 Never 122 (73.9) 25.2 (23.6,26.7) 26 (60.5) 32.4 (29.8,35.0) Ref
 Ever (>3 months ago) 35 (21.2) 22.1 (19.9,24.2) 0.012* 10 (23.3) 29 (24.2,33.8) 0.34
 Past 3 months 8 (4.8) 20.9 (17.3,24.4) <0.001** 7 (16.3) 33.4 (29.0,37.9) 0.179
Physical
 Never 83 (50.3) 24.6 (22.7,26.5) 27 (62.8) 32.1 (29.3,34.8) Ref
 Ever (>3 months ago) 67 (40.6) 23.8 (21.8,25.8) 0.615 9 (20.9) 33.1 (29.7,36.5) 0.686
 Past 3 months 15 (9.1) 24.7 (21.8,27.7) 0.953 7 (16.3) 29 (23.3,34.7) 0.001**
Client violence
Sexual
 Never 76 (46.1) 26 (24.2,27.8) 17 (39.5) 35.5 (33.7,37.4) Ref
 Ever (>3 months ago) 64 (38.8) 23.7 (21.8,25.6) 0.043* 15 (34.9) 28.9 (24.9,32.9) 0.015*
 Past 3 months 25 (15.2) 20.6 (17.1,24.2) <0.001** 11 (25.6) 29.7 (25.5,33.9) 0.288
Physical
 Never 80 (48.5) 25.6 (23.7,27.4) 19 (44.2) 34.3 (31.9,36.6) Ref
 Ever (>3 months ago) 62 (37.6) 24 (22.2,25.9) 0.148 12 (27.9) 29.4 (25.0,33.8) 0.074
 Past 3 months 23 (13.9) 20.7 (16.8,24.5) <0.001** 12 (27.9) 30.4 (26.2,34.7) 0.518
Police violence 32.6 (29.7,35.6)
Sexual 31.4 (28.3,34.4)
 Never 123 (74.5) 24.8 (23.4,26.2) 27 (62.8) 32.5 (28.8,36.2) Ref
 Ever (>3 months ago) 36 (21.8) 25.1 (22.7,27.6) 0.78 13 (30.2) 31.5 (28.5,34.5) 0.951
 Past 3 months 6 (3.6) 9.7 (3.3,16.0) <0.001** 3 (7.0) 27.7 (20.2,35.2) 0.537
Physical
 Never 114 (69.1) 24.1 (22.5,25.6) 30 (69.8) Ref
 Ever (>3 months ago) 45 (27.3) 25.6 (23.3,27.8) 0.208 12 (27.9) 32.4 (29.8,35.0) 0.122
 Past 3 months 6 (3.6) 19.3 (10.5,28.1) 0.302 1 (2.3) 29 (24.2,33.8) <0.001**
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P-values derived from bivariate regression with continuous outcome (resilience) and adjusted for clustering by recruitment zone.

*

p<0.05

**

p<0.01

Fifty-two percent of cisgender and 44% of transgender sex workers experienced childhood physical or sexual violence. The frequency of entry into sex work as a minor was nearly three times higher among transgender (56%) than cisgender (19%) sex workers. Coercion into sex work was rare but consistent across groups (7%). Lifetime prevalence of intimate partner violence (cisgender sex workers 56%, transgender sex workers 51%), client violence (cisgender sex workers 63%, transgender sex workers 72%), and police violence (cisgender sex workers : 44%, transgender sex workers 49%) were high in both cohorts; however, transgender women experienced higher rates of recent intimate partner violence (23% vs 12%), client violence (35% vs 18%), and police violence (9% vs 6%).

Among cisgender sex workers, lifetime and recent sexual intimate partner violence were associated with lower mean resilience, and a dose response was observed. Those reporting no sexual violence history had a mean resilience of 25.2 vs 22.1 among those with any history (p=0.012), and 20.9 among those with recent episodes of sexual violence (p<0.001). The same pattern was noted when sexual violence was perpetrated by clients, with lowest mean resilience among women with recent exposure (20.6; p<0.001), followed by lifetime exposure (23.7; p=0.043), relative to no history (mean resilience 24.6). Recent physical violence by clients was also associated with reduced resilience (20.7 vs 25.6; p<0.001), as was recent police sexual violence (9.7 vs 24.8; p<0.001), though the latter was rare.

Resilience among transgender sex workers was slightly elevated among those with any history of childhood violence (32.6 vs 31.5; p=0.001). Recent physical violence by an intimate partner or police officer was associated with reductions in resilience (29.0 vs 32.1; p=0.001; 28.0 vs 33.0; p<0.001). Lifetime history of client sexual violence (28.9 vs 35.5; p=0.015) or ever experiencing physical or sexual IPV (29.4 vs 33.9; p=0.015) were also significant correlates of lower resilience.

Multivariable models.

Variables included in adjusted linear models are shown in Table 3. After adjustment for other variables, positive correlates of resilience among cisgender sex workers were: being Black, Hispanic, or other race (ß=2.7, p=0.004), having housing (ß = 1.9, p=0.034), and scoring high on the social cohesion scale (ß=0.2, p=0.047). Significant correlates of lower resilience were: experiencing recent sexual violence (ß = −4.9, p=0.001) and having a high score for exposure to egregious policing (ß = −0.63, p=0.023). Conversely, engaging in injection drug use, though a hypothesized risk factor, was significantly associated with increased resilience (ß = 3.7, p<0.001) scores. Among transgender sex workers, significant positive correlates of resilience were: higher educational achievement (ß = 8.9, p<0.001), food security (ß = 3.5, p=0.005), and housing (ß = 2.0, p<0.001). Engaging in daily drug use (ß = −3.3, p<0.001) and experiencing physical violence (lifetime; ß = 2.9, p<0.001) were significant correlates of lower resilience.

Table 3:

Adjusted correlates of resilience among women sex workers in Baltimore, Maryland.

Cisgender Sex Workers (n=165) Transgender Sex Workers (n=42)
ß 95%CI P-value ß 95%CI P-value
Sociodemographic characteristics
Length of time in sex work (>5 years vs <=5 years) 1.70 −0.15, 3.79 0.072 −0.62 −1.77, 0.53 0.288
Race (Black, Hispanic, other v White) 2.7 0.88, 4.57 0.004**
Resilience promoting factors
Relationship status (not single vs single) 0.09 −2.14, 2.32 0.939
Educational achievement (high school or greater) 8.82 10.13, 7.52 <0.001**
Food security 3.53 6.01, 1.05 0.005**
Housing stability 1.86 3.58, 0.14 0.034* 2.02 3, 1.03 <0.001**
Social cohesion 0.18 0.003, 0.36 0.047*
Resilience risk factors
Daily injection 3.71 1.84, 5.58 <0.001**
Daily non-injection drug use, past 3 months −3.3 −3.74, −2.87 <0.001**
Physical or sexual abuse in childhood −1.13 −4.62, 2.36 0.526
Sexual violence in adulthood¥ −4.75 −8.15, −1.34 0.006** −0.97 −11.65, 9.7 0.858
Physical violence in adulthood¥ 1.84 −1.90, 5.58 0.335 −2.92 −3.94, −1.89 <0.001**
Forced or coerced into sex work −2.30 −5.89, 1.28 0.208
Egregious policing scale −0.63 −1.13, −0.12 0.015*
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Grey boxes represent variables that were not included in each respective adjusted model.

¥

Among cisgender sex workers, recent (past 3 months) sexual and physical violence were modeled as predictors of resilience; among transgender sex workers, this variable captures lifetime exposure in adulthood.

*

p<0.05

**

p<0.01

Discussion.

This study is the first to provide a comparative description of resilience among cisgender and transgender women who engage in sex work, using a well-validated scale and longitudinal data on multiple co-occurring and interacting risk and resilience factors. We observed consistent patterns in correlates of resilience, such as access to housing and the impacts of interpersonal violence. The study design also enabled us to provide a portrait of support, trauma, and resilience among cisgender and transgender sex workers separately, highlighting contrasting relationships with factors such as drug use and food security.

Estimates of resilience among other populations of high-risk women in the United States, including women living with or at high risk for HIV and/or with histories of abuse, report mean resilience of 29–39 points on the CD-RISC scale employed (Dale et al., 2014; Dale et al., 2015; Wingo et al., 2010). While our transgender population falls within that range, we report considerably lower resilience among cisgender sex workers (24 points). The few studies that have examined correlates of resilience among sex workers specifically have often been conducted in international settings or employed different methods and scales, making comparisons challenging. Our results build upon findings from a large quantitative study conducted from 2007–2010, which measured resilience using a different scale among African American cisgender sex workers in Miami (Buttram et al., 2014). This study captured many of the intersecting risk covariates explored in the present analysis and found educational attainment and social support to be significant predictors of greater resilience, while HIV was associated with lower resilience. Together with our study, these works comprise the most extensive description of resilience among sex workers in the United States, and both highlight potential targets for intervention design. Structural factors such as attaining a high school degree or retaining housing and food security are tangible targets that may bolster resilience. Integrating case management or social connectedness interventions into existing services such as drop-in centers, and addressing an unmet need for education among vulnerable cisgender sex workers (Buttram et al., 2014), may be tools for health promotion in this context.

We observed stronger associations between resilience and hypothesized resilience-promoting factors, including educational achievement and food security, in the transgender cohort. However, housing was significantly associated with increased resilience in both groups. This variable referred to recent homelessness, rather than lifetime exposure, which was even greater: 92% of cisgender and 57% transgender sex workers reported ever experiencing homelessness at baseline. This highlights the extent of housing insecurity, beyond this study period, that women face—a factor that our findings suggest may compromise their resilience. Another common theme was the high exposure to violence and its inverse relationship to resilience. Our data show greater impacts of recent violence, either “ever” in adulthood or more proximally, on resilience in this population. Other work has noted that while childhood abuse is an important risk factor for negative outcomes in adulthood, episodes occurring or recurring later in life can also have profound impacts and represent an actionable opportunity for interventions (Decker et al., 2016). In bivariate analyses, we observed some evidence of a dose response: cisgender sex workers reporting recent violence had lower resilience than those with lifetime exposure. While not always statistically significant among transgender participants, possibly due to the small sample, a similar pattern was also apparent. These findings support other observations here and elsewhere describing the impact of violence on resilience (Catabay et al., 2019; Tsirigotis & Luczak, 2018) and how this impact may differ by perpetrator (Namy et al., 2017), and we add value by beginning to tease out impacts of proximal versus distal events. In a population whose ongoing incidence of violence is so elevated, it is important to consider the potentially additive deleterious effects on resilience; how long does it take to recover or regain resiliency after a traumatic event, and what are the implications when episodes recur so frequently?

Elements of the risk environment differed between cisgender and transgender participants, which may have impacted overall resilience scores in each group. Cisgender sex workers were predominantly White, reported considerably lower levels of food and housing stability, and had a high prevalence of injection drug use. Daily injection drug use was associated with increased resilience, an unexpected finding that potentially reflects survival bias and indicates the level of perseverance needed to sustain such high-risk drug use. Black, Hispanic, and other race and social cohesion were also significantly associated with increased resilience among cisgender sex workers. Histograms illustrated a comparatively higher distribution of resilience scores among transgender sex workers; while the reason for this is not immediately clear from the analysis, it may relate to their greater access to housing, food, or licit employment, or feelings of social connectedness or solidarity that can be enhanced in more marginalized racial or sexual/gender identity groups (Liao et al., 2016; Lincoln, Chatters et al., 2003; Pflum et al., 2015). This group was comprised exclusively of Black participants with higher reported social cohesion. While sex workers face common challenges, these observations highlight the importance of conducting further research on unique needs of populations with different gender identities, sexual histories and patterns of structural risk and support.

Our study had several limitations. First, while we employed a well-validated scale with clinical criteria for interpreting scores and found that it demonstrated high internal consistency, we recognize that it is limited by reliance on individual and cognitive factors. Research in this population may benefit from measures that more thoroughly incorporate social and interpersonal factors (Madewell & Ponce-Garcia, 2016), particularly given that qualitative work in similar groups highlights the many components of social support and connectedness that influence resilience (Burnes et al., 2018). This study is also limited by loss to follow-up, a frequent challenge in street-based, high-risk populations, and our results may be biased by retention patterns. Finally, our sample size of transgender sex workers was small, and some of our tools may not have optimally captured experiences in this group. For example, our social cohesion scale, while adapted for sex workers, did not distinguish between cisgender and transgender participants—i.e., cisgender and transgender sex workers were asked the same questions in reference to “other sex workers,” rather than other sex workers sharing their gender identity and experience. We may not have captured within-group cohesion or connectedness that would be more likely to impact overall resilience among transgender sex workers, or the sample size was too small to detect such relationships.

Implications for policy and practice

This work helps identify actionable targets to promote resilience among cisgender and transgender sex workers alike. Intervening to avert ongoing and recent violence experienced by sex workers (Burnes et al., 2018) can make a difference in mitigating the long-term mental health effects of trauma, even in a population with high exposure to childhood violence. Promoting access to food and housing should also be prioritized as programmatic targets not only for direct health and safety but potentially to fortify women against negative consequences of other risk factors they face. These insights are of clear relevance to programs looking to identify immediate, tangible ways to promote resilience among women engaging in sex work.

Conclusions.

Despite the alarming rates of violence and negative health outcomes among women sex workers, data on resilience in these populations is scant. This is one of the first studies to examine these trends in this group, and is unique in its inclusion of transgender women who face additional layers of marginalization even within the sex work community (Mizock & Lewis, 2008). Results highlight tangible intervention targets like reducing exposure to sexual and physical violence and egregious policing, and scaling up access to food and housing, for promoting empowerment and survival among a uniquely vulnerable population of women.

Acknowledgements

We thank the SAPPHIRE research staff, community, and most of all the women participating in the study.

Funding Information.

Dr. Rouhani is an NIH Drug Dependency Epidemiology Fellow, supported by the National Institute for Drug Abuse/National Institute of Health (T32DA007292). Dr. Allen is supported by the NIH (K01DA046234). Dr. Sherman is supported by the Johns Hopkins University Center for AIDS Research (1P30AI094189). Funding sources were not involved in study design, analysis or interpretation.

Abbreviations

STI

Sexually transmitted infections

CD-RISC

Connor-Davidson Resilience Scale

Biographies

Author Biographies

Saba Rouhani, PhD, MSc, is an NIH Postdoctoral Fellow at the Johns Hopkins Bloomberg School of Public Health. Her research focuses on disease prevention and the social and structural determinants of health in marginalized populations.

Michele R. Decker, ScD, is an Associate Professor in the Department of Population, Family, and Reproductive Health and directs the Women’s Health & Rights Program at the Center for Public Health and Human Rights at the Johns Hopkins Bloomberg School of Public Health. Her research focuses on social determinants of women’s health and gender equity with an emphasis on gender-based violence.

Catherine Tomko, MHS, is a doctoral candidate in the Department of Health, Behavior and Society at the Johns Hopkins Bloomberg School of Public Health. Her research focuses on mental health of women who use drugs and/or sell sex.

Bradley Silberzahn, MA, is a second year graduate student in the Department of Sociology at University of Texas at Austin. His research focuses on the criminal justice system and its impact on vulnerable populations.

Sean T. Allen DrPH, MPH, is an Assistant Scientist in the Department of Health, Behavior, and Society at the Johns Hopkins Bloomberg School of Public Health. His mixed-methods research examines the structural drivers of public health among marginalized populations, including people who use drugs.

Ju Nyeong Park, PhD, MHS, is an Assistant Scientist in the Department of Health, Behavior, and Society at the Johns Hopkins Bloomberg School of Public Health. Her research focuses on substance use, trauma, and HIV among underserved populations.

Katherine H.A. Footer, MSc, is an Associate Scientist in the Department of Health, Behavior, and Society at the Johns Hopkins Bloomberg School of Public Health. Her research is focused on the intersection of human rights law and public health, and employing ethnography and qualitative research methods to understand the health and risk environments of sex workers.

Susan G. Sherman, PhD, MPH, is a Professor in the Department of Health, Behavior, and Society who focuses on improving the health of marginalized populations, particularly people who use drugs and/or sell sex. She is interested in the structural drivers of health and risk in both the conduct of observational and intervention research. She has over 17 years of experience in developing and evaluating HIV prevention, peer-outreach behavioral and microenterprise interventions in Baltimore, Pakistan, Thailand, and India.

Footnotes

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