ABSTRACT
Economic-dependent partnerships (EDP) are an understudied HIV risk correlate among young men who have sex with men (YMSM) in the U.S. We explored whether YMSM's psychological resilience buffered against the effect of socioeconomic disadvantage on EDPs, after accounting for other psychosocial risks. Data come from an observational study assessing YMSM’s HIV vulnerabilities. We developed indices for socioeconomic disadvantage, psychosocial profiles, and cumulative promotive factors. Multivariable logistic regressions tested the main associations of these indices on EDPs. Protective models tested whether psychosocial profiles exacerbated and cumulative promotive factors buffered the effects of socioeconomic disadvantage on EDPs. 31% and 23% of YMSM reported EDPs with main and casual partners, respectively. For both outcomes, we found support for adjusted compensatory models. Socioeconomic disadvantage was associated with increased odds of EDPs with main (AOR = 1.45, p < .001) and casual (AOR = 1.47, p < .001) partners. Psychosocial profiles were also associated with increased odds of EDPs with main (AOR = 1.53, p = .001) and casual (AOR = 1.67, p < .001) partners. Cumulative promotive factors was associated with decreased odds of EDPs with main (AOR = 0.66, p = .003) and casual (AOR = 0.72, p = .035) partners. Our findings elucidate the need for multilevel interventions that provide opportunities for socioeconomic advancement and improve psychosocial/psychological functioning for at-risk YMSM.
Introduction
Young men who have sex with men (YMSM; ages 13–29 years; CDC, Citation2017), particularly racial/ethnic minority YMSM, account for a large proportion of new HIV diagnoses in the United States. These disparities manifest most acutely within socioeconomically disadvantaged regions (e.g., areas characterized by high poverty, unemployment, and racial segregation) (Bauermeister, Eaton, & Stephenson, Citation2016; Pellowski, Kalichman, Matthews, & Adler, Citation2013). Given these circumstances, YMSM are at greater risk for creating or maintaining economic-dependent partnerships (EDP) – that is, partnerships based on economic means for survival.
EDPs warrant distinction from transactional sex and commercial sex work (i.e., the exchange of sexual activity for needs such as money, housing/shelter, and material goods; Baral et al., Citation2015; Bimbi, Citation2007; Bauermeister et al., Citation2016; Gangamma, Slesnick, Toviessi, & Serovich, Citation2008; Keuroghlian, Shtasel, & Bassuk, Citation2014; Marshall, Shannon, Kerr, Zhang, & Wood, Citation2010; Mustanski, Newcomb, & Clerkin, Citation2011). For one, though there is significant overlap, EDPs do not necessarily imply the occurrence of a sexual transaction. Prior work has demonstrated positive associations between YMSM’s socioeconomic stress and risk outcomes and correlates (e.g., substance use; Pellowski et al., Citation2013; Wong, Kipke, Weiss, & McDavitt, Citation2010), warranting a better understanding of EDPs as a risk correlate for HIV. Secondly, EDPs have a greater focus on a personal relationship whereas transactional sex or commercial sex work are more client/consumer-focused (Koken & Bimbi, Citation2014). In all of these contexts, individuals’ sexual agency may be compromised (e.g., ability to negotiate safe sex practices) in fear of losing a dire and desired outcome (e.g., acquiring food or shelter; Biello et al., Citation2017; Gorbach & Holmes, Citation2003; Oldenburg, Perez-Brumer, Reisner, & Mimiaga, Citation2015; Walls & Bell, Citation2011). Given the potential power differential that inhibit individuals’ sexual health-promoting behaviors, EDP may contribute to primary partner-based HIV transmission. However, there remains a poor understanding of factors that contextualize the development of these partnerships.
Intertwining risk and promotive factors in YMSM’s lives shape their HIV vulnerability. Using risk frameworks, researchers have noted associations between social disadvantage (e.g., low education, unemployment, homelessness, and poverty) and HIV-related correlates and outcomes (Díaz, Ayala, & Bein, Citation2004; Duncan et al., Citation2017; Greenwood et al., Citation2001; Hope & MacArthur, Citation1998). Given these complex dynamics, researchers have advocated for the use of integrated approaches to understand how these risks converge and contribute to HIV risk behaviors, above and beyond the effect of individual negative psychosocial conditions on their own (Halkitis et al., Citation2015; Herrick, Stall, Egan, Schrager, & Kipke, Citation2014; Herrick, Stall, Goldhammer, Egan, & Mayer, 2013; Mustanski, Garofalo, Herrick, & Donenberg, Citation2007; Reed & Miller, Citation2016; Stall et al., Citation2003; Storholm, Halkitis, Siconolfi, & Moeller, Citation2011; Van den Berg et al., Citation2017). Furthermore, prior evidence suggests that the association of negative psychosocial conditions (e.g., current psychological and psychosocial distress and substance use) is especially profound among those who are multiply marginalized (e.g., socioeconomically disadvantaged, racial minorities; Nehl, Klein, Sterk, & Elifson, Citation2016; Wolitski, Valdiserri, & Stall, Citation2008).
As an alternative to risk framework approaches, HIV researchers have called for the inclusion of resilience-based frameworks in prevention research (Herrick, Stall, Egan, et al., Citation2014), as it may inform innovative intervention efforts. Resilience theory provides a strengths-based approach to explore the processes by which individuals overcome the negative effects of risk exposure (Fergus & Zimmerman, Citation2005). Two common approaches to resilience analyses include compensatory resilience modelling (i.e., do health promotive factors directly reduce the likelihood of a negative outcome?), and risk-protective modelling (i.e., do health promotive factors buffer the effects of a risk exposure on a negative outcome?) (Fergus & Zimmerman, Citation2005). Beyond informing how to circumvent or buffer risk, resilience research can also highlight the positive and health promotive aspects in YMSM’s lives (Harper, Brodsky, & Bruce, Citation2012). Similar to the syndemics literature, researchers have begun to examine how cumulative promotive/resilience factors (e.g., psychological adjustment and community resources) enhance well-being and/or reduce the likelihood of negative health outcomes among heterosexual youth (Stoddard et al., Citation2013). Within the HIV literature, though some studies have begun to explore resilience in samples of sex workers (Burnes, Long, & Schept, Citation2012; Buttram, Surratt, & Kurtz, Citation2014), few studies have addressed psychological/psychosocial resilience in the contexts of EDP in YMSM.
The goal of our study was to examine whether cumulative risk and resilience factors were associated with maintaining or initiating EDPs in a sample of YMSM living in Metropolitan Detroit. Consistent with prior research, we hypothesized that cumulative social disadvantage and YMSM’s syndemic profiles would be associated with greater likelihood of reporting EDPs. Building on the resilience framework, we then examined the association between participants’ cumulative health promotive factors and reporting EDPs. Consistent with the compensatory resilience model, we hypothesized cumulative protective factors would decrease the odds of YMSM reporting EDPs. Finally, we sought to test whether there was a risk-protective model. Therefore, we tested whether YMSM’s cumulative promotive factors modified the effect of social disadvantage and/or current psychosocial syndemic profiles on EDP among YMSM. We hypothesized that cumulative protective factors would attenuate the association between reporting EDPs and social disadvantage and psychosocial syndemic profile.
Materials & methods
Data for this manuscript come from a cross-sectional, observational study focused on examining the multilevel factors that shape YMSM’s vulnerability to HIV, conducted by a community-academic partnership in the Detroit Metropolitan Area (DMA). We recruited participants online and in-person from May to October 2012 (Bauermeister et al., Citation2014; Meanley et al., Citation2015). Online advertisements were placed on Facebook and Black Gay Chat Live. In-person advertisements were posted in DMA gay bars, clubs, and community events. Participation eligibility included being between the ages of 18–29 years, identifying as cis-male or transgender, residing in the DMA (verified by zip code and IP address), and reporting prior sexual intercourse with a man. Consenting, eligible participants completed a 45–60 min questionnaire ascertaining risk behaviors, self-reported HIV status, psychosocial factors, community/neighborhood characteristics, and sociodemographic characteristics. We used established guidelines to screen out duplicate and falsified entries by assessing participants’ online presence, email, IP addresses, operating system/browser information, irregular response patterns, and survey completion time (Bauermeister et al., Citation2012). We recruited 397 cis-male identified YMSM. Upon study completion, participants were emailed a $30 VISA e-gift card. The University of Michigan Institutional Review Board approved all procedures for this study.
Measures
Economic-dependent partnerships
For EDP with a main partner, participants indicated if they ever stayed with a main partner because they were worried about finances, a place to live, expenses such as groceries, utilities, and other bills, or in need of providing support for a dependent (4 items; 0 = No, 1 = Yes). For EDP with a new partner, participants indicated if they ever started a new sexual relationship because they hoped the new partner would help with finances, a place to live, expenses such as groceries, utilities, and other bills, or in need of providing support for a dependent (4 items; 0 = No, 1 = Yes). Each set of items were summed and recoded to indicate any economic-based partnership with a MAIN partner and any economic-based partnership with a NEW partner (0 = No, 1 = Yes).
Socioeconomic disadvantage
We dichotomized participants’ responses to education (0 = More than HS/GED, 1 = HS or less), employment status (0 = Full or part-time employment, 1 = Unemployed), income (0 = Above federal poverty line, 1 = Below federal poverty line), homelessness (0 = No nights homeless/transient; 1 = 1 + night homeless/transient), and health insurance status (0 = Any health insurance, 1 = No health insurance). These items were summed with higher scores reflecting greater disadvantage [range 0–5].
Current psychosocial syndemic profile
We selected validated measures for depressive symptoms, anxiety, internalized homophobia, and stimulant use (Derogatis & Melisaratos, Citation1983; Herek, Cogan, Gillis, & Gunt, Citation1998; Zhang et al., Citation2012). We selected these variables based on a fundamental definition of psychosocial conditions – any mental state, psychological trait, or aspect of the social environment that may influence a physical health outcome through a psychological mechanism (Macleod & Smith, Citation2003). Additionally, these factors have been observed to have independent associations with HIV risk in prior analyses with samples of sexual minority men (DeLonga et al., Citation2011; Frost, Parsons, & Nanín, Citation2007; Lelutiu-Weinberger et al., Citation2013; Newcomb & Mustanski, Citation2011; Safren, Reisner, Herrick, Mimiaga, & Stall, Citation2010).
To create psychosocial profiles, we employed methods similar to prior work by standardizing the composite scores for depression, anxiety, and internalized homophobia (Stoddard et al., Citation2013). These scores were then recoded to reflect high (>1 standard deviation (SD) above the mean), moderate (−1 to 1 SD from the mean), and low levels (>1 SD below the mean) of the risk factor. For stimulant use, we recoded the sum of any indication of using crack/cocaine, ecstasy/MDMA, methamphetamine/other amphetamines, or amyl nitrates (“poppers”) in the past 30 days (0 = No stimulant use, 1 = Any stimulant use). Finally, we summed and standardized these four variables with high scores reflecting higher cumulative psychosocial risk.
Cumulative promotive factors
We included validated scales assessing self-esteem, life purpose (meeting one’s own needs for purpose and self-worth), friend support, family support, and positive outlook (Connor & Davidson, Citation2003; Procidano & Heller, Citation1983; Rosenberg, Citation1965; Steger, Frazier, Oishi, & Kaler, Citation2006; Vinokur & Van Ryn, Citation1993). Self-esteem and social support were selected given prior work that demonstrated their protective association with sexual risk outcomes (Glick & Golden, Citation2014; Rosario, Schrimshaw, & Hunter, Citation2006). We included life purpose and positive outlook based on prior literature in positive psychology on the ways common adversity-related triggers (e.g., HIV infection) potentiate positive adaptation (e.g., reorienting life philosophies and self-evaluations; Linley & Joseph, Citation2011).
Similar to the psychosocial profile, we standardized the composite scores of each protective factor scale to reflect high (>1 SD above the mean), moderate (−1 to 1 SD from the mean), and low levels (>1 SD below the mean) of the promotive factor. We standardized the summation of these five factors with high scores reflecting high cumulative promotive factors.
Sociodemographic characteristics
Participants self-reported their age, race/ethnicity (Non-Hispanic White, Non-Hispanic Black, Hispanic/Latino All-Races, and Other/Multiple Races), sexual identity (gay/homosexual, bisexual, and Other MSM identity), and HIV status (negative, positive, and unaware).
Data analytic strategies
We used listwise deletion to remove participants with missing data given no statistically significant sociodemographic differences between participants with missing and non-missing responses. Our final analytic sample was N = 374 YMSM. We tested bivariate associations of our EDP outcomes by independent variables using unadjusted logistic regressions. These tests informed model building for our compensatory and risk-protective resilience models. Multivariable compensatory models (logistic regressions) assessed independent associations of cumulative socioeconomic disadvantage, psychosocial profile, and cumulative promotive factors on the odds of reporting any EDP with main and new partners. Lastly, we examined whether participants’ psychosocial profiles and cumulative promotive factors moderated the effect of socioeconomic disadvantage on EDP (risk-protective models).
Results
Participant characteristics
The mean age of the sample was 23.11 years (sd = 2.84; ). We had a racially/ethnically diverse sample consisting of 49% Non-Hispanic Black, 28% Non-Hispanic White, 8% Hispanic/Latino all races, and 16% who reported Other/Mixed Race. Participants predominantly identified as gay/homosexual (84%) with smaller numbers of bisexual (8%) or Other MSM (8%) identities. Ten percent of our sample self-reported being HIV-positive and HIV status-unaware, respectively. Regarding socioeconomic disadvantage, 32% reported an education level at or below a high school level, 30% were currently unemployed, 48% reported a yearly income below the federal poverty line, 16% indicated 1+ nights transient/homeless in the past 30 days, and 42% had no current health insurance.
Table 1. Sample characteristics by economic-dependent partnership type, N = 374.
Economic-dependent partnership with a main partner
Among our sample, 31% reported ever being in an EDP with a main partner. Unadjusted models () indicated increased odds of being in an EDP with increases in cumulative socioeconomic disadvantage (OR = 1.49, 95% CI: 1.28–1.74) and psychosocial syndemic profiles (OR = 1.74, 95% CI: 1.38–2.19) as well as decreased odds with increases in cumulative promotive factors (OR = 0.56, 95% CI: 0.44–0.72). Unadjusted models indicated no associations by age, race/ethnicity, sexual identity, or HIV status. In our multivariable compensatory model, increases in socioeconomic disadvantage (AOR = 1.46, 95% CI: 1.24–1.72) and psychosocial syndemic profile (AOR = 1.53, 95% CI: 1.18–1.98) remained associated with increased odds and cumulative promotive factors (AOR = 0.66, 95% CI: 0.50–0.86) remained associated with decreased odds of being in an EDP with a main partner. Our risk-protective model yielded no statistically significant interactions between socioeconomic disadvantage and syndemic profile or cumulative promotive factors, respectively.
Table 2. Logistic regression models on economic-dependent partnerships with a main partner among young sexual minority men, N = 374.
Economic-dependent partnership with a new partner
Among our sample, 23% reported ever being in an EDP with a new partner. Unadjusted models () indicated that Non-Hispanic White participants exhibited decreased odds of being in an EDP with a new partner compared to their Non-Hispanic Black counterparts (OR = 0.28, 95% CI: 0.13–0.59). Increases in socioeconomic disadvantage (OR = 1.54, 95% CI: 1.30–1.83) and psychosocial syndemic profiles (OR = 1.87, 95% CI: 1.46–2.39) were associated with greater odds of being in an EDP with a new partner. Cumulative promotive factors were associated with decreased odds of being in an EDP with a new partner (OR = 0.61, 95% CI: 0.47, 0.80). There were no unadjusted associations by age, sexual identity, and HIV status. Socioeconomic disadvantage (AOR = 1.47, 95% CI: 1.22–1.77), psychosocial syndemic profile (AOR = 1.67, 95% CI: 1.26–2.21), and cumulative protective factors (AOR = 0.72, 95% CI: 0.53–0.98) maintained statistically significant associations with the odds of ever being in an EDP in our compensatory model. We observed no statistically significant interactions of socioeconomic disadvantage by psychosocial syndemic profile or cumulative protective factors in our risk-protective model.
Table 3. Logistic regression models on economic-dependent partnerships with a new partner among young sexual minority men, N = 374.
Discussion
EDPs are both a survival method and a risk factor for HIV among YMSM. EPBs have been understudied in the behavioral health literature, particularly in high HIV risk groups like YMSM (Baral et al., Citation2015). Our sample of YMSM exhibited a high proportion reporting EDPs with nearly 1 in 3 indicating that they stayed with a main partner for economic needs and over 1 in 5 indicating they started a new sexual relationship for economic needs. Consistent with our hypotheses and prior literature, YMSM who experienced greater cumulative socioeconomic disadvantage were more likely to experience EDP with main and new partners alike (Bauermeister et al., Citation2016; Bimbi, Citation2007; Newman, Rhodes, & Weiss, Citation2004). These findings underscore the importance of contextualizing EDPs through YMSM’s composite socioeconomic profiles, rather than assuming that each disadvantaged characteristic is independent of each other.
Even after adjusting for cumulative socioeconomic disadvantage, non-Hispanic Whites were less likely than their Black counterparts to EDP with a new sexual partner. These findings may also speak to Black YMSM’s increased risk for HIV infection compared to White YMSM, with Black YMSM prioritizing socioeconomic needs over sexual/physical health needs (Graham, Aronson, Pulliam, Mann, & Rhodes, Citation2014). These racial/ethnic disparities might also suggest that other social mechanisms might increase Black YMSM’s economic reliance on new partners. For instance, researchers and policymakers have recognized that the earning worth of a dollar among Whites is the equivalent of .80 cents for African Americans (Williams & Collins, Citation2001); understanding how to account for these racial/inequities in the measurement of cumulative socioeconomic disadvantage are warranted. Given data suggesting that beyond these income-level associations, for example, community-level disadvantage might also contribute to the persisting HIV-related socioeconomic disparities experienced by Black/African American communities in the DMA (Bauermeister, Connochie, et al., Citation2017; New Detroit: The Coalition, Citation2014). Future research examining how these processes manifest are warranted.
Consistent with prior research, greater negative psychosocial conditions (syndemic profiles) were associated with EDPs. The sole focus on current psychosocial profiles, however, may overstate risk-driven frameworks and miss opportunities to promote resilience in future HIV interventions (Herrick, Stall, Egan, et al., Citation2014). In our analyses, for instance, we found that the impact of psychosocial factors on EDP is countered in the presence of promotive factors. Consistent with a compensatory resilience model (Fergus & Zimmerman, Citation2005), YMSM with greater cumulative promotive factors were less likely to report being in EDPs than those with less promotive factors, even while controlling for cumulative socioeconomic disadvantage and psychosocial profiles. These findings highlight the need to include promotive factors in efforts targeting behavioral risk factors for HIV infection. In our analyses, however, we found no support for a risk-protective model. Future research should explore whether the buffering effect of promotive factors on the relationship between EDP and psychosocial profiles might be attributable to community and structural factors (e.g., access to financial assistance programs; beneficial social connections and community resources) rather than individual-level factors, as measured in our study. Furthermore, given its connection to HIV risk (Koblin et al., Citation2006; Mustanski et al., Citation2007), future studies should seek to understand the interaction of intimate partner violence on the association between EDPs, sexual risk behaviors, and HIV seroconversion in YMSM.
In light of our findings, we also acknowledge the limitations of our study. Though we nest EDPs within an HIV-risk framework, we are unable to ascertain YMSM’s health promotive behaviors in these contexts; specifically, our findings do not account for condom-use or other protective methods while engaging in EDPs (Note: Data for this study were collected prior to PrEP rollout). A current understanding of protective factors that inform sexual health promotive behaviors may inform harm-reduction strategies for YMSM who are in EDPs.
Though commonly applied, the additive/count approach to indexing cumulative variables (e.g., socioeconomic disadvantage, psychosocial profile, and promotive factors) is not without its challenges. Experts have argued that this approach assumes equal weighting with respect to how they shape health outcomes, includes factors that may interact with one another, and provides limited information with respect to areas for intervention (Tsai & Burns, Citation2015). Future efforts may benefit from structural equation modeling approaches using latent variables to account for these concerns. Another limitation of this study is that we are unable to assert causal inferences based on the inherent limitations of the cross-sectional study design (e.g., lack temporal directionality of independent and dependent variables; inability to randomize on the independent variables). Future studies should assess longitudinal patterns of YMSM’s engagement in EDPs and their contribution to HIV vulnerability. The generalizability of our findings are also limited given our recruitment catchment area was restricted to the DMA. Though our sample is socioeconomically diverse, future studies should seek to replicate our analyses with other community samples of YMSM as a means to better understand the reliability and robustness of these partnerships.
Despite these limitations, our study has notable strengths. Our study sought to acknowledge calls-to-action that emphasize the importance of resilience frameworks when contextualizing HIV vulnerability by juxtaposing the distinct effects of YMSM’s socioeconomic and psychosocial stress (McGarrity, Citation2014). In addition, we sought to account for YMSM’s embedded individual and interpersonal strengths that may elucidate how resilience manifests within socioeconomic stressful contexts (Herrick et al., Citation2011). To our knowledge, our study is the first to examine YMSM’s engagement in EDP by integrating risk and resilience theoretical approaches. Though psychosocial profiles and cumulative protective factors do not interact with socioeconomic disadvantage, we establish the relevance and importance of these constructs in assessing YMSM’s EDP. Lastly, our findings support the general body of work that continues to demonstrate that resilience is an important and prevalent characteristic of YMSM despite ongoing risk. These findings could also inform the decision of local community organizations and AIDS service organizations to support and build health promotive factors in these men.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
References
- Baral, S. D., Friedman, M. R., Geibel, S., Rebe, K., Bozhinov, B., Diouf, D., … Cáceres, C. F. (2015). Male sex workers: Practices, contexts, and vulnerabilities for HIV acquisition and transmission. The Lancet, 385(9964), 260–273.
- Bauermeister, J. A., Connochie, D., Eaton, L., Demers, M., & Stephenson, R. (2017). Geospatial indicators of space and place: A review of multilevel studies of HIV prevention and care outcomes among young men who have sex with men in the United States. The Journal of Sex Research, 54(4-5), 446–464.
- Bauermeister, J. A., Eaton, L., Meanley, S., & Pingel, E. S., on behalf of the UHIP Partnership. (2017). Transactional sex with regular and casual partners among young men who have sex with me in the Detroit Metro Area. American Journal of Men’s Health, 11(3), 498–507.
- Bauermeister, J., Eaton, L., & Stephenson, R. (2016). A multilevel analysis of neighborhood socioeconomic disadvantage and transactional sex with casual partners among young men who have sex with men living in metro detroit. Behavioral Medicine, 42, 197–204.
- Bauermeister, J. A., Meanley, S., Hickok, A., Pingel, E., VanHemert, W., & Loveluck, J. (2014). Sexuality-related work discrimination and its association with the health of sexual minority emerging and young adult men in the Detroit Metro Area. Sexuality Research and Social Policy, 11(1), 1–10.
- Bauermeister, J. A., Pingel, E., Zimmerman, M., Couper, M., Carballo-Diéguez, A., & Strecher, V. J. (2012). Data quality in HIV/AIDS web-based surveys: Handling invalid and suspicious data. Field Methods, 24(3), 272–291.
- Biello, K. B., Thomas, B. E., Johnson, B. E., Closson, E. F., Navakodi, P., Dhanalakshmi, A., … Mimiaga, M. J. (2017). Transactional sex and the challenges to safer sexual behaviors: A study among male sex workers in Chennai, India. AIDS Care, 29(2), 231–238.
- Bimbi, D. S. (2007). Male prostitution: Pathology, paradigms and progress in research. Journal of Homosexuality, 53, 7–35.
- Burnes, T. R., Long, S. L., & Schept, R. A. (2012). A resilience-based lens of sex work: Implications for professional psychologists. Professional Psychology: Research and Practice, 43(2), 137–144.
- Buttram, M. E., Surratt, H. L., & Kurtz, S. P. (2014). Resilience and syndemic risk factors among African-American female sex workers. Psychology, Health & Medicine, 19(4), 442–452.
- Centers for Disease Control and Prevention (CDC). (2017). HIV among gay and bisexual men. Retrieved from https://www.cdc.gov/hiv/group/msm/index.html
- Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The connor-davidson resilience scale (CD-RISC). Depression and Anxiety, 18, 76–82.
- DeLonga, K., Torres, H. L., Kamen, C., Evans, S. N., Lee, S., Koopman, C., & Gore-Felton, C. (2011). Loneliness, internalized homophobia, and compulsive internet use: Factors associated with sexual risk behavior among a sample of adolescent males seeking services at a community LGBT center. Sexual Addiction & Compulsivity, 18(2), 61–74.
- Derogatis, L. R., & Melisaratos, N. (1983). The brief symptom inventory: An introductory report. Psychological Medicine, 13(3), 595–605.
- Díaz, R. M., Ayala, G., & Bein, E. (2004). Sexual risk as an outcome of social oppression: Data from a probability sample of Latino gay men in three U.S. cities. Cultural Diversity and Ethnic Minority Psychology, 10(3), 255–267.
- Duncan, D. T., Park, S. H., Schneider, J. A., Al-Ajlouni, Y. A., Goedel, W. C., Elbel, B., … Mayer, K. M. (2017). Financial hardship, condomless anal intercourse and HIV risk among men who have sex with men. AIDS and Behavior, 21, 3478–3485.
- Fergus, S., & Zimmerman, M. A. (2005). Adolescent resilience: A framework for understanding healthy development in the face of risk. Annual Review of Public Health, 26, 399–419.
- Frost, D. M., Parsons, J. T., & Nanín, J. E. (2007). Stigma, concealment and symptoms of depression as explanations for sexually transmitted infections among gay men. Journal of Health Psychology, 12(4), 636–640.
- Gangamma, R., Slesnick, N., Toviessi, P., & Serovich, J. (2008). Comparison of HIV risk among gay, lesbian, bisexual and heterosexual homeless youth. Journal of Youth and Adolescence, 37, 456–464.
- Glick, S. N., & Golden, M. R. (2014). Early male partnership patterns, social support, and sexual risk behavior among young men who have sex with men. AIDS and Behavior, 18(8), 1466–1475.
- Gorbach, P. M., & Holmes, K. K. (2003). Transmission of STIs/HIV at the partnership level: Beyond individual-level analyses. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 80(4), iii15–iii25.
- Graham, L. F., Aronson, R. E., Pulliam, R. M., Mann, L., & Rhodes, S. D. (2014). Preventing HIV among black men in college using a CBPR approach. In S. D. Rhodes (Ed.), Innovations in HIV prevention research and practice through community engagement (pp. 35–54). New York, NY: Springer Science Business Media.
- Greenwood, G. L., White, E. W., Page-Shafer, K., Being, E., Osmond, D. H., Paul, J., & Stall, R. D. (2001). Correlates of heavy substance use among young gay and bisexual men: The San Francisco young men’s health study. Drug and Alcohol Dependence, 61, 105–112.
- Halkitis, P. N., Kapadia, F., Bub, K. L., Barton, S., Moreira, A. D., & Stults, C. B. (2015). A longitudinal investigation of syndemic conditions among young gay, bisexual, and other MSM: The P18 cohort study. AIDS and Behavior, 19, 970–980.
- Harper, G. W., Brodsky, A., & Bruce, D. (2012). What’s good about being gay? Perspectives from youth. Journal of LGBT Youth, 9(1), 22–41.
- Herek, G. M., Cogan, J. C., Gillis, J. R., & Gunt, E. K. (1998). Correlates of internalized homophobia in a community sample of lesbians and gays. Journal-Gay and Lesbian Medical Association, 2, 17–26.
- Herrick, A. L., Lim, S. H., Plankey, M. W., Chmiel, J. S., Guadamuz, T. T., Kao, U., … Stall, R. (2013). Adversity and syndemic production Among Men participating in the multicenter AIDS cohort study: A life-course approach. American Journal of Public Health, 103, 79–85.
- Herrick, A. L., Lim, S. H., Wei, C., Smith, H., Guadamuz, T., Friedman, M. S., & Stall, R. (2011). Resilience as an untapped resource in behavioral intervention design for gay men. AIDS and Behavior, 15, S25–S29.
- Herrick, A., Stall, R., Egan, J., Schrager, S., & Kipke, M. (2014). Pathways towards risk: Syndemic conditions mediate the effect of adversity on HIV risk behaviors among young men who have sex with men (YMSM). Journal of Urban Health, 91(5), 969–982.
- Herrick, A. L., Stall, R., Goldhammer, H., Egan, J. E., & Mayer, K. H. (2014). Resilience as a research framework and as a cornerstone of prevention research for gay and bisexual men: Theory and evidence. AIDS and Behavior, 18, 1–9.
- Hope, V. D., & MacArthur, C. (1998). Safer sex and social class: Findings from a study of men using the ‘gay scene’ in the west midlands region of the United Kingdom. AIDS Care, 10(1), 81–88.
- Keuroghlian, A. S., Shtasel, D., & Bassuk, E. L. (2014). Out on the street: A public health and policy agenda for lesbian, gay, bisexual, and transgender youth who are homeless. American Journal of Orthopsychiatry, 84(1), 66–72.
- Koblin, B. A., Torian, L., Xu, G., Guilin, V., Makki, H., Mackellar, D., & Valleroy, L. (2006). Violence and HIV-related risk among young men who have sex with men. AIDS Care, 18, 961–967.
- Koken, J. A., & Bimbi, D. S. (2014). Mental health aspects of male sex work. In V. Minichiello & J. Scott (Eds.), Male sex work and society (pp. 223–239). New York, NY: Harrington Park Press.
- Lelutiu-Weinberger, C., Pachankis, J. E., Golub, S. A., Walker, J. J., Bamonte, A. J., & Parsons, J. T. (2013). Age cohort differences in the effects of gay-related stigma, anxiety and identification with the gay community on sexual risk and substance use. AIDS and Behavior, 17(1), 340–349.
- Linley, P. A., & Joseph, S. (2011). Meaning in life and posttraumatic growth. Journal of Loss and Trauma, 16, 150–159.
- Macleod, J., & Smith, G. D. (2003). Psychosocial factors and public health: A suitable case for treatment. Journal of Epidemiology and Community Health, 57, 565–570.
- Marshall, B. D., Shannon, K., Kerr, T., Zhang, R., & Wood, E. (2010). Survival sex work and increased HIV risk among sexual minority street-involved youth. Journal of Acquired Immune Deficiency Syndromes, 53, 661–664.
- McGarrity, L. A. (2014). Socioeconomic status as context for minority stress and health disparities among lesbian, gay, and bisexual individuals. Psychology of Sexual Orientation and Gender Diversity, 1(4), 383–397.
- Meanley, S., Gale, A., Harmell, C., Jadwin-Cakmak, L., Pingel, E., & Bauermeister, J. A. (2015). The role of provider interactions on comprehensive sexual healthcare among young men who have sex with men. AIDS Education and Prevention, 27(1), 15–26.
- Mustanski, B., Garofalo, R., Herrick, A., & Donenberg, G. (2007). Psychosocial health problems increase risk for HIV among urban young men who have sex with men: Preliminary evidence of a syndemic in need of attention. Annals of Behavioral Medicine, 34(1), 37–45.
- Mustanski, B., Newcomb, M. E., & Clerkin, E. M. (2011). Relationship characteristics and sexual risk-taking in young men who have sex with men. Health Psychology, 30(5), 597–605.
- Nehl, E. J., Klein, H., Sterk, C. E., & Elifson, K. W. (2016). Prediction of HIV sexual risk behaviors among disadvantaged African American adults using a syndemic conceptual framework. AIDS and Behavior, 20, 449–460.
- Newcomb, M. E., & Mustanski, B. (2011). Moderators of the relationship between internalized homophobia and risky sexual behavior in men who have sex with men: A meta-analysis. Archives of Sexual Behavior, 40(1), 189–199.
- New Detroit: The Coalition. (2014). Metropolitan Detroit race equity report. Retrieved from http://www.newdetroit.org/docs/press/MetropolitanDetroit_RaceEquity_Report_NewDetroit.pdf
- Newman, P. A., Rhodes, F., & Weiss, R. E. (2004). Correlates of sex trading among drug-using men who have sex with men. American Journal of Public Health, 94(11), 1998–2003.
- Oldenburg, C. E., Perez-Brumer, A. G., Reisner, S. L., & Mimiaga, M. J. (2015). Transactional sex and the HIV epidemic among men who have sex with men (MSM): Results from a systematic review and meta-analysis. AIDS and Behavior, 19, 2177–2183.
- Pellowski, J. A., Kalichman, S. C., Matthews, K. A., & Adler, N. (2013). A pandemic of the poor: Social disadvantage and the U.S. HIV epidemic. American Psychologist, 68(4), 197–209.
- Procidano, M. E., & Heller, K. (1983). Measures of perceived social support from friends and from family: Three validation studies. American Journal of Community Psychology, 11(1), 1–24.
- Reed, S. J., & Miller, R. L. (2016). Thriving and adapting: Resilience, sense of community, and syndemics among young black gay and bisexual men. American Journal of Community Psychology, 57, 129–143.
- Rosario, M., Schrimshaw, E. W., & Hunter, J. (2006). A model of sexual risk behaviors among young gay and bisexual men: Longitudinal associations of mental health, substance abuse, sexual abuse, and the coming-out process. AIDS Education and Prevention, 18(5), 444–460.
- Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press.
- Safren, S. A., Reisner, S. L., Herrick, A., Mimiaga, M. J., & Stall, R. (2010). Mental health and HIV risk in men who have sex with men. Journal of Acquired Immune Deficiency Syndromes, 55(Suppl. 2), S74–S77.
- Stall, R., Mills, T. C., Williamson, J., Hart, T., Greenwood, G., Paul, J., & Catania, J. A. (2003). Association of co-occuring psychosocial health problems and increased vulnerability to HIV/AIDS among urban men who have sex with men. American Journal of Public Health, 93, 939–942.
- Steger, M. F., Frazier, P., Oishi, S., & Kaler, M. (2006). The meaning in life questionnaire: Assessing the presence of and search for meaning in life. Journal of Counseling Psychology, 53, 80–93.
- Stoddard, S. A., Whiteside, L., Zimmerman, M. A., Cunningham, R. M., Chermack, S. T., & Walton, M. A. (2013). The relationship between cumulative risk and promotive factors and violent behavior among urban adolescents. American Journal of Community Psychology, 51, 57–65.
- Storholm, E. D., Halkitis, P. N., Siconolfi, D. E., & Moeller, R. W. (2011). Cigarette smoking as part of a syndemic among young men who have sex with men ages 13–29 in New York City. Journal of Urban Health, 88(4), 663–676.
- Tsai, A. C., & Burns, B. F. (2015). Syndemics of psychosocial problems and HIV risk: A systematic review of empirical tests of the disease interaction concept. Social Science & Medicine, 139, 26–35.
- Van den Berg, J. J., Fernández, M. I., Fava, J. L., Operario, D., Rudy, B. J., Wilson, P. A., & the ATN 086, 104 Protocol Teams for the Adolescent Medicine Trials Network for HIV/AIDS Interventions. (2017). Using syndemics theory to investigate risk and protective factors associated with condomless sex among youth living with HIV in 17 U.S. cities. AIDS and Behavior, 21, 833–844.
- Vinokur, A. D., & Van Ryn, M. (1993). Social support and undermining in close relationships: Their independent effects on the mental health of unemployed persons. Journal of Personality and Social Psychology, 65, 350–359.
- Walls, N. E., & Bell, S. (2011). Correlates of engaging in survival sex among homeless youth and young adults. Journal of Sex Research, 48, 423–436.
- Williams, D. R., & Collins, C. (2001). Racial residential segregation: A fundamental cause of racial disparities in health. Public Health Reports, 116, 404–416.
- Wolitski, R. J., Valdiserri, R. O., & Stall, R. (2008). Health disparities affecting gay and bisexual men in the United States. In Unequal opportunity: Health disparities affecting gay and bisexual men in the United States: An introduction (pp. 3–32). New York, NY: Oxford University Press.
- Wong, C. F., Kipke, M. D., Weiss, G., & McDavitt, B. (2010). The impact of recent stressful experiences on HIV-risk related behaviors. Journal of Adolescence, 33(3), 463–475.
- Zhang, W., O’Brient, N., Forrest, J. I., Salters, K. A., Patterson, T. L., Montaner, J., … Lima, V. D. (2012). Validating a shortened depression scale (10 item CES-D) among HIV-positive people in British Columbia, Canada. PLoS One, 7(7), e40793.