Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Sep 6.
Published in final edited form as: Drug Alcohol Depend. 2022 Jun 30;238:109550. doi: 10.1016/j.drugalcdep.2022.109550

A latent class analysis of tailored substance use treatment programs: Implications for treating syndemic conditions facing sexual and gender minority populations

Emily C Helminen a,1, Cory J Cascalheira a,b,2, Thomas J Shaw a,3, Sarah Zollweg c,4, Tonda L Hughes c,d, Jillian R Scheer a,*,5
PMCID: PMC9444885  NIHMSID: NIHMS1822438  PMID: 35820291

Abstract

Background:

Syndemics (i.e., multiple, co-occurring, and synergistic conditions) contribute to elevated substance use among sexual and gender minority (SGM) people relative to heterosexual, cisgender people. Research suggests that syndemic-informed and SGM-tailored treatments are effective in substance use treatment among SGM people. However, few studies have examined 1) the proportion of substance use treatment facilities offering syndemic-informed, SGM-tailored treatment programming; and 2) the availability and accessibility of syndemic-informed, SGM-tailored treatment programs across the U.S.

Methods:

We used the 2020 National Survey of Substance Abuse Treatment Services (N-SSATS) dataset to perform a latent class analysis examining whether substance use treatment facilities’ tailored treatment programs cluster together to form distinct classes indicating whether facilities offer syndemic-informed and SGM-tailored programming. We then used multinomial logistic regression to examine associations between class membership and facility availability and accessibility.

Results:

Analyses revealed four classes of substance use treatment facilities’ tailored programs. Facilities with syndemic-informed and SGM-tailored treatment programs compared to facilities with no tailored programs were more likely to be in the Northeast compared to the Midwest and South; to offer payment assistance versus not offer payment assistance; and to be private, for-profit facilities versus public or non-profit facilities.

Conclusions:

This study’s findings identify the need for more facilities with syndemic-informed and SGM-tailored treatment, particularly in the Midwestern and Southern U.S. regions. Facilities offering syndemic-informed and SGM-tailored treatment might present accessibility barriers for low-income SGM people, as they were more likely to be private, for-profit facilities; however, they were more likely to offer payment assistance.

Keywords: Substance use, Sexual minority, Gender minority, Syndemic theory, Treatment facilities

1. Introduction

Sexual and gender minority (SGM) people are substantially more likely than heterosexual, cisgender people to report alcohol and other drug use disorders (Connolly and Gilchrist, 2020; Drabble et al., 2018; Marshal et al., 2008). For instance, relative to heterosexual adults, sexual minority adults are 1.8–2 times as likely to report any past-year substance use disorder and up to 2.4 times as likely to report any lifetime substance use disorder (Kerridge et al., 2017). Relative to cisgender people, gender minority people (e.g., transgender, genderqueer) report 3.6 times the prevalence of any substance use disorder (Hughto et al., 2021). These documented disparities may be due, in part, to minority stress, including distal minority stress (e.g., anti-SGM discrimination, victimization) and proximal minority stress (e.g., internalized homophobia, internalized transphobia; Brooks, 1981; Meyer, 2003). SGM people are also more likely to report higher violence and posttraumatic stress disorder (PTSD) than heterosexual, cisgender people (Conron et al., 2010; Drabble et al., 2020; Hughes et al., 2010; Edwards et al., 2015; Roberts et al., 2010; Scheer et al., 2020). Beyond known disparities among singularly reported mental and behavioral health conditions, SGM people are also more likely than heterosexual, cisgender people to report multiple conditions concurrently (Evans-Polce et al., 2020).

1.1. Syndemic-Informed and SGM-Tailored Substance Use Treatment

Co-occurring conditions among SGM people may be understood within a syndemic framework, which posits that co-occurring conditions synergistically increase the overall health burden among socially disadvantaged individuals (Singer, 1994). A syndemic represents an interaction between two or more health concerns, environmental factors, or social conditions (Singer et al., 2017). For instance, comorbid substance use and PTSD not only interact as potentially maladaptive coping processes (e.g., drinking to cope with PTSD symptoms; Dworkin et al., 2021), but are also exacerbated by environmental disadvantages (e.g., homelessness; Hao et al., 2021), societal stressors (Helminen et al., 2021), and SGM-specific stressors, such as social exclusion and prejudice (Bandermann and Szymanski, 2014; Coulter et al., 2015).

Several studies have examined syndemics among SGM people, particularly to inform treatment of syndemic conditions (Brennan et al., 2012; Coulter et al., 2015; Logie et al., 2017; Parsons et al., 2012; Scheer and Pachankis, 2019; Valentine et al., 2015). For example, studies have shown that the presence of multiple syndemic conditions contributes to worse health outcomes (Brennan et al., 2012; Parsons et al., 2012; Scheer and Pachankis, 2019). Findings underscore the importance of transdiagnostic treatment approaches that target syndemic conditions among SGM people, rather than treating single conditions separately (Fletcher and Reback, 2015; LoSchiavo et al., 2021; Martinez et al., 2019; Pachankis, 2015). For instance, a recent study found that a cognitive-behavioral intervention targeting co-occurring PTSD symptoms and sexual-risk behavior among sexual minority men led to better outcomes than targeting sexual risk behavior alone (O’Cleirigh et al., 2019). In addition, a recent meta-analysis of multifaceted treatment programs, relative to various control groups (e.g., waitlist, treatment as usual, single-component treatment programs), demonstrated that multifaceted treatment programs targeting syndemic conditions more effectively reduced substance use and sexual-risk behavior, improved mental health, and increased medication adherence among sexual minority men (Pantalone et al., 2020).

Transdiagnostic treatment programs also show promising efficacy for addressing SGM-specific drivers of syndemic conditions. For example, SGM-tailored treatments targeting SGM-specific stressors (e.g., family rejection, internalized stigma) and protective factors (e.g., SGM community engagement; Craig et al., 2012; Logie et al., 2015; Pachankis et al., 2020) demonstrated consistent reductions in smoking, alcohol use, and other drug use among SGM people (Pachankis et al., 2015, 2020; Schwinn et al., 2015; Vogel et al., 2020). Thus, in addition to targeting syndemic conditions (e.g., substance use, PTSD symptoms), treatment programs that address SGM-specific stressors may be well-suited for SGM people’s presenting concerns. However, whether substance use treatment facilities are equipped to address SGM people’s syndemic conditions and SGM-specific stressors remains unknown.

An effective way to understand whether substance use treatment facilities are equipped to address SGM people’s syndemic conditions is by using a person-centered (or in this case, facility-centered) method. Latent class analysis (LCA; Lanza and Rhoades, 2013) is an analytic approach that assumes heterogeneity exists and can be used to identify latent classes of substance use treatment facilities that cluster together based on facility characteristics. For instance, there could be a latent class of treatment facilities characterized by offering tailored programs for SGM-specific care, co-occurring mental health and substance use concerns, trauma, and HIV/AIDS (e.g., a “Syndemic-Informed and SGM-Tailored Programs” class), whereas another latent class of facilities might offer tailored programs for trauma only (e.g., a “Trauma-Specific Programs” class). In this example, the first class of facilities may be better equipped to treat SGM people with syndemic conditions as it is characterized by offering tailored treatment for both syndemic conditions and SGM-specific care. Beyond simply identifying whether facilities may be equipped to treat SGM people’s syndemic conditions, an LCA approach is also effective in understanding whether latent classes may be associated with availability (e.g., dispersion across the U.S.) and accessibility (e.g., ability to access treatment programs) of syndemic-informed and SGM-tailored treatment programs.

1.2. Availability and Accessibility of Substance Use Treatment Programs for SGM People

Studies documenting the availability and accessibility of syndemic-informed and SGM-tailored treatment programs are sparse. Of the few existing studies (Cochran et al., 2007; Qeadan et al., 2021; Williams and Fish, 2020), all have relied on variable-centered approaches. For example, in a study of substance use treatment facilities in the US, Williams and Fish (2020) found that facilities offering SGM-tailored programming were more likely to be private for-profit than private non-profit or public (e.g., local, state, or federal government facilities. Qeadan and colleagues (2021) found that facilities located in the West, compared to the Northeast, were more likely to have SGM-tailored programs. These studies are limited because variable-centered approaches are not able to examine whether facilities’ tailored programming offerings cluster together to form latent classes (e.g., a “Syndemic-Informed and SGM-Tailored Programs” class), and whether these latent classes may be associated with availability and accessibility. Using a facility-centered approach would assist in identifying whether one or more “Syndemic-Informed and SGM-Tailored Programs” classes exist, and subsequently, the availability and accessibility of these latent classes of facilities. This information is important in understanding whether classes of facilities that are equipped to treat SGM people with syndemic conditions are also available and accessible to SGM people.

In the present study we sought to examine (a) whether tailored treatment programs offered at substance use treatment facilities across the U.S. cluster together around syndemic-informed and SGM-tailored treatment programs (i.e., a syndemic-informed and SGM-tailored latent class); and (b) associations between latent classes of substance use treatment facilities and U.S. location, payment assistance options, and facility type.

2. Material and methods

2.1. Data source and sample

Data are from the 2020 National Survey of Substance Abuse Treatment Services (N-SSATS) conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA). The N-SSATS collects information on characteristics of substance use treatment centers across the U.S., such as services offered, location, facility type, and payment assistance options. Data were collected from March to December 2020 for the 2020 N-SSATS, with a response rate of 90.2% (SAMSHA, 2021). Of the 16,066 facilities included in the dataset, 22 did not report data on tailored intervention programs and were excluded, resulting in an analytic sample size of 16,022 facilities.

2.2. Measures

2.2.1. Tailored programs

Substance use treatment facilities’ tailored programs were assessed with the question, “For which client categories does this facility at this location offer a substance use treatment program or group specifically tailored for clients in that category?” Response options included: SGM-tailored programming, HIV/AIDS, co-occurring mental health and substance use concerns, co-occurring pain and substance use, sexual abuse, domestic violence/interpersonal violence, and trauma. These seven response options were used as indicators for the LCA.

2.2.2. Region

Region was assessed using the state in which the substance use treatment facility was located. Facilities were coded as Northeast, Midwest, South, or West based on Census Bureau designations of U.S. regions. Facilities outside of these designations (e.g., Puerto Rico) were coded as ‘other.’.

2.2.3. Payment assistance

Payment assistance was assessed with one question asking whether substance use treatment facilities use sliding fee scales, one question asking whether facilities offer treatment at no charge or for a minimal payment for those who cannot afford to pay, and one question asking whether substance use treatment is free for all clients. Facilities that provided an affirmative response to any of these questions were coded as offering payment assistance (1) vs no payment assistance (0).

2.2.4. Facility type

Facility type was assessed with a question asking whether the substance use treatment facility was operated by: (a) a private for-profit operation; (b) a private non-profit organization; (c) state government; (d) local, county, or community government; (e) tribal government; or (f) federal government. Response options (c) through (e) were combined into a non-federal government category.

2.3. Data analysis

Descriptive statistics were conducted in IBM SPSS Statistics (Version 27). Seven types of tailored programs were entered into LatentGOLD, version 5.1 to conduct the LCA. LatentGOLD uses the three-step latent class analytic approach to prevent measurement bias by correcting for classification error (Bakk et al., 2013). We fit 1- to 8-class models and assessed the local independence assumption for each model by examining bivariate residuals among each pair of indicators (Vermunt and Magidson, 2016). Residual correlations were included in models that violated the local independence assumption.

The most optimally fitting model was chosen by selecting the model with relatively low model fit statistics (i.e., Log Likelihood, Akaike Information Criteria [AIC], Bayesian Information Criteria [BIC], sample-size-adjusted BIC [aBIC]), relatively high entropy, relatively few free parameters, and smallest class size > 5% of the sample (Lanza and Rhoades, 2013; Weller et al., 2020). Next, to examine correlates of latent class membership, we conducted multinomial logistic regression using the bias-adjusted maximum likelihood approach, which is recommended when variables are covariates or categorical dependent variables (Vermunt and Magidson, 2016). Specifically, we examined whether U.S. region, facility type, and payment assistance options were associated with latent classes.

3. Results

Characteristics of the facilities, including tailored treatment programming, location, payment assistance, and facility type are displayed in Table 1.

Table 1.

Frequencies of Study Variables Among Substance Use Providers (N-SSATS 2020).

Total sample (N = 16,022)
n %
Types of Tailored Programs
SGM clients 3901 24.3
Clients with co-occurring mental and substance use disorders 8907 55.6
Clients with co-occurring pain and substance use 3499 21.8
Clients with HIV or AIDS 3366 21.0
Clients who have experienced sexual abuse 4780 29.8
Clients who have experienced IPV/DV 4752 29.7
Clients who have experienced trauma 7269 45.4
Offers Payment Assistance
Yes 10,846 67.7
No 4862 30.3
Missing 314 2.0
Types of Facilities
Private non-profit organization 7985 49.8
Private for-profit organization 6513 40.7
Non-federal government 1202 7.5
Federal government 322 2.0
U.S. Region
Northeast 2947 18.4
Midwest 3795 23.7
South 4739 29.6
West 4430 27.6
Other 111 0.7
Open in a new tab

Note: Non-federal government facilities included those that are operated by state, local, county, community, or tribal governments. Payment assistance refers to facilities that offer a sliding fee scale, a no payment option/minimal payment option, and/or free services to all substance use treatment clients.

3.1. Model selection and class description

Model fit indices are displayed in Table 2. Fit indices, including the AIC, BIC, and aBIC decreased from one-class to seven-class models. The four-class solution was selected as the optimally fitting solution based on the following: (a) AIC, BIC, and aBIC was lower in the four-class solution relative to the one- through three-class solutions; (b) entropy was higher in the four-class solution relative to the six- through eight-class solutions; (c) the four-class solution contained relatively few free parameters compared to the five- through eight-class solutions; and (d) size of the smallest class was > 5% in the four-class solution, whereas it was < 5% in the five- through eight-class solutions. Tables 3, 4.

Table 2.

Model Fit Indices and Model Comparison Statistics for Mixture Modeling of Tailored Programs for Substance Use Treatment.

Number of classes Log Likelihood Bayesian Information Criterion Akaike Information Criterion Sample-Size Adjusted Bayesian Information Criterion Number of Free Parameters Entropy Smallest Class Size (%)
1 −67086 134240 134186 134218 7 N/A 100
2 −41902 84036 83852 83960 24 0.99 29.9
3 −41946 84135 83943 84056 25 0.79 20.9
4a −41776 83863 83617 83761 32 0.76 13.7
5 −41768 83914 83615 83790 39 0.77 1.8
6 −41721 83897 83536 83747 47 0.73 2.1
7 −41706 83946 83523 83771 55 0.75 1.7
8 −41664 83939 83454 83738 63 0.68 2.1
Open in a new tab

Note.

a

Model selected as providing the best fit, as demonstrated by the relatively small Akaike Information Criterion, Bayesian Information Criterion, relatively high entropy, and relatively few parameters while keeping class size above 5%. Models 2 through 4 included bivariate residuals (i.e., addition of residual associations [local dependencies]) due to violation of the local independence assumption for LCA. Each criterion is based upon the Log-Likelihood.

Table 3.

Probabilities of Tailored Program Offerings Across 4 Latent Classes for Substance Use Treatment Facilities (N = 16,022).

Tailored Programs Class 1 No Tailored Programs n = 7290 (45.5%) Class 2 Comorbid MH/SU Programs n = 3715 (23.1%) Class 3 Syndemic-Informed and SGM-Tailored Programs n = 2804 (17.6%) Class 4 Comorbid MH/SU and Trauma-Specific Programs n = 2195 (13.7%)
SGM 0.01 0.10 0.93 0.37
Co-occurring MH/SU concerns 0.15 0.83 0.99 0.87
Co-occurring pain/SU concerns 0.01 0.18 0.80 0.23
HIV/AIDS 0.01 0.07 0.88 0.24
Sexual abuse 0.001 0.01 0.996 0.88
IPV/DV 0.02 0.09 0.99 0.69
Trauma 0.03 0.56 0.996 0.96
Open in a new tab

Note. SGM = sexual and gender minorities; MH = mental health; SU = substance use; IPV = intimate partner violence; DV = domestic violence. Boldface type indicates probabilities > 0.60.

Table 4.

Multinomial Logistic Regression Model of Correlates of Latent Classes for Substance Use Treatment.

Class 2 (“Comorbid MH/SU Programs”; n = 3715; 23.1%)
 Class 3 (“Syndemic-Informed and SGM-Tailored Programs”; n = 2804; 17.6%)
 Class 4 (“Comorbid MH/SU and Trauma-Specific Programs”; n = 2195; 13.7%)
AOR (95% CI) AOR (95% CI) AOR (95% CI)
U.S. region
Northeast ref ref ref
Midwest 0.59 (0.51, 0.69) 0.50 (0.43, 0.59) 0.62 (0.52, 0.74)
South 0.67 (0.57, 0.78) 0.84 (0.73, 0.97) 0.78 (0.66, 0.93)
West 0.81 (0.70, 0.95) 1.05 (0.91, 1.22) 1.26 (1.07, 1.48)
Other 0.50 (0.25, 0.99) 1.10 (0.62, 1.92) 0.99 (0.52, 1.87)
Offers Pay Assistance
No ref ref ref
Yes 1.71 (1.51, 1.95) 1.77 (1.58, 1.99) 1.43 (1.25, 1.63)
Type of Organization
Private Non-Profit ref ref ref
Private For-Profit 0.59 (0.52, 0.67) 1.52 (1.36, 1.70) 0.95 (0.83, 1.08)
Non-Federal Government 0.92 (0.76, 1.10) 0.58 (0.46, 0.73) 0.75 (0.60, 0.94)
Federal Government 1.40 (0.98, 1.99) 1.04 (0.68, 1.58) 1.64 (1.15, 2.36)
Open in a new tab

Note. MH = mental health; SU = substance use; AOR = adjusted odds ratio; CI = confidence interval; ref = reference group. Boldface type indicates a significant AOR. Omitted (reference) category is Class 1 (“No Tailored Programs”; n = 7290; 45.5%), which was characterized by low probabilities of offering any tailored programs. Class 2 (“Comorbid MH/SU Programs”) was characterized by high probabilities of offering programs for clients with comorbid mental health/substance use concerns; Class 3 (“Syndemic-Informed and SGM-Tailored Programs”) was characterized by high probabilities of offering all types of tailored programming, and was the only class characterized by high probability of offering SGM-tailored programming; Class 4 (“Comorbid MH/SU and Trauma-Specific Programs”) was characterized by offering tailored programs for clients with comorbid mental health/substance use concerns and clients with a history of sexual abuse, intimate partner violence or domestic violence, and/or other trauma. All models utilized the bias-adjusted maximum likelihood approach.

Class 1 was the largest latent class (45.5% of facilities) characterized by low probabilities of offering any tailored programming ("No Tailored Programs" Class). Class 2 (23.1%) was characterized by high probabilities of tailored programs for clients with co-occurring mental health/substance use concerns ("Comorbid Mental Health/Substance Use Tailored Programs" Class). Class 3 (17.6%) was characterized by high probabilities across all types of tailored programs, and it was the only class to be characterized by a high probability of SGM-tailored programming ("Syndemic-Informed and SGM-Tailored Programs" Class). Class 4 (13.7%) was characterized by high probabilities of tailored programs for clients with co-occurring mental health/substance use concerns, history of sexual abuse, intimate partner violence/domestic violence, and trauma ("Comorbid Mental Health/Substance Use and Trauma-Specific Tailored Programs" Class).

3.2. Latent class associations with availability and accessibility

U.S. region, payment assistance, and facility type were all associated with class membership. Within this section, results will be described for Classes 2 through 4 relative to Class 1, the “No Tailored Programs” class. For the “Comorbid Mental Health/Substance Use Concerns Tailored Programs” latent class (Class 2), relative to the “No Tailored Programs” class, facilities were less likely to be in the Midwest (AOR = 0.59, 95% CI = 0.51–0.69), South (AOR = 0.67, 95% CI = 0.57–0.78), West (AOR = 0.81, 95%CI = 0.70–0.95), and other regions (AOR = 0.50, 95% CI = 0.25–0.99) compared to the Northeast. Facilities in this class were more likely to offer payment assistance options (AOR = 1.71, 95% CI = 1.51–1.92) relative to the “No Tailored Programs” class. Regarding facility type, facilities in this class, relative to the “No Tailored Programs” class, were less likely to be private for-profit facilities (AOR = 0.59, 95% CI = 0.52–0.67) than private non-profit facilities.

For the “Syndemic-Informed and SGM-Tailored Programs” latent class (Class 3), facilities were less likely to be in the Midwest (AOR = 0.50, 95% CI = 0.43–0.59) and South (AOR = 0.84, 95% CI = 0.73–0.97) compared to the Northeast. Facilities in this class were more likely to offer payment assistance options (AOR = 1.77, 95% CI = 1.58–1.99). Facilities in this class were also more likely to be private for-profit facilities (AOR = 1.52, 95% CI = 1.36–1.70) and less likely to be state, local, county, community, or tribal (i.e., non-federal) government facilities (AOR = 0.58, 95% CI = 0.46–0.73) than private non-profit facilities. Facilities in this class were just as likely as private non-profit facilities to be federal government facilities (AOR = 1.04, 95% CI = 0.68–1.58).

For the “Comorbid Mental Health/Substance Use Concerns and Trauma-Specific Tailored Programs” latent class (Class 4), facilities were less likely to be in the Midwest (AOR = 0.62, 95% CI = 0.52–0.74) and South (AOR = 0.78, 95% CI = 0.66–0.93), and more likely to be in the West (AOR = 1.26, 95% CI = 1.07–1.48) compared to the Northeast. Facilities in this class were more likely to offer payment assistance options (AOR = 1.43, 95% CI = 1.25–1.63). Regarding facility type, facilities in this class were less likely to be state, local, county, community, or tribal (i.e., non-federal) government facilities (AOR = 0.75, 95% CI = 0.60–0.94), and more likely to be federal government facilities (AOR = 1.64, 95% CI = 1.15–2.36) than private non-profit facilities.

4. Discussion

We examined whether substance use treatment facilities’ tailored programs cluster together and whether class membership is characterized by syndemic-informed and SGM-tailored treatment programs. Using this facility-centered analytic approach, a four-class solution revealed only one relatively small latent class (17.6% of facilities) that was characterized by high probabilities of offering both syndemic-informed and SGM-tailored programming. Facilities in the “Syndemic-Informed and SGM-Tailored Programs” class were underrepresented in the Midwestern and the Southern regions of the U.S., were more likely to be private, for-profit facilities, and were also more likely to offer payment assistance options.

In terms of service availability, fewer facilities in the “Syndemic-Informed and SGM-Tailored Programs” class were in the Midwest and South relative to the Northeast. Although this study demonstrated that the number of overall substance use treatment facilities is greater in the Midwest and South than in the Northeast, the Midwest and South cover a larger geographic territory and have a higher proportion of medically underserved areas relative to the Northeast (Health Resources and Services Administration, 2021). Underserved areas are less likely to have specialty care (e.g., syndemic-informed and SGM-tailored substance use treatment; Anon, 2020), which may explain why facilities in the “Syndemic-Informed and SGM-Tailored Programs” class are less likely to be in the Midwest and South relative to the Northeast.

In addition, facilities in the “Syndemic-Informed and SGM-Tailored Programs” class may be less likely to be in the Midwest and South relative to the Northeast because these areas tend to have less public support for SGM rights (Twenge and Blake, 2021), and prior research indicates that policy is generally responsive to public opinion (Lax and Phillips, 2009). Indeed, relative to the Northeast, the Midwest and South have higher concentrations of anti-SGM state-level policies (Anon, 2020). Consequently, less public support for SGM rights and more hostile policy environments could disincentivize providing SGM-tailored programming at substance use treatment facilities in these areas. Findings in the literature underscore associations between hostile policy environments (e.g., lack of support for same-sex marriage, lack of sexual-orientation-related nondiscrimination statutes) and greater substance use and worse substance use outcomes among SGM people in the Midwest and South (Greene et al., 2021; Hatzenbuehler et al., 2010, 2017). Research has also demonstrated that policy-level improvements are associated with improvements in individual-level substance use outcomes (Everett et al., 2016). Such findings highlight the importance of SGM-affirmative policies and the expansion of syndemic-informed and SGM-tailored substance use treatment programming in these regions. Legislative bodies could partially address the lack of syndemic-informed and SGM-tailored treatment by requiring these types of services. Additionally, if policies require SGM-based insurance protections and reimbursements, facilities might be incentivized to provide SGM-tailored treatment regardless of their location and type.

Latent class membership was also associated with accessibility. For the “Syndemic-Informed and SGM-Tailored Programs” class, associations with accessibility were mixed. Compared to private non-profit facilities, facilities in this class were more likely to be private for-profit and less likely to be non-federal (i.e., state, local, county, community, or tribal) government facilities. These findings suggest that substance use treatment may be less accessible among clients from low-income backgrounds relative to those with more financial means, as previous research has demonstrated that private for-profit, relative to private non-profit, facilities often serve higher-income clients (Pollack and Armstrong, 2009; Wheeler et al., 1992; Wheeler and Nahra, 2000). However, the “Syndemic-Informed and SGM-Tailored Programs” class was also more likely than the “No Tailored Programs” class to offer payment assistance options, which may be indicative of greater accessibility. However, research indicates that when private for-profit substance use treatment facilities serve clients who are unable to pay for services, treatment options may be limited or of shorter duration (Nahra et al., 2009). As such, even if payment assistance options are available, substance use treatment may not be equitable for those who use such options, particularly since a long length of substance use treatment is often associated with better outcomes (Greenfield et al., 2004; Staiger et al., 2020; Teesson et al., 2008).

4.1. Limitations and future directions

Results should be considered in light of several limitations. These data are cross-sectional, which precludes causal inferences about associations among facility characteristics, availability, and accessibility. A longitudinal approach could examine whether combinations of facilities’ tailored program offerings change over time, and whether these changes are prospectively associated with availability and accessibility. Longitudinal studies could also incorporate additional variables, such as policy changes, to understand whether these variables are associated with increases in syndemic-informed and SGM-tailored programming (Cascalheira et al., 2022). Different research designs and analytic approaches, such as qualitative research, could improve understanding of how SGM clients experience syndemic-informed and SGM-tailored programming relative to non-syndemic-informed and non-SGM-tailored treatment programs.

Another limitation of this study was the use of self-report data, which raises questions related to social desirability and/or facility personnel’s understanding of the questions about tailored treatment programming. For SGM-tailored treatment programs specifically, previous research has indicated that SGM-tailored treatment programs vary widely and may report services that are actually not available (Cochran et al., 2007). For instance, using data from the 2002 N-SSATS database, Cochran et al. (2007) contacted the 911 facilities claiming to offer SGM-tailored treatment and found that only 7.4% offered such services. Although question specificity improved from the 2002–2019 N-SSATS survey (SAMHSA, 2019), the extent to which self-report bias continues to inflate the actual availability of SGM-tailored programming remains unclear (Ji, 2021).

Although we examined whether facilities offered both syndemic-informed and SGM-tailored treatment programming, even programs that reported both may not offer both together as a comprehensive treatment program. Thus, SGM people seeking substance use treatment might participate in multiple treatment programs. Further, this study did not permit examination of treatment programming, availability, and accessibility for specific SGM subgroups (e.g., sexual minority women). Scheer et al. (2022a),(2022b) found that when working with sexual minority women, it is important to attend to gender identity and expression, and to focus on gender-based stress in treatment. Beyond tailoring treatment for specific SGM subgroups, it may be important to tailor treatment to SGM people with multiply marginalized identities (e. g., racial/ethnic minority SGM people). For instance, Babor et al. (2007) found that young, Black, and low-income sexual minority women who engage in heavy episodic drinking may benefit from increased access to brief behavioral and mental health interventions (e.g., Screening, Brief Intervention, and Referral to Treatment) and with identity-affirming providers (Scheer et al., 2022a,2022b). Future research should continue examining factors related to substance use treatment availability and accessibility specifically for racial/ethnic minority SGM people.

Additional limitations to this study were related to construct measurement. Availability and accessibility in this study were based on facility location by U.S. region, facility type, and the availability of payment assistance options. However, even if facilities with syndemic-informed and SGM-tailored programming became widely available across U.S. regions and became financially accessible, additional treatment access barriers for SGM people may persist. It will be important for future research to consider greater specificity than regional-level availability (e.g., city-level availability). For example, a recent systematic review found SGM people tend to be more concentrated in regions with greater healthcare resources (Lee et al., 2018). However, within high-resource regions, SGM people may be more concentrated in cities that have fewer resources (Lee et al., 2018), indicating that treatment availability may continue to be a concern for SGM people even if improvements are made in regional facility availability. SGM people also often report sexual orientation-based stigma from treatment providers when seeking substance use treatment (Cochran, Peavy, and Cauce, 2007; Drabble and Eliason, 2012; Lyons et al., 2015; Scheer et al., 2022a,2022b). Thus, in addition to considering logistical availability and accessibility concerns, it is important to address other potential barriers, such as substance use treatment providers’ abilities to provide SGM-affirming care.

5. Conclusion

Despite the efficacy of syndemic-informed and SGM-tailored treatment interventions, less than a sixth of substance use treatment facilities report offering both syndemic-informed and SGM-tailored substance use treatment options. Facilities that are equipped to provide syndemic-informed and SGM-tailored treatment are not equally distributed across the U.S. and are particularly underrepresented in the Midwest and the Southern regions of the U.S. Additionally, these facilities are more likely to be private, for-profit, suggesting that effective syndemic-informed and SGM-tailored substance use treatment may be unaffordable for SGM people facing challenging environmental disadvantages. Accordingly, results of this study highlight the need for more facilities with syndemic-informed and SGM-tailored treatment in general, and in particular in the Midwest and the Southern regions of the U.S. In addition, facilities funded by non-profit mechanisms or government agencies should be encouraged to increase syndemic-informed and SGM-tailored treatment offerings.

Acknowledgments

Jillian Scheer is supported by a Mentored Scientist Development Award (K01AA028239) from the National Institute on Alcohol Abuse and Alcoholism. Cory Cascalheira is supported as a RISE Fellow by the National Institutes of Health (R25GM061222). Sarah Zollweg is supported by an NIH Ruth L. Kirschstein National Service Research Award Individual Predoctoral Fellowship (F31AA029847) from the National Institute on Alcohol Abuse and Alcoholism. Tonda Hughes is supported by a Research Project Grant (R01AA013328) from the National Institute on Alcohol Abuse and Alcoholism.

Footnotes

Conflict of Interest

No conflict declared.

References

  1. Brennan J, Kuhns LM, Johnson AK, Belzer M, Wilson EC, Garofalo R, Adolescent Medicine Trials Network for HIV/AIDS Interventions, 2012. Syndemic theory and HIV-related risk among young transgender women: the role of multiple, co-occurring health problems and social marginalization. Am. J. Public Health 102 (9), 1751–1757. 10.2105/AJPH.2011.300433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Connolly D, Gilchrist G, 2020. Prevalence and correlates of substance use among transgender adults: A systematic review. Addict. Behav. 111, 106544 10.1016/j.addbeh.2020.106544. [DOI] [PubMed] [Google Scholar]
  3. Resources Health & Administration Services, 2021. Medically underserved areas/populations. HRSA Map Gallery. https://data.hrsa.gov/ExportedMaps/MapGallery/MUA.pdf. [Google Scholar]
  4. AnonMovement Advancement Project. (2020, February). Mapping LGBTQ equality: 2010 to 2020. https://www.lgbtmap.org/2020-tally-report.
  5. AnonU.S. Committee on Ways and Means. (2020, July). Left out: Barriers to health equity for rural and underserved communities. Report of the Committee on Ways and Means Majority U.S. House of Representatives. https://waysandmeans.house.gov/sites/democrats.waysandmeans.house.gov/files/documents/WMD%20Health%20Equity%20Report_07.2020_FINAL.pdf?emci=8f3b7b63-8b61-eb11-9889-00155d43c992&emdi=ea000000-0000-0000-0000-000000000001&ceid=.
  6. Babor TF, McRee BG, Kassebaum PA, Grimaldi PL, Ahmed K, Bray J, 2007. Screening, Brief Intervention, and Referral to Treatment (SBIRT): toward a public health approach to the management of substance abuse. Subst. Abus. 28 (3), 7–30. 10.1300/J465v28n03_03. [DOI] [PubMed] [Google Scholar]
  7. Bakk Z, Tekle FB, Vermunt JK, 2013. Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociol. Methodol. 43 (1), 272–311. 10.1177/0081175012470644. [DOI] [Google Scholar]
  8. Bandermann KM, Szymanski DM, 2014. Exploring coping mediators between heterosexist oppression and posttraumatic stress symptoms among lesbian, gay, and bisexual persons. Psychol. Sex. Orientat. Gend. Divers. 1 (3), 213–224. 10.1037/sgd0000044. [DOI] [Google Scholar]
  9. Brooks VR, 1981. Minority Stress and Lesbian Women. Lexington Books. [Google Scholar]
  10. Cochran BN, Peavy KM, Robohm JS, 2007. Do specialized services exist for LGBT individuals seeking treatment for substance misuse? A study of available treatment programs. Subst. Use Misuse 42 (1), 161–176. 10.1080/10826080601094207. [DOI] [PubMed] [Google Scholar]
  11. Cascalheira CJ, Helminen EC, Shaw TJ, Scheer JR, 2022. Structural Determinants and Tailored Behavioral Health Services for Sexual and Gender Minorities in the United States, 2010 to 2020. Unpublished manuscript. Submitted for publication. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cochran BN, Peavy KM, Cauce AM, 2007. Substance abuse treatment providers’ explicit and implicit attitudes regarding sexual minorities. J. Homosex. 53 (3), 181–207. 10.1300/J082v53n03_10. [DOI] [PubMed] [Google Scholar]
  13. Conron KJ, Mimiaga MJ, Landers SJ, 2010. A population-based study of sexual orientation identity and gender differences in adult health. Am. J. Public Health 100 (10), 1953–1960. 10.2105/AJPH.2009.174169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Coulter RWS, Kinsky SM, Herrick AL, Stall RD, Bauermeister JA, 2015. Evidence of syndemics and sexuality-related discrimination among young sexual-minority women. LGBT Health 2 (3), 250–257. 10.1089/lgbt.2014.0063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Craig SL, McInroy L, Austin A, Smith M, Engle B, 2012. Promoting self-efficacy and self-esteem for multiethnic sexual minority youth: an evidence-informed intervention. J. Soc. Serv. Res. 38 (5), 688–698. 10.1080/01488376.2012.718194. [DOI] [Google Scholar]
  16. Drabble L, Eliason MJ, 2012. Substance Use Disorders Treatment for Sexual Minority Women. J. LGBT Issues Couns. 6 (4), 274–292. 10.1080/15538605.2012.726150. [DOI] [Google Scholar]
  17. Drabble LA, Trocki KF, Korcha RA, Klinger JL, Veldhuis CB, Hughes TL, 2018. Comparing substance use and mental health outcomes among sexual minority and heterosexual women in probability and non-probability samples. Drug Alcohol Depend. 185, 285–292. 10.1016/j.drugalcdep.2017.12.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Drabble LA, Mericle AA, Karriker-Jaffe KJ, Trocki KF, 2020. Harmful drinking, tobacco, and marijuana use in the 2000–2015 national alcohol surveys: examining differential trends by sexual identity. Subst. Abus. 10.1080/08897077.2019.1709251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Dworkin ER, Jaffe AE, Fitzpatrick S, Rhew IC, Kaysen D, 2021. Daily relationships between posttraumatic stress symptoms, drinking motives, and alcohol consumption in trauma-exposed sexual minority women. Psychol. Addict. Behav. 35 (1), 3–15. 10.1037/adb0000680. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Edwards KM, Sylaska KM, Neal AM, 2015. Intimate partner violence among sexual minority populations: a critical review of the literature and agenda for future research. Psychol. Violence 5 (2), 112–121. 10.1037/a0038656. [DOI] [Google Scholar]
  21. Evans-Polce RJ, Kcomt L, Veliz PT, Boyd CJ, McCabe SE, 2020. Alcohol, tobacco, and comorbid psychiatric disorders and associations with sexual identity and stress-related correlates. Am. J. Psychiatry 177 (11), 1073–1081. 10.1176/appi.ajp.2020.20010005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Everett BG, Hatzenbuehler ML, Hughes TL, 2016. The impact of civil union legislation on minority stress, depression, and hazardous drinking in a diverse sample of sexual-minority women: a quasi-natural experiment. Soc. Sci. Med. (1982) 169, 180–190. 10.1016/j.socscimed.2016.09.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Fletcher JB, Reback CJ, 2015. Depression mediates and moderates effects of methamphetamine use on sexual risk taking among treatment-seeking gay and bisexual men. Health Psychol.: Off. J. Div. Health Psychol., Am. Psychol. Assoc. 34 (8), 865–869. 10.1037/hea0000207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Greene N, Johnson R, Rosen J, German D, Cohen J, 2021. Are binge drinking disparities by sexual identity lower in U.S. states with nondiscrimination statutes that include sexual orientation? J. Health Disparities Res. Pract. 13 (4). https://digitalscholarship.unlv.edu/jhdrp/vol13/iss4/5. [Google Scholar]
  25. Greenfield L, Burgdorf K, Chen X, Porowski A, Roberts T, Herrell J, 2004. Effectiveness of long-term residential substance abuse treatment for women: Findings from three national studies. Am. J. Drug Alcohol Abus. 30 (3), 537–550. 10.1081/ada-200032290. [DOI] [PubMed] [Google Scholar]
  26. Hao J, Beld M, Khoddam-Khorasani L, Flentje A, Kersey E, Mousseau H, Frank J, Leonard A, Kevany S, Dawson-Rose C, 2021. Comparing substance use and mental health among sexual and gender minority and heterosexual cisgender youth experiencing homelessness. PLOS ONE 16 (3), e0248077. 10.1371/journal.pone.0248077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hatzenbuehler ML, McLaughlin KA, Keyes KM, Hasin DS, 2010. The impact of institutional discrimination on psychiatric disorders in lesbian, gay, and bisexual populations: a prospective study. Am. J. Public Health 100 (3), 452–459. 10.2105/AJPH.2009.168815. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hatzenbuehler ML, Flores AR, Gates GJ, 2017. Social attitudes regarding same-sex marriage and LGBT health disparities: Results from a national probability sample. J. Soc. Issues 73 (3), 508–528. 10.1111/josi.12229. [DOI] [Google Scholar]
  29. Helminen EC, Scheer JR, Jackson SD, Brisbin CD, Batchelder AW, Cascalheira CJ, Sullivan TP, 2021. PTSD symptoms and hazardous drinking indicators among trauma-exposed sexual minority women during heightened societal stress. Behav. Med. (Wash., D. C. ) 1–12. 10.1080/08964289.2021.2006132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hughes T, McCabe SE, Wilsnack SC, West BT, Boyd CJ, 2010. Victimization and substance use disorders in a national sample of heterosexual and sexual minority women and men. Addict. (Abingdon, Engl. ) 105 (12), 2130–2140. 10.1111/j.1360-0443.2010.03088.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hughto JMW, Quinn EK, Dunbar MS, Rose AJ, Shireman TI, Jasuja GK, 2021. Prevalence and co-occurrence of alcohol, nicotine, and other substance use disorder diagnoses among us transgender and cisgender adults. e2036512–e2036512 JAMA Netw. Open 4 (2). 10.1001/jamanetworkopen.2020.36512. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Ji C, 2021. 2020 LGBTQ Specific Substance Use Service Survey: A Study on the Availability and Perceived Helpfulness of Treatment Programs. Graduate Student Theses, Dissertations, & Professional Papers. https://scholarworks.umt.edu/etd/11727. [Google Scholar]
  33. Kerridge BT, Pickering RP, Saha TD, Ruan WJ, Chou SP, Zhang H, Jung J, Hasin DS, 2017. Prevalence, sociodemographic correlates and DSM-5 substance use disorders and other psychiatric disorders among sexual minorities in the United States. Drug Alcohol Depend. 170, 82–92. 10.1016/j.drugalcdep.2016.10.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Lanza ST, Rhoades BL, 2013. Latent class analysis: an alternative perspective on subgroup analysis in prevention and treatment. Prev. Sci.: Off. J. Soc. Prev. Res. 14 (2), 157–168. 10.1007/s11121-011-0201-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Lax JR, Phillips JH, 2009. Gay rights in the states: public opinion and policy responsiveness. Am. Political Sci. Rev. 103 (3), 367–386. 10.1017/S0003055409990050. [DOI] [Google Scholar]
  36. Lee JGL, Wimark T, Ortiz KS, Sewell KB, 2018. Health-related regional and neighborhood correlates of sexual minority concentration: a systematic review. PLOS ONE 13 (6), e0198751. 10.1371/journal.pone.0198751. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Logie CH, Lacombe-Duncan A, Weaver J, Navia D, Este D, 2015. A pilot study of a group-based HIV and STI prevention intervention for lesbian, bisexual, queer, and other women who have sex with women in Canada. AIDS Patient Care STDs 29 (6), 321–328. 10.1089/apc.2014.0355. [DOI] [PubMed] [Google Scholar]
  38. Logie CH, Lacombe-Duncan A, Poteat T, Wagner AC, 2017. Syndemic factors mediate the relationship between sexual stigma and depression among sexual minority women and gender minorities. Women’s Health Issues 27 (5), 592–599. 10.1016/j.whi.2017.05.003. [DOI] [PubMed] [Google Scholar]
  39. LoSchiavo C, Acuna N, Halkitis PN, 2021. Evidence for the confluence of cigarette smoking, other substance use, and psychosocial and mental health in a sample of urban sexual minority young adults: the P18 cohort study. Ann. Behav. Med. 55 (4), 308–320. 10.1093/abm/kaaa052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lyons T, Shannon K, Pierre L, Small W, Krüsi A, Kerr T, 2015. A qualitative study of transgender individuals’ experiences in residential addiction treatment settings: stigma and inclusivity. Subst. Abus. Treat., Prev., Policy 10 (1), 17. 10.1186/s13011-015-0015-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Marshal MP, Friedman MS, Stall R, King KM, Miles J, Gold MA, Bukstein OG, Morse JQ, 2008. Sexual orientation and adolescent substance use: a meta-analysis and methodological review*. Addiction 103 (4), 546–556. 10.1111/j.1360-0443.2008.02149.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Martinez O, Lopez N, Woodard T, Rodriguez-Madera S, Icard L, 2019. Transhealth information project: a peer-led HIV prevention intervention to promote HIV protection for individuals of transgender experience. Health Soc. Work 44 (2), 104–112. 10.1093/hsw/hlz008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Meyer IH, 2003. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol. Bull. 129 (5), 674–697. 10.1037/0033-2909.129.5.674. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Nahra TA, Alexander J, Pollack H, 2009. Influence of ownership on access in outpatient substance abuse treatment. J. Subst. Abus. Treat. 36 (4), 355–365. 10.1016/j.jsat.2008.06.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. O’Cleirigh C, Safren SA, Taylor SW, Goshe BM, Bedoya CA, Marquez SM, Boroughs MS, Shipherd JC, 2019. Cognitive behavioral therapy for trauma and self-care (CBT-TSC) in men who have sex with men with a history of childhood sexual abuse: a randomized controlled trial. AIDS Behav. 23 (9), 2421–2431. 10.1007/s10461-019-02482-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Pachankis JE, 2015. A transdiagnostic minority stress treatment approach for gay and bisexual men’s syndemic health conditions. Arch. Sex. Behav. 44 (7), 1843–1860. 10.1007/s10508-015-0480-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Pachankis JE, Hatzenbuehler ML, Rendina HJ, Safren SA, Parsons JT, 2015. LGB-affirmative cognitive-behavioral therapy for young adult gay and bisexual men: a randomized controlled trial of a transdiagnostic minority stress approach. J. Consult. Clin. Psychol. 83 (5), 875–889. 10.1037/ccp0000037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Pachankis JE, McConocha EM, Clark KA, Wang K, Behari K, Fetzner BK, Brisbin CD, Scheer JR, Lehavot K, 2020. A transdiagnostic minority stress intervention for gender diverse sexual minority women’s depression, anxiety, and unhealthy alcohol use: a randomized controlled trial. J. Consult. Clin. Psychol. 88 (7), 613–630. 10.1037/ccp0000508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Pantalone DW, Nelson KM, Batchelder AW, Chiu C, Gunn HA, Horvath KJ, 2020. A systematic review and meta-analysis of combination behavioral interventions co-targeting psychosocial syndemics and HIV-related health behaviors for sexual minority men. J. Sex. Res. 57 (6), 681–708. 10.1080/00224499.2020.1728514. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Parsons JT, Grov C, Golub SA, 2012. Sexual compulsivity, co-occurring psychosocial health problems, and hiv risk among gay and bisexual men: further evidence of a syndemic. Am. J. Public Health 102 (1), 156–162. 10.2105/AJPH.2011.300284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Pollack CE, Armstrong K, 2009. The geographic accessibility of retail clinics for underserved populations.; discussion 950–953 Arch. Intern. Med. 169 (10), 945–949. 10.1001/archinternmed.2009.69. [DOI] [PubMed] [Google Scholar]
  52. Qeadan F, Akofua Mensah N, Gu LY, Barbeau WA, Madden EF, Porucznik CA, English K, 2021. Factors associated with the availability of tailored programs for LGBT clients in substance use disorder treatment facilities in the U.S. from 2008 to 2018. J. Gay Lesbian Soc. Serv. 1–22. 10.1080/10538720.2021.1954125.34140762 [DOI] [Google Scholar]
  53. Roberts AL, Austin SB, Corliss HL, Vandermorris AK, Koenen KC, 2010. Pervasive trauma exposure among US sexual orientation minority adults and risk of posttraumatic stress disorder. Am. J. Public Health 100 (12), 2433–2441. 10.2105/AJPH.2009.168971. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. SAMSHA, 2021. National Survey of Substance Abuse Treatment Services (N-SSATS): 2020. Data on Substance Abuse Treatment Facilities. Substance Abuse and Mental Health Services Administration. [Google Scholar]
  55. Scheer JR, Pachankis JE, 2019. Psychosocial syndemic risks surrounding physical health conditions among sexual and gender minority individuals. LGBT Health 6 (8), 377–385. 10.1089/lgbt.2019.0025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Scheer JR, Pachankis JE, Bränström R, 2020. Gender-based Structural Stigma and Intimate Partner Violence Across 28 Countries: A Population-based Study of Women Across Sexual Orientation, Immigration Status, and Socioeconomic Status, 0886260520976212 J. Interpers. Violence. 10.1177/0886260520976212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Scheer JR, Batchelder AW, Bochicchio LA, Kidd JD, Hughes TL, 2022a. Alcohol use, behavioral and mental health help-seeking, and treatment satisfaction among sexual minority women. Alcohol.: Clin. Exp. Res. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Scheer JR, Clark KA, McConocha E, Wang K, Pachankis JE, 2022b. Toward cognitive-behavioral therapy for sexual minority women: voices from stakeholders and community members. Cogn. Behav. Pract. 10.1016/j.cbpra.2022.02.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Schwinn TM, Thom B, Schinke SP, Hopkins J, 2015. Preventing drug use among sexual-minority youths: findings from a tailored, web-based intervention. J. Adolesc. Health 56 (5), 571–573. 10.1016/j.jadohealth.2014.12.015. [DOI] [PubMed] [Google Scholar]
  60. Singer M, 1994. Aids and the health crisis of the U.S. urban poor; the perspective of critical medical anthropology. Soc. Sci. Med. 39 (7), 931–948. 10.1016/0277-9536(94)90205-4. [DOI] [PubMed] [Google Scholar]
  61. Singer M, Bulled N, Ostrach B, Mendenhall E, 2017. Syndemics and the biosocial conception of health. Lancet 389 (10072), 941–950. 10.1016/S0140-6736(17)30003-X. [DOI] [PubMed] [Google Scholar]
  62. Staiger PK, Liknaitzky P, Lake AJ, Gruenert S, 2020. Longitudinal substance use and biopsychosocial outcomes following therapeutic community treatment for substance dependence. J. Clin. Med. 9 (1), 118. 10.3390/jcm9010118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Teesson M, Mills K, Ross J, Darke S, Williamson A, Havard A, 2008. The impact of treatment on 3 years’ outcome for heroin dependence: Findings from the Australian Treatment Outcome Study (ATOS). Addict. (Abingdon, Engl. ) 103 (1), 80–88. 10.1111/j.1360-0443.2007.02029.x. [DOI] [PubMed] [Google Scholar]
  64. Twenge JM, Blake AB, 2021. Increased support for same-sex marriage in the US: disentangling age, period, and cohort effects. J. Homosex. 68 (11), 1774–1784. 10.1080/00918369.2019.1705672. [DOI] [PubMed] [Google Scholar]
  65. Valentine SE, Elsesser S, Grasso C, Safren SA, Bradford JB, Mereish E, O’Cleirigh C, 2015. The predictive syndemic effect of multiple psychosocial problems on health care costs and utilization among sexual minority women. J. Urban Health 92 (6), 1092–1104. 10.1007/s11524-015-9989-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Vermunt J, & Magidson J (2016). Technical Guide for Latent GOLD 5.1: Basic, Advanced, and Syntax 1. Undefined. https://www.semanticscholar.org/paper/Technical-Guide-for-Latent-GOLD-5.1%3A-Basic%2C-and-1-Vermunt-Magidson/c7ec7772e43c2daf284d1f89902c21799baa9b7d.
  67. Vogel EA, Ramo DE, Meacham MC, Prochaska JJ, Delucchi KL, Humfleet GL, 2020. The Put It Out Project (POP) facebook intervention for young sexual and gender minority smokers: outcomes of a pilot, randomized, controlled trial. Nicotine Tob. Res. 22 (9), 1614–1621. 10.1093/ntr/ntz184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Weller BE, Bowen NK, Faubert SJ, 2020. Latent class analysis: a guide to best practice. J. Black Psychol. 46 (4), 287–311. 10.1177/0095798420930932. [DOI] [Google Scholar]
  69. Wheeler JR, Nahra TA, 2000. Private and public ownership in outpatient substance abuse treatment: do we have a two-tiered system? Adm. Policy Ment. Health 27 (4), 197–209. 10.1023/a:1021357318246. [DOI] [PubMed] [Google Scholar]
  70. Wheeler JR, Fadel H, D’Aunno TA, 1992. Ownership and performance of outpatient substance abuse treatment centers. Am. J. Public Health 82 (5), 711–718. 10.2105/ajph.82.5.711. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Williams ND, Fish JN, 2020. The availability of LGBT-specific mental health and substance abuse treatment in the United States. Health Serv. Res. 55 (6), 932–943. 10.1111/1475-6773.13559. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES