Barriers to Mental Health Care Identified by Sexual and Gender Minority Individuals in Georgia and South Carolina.

OBJECTIVE: Geographic location can affect access to appropriate, affirming mental health care for sexual and gender minority (SGM) individuals, especially for those living in rural settings. Minimal research has examined barriers to mental health care for SGM communities in the southeastern United States. The objective of this study was to identify and characterize perceived barriers to obtaining mental health care for SGM individuals living in an underserved geographic area. METHODS: Drawing from a health needs survey of SGM communities in Georgia and South Carolina, 62 participants provided qualitative responses describing barriers they encountered to accessing mental health care when needed in the previous year. Four coders used a grounded theory approach to identify themes and summarize the data. RESULTS: Three themes of barriers to care emerged: personal resource barriers, personal intrinsic factors, and healthcare system barriers. Participants described barriers that can inhibit access to mental health care regardless of one's sexual orientation or gender identity, such as finances or lack of knowledge about services, but several of the identified barriers intersect with SGM-related stigma or may be magnified by participants' location in an underserved region of the southeastern United States. CONCLUSIONS: SGM individuals living in Georgia and South Carolina endorsed several barriers to receiving mental health services. Personal resource and intrinsic barriers were the most common, but healthcare system barriers were present as well. Some participants described simultaneously encountering multiple barriers, illustrating that these factors can interact in complex ways to affect SGM individuals' mental health help seeking.

High-risk polysubstance use among LGBTQ+ people who use drugs in the United States: An application of syndemic theory.

BACKGROUND: Compared to heterosexual and cisgender people, lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority (LGBTQ+) people are more likely to develop problems with high-risk polysubstance use. According to syndemic theory, this disparity in high-risk polysubstance use is produced by the LGBTQ+ community's increased vulnerability to experiencing psychosocial (e.g., discrimination, unwanted sex) and structural (e.g., food insecurity, homelessness) conditions, greater likelihood of coping with concurrent health problems (e.g., human immunodeficiency virus [HIV]), and decreased opportunities to develop protective factors (e.g., social support, resilience). METHODS: Data from 306 LGBTQ+ participants living in the United States (U.S.) with a lifetime history of alcohol and drug use were analyzed; 21.2% reported lifetime problems with 10 different drugs. Bootstrapped hierarchical multiple regression was used to test demographic correlates and syndemic predictors of high-risk polysubstance use. One-way ANOVA and post-hoc comparison tests were used to test subgroup differences by gender. RESULTS: Results indicated that income, food insecurity, sexual orientation-based discrimination, and social support were associated with high-risk polysubstance use, explaining 43.9% of the variance of high-risk polysubstance use. Age, race, unwanted sex, gender identity-based discrimination, and resilience were not significant. Group comparison tests revealed that, compared to nonbinary people and cisgender sexual minority men and women, transgender individuals experienced significantly higher levels of high-risk polysubstance use and sexual orientation-based discrimination but significantly lower levels of homelessness and social support. CONCLUSION: This study provided further evidence for conceptualizing polysubstance use as an adverse outcome of syndemic conditions. Harm reduction strategies, anti-discrimination laws, and gender-affirming residential treatment options should be considered in U.S. drug policy. Clinical implications include targeting syndemic conditions to reduce high-risk polysubstance use among LGBTQ+ people who use drugs.

Correction: Desires for Individual- and Interpersonal-Level Patient Portal Use for HIV Prevention Among Urban Sexual Minority Men: Cross-sectional Study.

[This corrects the article DOI: 10.2196/43550.].

Desires for Individual- and Interpersonal-Level Patient Portal Use for HIV Prevention Among Urban Sexual Minority Men: Cross-sectional Study.

BACKGROUND: Gay, bisexual, and other sexual minority men have expressed the acceptability of patient portals as tools for supporting HIV prevention behaviors, including facilitating disclosure of HIV and other sexually transmitted infection (STI/HIV) laboratory test results to sex partners. However, these studies, in which Black or African American sexual minority men were undersampled, failed to determine the relationship of reported history of discussing HIV results with sex partners and anticipated willingness to disclose web-based STI/HIV test results using a patient portal. OBJECTIVE: Among a sample of predominantly Black sexual minority men, this study aimed to (1) determine preferences for patient portal use for HIV prevention and (2) test the associations between reported history of discussing HIV results and anticipated willingness to disclose web-based STI/HIV test results with most recent main and nonmain partners using patient portals. METHODS: Data come from audio-computer self-assisted interview survey data collected during the 3-month visit of a longitudinal cohort study. Univariate analysis assessed patient portal preferences by measuring the valuation rankings of several portal features. Multiple Poisson regression models with robust error variance determined the associations between history of discussing HIV results and willingness to disclose those results using web-based portals by partner type, and to examine criterion validity of the enhancing dyadic communication (EDC) scale to anticipated willingness. RESULTS: Of the 245 participants, 71% (n=174) were Black and 22% (n=53) were White. Most participants indicated a willingness to share web-based STI/HIV test results with their most recent main partner. Slightly fewer, nonetheless a majority, indicated a willingness to share web-based test results with their most recent nonmain partner. All but 2 patient portal features were valued as high or moderately high priority by >80% of participants. Specifically, tools to help manage HIV (n=183, 75%) and information about pre- and postexposure prophylaxis (both 71%, n=173 and n=175, respectively) were the top-valuated features to include in patient portals for HIV prevention. Discussing HIV test results was significantly associated with increased prevalence of willingness to disclose web-based test results with main (adjusted prevalence ratio [aPR] 1.46, 95% CI 1.21-1.75) and nonmain partners (aPR 1.54, 95% CI 1.23-1.93). CONCLUSIONS: Our findings indicate what features Black sexual minority men envision may be included in the patient portal's design to optimize HIV prevention, further supporting the criterion validity of the EDC scale. Efforts should be made to support Black sexual minority men's willingness to disclose STI/HIV testing history and status with partners overall as it is associated significantly with a willingness to disclose testing results digitally via patient portals. Future studies should consider discussion behaviors regarding past HIV test results with partners when tailoring interventions that leverage patient portals in disclosure events.

Models of Gender Dysphoria Using Social Media Data for Use in Technology-Delivered Interventions: Machine Learning and Natural Language Processing Validation Study.

BACKGROUND: The optimal treatment for gender dysphoria is medical intervention, but many transgender and nonbinary people face significant treatment barriers when seeking help for gender dysphoria. When untreated, gender dysphoria is associated with depression, anxiety, suicidality, and substance misuse. Technology-delivered interventions for transgender and nonbinary people can be used discretely, safely, and flexibly, thereby reducing treatment barriers and increasing access to psychological interventions to manage distress that accompanies gender dysphoria. Technology-delivered interventions are beginning to incorporate machine learning (ML) and natural language processing (NLP) to automate intervention components and tailor intervention content. A critical step in using ML and NLP in technology-delivered interventions is demonstrating how accurately these methods model clinical constructs. OBJECTIVE: This study aimed to determine the preliminary effectiveness of modeling gender dysphoria with ML and NLP, using transgender and nonbinary people's social media data. METHODS: Overall, 6 ML models and 949 NLP-generated independent variables were used to model gender dysphoria from the text data of 1573 Reddit (Reddit Inc) posts created on transgender- and nonbinary-specific web-based forums. After developing a codebook grounded in clinical science, a research team of clinicians and students experienced in working with transgender and nonbinary clients used qualitative content analysis to determine whether gender dysphoria was present in each Reddit post (ie, the dependent variable). NLP (eg, n-grams, Linguistic Inquiry and Word Count, word embedding, sentiment, and transfer learning) was used to transform the linguistic content of each post into predictors for ML algorithms. A k-fold cross-validation was performed. Hyperparameters were tuned with random search. Feature selection was performed to demonstrate the relative importance of each NLP-generated independent variable in predicting gender dysphoria. Misclassified posts were analyzed to improve future modeling of gender dysphoria. RESULTS: Results indicated that a supervised ML algorithm (ie, optimized extreme gradient boosting [XGBoost]) modeled gender dysphoria with a high degree of accuracy (0.84), precision (0.83), and speed (1.23 seconds). Of the NLP-generated independent variables, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) clinical keywords (eg, dysphoria and disorder) were most predictive of gender dysphoria. Misclassifications of gender dysphoria were common in posts that expressed uncertainty, featured a stressful experience unrelated to gender dysphoria, were incorrectly coded, expressed insufficient linguistic markers of gender dysphoria, described past experiences of gender dysphoria, showed evidence of identity exploration, expressed aspects of human sexuality unrelated to gender dysphoria, described socially based gender dysphoria, expressed strong affective or cognitive reactions unrelated to gender dysphoria, or discussed body image. CONCLUSIONS: Findings suggest that ML- and NLP-based models of gender dysphoria have significant potential to be integrated into technology-delivered interventions. The results contribute to the growing evidence on the importance of incorporating ML and NLP designs in clinical science, especially when studying marginalized populations.

Matching Variables With the Appropriate Statistical Tests in Counseling Research.

Quantitative research literacy, including matching variables with the appropriate statistical tests, is a key element in counselor education and preparation. Counselor educators are tasked with teaching quantitative research and statistics, which counselors-in-training tend to find anxiety-producing. Authors aimed to provide a succinct overview of matching variables with appropriate statistical tests and provide strategies counselor educators can use to enhance their pedagogy.