Sexual Orientation, Social Determinants of Health, and Unmet Substance Use Treatment Need: Findings from a National Survey

Social complexity of a fentanyl vaccine to prevent opioid overdose conference proceedings: Radcliffe Institute for Advanced Study conference proceedings

Despite significant public health attention and investment, hundreds of thousands of individuals have suffered fatal opioid overdose since the onset of the opioid crisis. Risk of opioid overdose has been exacerbated by the influx of fentanyl, a powerful synthetic opioid, into the drug supply. The National Institutes of Health Helping End Addiction Long-term (HEAL) Initiative is supporting the development of vaccines targeting fentanyl to protect against overdose. If successful, a vaccine would induce anti-fentanyl antibodies to sequester fentanyl (but not other opioids) in the blood, preventing fentanyl from crossing into the brain and reaching the central nervous system where it can cause overdose. Introduction of an overdose preventing strategy that relies on a vaccine to confer passive protection may be impactful. However, vaccines are poorly understood by the public and politicized. Moreover, the overdose ecosystem is complex and extends across numerous social, economic, medical, and cultural systems. As such, optimal use of a vaccine strategy to address overdose may benefit from multidisciplinary consideration of the social, ethical, and systemic factors that influence substance use and overdose that may also impact the acceptability of a fentanyl vaccine and related implementation strategies. In March 2022, Dr. Elissa Weitzman convened a two-day conference at the Harvard Radcliffe Institute for Advanced Study on the Social Complexity of a Fentanyl Vaccine to Prevent Opioid Overdose. In all, 19 professionals from diverse disciplines (medicine, psychology, history, ethics, immunology, vaccinology, communications, policy) attended the conference and led discussions that centered on population health and epidemiology, history of medicine and frameworks for understanding substance use, ethics, decision-making and attitudes, and operational issues to the question of a novel immunotherapy targeting fentanyl overdose. Participants also debated the risks and benefits of vaccine administration in response to fictional clinical case vignettes. A summary of the conference presentations and discussions follows.

LGBTQIA+ vs the Brazilian Unified Health System: Basic Health Unit Use and Associated Factors

The Brazilian Unified Health System provides universal health care access without regard to sexual orientation and gender identity. We conducted a nationwide study with a cross-sectional design and intentional sampling methods to investigate factors associated with Basic Health Unit (BHU) use by the LGBTQIA+ community. Data were collected via a questionnaire available through social networks. Statistical analysis included Poisson regression with robust variance. A total of 603 LGBTQIA+ community members participated in the study, of whom 417 (69.2%) had visited a BHU in the last year. The factors "transgender woman" and "self-rated health status as very good/good/fair" increased the probability of BHU use in the last year by 10% (PR: 1.10; 95% CI: 1.00-1.20) and 9% (PR = 1.09; 95% CI: 1.01-1.18), respectively. "Not suffering sexual orientation-related discrimination at a BHU" and "Not suffering discrimination by a receptionist or waiting room worker" increased the probability of use by 28% (PR = 1.28; 95% CI: 1.22-1.34) and 22% (PR = 1.22; 95% CI: 1.14-1.30), respectively. Our study supports evidence that access to primary health care services in Brazil can be influenced by the social determinants gender identity and sexual discrimination.

Risk factors of substance use treatment gaps among a nationally representative sample of black American adults in relation to sexual minority status and health insurance coverage

BACKGROUND

Little research has investigated predictors of specialty substance use treatment gaps among Black adults. This study examined differential odds of experiencing self-reported, past-year treatment gaps among Black adults with respect to sexual minority status and health insurance coverage, accounting for social cofactors.

METHOD

This cross-sectional study comprised 36,098 Black Americans aged 18 and older who completed the 2015-2019 National Survey on Drug Use and Health (NSDUH) and provided responses for all selected survey items. Design-based multivariable logistic regression models were used to examine predictors of drug and alcohol treatment gaps.

RESULTS

Sexual minority Black adults reported greater odds of experiencing treatment gaps to specialty treatment (i.e., inpatient hospital, inpatient/outpatient rehabilitation facility, or mental health center) compared to Black heterosexuals in adjusted models (Gay or lesbian: AOR = 2.01, 95% CI = 1.39-2.89; Bisexual: AOR = 2.35, 95% CI = 1.77-3.12), with bisexual Black women experiencing the greatest odds (AOR = 3.10, 95% CI = 2.33-4.14). Black adults with no health insurance were significantly more likely to report substance use treatment gaps relative to their peers with health insurance coverage (AOR = 50, 95% CI = 1.26-1.78).

CONCLUSION

The results suggest a critical need for more investigations into patterns of specialty substance use treatment gaps within Black populations and for developing sexual identity-affirming mechanisms for closing the disparity gap, particularly for Black sexual minorities and those who lack health insurance coverage.

Treating Depression in Adolescents and Young Adults Using Remote Intensive Outpatient Programs: Quality Improvement Assessment

BACKGROUND

Youth and young adults face barriers to mental health care, including a shortage of programs that accept youth and a lack of developmentally sensitive programming among those that do. This shortage, along with the associated geographically limited options, has contributed to the health disparities experienced by youth in general and by those with higher acuity mental health needs in particular. Although intensive outpatient programs can be an effective option for youth with more complex mental health needs, place-based intensive outpatient programming locations are still limited to clients who have the ability to travel to the clinical setting several days per week.

OBJECTIVE

The objective of the analysis reported here was to assess changes in depression between intake and discharge among youth and young adults diagnosed with depression attending remote intensive outpatient programming treatment. Analysis of outcomes and the application of findings to programmatic decisions are regular parts of ongoing quality improvement efforts of the program whose results are reported here.

METHODS

Outcomes data are collected for all clients at intake and discharge. The Patient Health Questionnaire (PHQ) adapted for adolescents is used to measure depression, with changes between intake and discharge regularly assessed for quality improvement purposes using repeated measures t tests. Changes in clinical symptoms are assessed using McNamar chi-square analyses. One-way ANOVA is used to test for differences among age, gender, and sexual orientation groups. For this analysis, 1062 cases were selected using criteria that included a diagnosis of depression and a minimum of 18 hours of treatment over a minimum of 2 weeks of care.

RESULTS

Clients ranged in age from 11 to 25 years, with an average of 16 years. Almost one-quarter (23%) identified as nongender binary and 60% identified as members of the lesbian, gay, bisexual, transgender, queer (LGBTQ+) community. Significant decreases (mean difference -6.06) were seen in depression between intake and discharge (t₉₆₇=-24.68; P<.001), with the symptoms of a significant number of clients (P<.001) crossing below the clinical cutoff for major depressive disorder between intake and discharge (388/732, 53%). No significant differences were found across subgroups defined by age (F_2,958=0.47; P=.63), gender identity (F_7,886=1.20; P=.30), or sexual orientation (F_7,872=0.47; P=.86).

CONCLUSIONS

Findings support the use of remote intensive outpatient programming to treat depression among youth and young adults, suggesting that it may be a modality that is an effective alternative to place-based mental health treatment. Additionally, findings suggest that the remote intensive outpatient program model may be an effective treatment approach for youth from marginalized groups defined by gender and sexual orientation. This is important given that youth from these groups tend to have poorer outcomes and greater barriers to treatment compared to cisgender, heterosexual youth.

Demand prediction of medical services in home and community-based services for older adults in China using machine learning

Background

Home and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services.

Methods

This was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model.

Results

Random Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education.

Conclusion

Andersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.

Alcohol use and treatment utilization in a national sample of veterans and nonveterans

BACKGROUND

Research comparing prevalence of alcohol use problems and alcohol treatment utilization between veterans and nonveterans is lacking. Whether predictors of alcohol use problems and alcohol treatment utilization differ in veterans vs. nonveterans is also unclear.

METHODS

Using survey data from national samples of post-9/11 veterans and nonveterans (N = 17,298; 13,451 veterans, 3847 nonveterans), we investigated associations between veteran status and 1) alcohol consumption, 2) need for intensive alcohol treatment, and 3) past-year and lifetime alcohol treatment utilization. We also investigated associations between predictors and these three outcomes in separate models for veterans and nonveterans. Predictors included age, gender, racial/ethnic identity, sexual orientation, marital status, education, health coverage, financial difficulty, social support, adverse childhood experiences (ACEs), and adult sexual trauma.

RESULTS

Population weighted regression models demonstrated that veterans reported modestly higher alcohol consumption than nonveterans, but were not significantly more likely to need intensive alcohol treatment. Veterans and nonveterans did not differ in past-year alcohol treatment utilization, but veterans were 2.8 times more likely to utilize lifetime treatment than nonveterans. We found several differences between veterans and nonveterans in associations between predictors and outcomes. For veterans, being male, having higher financial difficulty, and lower social support were associated with need for intensive treatment, but for nonveterans, only ACEs were associated with need for intensive treatment.

CONCLUSIONS

Veterans may benefit from interventions with social and financial support to reduce alcohol problems. These findings can help to identify veterans and nonveterans who are more likely to need treatment.

Barriers in care pathways and unmet mental health needs in LGBTIQ + communities

Lesbian, gay, bisexual, transgender, intersex, queer people and minority gender identities and sexualities (LGBTIQ+) are often stigmatized and experience discrimination in health care settings, leading to poorer mental health outcomes and unmet needs compared to heterosexual and cisgendered peers. It is thus imperative that mental health providers consider and address structural challenges in order to reduce mental health inequalities of this population. This narrative review assessed the barriers that may prevent access to care and the pathways for care in LGBTIQ + communities. PubMed, PsycInfo, Embase, and Scopus were searched for papers published between December 2021 and February 2022. A total of 107 papers were included with studies reflecting five themes: (1) Unmet mental health needs; (2) Young people; (3) Substance abuse and addiction; (4) Barriers and pathways to care; and (5) Interventions. Findings demonstrate that LGBTIQ + people experience stigmatization and higher rates of substance misuse and mental ill health, which may lead to barriers in accessing health care services, and fewer tailored interventions being provided. These findings have implications for policy, health care screening, and how specialist services are structured. Substantial gaps in the evidence-base exist, and future research should examine how mental health care providers can challenge social issues that maintain discriminatory and stigmatizing practices, and support LGBTIQ + individuals to sustain their resilience.

Unmet Need in Relation to Mental Healthcare and Past-Month Drug Use among People with Mental Illness in the United States

Individuals with mental illness are at risk of developing co-occurring substance use disorders (SUDs). We assessed whether unmet need for mental health treatment in the past year was a risk factor for past-month use of marijuana, cocaine, methamphetamine, and misuse of prescription opioids in this population. Data from adults diagnosed with mental illness who were not diagnosed with SUD were examined from the 2015-2018 National Survey on Drug Use and Health (N = 33,104). An estimated 20.8% (95% CI: 20.1-21.5) of adults in the US with mental illness have experienced unmet need in the past year. Those reporting marijuana use (29.7% vs. 19.5%, p < .001) and/or prescription opioid misuse (35.7% vs. 20.5%, p < .001) were more likely to report unmet need than those not reporting use. In multivariable models, unmet need remained a risk factor for marijuana use (aOR = 1.37, 95% CI: 1.24-1.54) and prescription opioid misuse (aOR = 1.65, 95% CI: 1.29-2.13). Unmet need was not a risk factor for cocaine or methamphetamine use. Cost as a barrier to treatment was a risk factor for marijuana use (aOR = 1.37, 95% CI: 1.19-1.58) and prescription opioid misuse (aOR = 1.95, 95% CI: 1.43-2.64). Policies aimed at improving mental healthcare access may be effective in reducing substance use in this population.