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Importance: Telehealth services expanded rapidly during the COVID-19 public health emergency (PHE). Objective: To evaluate changes in availability of telehealth services at outpatient mental health treatment facilities (MHTFs) throughout the US during and after the COVID-19 PHE. Design, Setting, and Participants: In this cohort study, callers posing as prospective clients contacted a random sample of 1404 MHTFs drawn from the Substance Abuse and Mental Health Services Administration's Behavioral Health Treatment Locator from December 2022 to March 2023 (wave 1 [W1]; during PHE). From September to November 2023 (wave 2 [W2]; after PHE), callers recontacted W1 participants. Analyses were conducted in January 2024. Main Outcomes and Measures: Callers inquired whether MHTFs offered telehealth (yes vs no), and, if yes, whether they offered (1) audio-only telehealth (vs audio and video); (2) telehealth for therapy, medication management, and/or diagnostic services; and (3) telehealth for comorbid alcohol use disorder (AUD). Sustainers (offered telehealth in both waves), late adopters (did not offer telehealth in W1 but did in W2), nonadopters (did not offer telehealth in W1 or W2), and discontinuers (offered telehealth in W1 but not W2) were all compared. Results: During W2, 1001 MHTFs (86.1%) were successfully recontacted. A total of 713 (71.2%) were located in a metropolitan county, 151 (15.1%) were publicly operated, and 935 (93.4%) accepted Medicaid as payment. The percentage offering telehealth declined from 799 (81.6%) to 765 (79.0%) (odds ratio [OR], 0.84; 95% CI, 0.72-1.00; P < .05). Among MHTFs offering telehealth, a smaller percentage in W2 offered audio-only telehealth (369 [49.3%] vs 244 [34.1%]; OR, 0.53; 95% CI, 0.44-0.64; P < .001) and telehealth for comorbid AUD (559 [76.3%] vs 457 [66.5%]; OR, 0.62; 95% CI, 0.50-0.76; P < .001) compared with W1. In W2, MHTFs were more likely to report telehealth was only available under certain conditions for therapy (141 facilities [18.0%] vs 276 [36.4%]; OR, 2.62; 95% CI, 1.10-3.26; P < .001) and medication management (216 facilities [28.0%] vs 304 [41.3%]; OR, 1.81; 95% CI, 1.48-2.21; P < .001). A total of 684 MHTFs (72.0%) constituted sustainers, 94 (9.9%) were discontinuers, 106 (11.2%) were nonadopters, and 66 (7.0%) were late adopters. Compared with sustainers, discontinuers were less likely to be private for-profit (adjusted OR [aOR], 0.28; 95% CI, 0.11-0.68) or private not-for-profit (aOR, 0.26; 95% CI, 0.14-0.48) after adjustment for facility and area characteristics. Conclusions and Relevance: Based on this longitudinal cohort study of 1001 MHTFs, telehealth availability has declined since the PHE end with respect to scope and modality of services, suggesting targeted policies may be necessary to sustain telehealth access.
Subject(s)
COVID-19 , Health Services Accessibility , Mental Health Services , SARS-CoV-2 , Telemedicine , Humans , COVID-19/epidemiology , COVID-19/therapy , Telemedicine/statistics & numerical data , Male , Female , Mental Health Services/organization & administration , Mental Health Services/statistics & numerical data , United States , Health Services Accessibility/statistics & numerical data , Adult , Middle Aged , Mental Disorders/therapy , Mental Disorders/epidemiology , Pandemics , Public Health/methods , Cohort StudiesABSTRACT
This study examined how race/ethnicity, sex/gender, and sexual orientation intersect under interlocking systems of oppression to socially pattern depression among US adults. With cross-sectional data from the 2015-2020 National Survey on Drug Use and Health (NSDUH; n=234,722), we conducted design-weighted multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) under an intersectional framework to predict past-year and lifetime major depressive episode (MDE). With 42 intersectional groups constructed from seven race/ethnicity, two sex/gender, and three sexual orientation categories, we estimated age-standardized prevalence and excess/reduced prevalence attributable to two-way or higher interaction effects. Models revealed heterogeneity across groups, with prevalence ranging from 1.9-19.7% (past-year) and 4.5-36.5% (lifetime). Approximately 12.7% (past-year) and 12.5% (lifetime) of total individual variance were attributable to between-group differences, indicating key relevance of intersectional groups in describing the population distribution of depression. Main effects indicated, on average, people who were White, women, gay/lesbian, or bisexual had greater odds of MDE. Main effects explained most between-group variance. Interaction effects (past-year: 10.1%; lifetime: 16.5%) indicated a further source of heterogeneity around averages with groups experiencing excess/reduced prevalence compared to main effects expectations. We extend the MAIHDA framework to calculate nationally representative estimates from complex sample survey data using design-weighted, Bayesian methods.
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BACKGROUND: Causal mediation analysis plays a crucial role in examining causal effects and causal mechanisms. Yet, limited work has taken into consideration the use of sampling weights in causal mediation analysis. In this study, we compared different strategies of incorporating sampling weights into causal mediation analysis. METHODS: We conducted a simulation study to assess 4 different sampling weighting strategies-1) not using sampling weights, 2) incorporating sampling weights into mediation "cross-world" weights, 3) using sampling weights when estimating the outcome model, and 4) using sampling weights in both stages. We generated 8 simulated population scenarios comprising an exposure (A), an outcome (Y), a mediator (M), and six covariates (C), all of which were binary. The data were generated so that the true model of A given C and the true model of A given M and C were both logit models. We crossed these 8 population scenarios with 4 different sampling methods to obtain 32 total simulation conditions. For each simulation condition, we assessed the performance of 4 sampling weighting strategies when calculating sample-based estimates of the total, direct, and indirect effects. We also applied the four sampling weighting strategies to a case study using data from the National Survey on Drug Use and Health (NSDUH). RESULTS: Using sampling weights in both stages (mediation weight estimation and outcome models) had the lowest bias under most simulation conditions examined. Using sampling weights in only one stage led to greater bias for multiple simulation conditions. DISCUSSION: Using sampling weights in both stages is an effective approach to reduce bias in causal mediation analyses under a variety of conditions regarding the structure of the population data and sampling methods.
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Causality , Mediation Analysis , Humans , Computer Simulation , Sampling Studies , Models, Statistical , Research Design/statistics & numerical data , Data Interpretation, StatisticalABSTRACT
BACKGROUND: We examined the number and characteristics of high-volume buprenorphine prescribers and the nature of their buprenorphine prescribing from 2009 to 2018. METHODS: In this observational cohort study, IQVIA Real World retail pharmacy claims data were used to characterize trends in high-volume buprenorphine prescribers (clinicians with a mean of 30 or more active patients in every month that they were an active prescriber) during 2009-2018. Very high-volume prescribing (mean of 100+ patients per month) was also examined. RESULTS: Overall, 94,491 clinicians prescribed buprenorphine dispensed during 2009-2018. The proportion of active prescribers meeting high-volume criteria increased from 7.4 % in 2009 to 16.7 % in 2018. High-volume prescribers accounted for 80 % of dispensed buprenorphine prescriptions during 2009-2018; very high-volume prescribers accounted for 26 %. Adult primary care physicians consistently comprised the majority of high-volume prescribers. Addiction specialists were much more likely to be high-volume prescribers compared to other specialties, including psychiatrists and pain specialists. By 2018, the proportion of prescriptions from high-volume prescribers paid by Medicaid had doubled to 40 %, accompanied by a decline in both self-pay and commercial insurance. High-volume prescribers were overwhelmingly concentrated in urban counties with the highest fatal overdose rates. In 2018, the highest density of high-volume prescribers was in New England and the mid-Atlantic region. CONCLUSIONS: Growth in high-volume prescribers outpaced the overall growth in buprenorphine prescribers across 2009-2018. High-volume prescribers play an increasingly central role in providing medication for OUD in the U.S., yet results indicate key regional variation in the availability of high-volume buprenorphine prescribers.
Subject(s)
Buprenorphine , Opiate Substitution Treatment , Opioid-Related Disorders , Practice Patterns, Physicians' , Buprenorphine/therapeutic use , Humans , Opioid-Related Disorders/drug therapy , Opioid-Related Disorders/epidemiology , Opiate Substitution Treatment/trends , Practice Patterns, Physicians'/trends , Adult , Male , Female , Middle Aged , United States , Cohort Studies , Drug Prescriptions/statistics & numerical data , Narcotic Antagonists/therapeutic use , Analgesics, Opioid/therapeutic useABSTRACT
Importance: Telehealth utilization for mental health care remains much higher than it was before the COVID-19 pandemic; however, availability may vary across facilities, geographic areas, and by patients' demographic characteristics and mental health conditions. Objective: To quantify availability, wait times, and service features of telehealth for major depressive disorder, general anxiety disorder, and schizophrenia throughout the US, as well as facility-, client-, and county-level characteristics associated with telehealth availability. Design, Settings, and Participants: Cross-sectional analysis of a secret shopper survey of mental health treatment facilities (MHTFs) throughout all US states except Hawaii from December 2022 and March 2023. A nationally representative sample of 1938 facilities were contacted; 1404 (72%) responded and were included. Data analysis was performed from March to July 2023. Exposure: Health facility, client, and county characteristics. Main Outcome and Measures: Clinic-reported availability of telehealth services, availability of telehealth services (behavioral treatment, medication management, and diagnostic services), and number of days until first telehealth appointment. Multivariable logistic and linear regression analyses were conducted to assess whether facility-, client-, and county-level characteristics were associated with each outcome. Results: Of the 1221 facilities (87%) accepting new patients, 980 (80%) reported offering telehealth. Of these, 97% (937 facilities) reported availability of counseling services; 77% (726 facilities), medication management; and 69% (626 facilities) diagnostic services. Telehealth availability did not differ by clinical condition. Private for-profit (adjusted odds ratio [aOR], 1.75; 95% CI, 1.05-2.92) and private not-for-profit (aOR, 2.20; 95% CI, 1.42-3.39) facilities were more likely to offer telehealth than public facilities. Facilities located in metropolitan counties (compared with nonmetropolitan counties) were more likely to offer medication management services (aOR, 1.83; 95% CI, 1.11-3.00) but were less likely to offer diagnostic services (aOR, 0.67; 95% CI, 0.47-0.95). Median (range) wait time for first telehealth appointment was 14 (4-75) days. No differences were observed in availability of an appointment based on the perceived race, ethnicity, or sex of the prospective patient. Conclusions and Relevance: The findings of this cross-sectional study indicate that there were no differences in the availability of mental telehealth services based on the prospective patient's clinical condition, perceived race or ethnicity, or sex; however, differences were found at the facility-, county-, and state-level. These findings suggest widespread disparities in who has access to which telehealth services throughout the US.
Subject(s)
Anxiety Disorders , Depressive Disorder, Major , Telemedicine , Humans , Health Services Accessibility , Cross-Sectional Studies , Pandemics , Depressive Disorder, Major/diagnosis , Depressive Disorder, Major/epidemiology , Depressive Disorder, Major/therapy , Prospective StudiesABSTRACT
BACKGROUND: Depressive symptoms are common in knee osteoarthritis (OA), exacerbate knee pain severity and may influence outcomes of oral analgesic treatments. The aim was to assess whether oral analgesic effectiveness in knee OA varies by fluctuations in depressive symptoms. METHODS: The sample included Osteoarthritis Initiative (OAI) participants not treated with oral analgesics at enrolment (n = 1477), with radiographic disease at the first follow-up visit (defined as the index date). Oral analgesic treatment and depressive symptoms, assessed with the Center for Epidemiological Studies Depression [(CES-D) score ≥16] Scale, were measured over three annual visits. Knee pain severity was measured at visits adjacent to treatment and modifier using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale (rescaled range = 0-100). Structural nested mean models (SNMMs) estimated causal mean differences in knee pain severity comparing treatment versus no treatment. RESULTS: The average causal effects of treated versus not treated for observations without depressive symptoms showed negligible differences in knee pain severity. However, causal mean differences in knee pain severity comparing treatment versus no treatment among observations with depressive symptoms increased over time from -0.10 [95% confidence interval (CI): -9.94, 9.74] to -16.67 (95% CI: -26.33, -7.01). Accordingly, the difference in average causal effects regarding oral analgesic treatment for knee pain severity between person-time with and without depressive symptoms was largest (-16.53; 95% CI: -26.75, -6.31) at the last time point. Cumulative treatment for 2 or 3 years did not yield larger causal mean differences. CONCLUSIONS: Knee OA patients with persistent depressive symptoms and chronic pain may derive more analgesic treatment benefit than those without depressive symptoms and less pain.
Subject(s)
Osteoarthritis, Knee , Humans , Osteoarthritis, Knee/complications , Osteoarthritis, Knee/drug therapy , Depression/drug therapy , Prospective Studies , Disease Progression , Pain/drug therapy , Pain/etiology , Analgesics/therapeutic useABSTRACT
OBJECTIVE: To provide step-by-step guidance and STATA and R code for using propensity score (PS) weighting to estimate moderation effects with categorical variables. RESEARCH DESIGN: Tutorial illustrating the key steps for estimating and testing moderation using observational data. Steps include: (1) examining covariate overlap across treatment groups within levels of the moderator; (2) estimating the PS weights; (3) evaluating whether PS weights improved covariate balance; (4) estimating moderated treatment effects; and (5) assessing the sensitivity of findings to unobserved confounding. Our illustrative case study uses data from 41,832 adults from the 2019 National Survey on Drug Use and Health to examine if gender moderates the association between sexual minority status (eg, lesbian, gay, or bisexual [LGB] identity) and adult smoking prevalence. RESULTS: For our case study, there were no noted concerns about covariate overlap, and we were able to successfully estimate the PS weights within each level of the moderator. Moreover, balance criteria indicated that PS weights successfully achieved covariate balance for both moderator groups. PS-weighted results indicated there was significant evidence of moderation for the case study, and sensitivity analyses demonstrated that results were highly robust for one level of the moderator but not the other. CONCLUSIONS: When conducting moderation analyses, covariate imbalances across levels of the moderator can cause biased estimates. As demonstrated in this tutorial, PS weighting within each level of the moderator can improve the estimated moderation effects by minimizing bias from imbalance within the moderator subgroups.
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Sexual and Gender Minorities , Substance-Related Disorders , Female , Humans , Adult , Propensity Score , Smoking/epidemiology , Tobacco Smoking , Substance-Related Disorders/epidemiologyABSTRACT
BACKGROUND: Policy evaluation studies that assess how state-level policies affect health-related outcomes are foundational to health and social policy research. The relative ability of newer analytic methods to address confounding, a key source of bias in observational studies, has not been closely examined. METHODS: We conducted a simulation study to examine how differing magnitudes of confounding affected the performance of 4 methods used for policy evaluations: (1) the two-way fixed effects difference-in-differences model; (2) a 1-period lagged autoregressive model; (3) augmented synthetic control method; and (4) the doubly robust difference-in-differences approach with multiple time periods from Callaway-Sant'Anna. We simulated our data to have staggered policy adoption and multiple confounding scenarios (i.e., varying the magnitude and nature of confounding relationships). RESULTS: Bias increased for each method: (1) as confounding magnitude increases; (2) when confounding is generated with respect to prior outcome trends (rather than levels), and (3) when confounding associations are nonlinear (rather than linear). The autoregressive model and augmented synthetic control method had notably lower root mean squared error than the two-way fixed effects and Callaway-Sant'Anna approaches for all scenarios; the exception is nonlinear confounding by prior trends, where Callaway-Sant'Anna excels. Coverage rates were unreasonably high for the augmented synthetic control method (e.g., 100%), reflecting large model-based standard errors and wide confidence intervals in practice. CONCLUSIONS: In our simulation study, no single method consistently outperformed the others, but a researcher's toolkit should include all methodologic options. Our simulations and associated R package can help researchers choose the most appropriate approach for their data.
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Public Policy , Humans , Bias , Computer SimulationABSTRACT
Importance: Although telehealth services expanded rapidly during the COVID-19 pandemic, the association between state policies and telehealth availability has been insufficiently characterized. Objective: To investigate the associations between 4 state policies and telehealth availability at outpatient mental health treatment facilities throughout the US. Design, Setting, and Participants: This cohort study measured whether mental health treatment facilities offered telehealth services each quarter from April 2019 through September 2022. The sample comprised facilities with outpatient services that were not part of the US Department of Veterans Affairs system. Four state policies were identified from 4 different sources. Data were analyzed in January 2023. Exposures: For each quarter, implementation of the following policies was indexed by state: (1) payment parity for telehealth services among private insurers; (2) authorization of audio-only telehealth services for Medicaid and Children's Health Insurance Program (CHIP) beneficiaries; (3) participation in the Interstate Medical Licensure Compact (IMLC), permitting psychiatrists to provide telehealth services across state lines; and (4) participation in the Psychology Interjurisdictional Compact (PSYPACT), permitting clinical psychologists to provide telehealth services across state lines. Main Outcome and Measures: The primary outcome was the probability of a mental health treatment facility offering telehealth services in each quarter for each study year (2019-2022). Information on the facilities was obtained from the Mental Health and Addiction Treatment Tracking Repository based on the Substance Abuse and Mental Health Services Administration Behavioral Health Treatment Service Locator. Separate multivariable fixed-effects regression models were used to estimate the difference in the probability of offering telehealth services after vs before policy implementation, adjusting for characteristics of the facility and county in which the facility was located. Results: A total of 12â¯828 mental health treatment facilities were included. Overall, 88.1% of facilities offered telehealth services in September 2022 compared with 39.4% of facilities in April 2019. All 4 policies were associated with increased odds of telehealth availability: payment parity for telehealth services (adjusted odds ratio [AOR], 1.11; 95% CI, 1.03-1.19), reimbursement for audio-only telehealth services (AOR, 1.73; 95% CI, 1.64-1.81), IMLC participation (AOR, 1.40, 95% CI, 1.24-1.59), and PSYPACT participation (AOR, 1.21, 95% CI, 1.12-1.31). Facilities that accepted Medicaid as a form of payment had lower odds of offering telehealth services (AOR, 0.75; 95% CI, 0.65-0.86) over the study period, as did facilities in counties with a higher proportion (>20%) of Black residents (AOR, 0.58; 95% CI, 0.50-0.68). Facilities in rural counties had higher odds of offering telehealth services (AOR, 1.67; 95% CI, 1.48-1.88). Conclusion and Relevance: Results of this study suggest that 4 state policies that were introduced during the COVID-19 pandemic were associated with marked expansion of telehealth availability for mental health care at mental health treatment facilities throughout the US. Despite these policies, telehealth services were less likely to be offered in counties with a greater proportion of Black residents and in facilities that accepted Medicaid and CHIP.
Subject(s)
COVID-19 , Telemedicine , United States/epidemiology , Child , Female , Pregnancy , Humans , COVID-19/epidemiology , Cohort Studies , Mental Health , Pandemics , Ambulatory Care FacilitiesABSTRACT
BACKGROUND: Buprenorphine is a key medication to treat opioid use disorder (OUD). Since its approval in 2002, buprenorphine access has grown markedly, spurred by major federal and state policy changes. This study characterizes buprenorphine treatment episodes during 2007 to 2018 with respect to payer, provider specialty, and patient demographics. METHODS: In this observational cohort study, IQVIA Real World pharmacy claims data were used to characterize trends in buprenorphine treatment episodes across four time periods: 2007-2009, 2010-2012, 2013-2015, and 2016-2018. RESULTS: In total, we identified more than 4.1 million buprenorphine treatment episodes among 2 540 710 unique individuals. The number of episodes doubled from 652 994 in 2007-2009 to 1 331 980 in 2016-2018. Our findings indicate that the payer landscape changed dramatically, with the most pronounced growth observed for Medicaid (increased from 17% of episodes in 2007-2009 to 37% of episodes in 2016-2018), accompanied by relative declines for both commercial insurance (declined from 35 to 21%) and self-pay (declined from 27 to 11%). Adult primary care providers (PCPs) were the dominant prescribers throughout the study period. The number of episodes among adults older than 55 increased more than 3-fold from 2007-2009 to 2016-2018. In contrast, youth under age 18 experienced an absolute decline in buprenorphine treatment episodes. Buprenorphine episodes increased in length from 2007-2018, particularly among adults over age 45. CONCLUSIONS: Our findings demonstrate that the U.S. experienced clear growth in buprenorphine treatment-particularly for older adults and Medicaid beneficiaries-reflecting some key health policy and implementation success stories. Yet, since the prevalence of OUD and fatal overdose rate have also approximately doubled during this period, the observed growth in buprenorphine treatment did not demonstrably impact the pronounced treatment gap. To date, only a minority of individuals with OUD currently receive treatment, indicating continued need for systemic efforts to equitably improve treatment uptake.
Subject(s)
Buprenorphine , Opioid-Related Disorders , Adolescent , United States/epidemiology , Humans , Aged , Middle Aged , Buprenorphine/therapeutic use , Opiate Substitution Treatment/methods , Opioid-Related Disorders/epidemiology , Medicaid , Cohort Studies , Analgesics, Opioid/therapeutic useABSTRACT
Understanding how best to estimate state-level policy effects is important, and several unanswered questions remain, particularly about the ability of statistical models to disentangle the effects of concurrently enacted policies. In practice, many policy evaluation studies do not attempt to control for effects of co-occurring policies, and this issue has not received extensive attention in the methodological literature to date. In this study, we utilized Monte Carlo simulations to assess the impact of co-occurring policies on the performance of commonly-used statistical models in state policy evaluations. Simulation conditions varied effect sizes of the co-occurring policies and length of time between policy enactment dates, among other factors. Outcome data (annual state-specific opioid mortality rate per 100,000) were obtained from 1999 to 2016 National Vital Statistics System (NVSS) Multiple Cause of Death mortality files, thus yielding longitudinal annual state-level data over 18 years from 50 states. When co-occurring policies are ignored (i.e., omitted from the analytic model), our results demonstrated that high relative bias (> 82%) arises, particularly when policies are enacted in rapid succession. Moreover, as expected, controlling for all co-occurring policies will effectively mitigate the threat of confounding bias; however, effect estimates may be relatively imprecise (i.e., larger variance) when policies are enacted in near succession. Our findings highlight several key methodological issues regarding co-occurring policies in the context of opioid-policy research yet also generalize more broadly to evaluation of other state-level policies, such as policies related to firearms or COVID-19, showcasing the need to think critically about co-occurring policies that are likely to influence the outcome when specifying analytic models.
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The Women's Reproductive Health Survey (WRHS) of active-duty service members represents the first time since the 1990s that the U.S. Department of Defense (DoD) has sponsored a department-wide survey of only service women. Maintaining the readiness of the U.S. armed forces requires attention to the health and health care needs of all who serve, including active-duty service women (ADSW). With respect to reproductive health, Congress passed two pieces of legislation in the 2016 and 2017 National Defense Authorization Acts that required DoD to provide ADSW access to comprehensive family planning and counseling services and to do so at predeployment and annual physical exams. The legislation also required DoD to conduct a survey of ADSW's experiences with family planning services and counseling and use and availability of preferred birth control methods. RAND Corporation researchers developed the WRHS to address these two pieces of congressional legislation. The Coast Guard requested that RAND also field the survey among its ADSW. In this study, the authors detail the methodology, sample demographics, and results from the survey (conducted between early August and early November 2020) across a number of domains: health care utilization, birth control and contraceptive use, reproductive health during training and deployment, fertility and pregnancy, and infertility. Differences are examined by service branch, pay grade, age group, race/ethnicity, marital status, and sexual orientation. The results are intended to inform policy initiatives to help support the readiness, health, and well-being of ADSW.
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This study examined how race/ethnicity, sex/gender, and sexual orientation intersect to socially pattern depression among US adults. We used repeated, cross-sectional data from the 2015-2020 National Survey on Drug Use and Health (NSDUH; n=234,772) to conduct design-weighted multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) for two outcomes: past-year and lifetime major depressive episode (MDE). With 42 intersectional groups constructed from seven race/ethnicity, two sex/gender, and three sexual orientation categories, we estimated group-specific prevalence and excess/reduced prevalence attributable to intersectional effects (i.e., two-way or higher interactions between identity variables). Models revealed heterogeneity between intersectional groups, with prevalence estimates ranging from 3.4-31.4% (past-year) and 6.7-47.4% (lifetime). Model main effects indicated that people who were Multiracial, White, women, gay/lesbian, or bisexual had greater odds of MDE. Additive effects of race/ethnicity, sex/gender, and sexual orientation explained most between-group variance; however, approximately 3% (past-year) and 12% (lifetime) were attributable to intersectional effects, with some groups experiencing excess/reduced prevalence. For both outcomes, sexual orientation main effects (42.9-54.0%) explained a greater proportion of between-group variance relative to race/ethnicity (10.0-17.1%) and sex/gender (7.5-7.9%). Notably, we extend MAIHDA to calculate nationally representative estimates to open future opportunities to quantify intersectionality with complex sample survey data.
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Background: Prominent theories suggest that individuals with co-occurring traumatic stress symptoms (TSS) and substance use (SU) may be less responsive to SU treatment compared to those with SU only. However, empirical findings in adult samples are mixed, and there has been limited work among adolescents. This study assesses the association between TSS and SU treatment outcomes among trauma-exposed adolescents, using statistical methods to reduce potential confounding from important factors such as baseline SU severity. Method: 2,963 adolescents with lifetime history of victimization received evidence-based SU treatment in outpatient community settings. At baseline, 3- and 6-months, youth were assessed using the Global Appraisal of Individual Needs Traumatic Stress Scale and the Substance Frequency Scale. Propensity score weighting was used to mitigate potential confounding due to baseline differences in sociodemographic characteristics and SU across youth with varying levels of TSS. Results: Propensity score weighting successfully balanced baseline differences in sociodemographic factors and baseline SU across youth. Among all youth, mean SU was lower at both 3- and 6- month follow-up relative to baseline, indicating declining use. After adjusting for potential confounders, we observed no statistically significant relationship between TSS and SU at either 3- or 6-month follow-up. Conclusions: Based on this investigation, conducted among a large sample of trauma-exposed youth receiving evidence-based outpatient SU treatment, baseline TSS do not appear to be negatively associated with SU treatment outcomes. However, future research should examine whether youth with TSS achieve better outcomes through integrative treatment for both SU and TSS.
The results of this study provide keenly needed evidence that, among youth with prior victimization, presence and level of traumatic stress symptoms at substance use treatment initiation does not lead to significantly worse treatment outcomes for youth in outpatient treatment. This suggests that evidence-based outpatient substance use treatment modalities may be effective at improving substance use outcomes even when co-existing traumatic stress symptoms are present.
Subject(s)
Stress Disorders, Post-Traumatic , Substance-Related Disorders , Adult , Humans , Adolescent , Substance-Related Disorders/therapy , Substance-Related Disorders/diagnosis , Outpatients , Treatment Outcome , Stress Disorders, Post-Traumatic/therapyABSTRACT
INTRODUCTION: Tobacco use among gay, lesbian, and bisexual individuals is disproportionately higher than among heterosexual individuals. Identifying the mechanisms behind these differences can inform prevention and cessation efforts aimed at advancing health equity. Internalizing and externalizing symptoms as mediators of tobacco (re)uptake among sexual minority individuals was examined. METHODS: Waves 4 and 5 of the Population Assessment of Tobacco and Health (2016-2019) study were analyzed in 2022. Adolescents aged ≥14 and adults years not using tobacco at Wave 4 (n=21,676) were included. Wave 4 sexual identity was categorized as heterosexual, gay/lesbian, bisexual, or something else. Associations of sexual identity with (re)uptake of cigarette use, E-cigarette use, and polytobacco use at Wave 5 were assessed, along with possible mediation of these associations by Wave 4âinternalizing and âexternalizing symptoms. RESULTS: Internalizing and externalizing symptoms predicted tobacco (re)uptake regardless of sexual identity, particularly for female individuals. Gay/lesbian females (AOR=2.26; 95% CI=1.14, 4.48) and bisexual females (AOR=1.36; 95% CI=1.06, 1.74) had greater odds of E-cigarette (re)uptake than heterosexual females. High internalizing and externalizing symptoms accounted for over one third of the difference in E-cigarette (re)uptake among bisexual compared with that among heterosexual females. Males who reported sexual identity as something-else had lower odds of cigarette (re)uptake than heterosexual males (AOR=0.19; 95% CI=0.06, 0.66); this association was not mediated by internalizing and externalizing symptoms. CONCLUSIONS: Internalizing and externalizing symptoms uniquely contribute to E-cigarette (re)uptake among bisexual females. Strategies that reduce sexual minority stressors and resulting psychological distress may help to reduce tobacco use disparities.
Subject(s)
Electronic Nicotine Delivery Systems , Homosexuality, Female , Sexual and Gender Minorities , Adult , Male , Adolescent , Humans , Female , Nicotiana , Bisexuality , Sexual BehaviorABSTRACT
OBJECTIVE: This study estimated mental health service use among lesbian, gay, and bisexual (LGB) adults in the United States who reported having made a suicide attempt. METHODS: Data came from the pooled 2015-2019 National Surveys on Drug Use and Health. Of the 191,954 adult respondents, 1,946 reported a past-year suicide attempt. Survey-weighted descriptive and regression analyses were conducted to compare mental health service use among LGB and heterosexual adults. RESULTS: Three percent of LGB adults (N=598) reported having attempted suicide in the past year, compared with 0.5% of heterosexual adults (N=1,348). Mental health treatment use was significantly higher among LGB adults than among heterosexual adults (64% versus 56%) before analyses were adjusted for sociodemographic characteristics. CONCLUSIONS: Because suicide attempts and mental health use are elevated among LGB adults, clinicians must provide evidence-based approaches for identifying and managing suicide risk to LGB adults in an affirming manner.
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Homosexuality, Female , Mental Health Services , Sexual and Gender Minorities , Female , Adult , Humans , United States/epidemiology , Suicide, Attempted , Homosexuality, Female/psychology , Bisexuality/psychologyABSTRACT
Purpose: The study objective was to compare use of 12 specific inhalants among lesbian, gay, and bisexual (LGB) adults relative to heterosexual adults among a national sample. Methods: Data on 210,392 adults, including 15,007 LGB adults, were from the 2015 to 2019 National Survey on Drug Use and Health. For each inhalant type, logistic regression was used to characterize differences by sexual identity and gender. Unadjusted and demographic adjusted odds ratios are reported. Results: All LGB groups exhibited elevated use of multiple inhalant types (ranging from 5 for gay males to 12 for bisexual females). The largest disparities were for poppers among gay and bisexual males. Gay and bisexual males initiated use at older ages. Conclusion: Observed disparities among LGB adults included inhalants used in a sexual or club context (e.g., poppers) as well as types with particularly elevated fatality risk (e.g., butane, propane, aerosol sprays, and nitrous oxide).
Subject(s)
Homosexuality, Female , Sexual and Gender Minorities , Male , Female , Adult , Humans , Bisexuality , Homosexuality, Male , Sexual BehaviorABSTRACT
INTRODUCTION: Lower perceived risk is a well-established risk factor for initiating substance use behaviors and an integral component of many health behavior theories. Established literature has shown that many substance use behaviors are more prevalent among individuals who identify as lesbian, gay, or bisexual than among those who identify as heterosexual. However, potential differences in perceived risk by sexual identity among individuals with no lifetime use have not been well characterized to date. METHODS: Data on 111,785 adults aged 18-34 years (including 11,377 lesbian, gay, and bisexual adults) were from the 2015-2019 National Survey on Drug Use and Health. Perceived risks (classified as great risk versus less than great risk) were assessed with 11 National Survey on Drug Use and Health survey items regarding 6 different substances (alcohol, cigarettes, marijuana, cocaine, lysergic acid diethylamide, and heroin). Survey-weighted and sex-stratified logistic regression models were used to estimate sexual identity differences regarding perceived great risk among those reporting no lifetime use. Analyses were conducted in 2021-2022. RESULTS: Gay men, bisexual men, lesbian/gay women, and bisexual women were all significantly less likely than heterosexual peers to perceive great risk associated with specific marijuana, cocaine, lysergic acid diethylamide, and heroin use behaviors. Bisexual men and women were also significantly less likely than heterosexual peers to perceive great risk associated with binge drinking behaviors and smoking ≥1 packs of cigarettes daily. CONCLUSIONS: This novel investigation among never users provides evidence that lesbian, gay, and bisexual adults perceive significantly lower risks associated with multiple substance use behaviors than heterosexual adults, which may indicate important sexual identity differences in susceptibility to substance use initiation.
Subject(s)
Cocaine , Sexual and Gender Minorities , Substance-Related Disorders , Humans , Young Adult , Male , Female , Heroin , Lysergic Acid Diethylamide , Bisexuality , Substance-Related Disorders/epidemiology , Heterosexuality , Sexual BehaviorABSTRACT
Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.