Can Education Compensate for Poor Healthcare? Racial Inequalities in Psychedelic-Associated Psychological Distress

Can Education Compensate for Poor Healthcare? 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Racial Inequalities in Psychedelic-Associated Psychological Distress Sean Vina This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8483640/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract While prior research suggests that healthcare context shapes the mental health correlates of psychedelic use, it remains unclear whether education can mitigate these disparities—particularly across racial and ethnic groups. This study examines whether educational attainment moderates the association between lifetime psychedelic use, health insurance context (public vs. private), and psychological distress, and whether these patterns vary by race/ethnicity. Using nationally representative data from the National Survey on Drug Use and Health (2008–2018; N = 484,732), we estimate ordinary least squares regression models stratified by racial and ethnic group. Results indicate that higher education is associated with lower psychological distress among psychedelic users primarily when paired with private insurance, a pattern observed most consistently among White respondents. In contrast, among individuals relying on public insurance, educational attainment offers little protection against elevated distress. A notable exception emerges among Native Hawaiian and Pacific Islander respondents, for whom higher education is associated with reduced distress despite public insurance coverage. Taken together, these findings suggest that education alone is insufficient to offset structurally patterned inequalities in healthcare and that the mental health correlates of psychedelic use remain contingent on institutional context. Medicine race ethnicity psychedelics inequality distress Introduction Although ample research finds psychedelic use is associated with improved mental and psychological health, including lower psychological distress, depression, and suicidality (Hendricks et al., 2015; Johansen & Krebs, 2015; Johnson et al., 2019; G. M. Jones & Nock, 2022; Pisano et al., 2017; Sexton et al., 2019; Zeifman et al., 2021), recent evidence suggests that healthcare inequality can substantially shape the magnitude and durability of these mental health benefits (Viña, 2025g). In line with the Medical Sociological and Social Epidemiological Psychedelics Paradigm (MSSEPP), which conceptualizes psychedelic outcomes as jointly produced by pharmacological effects and structurally distributed social conditions, associations observed between psychedelic use and mental health outcomes should be expected to vary across institutional contexts such as healthcare systems (Viña, 2025f) Specifically, prior research shows that the association between psychedelic use and reduced psychological distress is stronger among individuals with private healthcare, while those relying on public insurance programs—including Medicaid, Medicare, and TRICARE—not only experience diminished benefit but often report higher levels of psychological distress, identifying a particularly vulnerable and underserved population (Viña, 2025g). These differences likely reflect systemic weaknesses in public care systems, including limited provider networks, long wait times, regional disparities in service delivery, and fragmented care (Draper, 2013; Gleason & Beck, 2017; Gliner & Chukwura, 2023; MACPAC, 2017; Tynkkynen & Vrangbæk, 2018). The structure and quality of care itself may therefore act as a critical moderator of psychedelic outcomes. As psychedelic policy shifts toward broader medicalization, decriminalization, and therapeutic access (Nutt & Carhart-Harris, 2021; Williams et al., 2023), it becomes increasingly important to understand how disparities in mental health outcomes may be reproduced or attenuated under expanding access. If access to high-quality mental healthcare conditions the psychological benefits associated with psychedelic use, one potential avenue for mitigation is education. Educational attainment has long been linked to better mental health outcomes through multiple pathways, including improved ability to navigate healthcare systems, communicate effectively with providers, and advocate for appropriate mental health care (Hernandez et al., 2018; Verdonk et al., 2009). Education also improves the quality of doctor–patient interactions, often resulting in more personalized and attentive care, especially when providers perceive patients as more informed and proactive (Dyrbye et al., 2022; Kenny et al., 2010). Separately, education enhances psychological resources—such as self-efficacy, optimism, and a sense of mastery—that buffer stress and reduce psychological distress (Pearlin et al., 2007; Wheaton, 2010). These psychological resources may, in turn, complement the self-reflective, openness-inducing, and meaning-making properties of psychedelic experiences (Maclean et al., 2011; Wheaton, 2010). In theory, these advantages could allow individuals with higher education to better manage structural limitations in public care, making education a potential pathway to more equitable outcomes even in under-resourced healthcare contexts. However, education may not offer equal protection for all groups. A substantial body of research demonstrates that racial and ethnic minorities often experience diminished health returns from educational attainment due to systemic racism embedded in both healthcare institutions and broader social structures (Assari, 2020; Viña, 2024d). Compared to their White counterparts, highly educated Black, Hispanic, Asian, Indigenous, and Pacific Islander individuals are more likely to report negative experiences with healthcare providers, including being dismissed, rushed, or receiving lower-quality care (Burrage et al., 2022; Gone, 2023; Phelan & Link, 2015; Tran et al., 2010). Within MSSEPP, these patterns reflect a broader expectation that structural and cultural conditions shape not only who can access high-quality care, but also whether individual resources (like education) can be translated into improved health outcomes (Viña, 2025f). The theory of Minorities’ Diminished Psychedelic Returns (MDPR) extends this inequality logic to psychedelics, arguing that stratified environments reduce the effectiveness of psychedelics by disrupting both access to supportive care and the social conditions required for sustained healing (Altman & Magnus, 2024; Viña, 2025b, 2025e, 2025c; Viña & Stephens, 2023a). It remains unclear, then, whether education can compensate for healthcare inequality in psychedelic outcomes—or whether its effects are stratified by race and structural context. This study examines whether education moderates the relationship between psychedelic use, healthcare access, and psychological distress, and whether this moderating effect varies by race and ethnicity. Using nationally representative data from the National Survey on Drug Use and Health (NSDUH) collected between 2008 and 2019, the analytic sample includes 484,732 adults aged 18 and older. Ordinary least squares (OLS) regression models are used to test whether educational attainment interacts with healthcare type (public vs. private) to shape mental health outcomes among individuals who report psychedelic use. Models are stratified by racial and ethnic group to assess how structural inequality conditions these associations. Building on prior research that established the importance of healthcare access in shaping psychedelic outcomes (Viña, 2025g), this is the first large-scale study to test whether education can offset these disparities—and whether it does so equally across racial lines. Data and Methods This study used cross-sectional data from the National Survey of Drug Use and Health (NSDUH) from 2008 to 2019 (N= 484,732 ). The NSDUH is an annual, nationally representative survey of substance use and mental health in the U.S., with weights applied to reflect the civilian noninstitutionalized population. Table 1 provides descriptive statistics for all dependent, independent, and control variables, derived from publicly available data. Public-use data files are accessible through the NSDUH homepage (https://www.samhsa.gov/data/data-we-collect/nsduh-national-survey-drug-use-and-health/datafiles/2002-2019). The NSDUH survey protocol was reviewed and approved by the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Institutional Review Board, and informed consent was obtained from all participants at the time of data collection. The present study relies exclusively on secondary, de-identified, publicly available NSDUH data and does not involve any direct interaction with human subjects. As such, this analysis was reviewed by the author’s Institutional Review Board (IRB) and determined to be exempt from further ethical review, consistent with federal guidelines governing secondary data analysis. Study Replication This study builds directly on prior research examining stratified relationships between psychedelic use and health outcomes using data from the National Survey on Drug Use and Health (NSDUH) (Viña, 2024b, 2024d). It incorporates previously published and peer-reviewed variable constructions and modeling strategies, selected for conceptual and methodological consistency with earlier work rather than novel revalidation. This approach ensures comparability across studies while extending the analytic framework to evaluate whether educational attainment moderates healthcare-based disparities in psychedelic-related mental health outcomes. Dependent Variable Respondents completed the Kessler Psychological Distress Scale (K6) (Kessler et al., 2010) to assess their level of distress over the previous month. This instrument measures six feelings or experiences, such as feeling nervous, hopeless, restless, deeply depressed, perceiving everything as an effort, and feeling worthless. The respondents rated each item on a 5-point Likert scale. The scores on these measures were then summed to create a variable representing psychological distress in the past month, ranging from 0 to 24, with higher scores indicating higher levels of distress. The Kessler scale is a widely used and highly reliable measure for assessing psychological distress in individuals with panic disorder, generalized anxiety disorder, bipolar disorder, and schizophrenia (Umucu et al., 2022). Independent variables First, race/ethnicity is a categorical variables with seven categories: Racial/ethnic identity is based on self-reported responses and includes the following categories: White (reference group), Black or African American, Hispanic or Latino, Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and individuals identifying as two or more races.[1] These classifications follow federal guidelines established by the Office of Management and Budget for collecting race and ethnicity data. Next, educational attainment includes four categories and is treated as continuous: (1) less than high School Degree, (2) High School degree, (3) Some College, and (4) College degree or higher.[2] Next, respondents were asked to indicate whether they had health insurance. Those who had health insurance could then select from five variables to indicate their types of coverage: private health insurance, Medicare, Medicaid, Tricare, and other healthcare. While private care remained a binary variable, this study used a similar methodology to a previous study, and combined Medicare, Medicaid, and Tricare into a single variable called Public insurance (yes vs no) (Viña, 2025g). The "other" insurance category was included as a control variable in the regression analysis. To assess psychedelic use, respondents were asked whether they had ever used any of the following substances, even once: MDMA, N,N-dimethyltryptamine (DMT), psilocybin, lysergic acid diethylamide (LSD), and mescaline, as well as ayahuasca and peyote as they are listed in the NSDUH instrument. Because ayahuasca and peyote are plant-based preparations rather than single molecules, they are included here as survey categories that typically contain psychedelic compounds—most commonly DMT in ayahuasca (along with β-carbolines that allow oral activity) and mescaline in peyote. To maintain consistency with prior research, the classic psychedelic items measured in NSDUH—DMT, psilocybin, LSD, mescaline, and the plant-based preparations ayahuasca and peyote—were grouped into a measure of Lifetime Classic Psychedelic Use (LCPU), as these exposures are generally considered to have low physiological risk and are associated with neurogenesis and positive mental health outcomes (dos Santos et al., 2018; Ly et al., 2018). MDMA was analyzed separately, as it functions primarily by increasing serotonin levels and has shown promise in both clinical trials and population-based studies of mental health (Brewerton et al., 2022; G. M. Jones & Nock, 2022). To enhance cultural and methodological sensitivity, the study followed previous recommendations to analyze each psychedelic substance individually (Viña, 2024d), and peyote and mescaline were grouped due to their shared botanical and ritual origins (P. N. Jones, 2007). This approach also reflects the understanding that the social and symbolic meanings associated with psychedelics may vary by group and context (Fotiou, 2019; Omágua-Kambeba et al., 2023). Socioeconomic, Demographic, and Drug Use Control Variables Sociodemographic control variables include gender, age, marital status, annual household income, educational attainment, religious attendance, religious salience, year of the survey, age of first alcohol use, self-reported risky behavior, and lifetime use of various substances. Substance use controls include lifetime use of cocaine, marijuana, phencyclidine (PCP), inhalants, other stimulants, sedatives, pain relievers, and tobacco products (e.g., smokeless tobacco, pipe tobacco, cigars, and daily cigarette use), which have been shown to correlate with health behaviors and distress (Altman & Magnus, 2024; Viña & Stephens, 2023a). Annual household income is measured using categorical brackets, ranging from less than $10,000 to $75,000 or more, and education is grouped into four levels: less than high school, high school graduate, some college, and college degree or more. Risk tolerance is measured using a thrill-seeking scale derived from two items asking whether respondents enjoy “dangerous” and “risky” activities (Cronbach’s α = 0.85). [Table 1 Here] Analytic Strategy Categorial and Continuous Variable Treatment While age, income, and education are originally collected as categorical variables, they are modeled as continuous in this study. Likelihood ratio tests (LRTs) confirmed that treating these variables continuously does not lead to significant differences in model fit. This approach follows established guidance prioritizing model simplicity and interpretability in large-scale survey analysis (Long & Mustillo, 2018). Accordingly, both descriptive and multivariate analyses incorporate these covariates in continuous form where applicable. Mean and Proportion Data Verification As an initial step to examine subgroup differences and assess the data structure prior to multivariate modeling, weighted means and proportions were calculated for all continuous and categorical variables, stratified by race/ethnicity and healthcare status (e.g., private vs. public insurance; White vs. non-White; Black vs. non-Black). Table 2 presents a condensed summary of key sociodemographic patterns, while the full set of mean and proportion differences is reported in Supplemental Tables 1–4. Post-estimation linear combination (LINCOM) tests were used to determine whether differences in group means or proportions were statistically significant (Long & Mustillo, 2018). For each comparison, differences were computed as the value of the reference group (e.g., those without private insurance or those not White) minus the value of the comparison group (e.g., those with private insurance or those who are White). This descriptive stage served as a foundational check for heterogeneity in psychological distress, insurance coverage, substance use, religiosity, and socioeconomic characteristics prior to estimating fully adjusted models. Regression Analysis The analysis employed a series of weighted ordinary least squares (OLS) regression models to estimate mainline and interaction associations between psychedelic use, health insurance status, and psychological distress. Full model results are reported in Supplemental Tables 5–21; Table 3 presents a condensed set of focal coefficients to facilitate comparison and conserve space. Supplemental Tables 5–7 report the mainline models. Model 1 estimated the association between MDMA and lifetime classic psychedelic use (LCPU) and psychological distress. Model 2 added health insurance indicators. Model 3 expanded the specification to include all six psychedelic measures, and Model 4 further incorporated health insurance variables. Supplemental Tables 8–21 report interaction models. The next set of models estimated two-way interactions between each psychedelic measure and health insurance status, followed by three-way interactions between education, health insurance, and each psychedelic measure. These interaction specifications were estimated separately for private and public health insurance (see Supplemental Tables 8–9). To examine racial and ethnic differences, the study adopted an intersectional modeling strategy that compares substantively meaningful social positions by estimating separate race- and ethnicity-specific models (Long & Mustillo, 2018). These models are reported as follows: White respondents (Supplemental Tables 10–11), Black respondents (12–13), Hispanic respondents (14–15), Asian respondents (16–17), Native Hawaiian or Other Pacific Islander respondents (18–19), and Native American/Alaska Native respondents (20–21). Table 3 summarizes selected mainline, two-way, and three-way interaction coefficients drawn from these models, while full coefficient vectors, standard errors, model fit statistics, and covariates are available in the corresponding supplemental tables. Statistical differences in coefficients across race-specific models were assessed using post-estimation seemingly unrelated estimation (SUEST) procedures, which allow for formal comparison of parameters estimated on the same or overlapping samples (Oberfichtner & Tauchmann, 2021). Multiple Comparisons and Weighting Adjustments All analyses accounted for the NSDUH’s complex sampling design by applying the appropriate person-level weights, which were adjusted using scalar factors to estimate national population parameters across pooled survey years. These weights were incorporated into all models using STATA 18, ensuring nationally representative estimates and accurate variance calculation. Given the number of subgroup comparisons and interaction effects tested, this study also addresses concerns about inflated Type I error due to multiple comparisons. Specifically, the Benjamini-Hochberg False Discovery Rate (BH-FDR) procedure was applied to control the expected proportion of false positives while maintaining statistical power (Armstrong, 2014). Compared to more conservative alternatives like Bonferroni correction, BH-FDR is widely recommended in epidemiological and social science research for balancing rigor and interpretability (Li & Barber, 2019; Storey, 2002). Although earlier NSDUH-based psychedelic studies did not typically apply multiple testing corrections (Viña & Stephens, 2023b, 2023a), this study adopts a more cautious approach. The significance threshold was set at 0.05, and sensitivity checks confirmed the robustness of findings under this adjustment strategy [1] The "two or more races" category is included as a control variable (not the focus of subgroup analysis) and accounts for respondents who selected more than one racial group. [2] A sensitivity analysis was run to test the variable as both a continuous and categorical variable. Because substantive results provided the same conclusions, the variable left as a continuous variable for ease of interpretation. Results As shown in Table 2, individuals with private health insurance exhibit higher levels of educational attainment and lower psychological distress, whereas those with public insurance show lower educational attainment and higher levels of distress (all p < .001). Racial and ethnic differences further reveal that White and Asian respondents, relative to comparison groups, are more likely to have higher education, private insurance coverage, lower reliance on public insurance, and lower distress (all p < .001). In contrast, Black, Hispanic, Native Hawaiian or Other Pacific Islander (NHOPI), and Native Indian/Alaska Native (NI/AN) respondents display the opposite pattern, characterized by lower education, reduced access to private insurance, greater reliance on public insurance, and higher psychological distress (all p < .001). Patterns of lifetime psychedelic use also vary by race/ethnicity: while White respondents are generally more likely to report lifetime psychedelic use (with the exception of ayahuasca), Black, Hispanic, Asian, and NHOPI respondents are less likely to report any psychedelic use (all p < .001). NI/AN respondents, however, are more likely than all other groups to report lifetime use of ayahuasca, peyote/mescaline, and classic psychedelics overall (all p < .001). Complete descriptive results for all variables are provided in Supplemental Tables 1–4. Total Population Among the total population, mainline associations indicate that having private health insurance is associated with lower psychological distress (b = −0.989, p < .001), whereas having public health insurance is associated with higher distress (b = 0.170, p < .01). Two-way interaction results show that the negative association between private insurance and distress is stronger among individuals who reported lifetime classic psychedelic use (LCPU; b = −0.348, p < .01). In the substance-specific models, this same pattern is also observed for psilocybin (b = −0.281, p < .05) and LSD (b = −0.302, p < .05). In contrast, the positive association between public insurance and distress is amplified among those who reported use of LCPU (b = 0.931, p < .001), MDMA (b = 0.601, p < .001), psilocybin (b = 0.922, p < .001), peyote/mescaline (b = 0.712, p < .05), and LSD (b = 0.789, p < .001). Three-way interactions further indicate that the negative association between private insurance and distress becomes stronger at higher levels of education among individuals who reported use of LCPU (b = −0.302, p < .05), MDMA (b = −0.240, p < .05), psilocybin (b = −0.302, p < .05), ayahuasca (b = −5.892, p < .05), and LSD (b = −0.302, p < .05). In contrast, higher education intensified the positive association between public insurance and distress only among those who reported MDMA use (b = 0.538, p < .05). White People Among White respondents, private health insurance is associated with lower psychological distress (b = −1.166, p < .001), while no mainline association is observed for public insurance. Two-way interaction results indicate that psychedelic use does not condition the association between private insurance and distress for White respondents. However, the positive association between public insurance and distress is stronger among those who reported use of LCPU (b = 1.081, p < .001), MDMA (b = 0.888, p < .001), psilocybin (b = 1.061, p < .001), ayahuasca (b = 5.620, p < .05), peyote/mescaline (b = 0.756, p < .05), and LSD (b = 0.884, p < .001). Three-way interactions show that higher education strengthens the negative association between private insurance and distress among White respondents who reported use of LCPU (b = −0.357, p < .05), MDMA (b = −0.446, p < .05), psilocybin (b = −0.328, p < .05), peyote/mescaline (b = −0.528, p < .05), and LSD (b = −0.358, p < .05). In addition, higher education amplifies the positive association between public insurance and distress among those who reported MDMA use (b = 0.516, p < .05). Black People Among Black respondents, private health insurance is associated with lower psychological distress (b = −0.884, p < .001), while public health insurance is associated with higher distress (b = 0.319, p < .05). No significant two-way interactions are observed between psychedelic use and private insurance. No significant three-way interactions involving education are observed among Black respondents. Hispanics. Among Hispanic respondents, private health insurance is not significantly associated with psychological distress, whereas public insurance is associated with higher distress (b = 0.638, p < .001). Two-way interactions indicate that the association between private insurance and distress is substantially more negative among Hispanics who reported ayahuasca use (b = −20.10, p < .001). No significant two-way interactions are observed between psychedelic use and public insurance. Three-way interaction results show that higher education attenuates the positive association between public insurance and distress among Hispanics who reported DMT use (b = −4.666, p < .05). No three-way interactions are observed for private insurance. Asians Among Asian respondents, private health insurance is associated with lower psychological distress (b = −1.125, p < .001), while no mainline association is observed for public insurance. Two-way interactions indicate that the negative association between private insurance and distress is weaker among Asian respondents who reported DMT use (b = 5.651, p < .05) and peyote/mescaline use (b = 2.736, p < .05). No significant three-way interactions involving education are observed among Asian respondents. Native Hawaiian or Pacific Islander Among NHOPI respondents, no mainline associations are observed between psychological distress and either private or public insurance. Two-way interactions show that peyote/mescaline use strengthens the association between private insurance and distress (b = 8.887, p < .01) and also moderates the association between public insurance and distress (b = 6.509, p < .05). Three-way interactions indicate that, among those with private insurance, higher education is associated with higher distress among NHOPI respondents who reported use of LCPU (b = 4.819, p < .01), psilocybin (b = 4.390, p < .05), peyote/mescaline (b = 6.178, p < .05), and LSD (b = 3.718, p < .05). Conversely, higher education attenuates the association between public insurance and distress among those who reported use of LCPU (b = −4.816, p < .05), psilocybin (b = −6.390, p < .01), peyote/mescaline (b = −6.460, p < .05), and LSD (b = −3.700, p < .05). Native Indian or Alaskan Native Among NI/AN respondents, no mainline associations are observed between psychological distress and either private or public insurance. Two-way interaction results indicate that the association between private insurance and distress is stronger among NI/AN respondents who reported peyote/mescaline use (b = −2.534, p < .05). Three-way interactions further show that higher education is associated with lower distress among NI/AN respondents with private insurance who reported MDMA use (b = −4.250, p < .001), but higher distress among those who reported peyote/mescaline use (b = −2.092, p < .05). Discussion This study examined the relationship between psychedelics, healthcare insurance coverage, education, distress, and race/ethnicity. MSSEPP suggests that psychedelic outcomes are not produced by pharmacology alone, but by the intersection of drug effects with institutional arrangements (such as healthcare systems) and stratified social conditions that shape exposure, interpretation, risk, and capacity to benefit (Viña, 2025f). Importantly, the NSDUH measures lifetime psychedelic use in the general population, so the results primarily reflect naturalistic use rather than psychedelic administration or prescription within clinical care. Previous research has suggested that psychedelics may be impacted by structural inequalities associated with different insurance contexts and healthcare systems. This study specifically investigated whether educational attainment could influence these relationships and if the patterns were consistent across different racial and ethnic groups. The findings contribute to the growing body of literature indicating that psychedelics may not provide significant benefits for marginalized communities in population-based research (Argento et al., 2018; Hendricks et al., 2014; G. M. Jones, 2023; Viña, 2024c, 2024d, 2024e, 2024b, 2024a, 2025a; Viña & Stephens, 2023a). There were instances where a complementary relationship between psychedelics and private insurance coverage was observed, suggesting that individuals using psychedelics may be better positioned to realize lower distress in contexts associated with private coverage. However, this positive relationship was predominantly experienced by White individuals. In contrast, there were few instances where education mitigated the positive association between public insurance coverage and psychological distress, allowing psychedelic users to show a weaker linkage between public coverage and distress. Moreover, race and ethnic minorities appeared to derive less benefit from psychedelics overall. The study showed that those using public insurance coverage gained even fewer benefits. Additionally, the results indicated that within the total population relying on public insurance coverage, psychedelic use (including MDMA and several classic psychedelic exposures, such as psilocybin, LSD, and peyote/mescaline) was associated with higher levels of distress. While the findings do not imply that people are using psychedelics to cope with the distress caused by public insurance coverage, the pattern is consistent with selection into overlapping vulnerabilities—i.e., a subgroup with elevated distress that is also more likely to rely on public coverage and to report psychedelic use in their lifetime. Given that marginalized racial and ethnic populations are more likely to rely on public insurance coverage (Hahn et al., 2018), the overall literature suggests a shrinking population that will gain significant benefits from psychedelics. This highlights the need for addressing structural inequalities in healthcare to ensure broader access to the potential benefits of psychedelics, particularly as psychedelic interventions become more embedded in formal treatment systems and insurance-linked pathways. Results related to education provide several important implications. First, the pervasiveness of poor healthcare in contexts tied to public insurance coverage is so extensive that education did not seem to counter its effects. While there may be hope that increased education and subsequent medical knowledge can help people better manage the healthcare system, the results suggest that education may only benefit those with private insurance coverage. These individuals already have higher socioeconomic status (SES), less distress, and are navigating a healthcare system that is generally more accommodating than publicly insured contexts. Contrary to the hypothesis, there were instances where higher education was associated with better mental health profiles (lower distress) among psychedelic users in private coverage contexts. This pattern was found among White individuals who had used MDMA and Native Hawaiians and Other Pacific Islanders (NHOPI) who had used LCPU, psilocybin, peyote/mescaline, and LSD. Considering the evidence that both private coverage and psychedelic use are associated with less distress, these findings may capture a complementary relationship. Specifically, the data may be capturing highly educated people who are distressed but have enough medical/health knowledge to seek out alternative health coping strategies, including psychedelics. Overall, these results are consistent with MSSEPP’s expectation that individual resources (like education) translate into benefit primarily when institutional conditions are supportive—meaning education’s “protective” capacity is conditional on the healthcare environment (Viña, 2025f) and that the conversion of education into health gains is itself socially patterned. Accordingly, these findings should be interpreted as associations consistent with structurally patterned resource conversion, rather than as definitive evidence of mechanism. However, there were noteworthy instances in which higher education did seem to benefit NHOPI on public insurance coverage who used psychedelics, likely explained by structure. While NHOPI are interspersed around the continental United States, about 50% of the population lives within the state of Hawai’I (America Counts Staff, 2021). As the only state with universal healthcare, Hawai’i’s healthcare system is second in in Health Care Quality, third among the Public Health, and first in overall healthcare, has produced one of the highest expectancies (Radley et al., 2023). In short, NHOPI may be using a better public healthcare system while insured through public coverage than other average Americans, and those who have used psychedelics and have higher education are simply better able to access it (Carlton et al., 2006; Lim et al., 2019; Prizzia & Mokuah, 1991; Viña, 2025d). In MSSEPP terms, this pattern is precisely what institutional heterogeneity would predict: where public systems are better resourced and more navigable, education may function as a lever that helps individuals translate psychedelic use into improved mental health outcomes. Importantly, this interpretation aligns with my recent NHOPI-focused study, which finds that psychedelic use among NHOPI is associated with increased odds of engaging formal mental health care—suggesting that, in this population, psychedelics may operate in ways that are complementary to (rather than substitutive of) treatment-seeking within more trusted or supportive care contexts (Viña, 2025d). While there are many reasons to decriminalize psychedelics for personal and health purposes, including those related to racial justice (Williams et al., 2023), these results suggest a more pressing issue: the structural inequality within the healthcare system itself. In these cross-sectional data, the mental health correlates of psychedelic use appear to differ systematically by insurance context, with public coverage consistently marking higher distress and weaker or adverse associations for several psychedelic exposures. Importantly, the results also indicate that increasing individual education alone is insufficient in countering the negative consequences of these poor systems; a structural fix is necessary. The overall findings underscore the pervasive impact of systemic racism in medicine and health inequality. Racism in healthcare remains a significantly toxic factor that likely counters the positive effects of psychedelics on mental health for these groups. From the standpoint of MSSEPP, MDPR can be understood as a specific inequality-focused extension: it identifies how structurally patterned disadvantage limits the conditions under which psychedelics can function as a health resource (Viña, 2025f; Viña & Stephens, 2023a). The results related to NHOPI who likely use a public healthcare system that is among the best in the nation further emphasize the need to fix public systems that serve publicly insured populations across the board. Therefore, rather than focusing on increasing education to help people better utilize healthcare including psychedelics, policy should instead focus on systemic changes in healthcare that reduce institutional barriers and improve access, continuity, and quality of mental health care—especially for publicly insured groups—so that the potential benefits of psychedelic use and emerging psychedelic therapies are less likely to be stratified by insurance status. Limitations and Future Directions This study offers valuable insights into the associations between psychedelics, healthcare, education, and race/ethnicity. However, it is important to recognize the study's limitations. The analysis did not account for key factors such as personality traits, peak experiences, and dosage. From an MSSEPP perspective, these omissions matter because psychedelic outcomes are shaped by both individual-level processes and the social conditions in which use occurs, including culturally and structurally patterned set-and-setting. Additionally, there may be other unmeasured variables influencing these relationships. This study cannot establish causality; thus, future research should use longitudinal data to better understand these associations and consider the timing of psychedelic use. Furthermore, while the study draws on extensive research regarding inequality and healthcare disparities, it does not explore specific experiences within the medical field. For example, are Native Hawaiians and Other Pacific Islanders actually more satisfied with their public care than other marginalized groups? Future research should aim to investigate these specific contexts to provide a more comprehensive understanding, including mixed-methods work that can directly observe mechanisms (e.g., patient–provider interactions, care continuity, barriers to referrals) that may underlie the observed quantitative patterns. Despite its limitations, this study offers valuable insights into the relationship between psychedelics and health. While more detailed study designs (including longitudinal studies and clinical research) are needed to clarify causal pathways and specify mechanisms, the present findings remain consistent with the broader literature on structural inequality in medicine and highlight how institutional stratification may shape who is positioned to benefit from psychedelics. Declarations Acknowledgements: Not Applicable. Funding Statement: This research received no funding. Conflict Of Interest: The authors declare no conflict of interest in preparing this article. Data Availability Statement: The National Survey of Drug Use and Health (NSDUH) is public-use data and is available on their homepage: https://www.datafiles.samhsa.gov/dataset/nsduh-2002-2019-ds0001-nsduh-2002-2019-ds0001. References Altman, B., & Magnus, M. (2024). Association between lifetime hallucinogen use and psychological distress varies by sexual identity in a nationally representative sample. Journal of Psychopharmacology , 38 (10), 861–872. https://doi.org/10.1177/02698811241278774 America Counts Staff. (2021, August 25). HAWAII: 2020 Census . United States Census Bureau. https://www.census.gov/library/stories/state-by-state/hawaii-population-change-between-census-decade.html Argento, E., Braschel, M., Walsh, Z., Socias, M. E., & Shannon, K. (2018). The moderating effect of psychedelics on the prospective relationship between prescription opioid use and suicide risk among marginalized women. Journal of Psychopharmacology , 32 (12), 1385–1391. https://doi.org/10.1177/0269881118798610 Armstrong, R. A. (2014). When to use the Bonferroni correction. Ophthalmic and Physiological Optics , 34 (5), 502–508. https://doi.org/10.1111/opo.12131 Assari, S. (2020). Blacks’ Diminished Health Returns of Educational Attainment: Health and Retirement Study. Journal of Medical Research and Innovation , 4 (1), 1–11. Brewerton, T. D., Wang, J. B., Lafrance, A., Pamplin, C., Mithoefer, M., Yazar-Klosinki, B., Emerson, A., & Doblin, R. (2022). MDMA-assisted therapy significantly reduces eating disorder symptoms in a randomized placebo-controlled trial of adults with severe PTSD. Journal of Psychiatric Research , 149 , 128–135. https://doi.org/10.1016/j.jpsychires.2022.03.008 Burrage, R. L., Antone, M. M., Kaniaupio, K. N. M., & Rapozo, K. L. (2022). A culturally informed scoping review of Native Hawaiian mental health and emotional well-being literature. In C. E. Mckinley, M. S. Spencer, K. Walters, & C. R. Figley (Eds.), Indigenous Health Equity and Wellness (1st ed.). Routledge. Carlton, B. S., Goebert, D. A., Miyamoto, R. H., Andrade, N. N., Hishinuma, E. S., Makini, G. K., Yuen, N. Y. C., Bell, C. K., McCubbin, L. D., Else, ’Iwalani R.N., & Nishimura, S. T. (2006). Resilience, Family Adversity and Well-Being Among Hawaiian and Non-Hawaiian Adolescents. International Journal of Social Psychiatry , 52 (4), 291–308. https://doi.org/10.1177/0020764006065136 dos Santos, R. G., Bouso, J. C., Alcázar-Córcoles, M. Á., & Hallak, J. E. C. (2018). Efficacy, tolerability, and safety of serotonergic psychedelics for the management of mood, anxiety, and substance-use disorders: a systematic review of systematic reviews. In Expert Review of Clinical Pharmacology (Vol. 11, Issue 9, pp. 889–902). Taylor and Francis Ltd. https://doi.org/10.1080/17512433.2018.1511424 Draper, D. A. (2013). Defense Health Care: Multiyear Surveys Indicate Problems with Access to Care for Nonenrolled Beneficiaries . Dyrbye, L. N., West, C. P., Sinsky, C. A., Trockel, M., Tutty, M., Satele, D., Carlasare, L., & Shanafelt, T. (2022). Physicians’ Experiences With Mistreatment and Discrimination by Patients, Families, and Visitors and Association With Burnout. JAMA Network Open , 5 (5), e2213080. https://doi.org/10.1001/jamanetworkopen.2022.13080 Fotiou, E. (2019). The role of Indigenous knowledges in psychedelic science. Journal of Psychedelic Studies , 4 (1), 16–23. https://doi.org/10.1556/2054.2019.031 Gleason, J. L., & Beck, K. H. (2017). Examining Associations Between Relocation, Continuity of Care, and Patient Satisfaction in Military Spouses. Military Medicine , 182 (5), e1657–e1664. https://doi.org/10.7205/MILMED-D-16-00191 Gliner, M. D., & Chukwura, C. (2023). Evaluation of the TRICARE Program: Fiscal Year 2023 Report to Congress Access, Cost, and Quality Data through Fiscal Year 2022 . www.af.mil, Gone, J. P. (2023). Community Mental Health Services for American Indians and Alaska Natives: Reconciling Evidence-Based Practice and Alter-Native Psy-ence. Annual Review of Clinical Psychology Annu. Rev. Clin. Psychol. 2023 , 19 , 23–49. https://doi.org/10.1146/annurev-clinpsy-080921 Hahn, R. A., Truman, B. I., & Williams, D. R. (2018). Civil rights as determinants of public health and racial and ethnic health equity: Health care, education, employment, and housing in the United States. SSM - Population Health , 4 , 17–24. https://doi.org/10.1016/j.ssmph.2017.10.006 Hendricks, P. S., Clark, C. B., Johnson, M. W., Fontaine, K. R., & Cropsey, K. L. (2014). Hallucinogen use predicts reduced recidivism among substance-involved offenders under community corrections supervision. Journal of Psychopharmacology , 28 (1), 62–66. https://doi.org/10.1177/0269881113513851 Hendricks, P. S., Thorne, C. B., Clark, C. B., Coombs, D. W., & Johnson, M. W. (2015). Classic Psychedelic Use is Associated with Reduced Psychological Distress and Suicidality in the United States Adult Population. Journal of Psychopharmacology , 29 (3), 280–288. https://doi.org/10.1177/0269881114565653 Hernandez, E. M., Margolis, R., & Hummer, R. A. (2018). Educational and Gender Differences in Health Behavior Changes After a Gateway Diagnosis. Journal of Aging and Health , 30 (3), 342–364. https://doi.org/10.1177/0898264316678756 Johansen, P.-Ø., & Krebs, T. S. (2015). Psychedelics not linked to mental health problems or suicidal behavior: A population study. Journal of Psychopharmacology , 29 (3), 270–279. https://doi.org/10.1177/0269881114568039 Johnson, M. W., Hendricks, P. S., Barrett, F. S., & Griffiths, R. R. (2019). Classic psychedelics: An integrative review of epidemiology, therapeutics, mystical experience, and brain network function. Pharmacology & Therapeutics , 197 , 83–102. https://doi.org/10.1016/j.pharmthera.2018.11.010 Jones, G. M. (2023). Race and ethnicity moderate the associations between lifetime psychedelic use (MDMA/ecstasy and psilocybin) and major depressive episodes. Journal of Psychopharmacology , 37 (1), 61–69. https://doi.org/10.1177/02698811221127304 Jones, G. M., & Nock, M. K. (2022). MDMA/ecstasy use and psilocybin use are associated with lowered odds of psychological distress and suicidal thoughts in a sample of US adults. Journal of Psychopharmacology , 36 (1), 46–56. https://doi.org/10.1177/02698811211058923 Jones, P. N. (2007). The Native American Church, Peyote, and Health: Expanding Consciousness for Healing Purposes. Contemporary Justice Review , 10 (4), 411–425. Kenny, D. A., Veldhuijzen, W., Weijden, T. van der, LeBlanc, A., Lockyer, J., Légaré, F., & Campbell, C. (2010). Interpersonal perception in the context of doctor-patient relationships: A dyadic analysis of doctor-patient communication. Social Science & Medicine , 70 (5), 763–768. https://doi.org/10.1016/j.socscimed.2009.10.065 Kessler, R. C., Green, J. G., Gruber, M. J., Sampson, N. A., Bromet, E., Cuitan, M., Furukawa, T. A., Oye, G., Hinkov, H., Hu, C. Y., Lara, C., Lee, S., Mneimneh, Z., Myer, L., Oakley-Browne, M., Posada-Villa, J., Sagar, R., Viana, M. C., & Zaslavsky, A. M. (2010). Screening for serious mental illness in the general population with the K6 screening scale: Results from the WHO World Mental Health (WMH) survey initiative. International Journal of Methods in Psychiatric Research , 19 (SUPPL. 1), 4–22. https://doi.org/10.1002/mpr.310 Li, A., & Barber, R. F. (2019). Multiple Testing with the Structure-Adaptive Benjamini–Hochberg Algorithm. Journal of the Royal Statistical Society Series B: Statistical Methodology , 81 (1), 45–74. https://doi.org/10.1111/rssb.12298 Lim, E., Gandhi, K., Siriwardhana, C., Davis, J., & Chen, J. J. (2019). Racial and ethnic differences in mental health service utilization among the Hawaii medicaid population. Journal of Mental Health , 28 (5), 536–545. https://doi.org/10.1080/09638237.2018.1521917 Long, J. S., & Mustillo, S. A. (2018). Using Predictions and Marginal Effects to Compare Groups in Regression Models for Binary Outcomes. Sociological Methods & Research , 50 (3), 1284–1320. https://doi.org/10.1177/0049124118799374 Ly, C., Greb, A. C., Cameron, L. P., Wong, J. M., Barragan, E. V., Wilson, P. C., Burbach, K. F., Soltanzadeh Zarandi, S., Sood, A., Paddy, M. R., Duim, W. C., Dennis, M. Y., McAllister, A. K., Ori-McKenney, K. M., Gray, J. A., & Olson, D. E. (2018). Psychedelics Promote Structural and Functional Neural Plasticity. Cell Reports , 23 (11), 3170–3182. https://doi.org/10.1016/j.celrep.2018.05.022 Maclean, K. A., Johnson, M. W., & Griffiths, R. R. (2011). Psilocybin Lead to Increases in the Personality Domain of Openness. Journal of Psychoph , 25 (11), 1453–1461. https://doi.org/10.1177/0269881111420188.Mystical MACPAC. (2017). Medicaid Hospital Payment: A Comparison across States and to Medicare . Nutt, D., & Carhart-Harris, R. (2021). The Current Status of Psychedelics in Psychiatry. In JAMA Psychiatry (Vol. 78, Issue 2, pp. 121–122). American Medical Association. https://doi.org/10.1001/jamapsychiatry.2020.2171 Oberfichtner, M., & Tauchmann, H. (2021). Stacked linear regression analysis to facilitate testing of hypotheses across OLS regressions. The Stata Journal: Promoting Communications on Statistics and Stata , 21 (2), 411–429. https://doi.org/10.1177/1536867X211025801 Omágua-Kambeba, A., Labate, B. C., & Ribeiro, S. (2023). Psychedelic science and Indigenous shamanism: an urgent dialogue. Nature Mental Health , 1 (11), 815–816. https://doi.org/10.1038/s44220-023-00150-9 Pearlin, L. I., Nguyen, K. B., Schieman, S., & Milkie, M. A. (2007). The Life-Course Origins of Mastery among Older People. Journal of Health and Social Behavior , 48 (2), 164–179. https://doi.org/10.1177/002214650704800205 Phelan, J. C., & Link, B. G. (2015). Is Racism a Fundamental Cause of Inequalities in Health? Annual Review of Sociology , 41 , 311–330. https://doi.org/10.1146/annurev-soc-073014-112305 Pisano, V. D., Putnam, N. P., Kramer, H. M., Franciotti, K. J., Halpern, J. H., & Holden, S. C. (2017). The association of psychedelic use and opioid use disorders among illicit users in the United States. Journal of Psychopharmacology , 31 (5), 606–613. https://doi.org/10.1177/0269881117691453 Prizzia, R., & Mokuah, N. (1991). Mental health services for native Hawaiians: the need for culturally relevant services. Journal of Health and Human Resources Administration , 14 (1), 44–61. Radley, D. C., Baumgartner, J. C., Collins, S. R., & Zephyrn Lauri, C. (2023). 2023 Scorecard on State Health System Performance . Sexton, J. D., Crawford, M. S., Sweat, N. W., Varley, A., Green, E. E., & Hendricks, P. S. (2019). Prevalence and epidemiological associates of novel psychedelic use in the United States adult population. Journal of Psychopharmacology , 33 (9), 1058–1067. https://doi.org/10.1177/0269881119827796 Storey, J. D. (2002). A Direct Approach to False Discovery Rates. Journal of the Royal Statistical Society Series B: Statistical Methodology , 64 (3), 479–498. https://doi.org/10.1111/1467-9868.00346 Tran, A. G. T. T., Lee, R. M., & Burgess, D. J. (2010). Perceived discrimination and substance use in Hispanic/Latino, African-born Black, and Southeast Asian immigrants. Cultural Diversity and Ethnic Minority Psychology , 16 (2), 226–236. https://doi.org/10.1037/a0016344 Tynkkynen, L.-K., & Vrangbæk, K. (2018). Comparing public and private providers: a scoping review of hospital services in Europe. BMC Health Services Research , 18 (1), 141. https://doi.org/10.1186/s12913-018-2953-9 Umucu, E., Fortuna, K., Jung, H., Bialunska, A., Lee, B., Mangadu, T., Storm, M., Ergun, G., Mozer, D. A., & Brooks, J. (2022). A National Study to Assess Validity and Psychometrics of the Short Kessler Psychological Distress Scale (K6). Rehabilitation Counseling Bulletin , 65 (2), 140–149. https://doi.org/10.1177/00343552211043261 Verdonk, P., Benschop, Y. W. M., de Haes, H. C. J. M., & Lagro-Janssen, T. L. M. (2009). From gender bias to gender awareness in medical education. Advances in Health Sciences Education , 14 (1), 135–152. https://doi.org/10.1007/s10459-008-9100-z Viña, S. M. (2024a). Diminished Psychedelic Returns on Distress: Marital Status and Household Size. PLoS ONE , 19 (3), 1–23. https://doi.org/https://doi.org/10.1371/journal.pone.0293675 Viña, S. M. (2024b). Minorities’ Diminished Psychedelic Returns: Cardio-Metabolic Health. Drug Science, Policy and Law , 10 , 1–13. https://doi.org/doi.org/10.1177/20503245231225756 Viña, S. M. (2024c). Minorities’ Diminished Psychedelic Returns: Gender, Perceived Stigma, and Distress. Psychoactives , 3 , 303–317. https://doi.org/10.3390/psychoactives3020019 Viña, S. M. (2024d). Minorities’ Diminished Psychedelic Returns: Income and Educations Impact on Whites, Blacks, Hispanics, and Asians. Journal of Race and Ethnic Health Disparities . https://doi.org/https://doi.org/10.1007/s40615-024-02023-y Viña, S. M. (2024e). Religion, Psychedelics, Risky Behavior, and Violence. Journal of Psychoactive Drugs , 1–12. https://doi.org/10.1080/02791072.2024.2346132 Viña, S. M. (2025a). American Indian Areas and Psychedelic Health Outcomes: A Test of the Minorities’ Diminished Psychedelic Returns Theory. Journal of Rural Mental Health , 48 . https://doi.org/https://doi.org/10.1037/rmh0000302 Viña, S. M. (2025b). Educational Moderation of Gender Disparities in Psychedelic Health Outcomes. Academia Mental Health and Well-Being , 2 (1). https://doi.org/10.20935/MHealthWellB7580 Viña, S. M. (2025c). Minorities’ diminished psychedelic returns: Depression, suicide, distress, and serious mental illness. Drug Science, Policy and Law , 11 . https://doi.org/10.1177/20503245251337357 Viña, S. M. (2025d). Psychedelics and Mental Health Treatment Seeking Among Asians and Hawaiians. Psychoactives , 4 (32), 1–15. https://doi.org/https://doi.org/10.3390/psychoactives4030032 Viña, S. M. (2025e). Race and Gender Differences in the Moderating Relationship of Psychedelics on Stigma and Distress. Psychedelic Medicine . https://doi.org/10.1089/psymed.2024.0021 Viña, S. M. (2025f). The Medical Sociological and Social Epidemiological Psychedelics Paradigm (MSSEPP). Drug Science, Policy and Law , Accepted (Forthcoming). Viña, S. M. (2025g). The Relationships Between Healthcare Access, Gender, and Psychedelics and Their Effects on Distress. Healthcare , `1 (10), 1158. https://doi.org/https://doi.org/10.3390/healthcare13101158 Viña, S. M., & Stephens, A. L. (2023a). Minorities’ diminished psychedelic returns. Drug Science, Policy and Law , 9 , 1–19. https://doi.org/10.1177/20503245231184638 Viña, S. M., & Stephens, A. L. (2023b). Psychedelics and workplace harm. Frontiers in Psychiatry , 14 (JUNE), 1–9. https://doi.org/10.3389/fpsyt.2023.1186541 Wheaton, B. (2010). The Stress Process as a Successful Paradigm. In W. R. Avison, C. S. Aneshensel, S. Schieman, & B. Wheaton (Eds.), Advances in the Conceptualization of the Stress Process: Essays in Honor of Leonard I. Pearlin (pp. 231–252). Springer. https://doi.org/10.1007/978-1-4419-1021-9 Williams, M. T., Cabral, V., & Faber, S. (2023). Psychedelics and Racial Justice. International Journal of Mental Health and Addiction . https://doi.org/10.1007/s11469-023-01160-5 Zeifman, R. J., Singhal, N., Breslow, L., & Weissman, C. R. (2021). On the Relationship between Classic Psychedelics and Suicidality: A Systematic Review. In ACS Pharmacology and Translational Science (Vol. 4, Issue 2, pp. 436–451). American Chemical Society. https://doi.org/10.1021/acsptsci.1c00024 Tables Table 1. Descriptive Statistics for Dependent Variables, Independent Variables, and Controls (2008-2019) (weighted) Mean SD n % / min-max Key Predictor Variable Psychological Distress 9.59 6.08 161,537 0-24 Education 2.75 1.03 484,732 1-4 No Health Insurance 63,390 13.08 Private Insurance 321,954 66.42 Public Insurance 157,741 32.54 Other Health Insurance 9,635 1.99 Lifetime Psychedelic Use MDMA 34,224 7.06 Psilocybin 38,475 7.94 DMT 461 0.10 Ayahuasca 43 0.01 Peyote/Mescaline 13,091 2.70 LSD 35,666 7.36 Classic Psychedelic Use 66,854 13.79 Control Variables s Women 250,942 51.77 Age 8.67 2.31 484,732 1-24 Family Income 4.96 2.02 484,732 1-7 Marital Status Single 134,007 27.65 Married 254,501 52.50 Widowed 28,908 5.96 Divorced/Separated 67,316 13.89 Children 0.54 0.92 484,043 0-3 Race White 318,261 65.66 Black 56,784 11.71 Hispanic 73,291 15.12 Asian 24,930 5.14 Native American 2,543 0.52 Hawaiian 1,735 0.36 Multi-Racial 7,189 1.48 Religious Salience 4.92 2.60 472,653 0-9 Religious Attendance in Days 1.89 .92 480,882 0-5 Lifetime Drug Use Cocaine 78,221 16.14 Stimulants 49,164 10.14 Sedatives 40,022 8.26 Tranquilizer 79,692 16.44 Inhalants 42,851 8.85 Pain Relievers 174,374 35.97 Heroine 9,528 1.97 Marijuana 225,161 46.45 PCP 12,643 2.61 MDMA/ecstasy 44,156 9.12 Tobacco 277,750 57.30 Age of First Alcohol Use 2.88 1.16 484,732 1-5 Thrill Seeking Behavior 1.62 0.72 481,653 1-4 Source: 2008-2019 National Survey of Drug Use and Health, n = 484,732 Table 2. Weighted Mean and Proportion Differences in Psychological Distress, Education, Health Insurance Coverage, and Lifetime Psychedelic Use by Insurance Status and Race/Ethnicity (White vs. Non-White; Black vs. Non-Black; Hispanic vs. Non-Hispanic; Asian vs. Non-Asian; NI/AN vs. Non-NI/AN; NHOPI vs. Non-NHOPI) No Private Insurance Private Insurance No Private Health Insurance (-) Private Health Insurance No Public Insurance Public Insurance No Public Health Insurance (-) Public Health Insurance Psychological Distress in Last Month (K6) 10.99 8.87 2.12 *** 9.50 9.81 -0.31 *** (10.90-11.08) (8.81-8.92) (2.02-2.22) (9.44 - 9.55) (9.70 - 9.90) (-0.43 - -0.19) Educational Attainment 2.27 3.00 -0.73 *** 2.88 2.49 0.39 *** (2.26-2.28) (2.99-3.00) (-0.74--0.72) (2.87 - 2.89) (2.47 - 2.50) (0.38 - 0.40) Health Insurance Uninsured 0.39 0.00 0.39 *** 0.19 0.00 0.19 *** (0.39-0.39) (0.00 - 0.00) (0.39-0.39) (0.19 - 0.20) (0.00 - 0.00) (0.19 - 0.20) Private 0.78 0.43 0.35 *** (0.77 - 0.78) (0.42 - 0.44) (0.34 - 0.35) Public 0.55 0.21 0.34 *** (0.55-0.55) (0.21-0.21) (0.34-0.34) Other 0.06 0.00 0.06 *** 0.03 0.00 0.03 *** (0.06-0.06) (0.00-0.00) (0.06-0.06) (0.03 - 0.03) (0.00 - 0.00) (0.03 - 0.03) Lifetime Psychedelic Use MDMA 0.08 0.06 0.02 *** 0.09 0.04 0.04 *** (0.08-0.09) (0.06-0.07) (0.02-0.02) (0.08 - 0.09) (0.04 - 0.04) (0.04 - 0.05) Psilocybin 0.09 0.09 0.00 0.11 0.06 0.05 *** (0.09-0.10) (0.09-0.09) (-0.00-0.00) (0.11 - 0.11) (0.05 - 0.06) (0.05 - 0.06) DMT 0.00 0.00 0.00 * 0.00 0.00 0.00 *** (0.00-0.00) (0.00-0.00) (0.00-0.00) (0.00 - 0.00) (0.00 - 0.00) (0.00 - 0.00) Ayahuasca 0.00 0.00 0.00 0.00 0.00 0.00 * (0.00-0.00) (0.00-0.00) (-0.00-0.00) (0.00 - 0.00) (0.00 - 0.00) (0.00 - 0.00) Peyote/Mescaline 0.05 0.04 0.00 *** 0.05 0.04 0.01 *** (0.04-0.05) (0.04-0.04) (0.00-0.01) (0.04 - 0.05) (0.03 - 0.04) (0.00 - 0.01) LSD 0.11 0.10 0.01 *** 0.12 0.08 0.04 *** (0.11-0.11) (0.10-0.10) (0.01-0.01) (0.11 - 0.12) (0.07 - 0.08) (0.04 - 0.05) Classic Psychedelics 0.14 0.14 0.01 ** 0.16 0.09 0.06 *** (0.14-0.14) (0.14-0.14) (0.00-0.01) (0.15 - 0.16) (0.09 - 0.10) (0.06 - 0.07) Not White White Not White (-) White Not Black Black Not Black (-) Black Psychological Distress in Last Month (K6) 9.74 9.52 0.22 *** 9.62 9.34 0.28 *** (9.65-9.83) (9.46-9.58) (0.11-0.32) (9.56-9.67) (9.21-9.46) (0.14-0.42) Educational Attainment 2.51 2.88 -0.36 *** 2.78 2.51 0.28 *** (2.50-2.52) (2.87-2.88) (-0.37--0.35) (2.78-2.79) (2.49-2.52) (0.26-0.30) Health Insurance Uninsured 0.2 0.09 0.11 *** 0.13 0.16 -0.03 *** (0.20-0.21) (0.09-0.09) (0.11-0.11) (0.13-0.13) (0.16-0.17) (-0.04--0.03) Private 0.53 0.74 -0.21 *** 0.68 0.51 0.17 *** (0.52-0.53) (0.73-0.74) (-0.22--0.20) (0.68-0.69) (0.50-0.52) (0.16-0.18) Public 0.31 0.33 -0.02 *** 0.32 0.39 -0.07 *** (0.31-0.32) (0.33-0.33) (-0.02--0.01) (0.31-0.32) (0.38-0.40) (-0.08--0.07) Other 0.03 0.01 0.01 *** 0.02 0.03 -0.01 *** (0.03-0.03) (0.01-0.02) (0.01-0.02) (0.02-0.02) (0.03-0.03) (-0.01--0.01) Lifetime Psychedelic Use MDMA 0.06 0.08 -0.02 *** 0.07 0.04 0.03 *** (0.05-0.06) (0.08-0.08) (-0.03--0.02) (0.07-0.08) (0.04-0.05) (0.03-0.03) Psilocybin 0.04 0.12 -0.08 *** 0.1 0.02 0.09 *** (0.04-0.04) (0.12-0.12) (-0.08--0.08) (0.10-0.11) (0.01-0.02) (0.08-0.09) DMT 0 0 0 *** 0 0 0 *** (0.00-0.00) (0.00-0.00) (-0.00--0.00) (0.00-0.00) (0.00-0.00) (0.00-0.00) Ayahuasca 0 0 0 † 0 0 0 *** (0.00-0.00) (0.00-0.00) (-0.00-0.00) (0.00-0.00) (0.00-0.00) (0.00-0.00) Peyote/Mescaline 0.02 0.05 -0.03 *** 0.05 0.02 0.03 *** (0.02-0.02) (0.05-0.06) (-0.04--0.03) (0.05-0.05) (0.01-0.02) (0.03-0.03) LSD 0.05 0.13 -0.08 *** 0.11 0.03 0.08 *** (0.05-0.05) (0.13-0.13) (-0.09--0.08) (0.11-0.12) (0.03-0.04) (0.08-0.08) Classic Psychedelics 0.07 0.17 -0.1 *** 0.15 0.04 0.11 *** (0.07-0.07) (0.17-0.18) (-0.11--0.10) (0.15-0.15) (0.04-0.05) (0.10-0.11) Not Hispanic Hispanic Not Hispanic (-) Hispanic Not Asian Asian Not Asian (-) Asian Psychological Distress in Last Month (K6) 9.52 10.04 -0.52 *** 9.61 9.15 0.46 *** (9.47–9.58) (9.90–10.17) (-0.66––0.37) (9.56–9.66) (8.93–9.37) (0.24–0.68) Educational Attainment 2.84 2.23 0.61 *** 2.72 3.35 -0.63 *** (2.84–2.85) (2.22–2.24) (0.60–0.63) (2.71–2.73) (3.32–3.37) (-0.66––0.60) Health Insurance Uninsured 0.1 0.28 -0.18 *** 0.13 0.1 0.04 *** (0.10–0.11) (0.28–0.29) (-0.18––0.17) (0.13–0.13) (0.09–0.10) (0.03–0.04) Private 0.7 0.46 0.24 *** 0.66 0.75 -0.09 *** (0.70–0.70) (0.45–0.47) (0.23–0.25) (0.66–0.66) (0.74–0.76) (-0.10––0.08) Public 0.33 0.28 0.06 *** 0.33 0.2 0.13 *** (0.33–0.34) (0.27–0.28) (0.05–0.06) (0.33–0.33) (0.19–0.22) (0.12–0.14) Other 0.02 0.03 -0.01 *** 0.02 0.03 -0.01 *** (0.02–0.02) (0.03–0.03) (-0.01––0.01) (0.02–0.02) (0.02–0.03) (-0.01––0.00) Lifetime Psychedelic Use MDMA 0.07 0.06 0.01 *** 0.07 0.04 0.03 *** (0.07–0.07) (0.06–0.06) (0.01–0.02) (0.07–0.07) (0.04–0.05) (0.02–0.03) Psilocybin 0.1 0.05 0.05 *** 0.1 0.03 0.07 *** (0.10–0.10) (0.05–0.05) (0.05–0.05) (0.10–0.10) (0.03–0.03) (0.06–0.07) DMT 0 0 0 *** 0 0 0 *** (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) Ayahuasca 0 0 0 0 0 0 (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) Peyote/Mescaline 0.05 0.02 0.03 *** 0.04 0.01 0.04 *** (0.05–0.05) (0.02–0.02) (0.02–0.03) (0.04–0.05) (0.01–0.01) (0.04–0.05) LSD 0.11 0.06 0.06 *** 0.11 0.03 0.08 *** (0.11–0.11) (0.05–0.06) (0.05–0.06) (0.11–0.11) (0.03–0.03) (0.08–0.09) Classic Psychedelics 0.15 0.08 0.07 *** 0.14 0.04 0.1 *** (0.15–0.15) (0.08–0.08) (0.06–0.07) (0.14–0.14) (0.04–0.05) (0.10–0.11) Not NI/AN NI/AN Not NI/AN (-)NI/AN Not NHOPI NHOPI Not NHOPI (-)NHOPI Psychological Distress in Last Month (K6) 9.58 11.36 -1.78 *** 9.59 10.01 -0.42 (9.53–9.63) (10.84–11.88) (-2.31––1.26) (9.54–9.64) (9.24–10.78) (-1.19–0.34) Educational Attainment 2.75 2.3 0.45 *** 2.75 2.58 0.17 *** (2.75–2.76) (2.25–2.36) (0.40–0.51) (2.75–2.76) (2.50–2.66) (0.10–0.25) Health Insurance Uninsured 0.13 0.12 0.01 0.13 0.16 -0.03 * (0.13–0.13) (0.10–0.14) (-0.00–0.03) (0.13–0.13) (0.13–0.19) (-0.05––0.00) Private 0.67 0.38 0.29 *** 0.66 0.59 0.07 *** (0.66–0.67) (0.35–0.40) (0.26–0.31) (0.66–0.67) (0.56–0.62) (0.04–0.10) Public 0.32 0.43 -0.1 *** 0.33 0.32 0.01 (0.32–0.33) (0.40–0.45) (-0.13––0.07) (0.32–0.33) (0.28–0.36) (-0.03–0.04) Other 0.02 0.15 -0.13 *** 0.02 0.03 -0.01 * (0.02–0.02) (0.13–0.16) (-0.15––0.11) (0.02–0.02) (0.02–0.04) (-0.02–0.00) Lifetime Psychedelic Use MDMA 0.07 0.07 0 0.07 0.08 -0.01 (0.07–0.07) (0.06–0.08) (-0.01–0.01) (0.07–0.07) (0.06–0.09) (-0.02–0.01) Psilocybin 0.09 0.11 -0.01 0.09 0.06 0.04 *** (0.09–0.09) (0.09–0.12) (-0.03–0.00) (0.09–0.10) (0.04–0.07) (0.02–0.05) DMT 0 0 0 0 0 0 *** (0.00–0.00) (0.00–0.00) (-0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) Ayahuasca 0 0 0 *** 0 0 0 *** (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) (0.00–0.00) Peyote/Mescaline 0.04 0.14 -0.1 *** 0.04 0.02 0.02 *** (0.04–0.04) (0.12–0.17) (-0.13––0.08) (0.04–0.04) (0.01–0.03) (0.01–0.03) LSD 0.1 0.11 -0.01 0.1 0.07 0.04 *** (0.10–0.11) (0.10–0.13) (-0.02–0.00) (0.10–0.11) (0.05–0.09) (0.02–0.06) Classic Psychedelics 0.14 0.24 -0.1 *** 0.14 0.09 0.05 *** (0.14–0.14) (0.21–0.27) (-0.13––0.07) (0.14–0.14) (0.06–0.11) (0.03–0.07) Note. Values are weighted means or proportions (95% confidence intervals in parentheses). Difference columns reflect first group minus second group, as labeled in the column headers. Post-estimation linear combination (LINCOM) tests were used to determine whether differences in group means or proportions were statistically significant (Long & Mustillo, 2018). This table presents a condensed summary of key sociodemographic differences; see Supplemental Tables 1–4 for the full set of mean and proportion differences by insurance status and race/ethnicity, including additional substance use, marital status, income, age, religiosity, religious attendance, and other control variables. Source: 2008-2019 National Survey of Drug Use and Health, n= 484,732 a . Calculated with T-Tests b . Standard deviations in parentheses. † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001 (two-tailed) Table 3. Weighted Ordinary Least Squares Regression Estimates of Mainline and Interaction Associations of Health Insurance and Psychedelic Use with Psychological Distress among the Total Population and by Race/Ethnicity Variable Mainline Associations Private Insurance Public Insurance Two-Way Interactions Psychedelic (×) Insurance Three-way Interactions Education (×) Psychedelic (×) Insurance Two-Way Interactions Psychedelic (×) Insurance Three-way Interactions Education (×) Psychedelic (×) Insurance Total Population Private insurance −0.989*** — — — — Public insurance 0.170** — — — — LCPU −0.165* −0.348** −0.240* 0.931*** 0.158 MDMA 0.154 −0.005 −0.384* 0.601*** 0.538* Psilocybin −0.268** −0.281* −0.255* 0.922*** 0.276 DMT 0.552 0.142 1.626 −0.481 −0.909 Ayahuasca 1.271 −2.084 −5.892* 3.530 — Peyote/Mescaline −0.464*** −0.088 −0.297 0.712* 0.312 LSD 0.133 −0.302* −0.283* 0.789*** 0.214 White, Non Hispanic Private insurance −1.166*** — — — — Public insurance 0.086 — — — — LCPU −0.023 −0.177 −0.357* 1.081*** 0.141 MDMA 0.024 −0.0429 −0.446* 0.888*** 0.516* Psilocybin −0.345*** −0.108 −0.328* 1.061*** 0.260 DMT 0.461 0.294 1.284 −0.188 −0.475 Ayahuasca 0.117 −0.334 2.640 5.362* — Peyote/Mescaline −0.547*** 0.0877 −0.528* 0.756* 0.264 LSD 0.273** −0.121 −0.358* 0.893*** 0.175 Black, Non-Hispanic Private insurance −0.884*** — — — — Public insurance 0.319* — — — — LCPU −0.450 −0.532 −0.510 0.878 0.857 MDMA 0.294 0.823 −0.171 0.342 0.392 Psilocybin 1.608*** −0.492 1.272 1.658* 0.513 DMT −2.399 — — — — Ayahuasca — — — — — Peyote/Mescaline −1.084* −1.575 0.391 1.431 0.234 LSD −0.371 −0.709 −1.204 1.002 0.771 Hispanic Private insurance −0.330† — — — — Public insurance 0.634*** — — — — LCPU 0.0751 −2.046 0.708 0.226 −0.131 MDMA 0.191 1.180 −0.301 −2.573† 0.630 Psilocybin −0.485† −0.888 0.306 −2.008 0.619 DMT −0.103 −11.45 2.542 8.113 −4.666* Ayahuasca 2.697 −20.21*** — — — Peyote/Mescaline 0.453 1.166 0.123 −3.058 0.778 LSD −0.250 −2.278 0.743 0.246 −0.166 Asian, Non-Hispanic Private insurance −1.145*** — — — — Public insurance −0.122 — — — — LCPU 1.340 1.008 −0.583 −0.0150 −0.109 MDMA −0.341 0.807 −0.225 −2.713 0.727 Psilocybin 0.601 4.047 −1.473 5.270 −1.896 DMT 8.965** −6.434* — — — Ayahuasca −3.056*** — — — — Peyote/Mescaline −0.050 7.589† −1.622 0.813 0.485 LSD −0.007 −0.633 −0.203 0.143 −0.328 Native Hawaiian or Pacific Islander (NHOPI) Private insurance 0.738 — — — — Public insurance 1.342 — — — — LCPU −0.504 2.446 4.817** −2.712 −4.816* MDMA 0.140 1.431 3.059 −1.524 −0.948 Psilocybin 2.118* 1.573 4.390* −2.598 −6.390** DMT — — — — — Ayahuasca — — — — — Peyote/Mescaline −5.141** 8.887** 6.178* 6.509* −6.460* LSD −3.219** 1.750 3.713* −1.682 −3.700* Native Indian or Alaskan Native (NI/AN) Private insurance 0.081 — — — — Public insurance 0.739 — — — — LCPU 0.060 −1.736† −0.211 0.519 −0.626 MDMA 2.419** −1.320 −4.425*** 1.528 0.558 Psilocybin 1.074 −0.896 −0.805 1.486 −0.347 DMT −3.033 — — — — Ayahuasca — — — — — Peyote/Mescaline 0.137 −2.534* 2.092* 0.183 −1.890 LSD −2.349** −1.122 −1.132 1.010 0.803 Note: Table 3 reports selected coefficients from weighted ordinary least squares (OLS) models predicting psychological distress using data from the 2008–2019 National Survey of Drug Use and Health (NSDUH). To conserve space and improve readability, the table presents key mainline associations and interaction terms only. Insurance mainline effects and LCPU coefficients are drawn from Model 2, while psychedelic mainline effects are drawn from Model 4 of the corresponding supplemental models. Interaction terms reflect the insurance × psychedelic and insurance × education × psychedelic specifications. All coefficients shown were estimated in the underlying models. Blank cells indicate terms that were not estimable for a given subgroup or specification (e.g., due to limited cell size or model convergence), rather than omitted or excluded. Full regression results—including all estimated coefficients, standard errors, and model fit statistics—are available in Supplemental Tables 5–21. *p < .05, **p < .01, ***p < .001 (two-tailed). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8483640","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":570376501,"identity":"324bb240-2a53-4d1f-a8f5-5cb40dac3611","order_by":0,"name":"Sean Vina","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApUlEQVRIiWNgGAWjYDACZiD+wCAB4fAQq4VxBlALD/FaQLp4YKqJ0mJwnPfgZ9s2i8T9EgmMD962EaPlMF+ydG6bRGIPzwFmw7nEaJFs5jEAacntYW9gk+YlUovxb0uQFmYG9t9EaeFn5jGTZoTawky0FsuecxL1PWcONkvOOUeEFjb+M8Y3fpTVGbPPSD744U0ZEVqQAGMDaepHwSgYBaNgFOAGAOdlKxzXofH0AAAAAElFTkSuQmCC","orcid":"","institution":"University of the Incarnate Word","correspondingAuthor":true,"prefix":"","firstName":"Sean","middleName":"","lastName":"Vina","suffix":""}],"badges":[],"createdAt":"2025-12-30 18:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8483640/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8483640/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100237338,"identity":"4b7c41af-085c-470e-b24a-dfdbd9aaf240","added_by":"auto","created_at":"2026-01-14 12:41:56","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":397714,"visible":true,"origin":"","legend":"","description":"","filename":"12282025insuranceracefulldraftblinded.docx","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/cfb3c026bbc524f69c185cce.docx"},{"id":100237337,"identity":"cbca81a6-ba1d-4280-aab8-2f100b5a3f97","added_by":"auto","created_at":"2026-01-14 12:41:56","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3517,"visible":true,"origin":"","legend":"","description":"","filename":"f71c99b5422241a48d87396499e4f040.json","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/4d895f7b3f43e5c58a5be468.json"},{"id":100371404,"identity":"933b764d-494b-4f57-94b5-64cc184f7663","added_by":"auto","created_at":"2026-01-16 08:09:59","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":801711,"visible":true,"origin":"","legend":"","description":"","filename":"07022025insurraceeduSuptables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/40e0281b4f1aee255253c7e0.docx"},{"id":100371051,"identity":"cb7764ed-00a0-4d08-a22a-008d9fc0a998","added_by":"auto","created_at":"2026-01-16 08:09:18","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":275889,"visible":true,"origin":"","legend":"","description":"","filename":"f71c99b5422241a48d87396499e4f0401enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/8e2fe99acfc4a0deee82e192.xml"},{"id":100237342,"identity":"7552143a-3df7-4f9a-bba4-31019d5c1748","added_by":"auto","created_at":"2026-01-14 12:41:56","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":273572,"visible":true,"origin":"","legend":"","description":"","filename":"f71c99b5422241a48d87396499e4f0401structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/9234fd7f2aeec07dea884af8.xml"},{"id":100237339,"identity":"4cb758d3-2965-4d7a-85fe-473fefcd8297","added_by":"auto","created_at":"2026-01-14 12:41:56","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":284353,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/d74f86a0f0c642ac96fbdc40.html"},{"id":100383463,"identity":"618161a9-5abc-4261-b906-bc4c2a873c71","added_by":"auto","created_at":"2026-01-16 10:46:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1457070,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/d8ee9f92-64a6-455c-b39d-4c20a6b7191e.pdf"},{"id":100237343,"identity":"c2c6f824-d8ec-4114-83a4-ed8fe2a467a4","added_by":"auto","created_at":"2026-01-14 12:41:56","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":801711,"visible":true,"origin":"","legend":"","description":"","filename":"07022025insurraceeduSuptables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8483640/v1/e448957ceb89cc4ac68a5c61.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can Education Compensate for Poor Healthcare? Racial Inequalities in Psychedelic-Associated Psychological Distress","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough ample research finds psychedelic use is associated with improved mental and psychological health, including lower psychological distress, depression, and suicidality (Hendricks et al., 2015; Johansen \u0026amp; Krebs, 2015; Johnson et al., 2019; G. M. Jones \u0026amp; Nock, 2022; Pisano et al., 2017; Sexton et al., 2019; Zeifman et al., 2021), recent evidence suggests that healthcare inequality can substantially shape the magnitude and durability of these mental health benefits (Vi\u0026ntilde;a, 2025g). In line with the Medical Sociological and Social Epidemiological Psychedelics Paradigm (MSSEPP), which conceptualizes psychedelic outcomes as jointly produced by pharmacological effects and structurally distributed social conditions, associations observed between psychedelic use and mental health outcomes should be expected to vary across institutional contexts such as healthcare systems (Vi\u0026ntilde;a, 2025f)\u0026nbsp;Specifically, prior research shows that the association between psychedelic use and reduced psychological distress is stronger among individuals with private healthcare, while those relying on public insurance programs\u0026mdash;including Medicaid, Medicare, and TRICARE\u0026mdash;not only experience diminished benefit but often report higher levels of psychological distress, identifying a particularly vulnerable and underserved population (Vi\u0026ntilde;a, 2025g). These differences likely reflect systemic weaknesses in public care systems, including limited provider networks, long wait times, regional disparities in service delivery, and fragmented care (Draper, 2013; Gleason \u0026amp; Beck, 2017; Gliner \u0026amp; Chukwura, 2023; MACPAC, 2017; Tynkkynen \u0026amp; Vrangb\u0026aelig;k, 2018). The structure and quality of care itself may therefore act as a critical moderator of psychedelic outcomes.\u003c/p\u003e\n\u003cp\u003eAs psychedelic policy shifts toward broader medicalization, decriminalization, and therapeutic access (Nutt \u0026amp; Carhart-Harris, 2021; Williams et al., 2023), it becomes increasingly important to understand how disparities in mental health outcomes may be reproduced or attenuated under expanding access. If access to high-quality mental healthcare conditions the psychological benefits associated with psychedelic use, one potential avenue for mitigation is education. Educational attainment has long been linked to better mental health outcomes through multiple pathways, including improved ability to navigate healthcare systems, communicate effectively with providers, and advocate for appropriate mental health care (Hernandez et al., 2018; Verdonk et al., 2009). Education also improves the quality of doctor\u0026ndash;patient interactions, often resulting in more personalized and attentive care, especially when providers perceive patients as more informed and proactive (Dyrbye et al., 2022; Kenny et al., 2010). Separately, education enhances psychological resources\u0026mdash;such as self-efficacy, optimism, and a sense of mastery\u0026mdash;that buffer stress and reduce psychological distress (Pearlin et al., 2007; Wheaton, 2010). These psychological resources may, in turn, complement the self-reflective, openness-inducing, and meaning-making properties of psychedelic experiences (Maclean et al., 2011; Wheaton, 2010). In theory, these advantages could allow individuals with higher education to better manage structural limitations in public care, making education a potential pathway to more equitable outcomes even in under-resourced healthcare contexts.\u003c/p\u003e\n\u003cp\u003eHowever, education may not offer equal protection for all groups. A substantial body of research demonstrates that racial and ethnic minorities often experience diminished health returns from educational attainment due to systemic racism embedded in both healthcare institutions and broader social structures (Assari, 2020; Vi\u0026ntilde;a, 2024d). Compared to their White counterparts, highly educated Black, Hispanic, Asian, Indigenous, and Pacific Islander individuals are more likely to report negative experiences with healthcare providers, including being dismissed, rushed, or receiving lower-quality care (Burrage et al., 2022; Gone, 2023; Phelan \u0026amp; Link, 2015; Tran et al., 2010). Within MSSEPP, these patterns reflect a broader expectation that structural and cultural conditions shape not only who can access high-quality care, but also whether individual resources (like education) can be translated into improved health outcomes (Vi\u0026ntilde;a, 2025f). The theory of Minorities\u0026rsquo; Diminished Psychedelic Returns (MDPR) extends this inequality logic to psychedelics, arguing that stratified environments reduce the effectiveness of psychedelics by disrupting both access to supportive care and the social conditions required for sustained healing (Altman \u0026amp; Magnus, 2024; Vi\u0026ntilde;a, 2025b, 2025e, 2025c; Vi\u0026ntilde;a \u0026amp; Stephens, 2023a). It remains unclear, then, whether education can compensate for healthcare inequality in psychedelic outcomes\u0026mdash;or whether its effects are stratified by race and structural context.\u003c/p\u003e\n\u003cp\u003eThis study examines whether education moderates the relationship between psychedelic use, healthcare access, and psychological distress, and whether this moderating effect varies by race and ethnicity. Using nationally representative data from the National Survey on Drug Use and Health (NSDUH) collected between 2008 and 2019, the analytic sample includes 484,732 adults aged 18 and older. Ordinary least squares (OLS) regression models are used to test whether educational attainment interacts with healthcare type (public vs. private) to shape mental health outcomes among individuals who report psychedelic use. Models are stratified by racial and ethnic group to assess how structural inequality conditions these associations. Building on prior research that established the importance of healthcare access in shaping psychedelic outcomes (Vi\u0026ntilde;a, 2025g), this is the first large-scale study to test whether education can offset these disparities\u0026mdash;and whether it does so equally across racial lines.\u003c/p\u003e"},{"header":"Data and Methods","content":"\u003cp\u003eThis study used cross-sectional data from the National Survey of Drug Use and Health (NSDUH) from 2008 to 2019 (N=\u003cem\u003e484,732\u003c/em\u003e). The NSDUH is an annual, nationally representative survey of substance use and mental health in the U.S., with weights applied to reflect the civilian noninstitutionalized population. Table 1 provides descriptive statistics for all dependent, independent, and control variables, derived from publicly available data. Public-use data files are accessible through the NSDUH homepage (https://www.samhsa.gov/data/data-we-collect/nsduh-national-survey-drug-use-and-health/datafiles/2002-2019). The NSDUH survey protocol was reviewed and approved by the Substance Abuse and Mental Health Services Administration\u0026rsquo;s (SAMHSA) Institutional Review Board, and informed consent was obtained from all participants at the time of data collection. The present study relies exclusively on secondary, de-identified, publicly available NSDUH data and does not involve any direct interaction with human subjects. As such, this analysis was reviewed by the author\u0026rsquo;s Institutional Review Board (IRB) and determined to be exempt from further ethical review, consistent with federal guidelines governing secondary data analysis.\u003c/p\u003e\n\u003cp\u003eStudy Replication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study builds directly on prior research examining stratified relationships between psychedelic use and health outcomes using data from the National Survey on Drug Use and Health (NSDUH) (Vi\u0026ntilde;a, 2024b, 2024d). It incorporates previously published and peer-reviewed variable constructions and modeling strategies, selected for conceptual and methodological consistency with earlier work rather than novel revalidation. This approach ensures comparability across studies while extending the analytic framework to evaluate whether educational attainment moderates healthcare-based disparities in psychedelic-related mental health outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDependent Variable\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRespondents completed the Kessler Psychological Distress Scale (K6) (Kessler et al., 2010) to assess their level of distress over the previous month. This instrument measures six feelings or experiences, such as feeling nervous, hopeless, restless, deeply depressed, perceiving everything as an effort, and feeling worthless. The respondents rated each item on a 5-point Likert scale. The scores on these measures were then summed to create a variable representing psychological distress in the past month, ranging from 0 to 24, with higher scores indicating higher levels of distress. The Kessler scale is a widely used and highly reliable measure for assessing psychological distress in individuals with panic disorder, generalized anxiety disorder, bipolar disorder, and schizophrenia (Umucu et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIndependent variables\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFirst, race/ethnicity is a categorical variables with seven categories: Racial/ethnic identity is based on self-reported responses and includes the following categories: White (reference group), Black or African American, Hispanic or Latino, Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and individuals identifying as two or more races.[1] These classifications follow federal guidelines established by the Office of Management and Budget for collecting race and ethnicity data. Next, educational attainment includes four categories and is treated as continuous: (1) less than high School Degree, (2) High School degree, (3) Some College, and (4) College degree or higher.[2] Next, respondents were asked to indicate whether they had health insurance. Those who had health insurance could then select from five variables to indicate their types of coverage: private health insurance, Medicare, Medicaid, Tricare, and other healthcare. While private care remained a binary variable, this study used a similar methodology to a previous study, and combined Medicare, Medicaid, and Tricare into a single variable called Public insurance (yes vs no) (Vi\u0026ntilde;a, 2025g). The \u0026quot;other\u0026quot; insurance category was included as a control variable in the regression analysis.\u003c/p\u003e\n\u003cp\u003eTo assess psychedelic use, respondents were asked whether they had ever used any of the following substances, even once: MDMA, N,N-dimethyltryptamine (DMT), psilocybin, lysergic acid diethylamide (LSD), and mescaline, as well as ayahuasca and peyote as they are listed in the NSDUH instrument. Because ayahuasca and peyote are plant-based preparations rather than single molecules, they are included here as survey categories that typically contain psychedelic compounds\u0026mdash;most commonly DMT in ayahuasca (along with \u0026beta;-carbolines that allow oral activity) and mescaline in peyote. To maintain consistency with prior research, the classic psychedelic items measured in NSDUH\u0026mdash;DMT, psilocybin, LSD, mescaline, and the plant-based preparations ayahuasca and peyote\u0026mdash;were grouped into a measure of Lifetime Classic Psychedelic Use (LCPU), as these exposures are generally considered to have low physiological risk and are associated with neurogenesis and positive mental health outcomes (dos Santos et al., 2018; Ly et al., 2018). MDMA was analyzed separately, as it functions primarily by increasing serotonin levels and has shown promise in both clinical trials and population-based studies of mental health (Brewerton et al., 2022; G. M. Jones \u0026amp; Nock, 2022). To enhance cultural and methodological sensitivity, the study followed previous recommendations to analyze each psychedelic substance individually (Vi\u0026ntilde;a, 2024d), and peyote and mescaline were grouped due to their shared botanical and ritual origins (P. N. Jones, 2007). This approach also reflects the understanding that the social and symbolic meanings associated with psychedelics may vary by group and context (Fotiou, 2019; Om\u0026aacute;gua-Kambeba et al., 2023).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSocioeconomic, Demographic, and Drug Use Control Variables\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSociodemographic control variables include gender, age, marital status, annual household income, educational attainment, religious attendance, religious salience, year of the survey, age of first alcohol use, self-reported risky behavior, and lifetime use of various substances. Substance use controls include lifetime use of cocaine, marijuana, phencyclidine (PCP), inhalants, other stimulants, sedatives, pain relievers, and tobacco products (e.g., smokeless tobacco, pipe tobacco, cigars, and daily cigarette use), which have been shown to correlate with health behaviors and distress (Altman \u0026amp; Magnus, 2024; Vi\u0026ntilde;a \u0026amp; Stephens, 2023a). Annual household income is measured using categorical brackets, ranging from less than $10,000 to $75,000 or more, and education is grouped into four levels: less than high school, high school graduate, some college, and college degree or more. Risk tolerance is measured using a thrill-seeking scale derived from two items asking whether respondents enjoy \u0026ldquo;dangerous\u0026rdquo; and \u0026ldquo;risky\u0026rdquo; activities (Cronbach\u0026rsquo;s \u0026alpha; = 0.85).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e[Table 1 Here]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalytic Strategy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCategorial and Continuous Variable Treatment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWhile age, income, and education are originally collected as categorical variables, they are modeled as continuous in this study. Likelihood ratio tests (LRTs) confirmed that treating these variables continuously does not lead to significant differences in model fit. This approach follows established guidance prioritizing model simplicity and interpretability in large-scale survey analysis (Long \u0026amp; Mustillo, 2018). Accordingly, both descriptive and multivariate analyses incorporate these covariates in continuous form where applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMean and Proportion Data Verification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs an initial step to examine subgroup differences and assess the data structure prior to multivariate modeling, weighted means and proportions were calculated for all continuous and categorical variables, stratified by race/ethnicity and healthcare status (e.g., private vs. public insurance; White vs. non-White; Black vs. non-Black). Table 2 presents a condensed summary of key sociodemographic patterns, while the full set of mean and proportion differences is reported in Supplemental Tables 1\u0026ndash;4. Post-estimation linear combination (LINCOM) tests were used to determine whether differences in group means or proportions were statistically significant (Long \u0026amp; Mustillo, 2018). For each comparison, differences were computed as the value of the reference group (e.g., those without private insurance or those not White) minus the value of the comparison group (e.g., those with private insurance or those who are White). This descriptive stage served as a foundational check for heterogeneity in psychological distress, insurance coverage, substance use, religiosity, and socioeconomic characteristics prior to estimating fully adjusted models.\u003c/p\u003e\n\u003cp\u003eRegression Analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analysis employed a series of weighted ordinary least squares (OLS) regression models to estimate mainline and interaction associations between psychedelic use, health insurance status, and psychological distress. Full model results are reported in Supplemental Tables 5\u0026ndash;21; Table 3 presents a condensed set of focal coefficients to facilitate comparison and conserve space.\u003c/p\u003e\n\u003cp\u003eSupplemental Tables 5\u0026ndash;7 report the mainline models. Model 1 estimated the association between MDMA and lifetime classic psychedelic use (LCPU) and psychological distress. Model 2 added health insurance indicators. Model 3 expanded the specification to include all six psychedelic measures, and Model 4 further incorporated health insurance variables.\u003c/p\u003e\n\u003cp\u003eSupplemental Tables 8\u0026ndash;21 report interaction models. The next set of models estimated two-way interactions between each psychedelic measure and health insurance status, followed by three-way interactions between education, health insurance, and each psychedelic measure. These interaction specifications were estimated separately for private and public health insurance (see Supplemental Tables 8\u0026ndash;9).\u003c/p\u003e\n\u003cp\u003eTo examine racial and ethnic differences, the study adopted an intersectional modeling strategy that compares substantively meaningful social positions by estimating separate race- and ethnicity-specific models (Long \u0026amp; Mustillo, 2018). These models are reported as follows: White respondents (Supplemental Tables 10\u0026ndash;11), Black respondents (12\u0026ndash;13), Hispanic respondents (14\u0026ndash;15), Asian respondents (16\u0026ndash;17), Native Hawaiian or Other Pacific Islander respondents (18\u0026ndash;19), and Native American/Alaska Native respondents (20\u0026ndash;21).\u003c/p\u003e\n\u003cp\u003eTable 3 summarizes selected mainline, two-way, and three-way interaction coefficients drawn from these models, while full coefficient vectors, standard errors, model fit statistics, and covariates are available in the corresponding supplemental tables. Statistical differences in coefficients across race-specific models were assessed using post-estimation seemingly unrelated estimation (SUEST) procedures, which allow for formal comparison of parameters estimated on the same or overlapping samples (Oberfichtner \u0026amp; Tauchmann, 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMultiple Comparisons and Weighting Adjustments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses accounted for the NSDUH\u0026rsquo;s complex sampling design by applying the appropriate person-level weights, which were adjusted using scalar factors to estimate national population parameters across pooled survey years. These weights were incorporated into all models using STATA 18, ensuring nationally representative estimates and accurate variance calculation. Given the number of subgroup comparisons and interaction effects tested, this study also addresses concerns about inflated Type I error due to multiple comparisons. Specifically, the Benjamini-Hochberg False Discovery Rate (BH-FDR) procedure was applied to control the expected proportion of false positives while maintaining statistical power (Armstrong, 2014). Compared to more conservative alternatives like Bonferroni correction, BH-FDR is widely recommended in epidemiological and social science research for balancing rigor and interpretability (Li \u0026amp; Barber, 2019; Storey, 2002). Although earlier NSDUH-based psychedelic studies did not typically apply multiple testing corrections (Vi\u0026ntilde;a \u0026amp; Stephens, 2023b, 2023a), this study adopts a more cautious approach. The significance threshold was set at 0.05, and sensitivity checks confirmed the robustness of findings under this adjustment strategy\u003c/p\u003e\n\u003cp\u003e[1] The \u0026quot;two or more races\u0026quot; category is included as a control variable (not the focus of subgroup analysis) and accounts for respondents who selected more than one racial group.\u003c/p\u003e\n\u003cp\u003e[2] A sensitivity analysis was run to test the variable as both a continuous and categorical variable. Because substantive results provided the same conclusions, the variable left as a continuous variable for ease of interpretation. \u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in Table 2, individuals with private health insurance exhibit higher levels of educational attainment and lower psychological distress, whereas those with public insurance show lower educational attainment and higher levels of distress (all \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Racial and ethnic differences further reveal that White and Asian respondents, relative to comparison groups, are more likely to have higher education, private insurance coverage, lower reliance on public insurance, and lower distress (all \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). In contrast, Black, Hispanic, Native Hawaiian or Other Pacific Islander (NHOPI), and Native Indian/Alaska Native (NI/AN) respondents display the opposite pattern, characterized by lower education, reduced access to private insurance, greater reliance on public insurance, and higher psychological distress (all \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Patterns of lifetime psychedelic use also vary by race/ethnicity: while White respondents are generally more likely to report lifetime psychedelic use (with the exception of ayahuasca), Black, Hispanic, Asian, and NHOPI respondents are less likely to report any psychedelic use (all \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). NI/AN respondents, however, are more likely than all other groups to report lifetime use of ayahuasca, peyote/mescaline, and classic psychedelics overall (all \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Complete descriptive results for all variables are provided in Supplemental Tables 1\u0026ndash;4.\u003c/p\u003e\n\u003cp\u003eTotal Population\u003c/p\u003e\n\u003cp\u003eAmong the total population, mainline associations indicate that having private health insurance is associated with lower psychological distress (b = \u0026minus;0.989, p \u0026lt; .001), whereas having public health insurance is associated with higher distress (b = 0.170, p \u0026lt; .01). Two-way interaction results show that the negative association between private insurance and distress is stronger among individuals who reported lifetime classic psychedelic use (LCPU; b = \u0026minus;0.348, p \u0026lt; .01). In the substance-specific models, this same pattern is also observed for psilocybin (b = \u0026minus;0.281, p \u0026lt; .05) and LSD (b = \u0026minus;0.302, p \u0026lt; .05). In contrast, the positive association between public insurance and distress is amplified among those who reported use of LCPU (b = 0.931, p \u0026lt; .001), MDMA (b = 0.601, p \u0026lt; .001), psilocybin (b = 0.922, p \u0026lt; .001), peyote/mescaline (b = 0.712, p \u0026lt; .05), and LSD (b = 0.789, p \u0026lt; .001).\u003c/p\u003e\n\u003cp\u003eThree-way interactions further indicate that the negative association between private insurance and distress becomes stronger at higher levels of education among individuals who reported use of LCPU (b = \u0026minus;0.302, p \u0026lt; .05), MDMA (b = \u0026minus;0.240, p \u0026lt; .05), psilocybin (b = \u0026minus;0.302, p \u0026lt; .05), ayahuasca (b = \u0026minus;5.892, p \u0026lt; .05), and LSD (b = \u0026minus;0.302, p \u0026lt; .05). In contrast, higher education intensified the positive association between public insurance and distress only among those who reported MDMA use (b = 0.538, p \u0026lt; .05).\u003c/p\u003e\n\u003cp\u003eWhite People\u003c/p\u003e\n\u003cp\u003eAmong White respondents, private health insurance is associated with lower psychological distress (b = \u0026minus;1.166, p \u0026lt; .001), while no mainline association is observed for public insurance. Two-way interaction results indicate that psychedelic use does not condition the association between private insurance and distress for White respondents. However, the positive association between public insurance and distress is stronger among those who reported use of LCPU (b = 1.081, p \u0026lt; .001), MDMA (b = 0.888, p \u0026lt; .001), psilocybin (b = 1.061, p \u0026lt; .001), ayahuasca (b = 5.620, p \u0026lt; .05), peyote/mescaline (b = 0.756, p \u0026lt; .05), and LSD (b = 0.884, p \u0026lt; .001). Three-way interactions show that higher education strengthens the negative association between private insurance and distress among White respondents who reported use of LCPU (b = \u0026minus;0.357, p \u0026lt; .05), MDMA (b = \u0026minus;0.446, p \u0026lt; .05), psilocybin (b = \u0026minus;0.328, p \u0026lt; .05), peyote/mescaline (b = \u0026minus;0.528, p \u0026lt; .05), and LSD (b = \u0026minus;0.358, p \u0026lt; .05). In addition, higher education amplifies the positive association between public insurance and distress among those who reported MDMA use (b = 0.516, p \u0026lt; .05).\u003c/p\u003e\n\u003cp\u003eBlack People\u003c/p\u003e\n\u003cp\u003eAmong Black respondents, private health insurance is associated with lower psychological distress (b = \u0026minus;0.884, p \u0026lt; .001), while public health insurance is associated with higher distress (b = 0.319, p \u0026lt; .05). No significant two-way interactions are observed between psychedelic use and private insurance. No significant three-way interactions involving education are observed among Black respondents.\u003c/p\u003e\n\u003cp\u003eHispanics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong Hispanic respondents, private health insurance is not significantly associated with psychological distress, whereas public insurance is associated with higher distress (b = 0.638, p \u0026lt; .001). Two-way interactions indicate that the association between private insurance and distress is substantially more negative among Hispanics who reported ayahuasca use (b = \u0026minus;20.10, p \u0026lt; .001). No significant two-way interactions are observed between psychedelic use and public insurance. Three-way interaction results show that higher education attenuates the positive association between public insurance and distress among Hispanics who reported DMT use (b = \u0026minus;4.666, p \u0026lt; .05). No three-way interactions are observed for private insurance.\u003c/p\u003e\n\u003cp\u003eAsians\u003c/p\u003e\n\u003cp\u003eAmong Asian respondents, private health insurance is associated with lower psychological distress (b = \u0026minus;1.125, p \u0026lt; .001), while no mainline association is observed for public insurance. Two-way interactions indicate that the negative association between private insurance and distress is weaker among Asian respondents who reported DMT use (b = 5.651, p \u0026lt; .05) and peyote/mescaline use (b = 2.736, p \u0026lt; .05). No significant three-way interactions involving education are observed among Asian respondents.\u003c/p\u003e\n\u003cp\u003eNative Hawaiian or Pacific Islander\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong NHOPI respondents, no mainline associations are observed between psychological distress and either private or public insurance. Two-way interactions show that peyote/mescaline use strengthens the association between private insurance and distress (b = 8.887, p \u0026lt; .01) and also moderates the association between public insurance and distress (b = 6.509, p \u0026lt; .05). Three-way interactions indicate that, among those with private insurance, higher education is associated with higher distress among NHOPI respondents who reported use of LCPU (b = 4.819, p \u0026lt; .01), psilocybin (b = 4.390, p \u0026lt; .05), peyote/mescaline (b = 6.178, p \u0026lt; .05), and LSD (b = 3.718, p \u0026lt; .05). Conversely, higher education attenuates the association between public insurance and distress among those who reported use of LCPU (b = \u0026minus;4.816, p \u0026lt; .05), psilocybin (b = \u0026minus;6.390, p \u0026lt; .01), peyote/mescaline (b = \u0026minus;6.460, p \u0026lt; .05), and LSD (b = \u0026minus;3.700, p \u0026lt; .05).\u003c/p\u003e\n\u003cp\u003eNative Indian or Alaskan Native\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong NI/AN respondents, no mainline associations are observed between psychological distress and either private or public insurance. Two-way interaction results indicate that the association between private insurance and distress is stronger among NI/AN respondents who reported peyote/mescaline use (b = \u0026minus;2.534, p \u0026lt; .05). Three-way interactions further show that higher education is associated with lower distress among NI/AN respondents with private insurance who reported MDMA use (b = \u0026minus;4.250, p \u0026lt; .001), but higher distress among those who reported peyote/mescaline use (b = \u0026minus;2.092, p \u0026lt; .05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the relationship between psychedelics, healthcare insurance coverage, education, distress, and race/ethnicity. MSSEPP suggests that psychedelic outcomes are not produced by pharmacology alone, but by the intersection of drug effects with institutional arrangements (such as healthcare systems) and stratified social conditions that shape exposure, interpretation, risk, and capacity to benefit (Vi\u0026ntilde;a, 2025f). Importantly, the NSDUH measures lifetime psychedelic use in the general population, so the results primarily reflect \u003cem\u003enaturalistic\u003c/em\u003e use rather than psychedelic administration or prescription within clinical care. Previous research has suggested that psychedelics may be impacted by structural inequalities associated with different insurance contexts and healthcare systems. This study specifically investigated whether educational attainment could influence these relationships and if the patterns were consistent across different racial and ethnic groups. The findings contribute to the growing body of literature indicating that psychedelics may not provide significant benefits for marginalized communities in population-based research (Argento et al., 2018; Hendricks et al., 2014; G. M. Jones, 2023; Vi\u0026ntilde;a, 2024c, 2024d, 2024e, 2024b, 2024a, 2025a; Vi\u0026ntilde;a \u0026amp; Stephens, 2023a). There were instances where a complementary relationship between psychedelics and private insurance coverage was observed, suggesting that individuals using psychedelics may be better positioned to realize lower distress in contexts associated with private coverage. However, this positive relationship was predominantly experienced by White individuals. In contrast, there were few instances where education mitigated the positive association between public insurance coverage and psychological distress, allowing psychedelic users to show a weaker linkage between public coverage and distress. Moreover, race and ethnic minorities appeared to derive less benefit from psychedelics overall. The study showed that those using public insurance coverage gained even fewer benefits. Additionally, the results indicated that within the total population relying on public insurance coverage, psychedelic use (including MDMA and several classic psychedelic exposures, such as psilocybin, LSD, and peyote/mescaline) was associated with higher levels of distress. While the findings do not imply that people are using psychedelics to cope with the distress caused by public insurance coverage, the pattern is consistent with selection into overlapping vulnerabilities\u0026mdash;i.e., a subgroup with elevated distress that is also more likely to rely on public coverage and to report psychedelic use in their lifetime. Given that marginalized racial and ethnic populations are more likely to rely on public insurance coverage (Hahn et al., 2018), the overall literature suggests a shrinking population that will gain significant benefits from psychedelics. This highlights the need for addressing structural inequalities in healthcare to ensure broader access to the potential benefits of psychedelics, particularly as psychedelic interventions become more embedded in formal treatment systems and insurance-linked pathways.\u003c/p\u003e\n\u003cp\u003eResults related to education provide several important implications. First, the pervasiveness of poor healthcare in contexts tied to public insurance coverage is so extensive that education did not seem to counter its effects. While there may be hope that increased education and subsequent medical knowledge can help people better manage the healthcare system, the results suggest that education may only benefit those with private insurance coverage. These individuals already have higher socioeconomic status (SES), less distress, and are navigating a healthcare system that is generally more accommodating than publicly insured contexts. Contrary to the hypothesis, there were instances where higher education was associated with better mental health profiles (lower distress) among psychedelic users in private coverage contexts. This pattern was found among White individuals who had used MDMA and Native Hawaiians and Other Pacific Islanders (NHOPI) who had used LCPU, psilocybin, peyote/mescaline, and LSD. Considering the evidence that both private coverage and psychedelic use are associated with less distress, these findings may capture a complementary relationship. Specifically, the data may be capturing highly educated people who are distressed but have enough medical/health knowledge to seek out alternative health coping strategies, including psychedelics. Overall, these results are consistent with MSSEPP\u0026rsquo;s expectation that individual resources (like education) translate into benefit primarily when institutional conditions are supportive\u0026mdash;meaning education\u0026rsquo;s \u0026ldquo;protective\u0026rdquo; capacity is conditional on the healthcare environment (Vi\u0026ntilde;a, 2025f) and that the conversion of education into health gains is itself socially patterned. Accordingly, these findings should be interpreted as associations consistent with structurally patterned resource conversion, rather than as definitive evidence of mechanism.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, there were noteworthy instances in which higher education did seem to benefit NHOPI on public insurance coverage who used psychedelics, likely explained by structure. While NHOPI are interspersed around the continental United States, about 50% of the population lives within the state of Hawai\u0026rsquo;I (America Counts Staff, 2021). As the only state with universal healthcare, Hawai\u0026rsquo;i\u0026rsquo;s healthcare system is second in in Health Care Quality, third among the Public Health, and first in overall healthcare, has produced one of the highest expectancies (Radley et al., 2023). In short, NHOPI may be using a better public healthcare system while insured through public coverage than other average Americans, and those who have used psychedelics and have higher education are simply better able to access it (Carlton et al., 2006; Lim et al., 2019; Prizzia \u0026amp; Mokuah, 1991; Vi\u0026ntilde;a, 2025d). In MSSEPP terms, this pattern is precisely what institutional heterogeneity would predict: where public systems are better resourced and more navigable, education may function as a lever that helps individuals translate psychedelic use into improved mental health outcomes. Importantly, this interpretation aligns with my recent NHOPI-focused study, which finds that psychedelic use among NHOPI is associated with increased odds of engaging formal mental health care\u0026mdash;suggesting that, in this population, psychedelics may operate in ways that are complementary to (rather than substitutive of) treatment-seeking within more trusted or supportive care contexts (Vi\u0026ntilde;a, 2025d).\u003c/p\u003e\n\u003cp\u003eWhile there are many reasons to decriminalize psychedelics for personal and health purposes, including those related to racial justice (Williams et al., 2023), these results suggest a more pressing issue: the structural inequality within the healthcare system itself. In these cross-sectional data, the mental health correlates of psychedelic use appear to differ systematically by insurance context, with public coverage consistently marking higher distress and weaker or adverse associations for several psychedelic exposures. Importantly, the results also indicate that increasing individual education alone is insufficient in countering the negative consequences of these poor systems; a structural fix is necessary. The overall findings underscore the pervasive impact of systemic racism in medicine and health inequality. Racism in healthcare remains a significantly toxic factor that likely counters the positive effects of psychedelics on mental health for these groups. From the standpoint of MSSEPP, MDPR can be understood as a specific inequality-focused extension: it identifies how structurally patterned disadvantage limits the conditions under which psychedelics can function as a health resource (Vi\u0026ntilde;a, 2025f; Vi\u0026ntilde;a \u0026amp; Stephens, 2023a). The results related to NHOPI who likely use a public healthcare system that is among the best in the nation further emphasize the need to fix public systems that serve publicly insured populations across the board. Therefore, rather than focusing on increasing education to help people better utilize healthcare including psychedelics, policy should instead focus on systemic changes in healthcare that reduce institutional barriers and improve access, continuity, and quality of mental health care\u0026mdash;especially for publicly insured groups\u0026mdash;so that the potential benefits of psychedelic use and emerging psychedelic therapies are less likely to be stratified by insurance status.\u003c/p\u003e\n\u003cp\u003eLimitations and Future Directions\u003c/p\u003e\n\u003cp\u003eThis study offers valuable insights into the associations between psychedelics, healthcare, education, and race/ethnicity. However, it is important to recognize the study\u0026apos;s limitations. The analysis did not account for key factors such as personality traits, peak experiences, and dosage. From an MSSEPP perspective, these omissions matter because psychedelic outcomes are shaped by both individual-level processes and the social conditions in which use occurs, including culturally and structurally patterned set-and-setting. Additionally, there may be other unmeasured variables influencing these relationships. This study cannot establish causality; thus, future research should use longitudinal data to better understand these associations and consider the timing of psychedelic use. Furthermore, while the study draws on extensive research regarding inequality and healthcare disparities, it does not explore specific experiences within the medical field. For example, are Native Hawaiians and Other Pacific Islanders actually more satisfied with their public care than other marginalized groups? Future research should aim to investigate these specific contexts to provide a more comprehensive understanding, including mixed-methods work that can directly observe mechanisms (e.g., patient\u0026ndash;provider interactions, care continuity, barriers to referrals) that may underlie the observed quantitative patterns. Despite its limitations, this study offers valuable insights into the relationship between psychedelics and health. While more detailed study designs (including longitudinal studies and clinical research) are needed to clarify causal pathways and specify mechanisms, the present findings remain consistent with the broader literature on structural inequality in medicine and highlight how institutional stratification may shape who is positioned to benefit from psychedelics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements: Not Applicable.\u003c/p\u003e\n\u003cp\u003eFunding Statement: This research received no funding.\u003c/p\u003e\n\u003cp\u003eConflict Of Interest: The authors declare no conflict of interest in preparing this article.\u003c/p\u003e\n\u003cp\u003eData Availability Statement: The National Survey of Drug Use and Health (NSDUH) is public-use data and is available on their homepage: https://www.datafiles.samhsa.gov/dataset/nsduh-2002-2019-ds0001-nsduh-2002-2019-ds0001.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAltman, B., \u0026amp; Magnus, M. (2024). Association between lifetime hallucinogen use and psychological distress varies by sexual identity in a nationally representative sample. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(10), 861\u0026ndash;872. https://doi.org/10.1177/02698811241278774\u003c/li\u003e\n \u003cli\u003eAmerica Counts Staff. (2021, August 25). \u003cem\u003eHAWAII: 2020 Census\u003c/em\u003e. United States Census Bureau. https://www.census.gov/library/stories/state-by-state/hawaii-population-change-between-census-decade.html\u003c/li\u003e\n \u003cli\u003eArgento, E., Braschel, M., Walsh, Z., Socias, M. E., \u0026amp; Shannon, K. (2018). The moderating effect of psychedelics on the prospective relationship between prescription opioid use and suicide risk among marginalized women. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(12), 1385\u0026ndash;1391. https://doi.org/10.1177/0269881118798610\u003c/li\u003e\n \u003cli\u003eArmstrong, R. A. (2014). When to use the Bonferroni correction. \u003cem\u003eOphthalmic and Physiological Optics\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(5), 502\u0026ndash;508. https://doi.org/10.1111/opo.12131\u003c/li\u003e\n \u003cli\u003eAssari, S. (2020). Blacks\u0026rsquo; Diminished Health Returns of Educational Attainment: Health and Retirement Study. \u003cem\u003eJournal of Medical Research and Innovation\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 1\u0026ndash;11.\u003c/li\u003e\n \u003cli\u003eBrewerton, T. D., Wang, J. B., Lafrance, A., Pamplin, C., Mithoefer, M., Yazar-Klosinki, B., Emerson, A., \u0026amp; Doblin, R. (2022). MDMA-assisted therapy significantly reduces eating disorder symptoms in a randomized placebo-controlled trial of adults with severe PTSD. \u003cem\u003eJournal of Psychiatric Research\u003c/em\u003e, \u003cem\u003e149\u003c/em\u003e, 128\u0026ndash;135. https://doi.org/10.1016/j.jpsychires.2022.03.008\u003c/li\u003e\n \u003cli\u003eBurrage, R. L., Antone, M. M., Kaniaupio, K. N. M., \u0026amp; Rapozo, K. L. (2022). A culturally informed scoping review of Native Hawaiian mental health and emotional well-being literature. In C. E. Mckinley, M. S. Spencer, K. Walters, \u0026amp; C. R. Figley (Eds.), \u003cem\u003eIndigenous Health Equity and Wellness\u003c/em\u003e (1st ed.). Routledge.\u003c/li\u003e\n \u003cli\u003eCarlton, B. S., Goebert, D. A., Miyamoto, R. H., Andrade, N. N., Hishinuma, E. S., Makini, G. K., Yuen, N. Y. C., Bell, C. K., McCubbin, L. D., Else, \u0026rsquo;Iwalani R.N., \u0026amp; Nishimura, S. T. (2006). Resilience, Family Adversity and Well-Being Among Hawaiian and Non-Hawaiian Adolescents. \u003cem\u003eInternational Journal of Social Psychiatry\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(4), 291\u0026ndash;308. https://doi.org/10.1177/0020764006065136\u003c/li\u003e\n \u003cli\u003edos Santos, R. G., Bouso, J. C., Alc\u0026aacute;zar-C\u0026oacute;rcoles, M. \u0026Aacute;., \u0026amp; Hallak, J. E. C. (2018). Efficacy, tolerability, and safety of serotonergic psychedelics for the management of mood, anxiety, and substance-use disorders: a systematic review of systematic reviews. In \u003cem\u003eExpert Review of Clinical Pharmacology\u003c/em\u003e (Vol. 11, Issue 9, pp. 889\u0026ndash;902). Taylor and Francis Ltd. https://doi.org/10.1080/17512433.2018.1511424\u003c/li\u003e\n \u003cli\u003eDraper, D. A. (2013). \u003cem\u003eDefense Health Care: Multiyear Surveys Indicate Problems with Access to Care for Nonenrolled Beneficiaries\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eDyrbye, L. N., West, C. P., Sinsky, C. A., Trockel, M., Tutty, M., Satele, D., Carlasare, L., \u0026amp; Shanafelt, T. (2022). Physicians\u0026rsquo; Experiences With Mistreatment and Discrimination by Patients, Families, and Visitors and Association With Burnout. \u003cem\u003eJAMA Network Open\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(5), e2213080. https://doi.org/10.1001/jamanetworkopen.2022.13080\u003c/li\u003e\n \u003cli\u003eFotiou, E. (2019). The role of Indigenous knowledges in psychedelic science. \u003cem\u003eJournal of Psychedelic Studies\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 16\u0026ndash;23. https://doi.org/10.1556/2054.2019.031\u003c/li\u003e\n \u003cli\u003eGleason, J. L., \u0026amp; Beck, K. H. (2017). Examining Associations Between Relocation, Continuity of Care, and Patient Satisfaction in Military Spouses. \u003cem\u003eMilitary Medicine\u003c/em\u003e, \u003cem\u003e182\u003c/em\u003e(5), e1657\u0026ndash;e1664. https://doi.org/10.7205/MILMED-D-16-00191\u003c/li\u003e\n \u003cli\u003eGliner, M. D., \u0026amp; Chukwura, C. (2023). \u003cem\u003eEvaluation of the TRICARE Program: Fiscal Year 2023 Report to Congress Access, Cost, and Quality Data through Fiscal Year 2022\u003c/em\u003e. www.af.mil,\u003c/li\u003e\n \u003cli\u003eGone, J. P. (2023). Community Mental Health Services for American Indians and Alaska Natives: Reconciling Evidence-Based Practice and Alter-Native Psy-ence. \u003cem\u003eAnnual Review of Clinical Psychology Annu. Rev. Clin. Psychol. 2023\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e, 23\u0026ndash;49. https://doi.org/10.1146/annurev-clinpsy-080921\u003c/li\u003e\n \u003cli\u003eHahn, R. A., Truman, B. I., \u0026amp; Williams, D. R. (2018). Civil rights as determinants of public health and racial and ethnic health equity: Health care, education, employment, and housing in the United States. \u003cem\u003eSSM - Population Health\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 17\u0026ndash;24. https://doi.org/10.1016/j.ssmph.2017.10.006\u003c/li\u003e\n \u003cli\u003eHendricks, P. S., Clark, C. B., Johnson, M. W., Fontaine, K. R., \u0026amp; Cropsey, K. L. (2014). Hallucinogen use predicts reduced recidivism among substance-involved offenders under community corrections supervision. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(1), 62\u0026ndash;66. https://doi.org/10.1177/0269881113513851\u003c/li\u003e\n \u003cli\u003eHendricks, P. S., Thorne, C. B., Clark, C. B., Coombs, D. W., \u0026amp; Johnson, M. W. (2015). Classic Psychedelic Use is Associated with Reduced Psychological Distress and Suicidality in the United States Adult Population. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(3), 280\u0026ndash;288. https://doi.org/10.1177/0269881114565653\u003c/li\u003e\n \u003cli\u003eHernandez, E. M., Margolis, R., \u0026amp; Hummer, R. A. (2018). Educational and Gender Differences in Health Behavior Changes After a Gateway Diagnosis. \u003cem\u003eJournal of Aging and Health\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(3), 342\u0026ndash;364. https://doi.org/10.1177/0898264316678756\u003c/li\u003e\n \u003cli\u003eJohansen, P.-\u0026Oslash;., \u0026amp; Krebs, T. S. (2015). Psychedelics not linked to mental health problems or suicidal behavior: A population study. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(3), 270\u0026ndash;279. https://doi.org/10.1177/0269881114568039\u003c/li\u003e\n \u003cli\u003eJohnson, M. W., Hendricks, P. S., Barrett, F. S., \u0026amp; Griffiths, R. R. (2019). Classic psychedelics: An integrative review of epidemiology, therapeutics, mystical experience, and brain network function. \u003cem\u003ePharmacology \u0026amp; Therapeutics\u003c/em\u003e, \u003cem\u003e197\u003c/em\u003e, 83\u0026ndash;102. https://doi.org/10.1016/j.pharmthera.2018.11.010\u003c/li\u003e\n \u003cli\u003eJones, G. M. (2023). Race and ethnicity moderate the associations between lifetime psychedelic use (MDMA/ecstasy and psilocybin) and major depressive episodes. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(1), 61\u0026ndash;69. https://doi.org/10.1177/02698811221127304\u003c/li\u003e\n \u003cli\u003eJones, G. M., \u0026amp; Nock, M. K. (2022). MDMA/ecstasy use and psilocybin use are associated with lowered odds of psychological distress and suicidal thoughts in a sample of US adults. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(1), 46\u0026ndash;56. https://doi.org/10.1177/02698811211058923\u003c/li\u003e\n \u003cli\u003eJones, P. N. (2007). The Native American Church, Peyote, and Health: Expanding Consciousness for Healing Purposes. \u003cem\u003eContemporary Justice Review\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(4), 411\u0026ndash;425.\u003c/li\u003e\n \u003cli\u003eKenny, D. A., Veldhuijzen, W., Weijden, T. van der, LeBlanc, A., Lockyer, J., L\u0026eacute;gar\u0026eacute;, F., \u0026amp; Campbell, C. (2010). Interpersonal perception in the context of doctor-patient relationships: A dyadic analysis of doctor-patient communication. \u003cem\u003eSocial Science \u0026amp; Medicine\u003c/em\u003e, \u003cem\u003e70\u003c/em\u003e(5), 763\u0026ndash;768. https://doi.org/10.1016/j.socscimed.2009.10.065\u003c/li\u003e\n \u003cli\u003eKessler, R. C., Green, J. G., Gruber, M. J., Sampson, N. A., Bromet, E., Cuitan, M., Furukawa, T. A., Oye, G., Hinkov, H., Hu, C. Y., Lara, C., Lee, S., Mneimneh, Z., Myer, L., Oakley-Browne, M., Posada-Villa, J., Sagar, R., Viana, M. C., \u0026amp; Zaslavsky, A. M. (2010). Screening for serious mental illness in the general population with the K6 screening scale: Results from the WHO World Mental Health (WMH) survey initiative. \u003cem\u003eInternational Journal of Methods in Psychiatric Research\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(SUPPL. 1), 4\u0026ndash;22. https://doi.org/10.1002/mpr.310\u003c/li\u003e\n \u003cli\u003eLi, A., \u0026amp; Barber, R. F. (2019). Multiple Testing with the Structure-Adaptive Benjamini\u0026ndash;Hochberg Algorithm. \u003cem\u003eJournal of the Royal Statistical Society Series B: Statistical Methodology\u003c/em\u003e, \u003cem\u003e81\u003c/em\u003e(1), 45\u0026ndash;74. https://doi.org/10.1111/rssb.12298\u003c/li\u003e\n \u003cli\u003eLim, E., Gandhi, K., Siriwardhana, C., Davis, J., \u0026amp; Chen, J. J. (2019). Racial and ethnic differences in mental health service utilization among the Hawaii medicaid population. \u003cem\u003eJournal of Mental Health\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(5), 536\u0026ndash;545. https://doi.org/10.1080/09638237.2018.1521917\u003c/li\u003e\n \u003cli\u003eLong, J. S., \u0026amp; Mustillo, S. A. (2018). Using Predictions and Marginal Effects to Compare Groups in Regression Models for Binary Outcomes. \u003cem\u003eSociological Methods \u0026amp; Research\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(3), 1284\u0026ndash;1320. https://doi.org/10.1177/0049124118799374\u003c/li\u003e\n \u003cli\u003eLy, C., Greb, A. C., Cameron, L. P., Wong, J. M., Barragan, E. V., Wilson, P. C., Burbach, K. F., Soltanzadeh Zarandi, S., Sood, A., Paddy, M. R., Duim, W. C., Dennis, M. Y., McAllister, A. K., Ori-McKenney, K. M., Gray, J. A., \u0026amp; Olson, D. E. (2018). Psychedelics Promote Structural and Functional Neural Plasticity. \u003cem\u003eCell Reports\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(11), 3170\u0026ndash;3182. https://doi.org/10.1016/j.celrep.2018.05.022\u003c/li\u003e\n \u003cli\u003eMaclean, K. A., Johnson, M. W., \u0026amp; Griffiths, R. R. (2011). Psilocybin Lead to Increases in the Personality Domain of Openness. \u003cem\u003eJournal of Psychoph\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(11), 1453\u0026ndash;1461. https://doi.org/10.1177/0269881111420188.Mystical\u003c/li\u003e\n \u003cli\u003eMACPAC. (2017). \u003cem\u003eMedicaid Hospital Payment: \u0026nbsp;A Comparison across States and to Medicare\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eNutt, D., \u0026amp; Carhart-Harris, R. (2021). The Current Status of Psychedelics in Psychiatry. In \u003cem\u003eJAMA Psychiatry\u003c/em\u003e (Vol. 78, Issue 2, pp. 121\u0026ndash;122). American Medical Association. https://doi.org/10.1001/jamapsychiatry.2020.2171\u003c/li\u003e\n \u003cli\u003eOberfichtner, M., \u0026amp; Tauchmann, H. (2021). Stacked linear regression analysis to facilitate testing of hypotheses across OLS regressions. \u003cem\u003eThe Stata Journal: Promoting Communications on Statistics and Stata\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(2), 411\u0026ndash;429. https://doi.org/10.1177/1536867X211025801\u003c/li\u003e\n \u003cli\u003eOm\u0026aacute;gua-Kambeba, A., Labate, B. C., \u0026amp; Ribeiro, S. (2023). Psychedelic science and Indigenous shamanism: an urgent dialogue. \u003cem\u003eNature Mental Health\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(11), 815\u0026ndash;816. https://doi.org/10.1038/s44220-023-00150-9\u003c/li\u003e\n \u003cli\u003ePearlin, L. I., Nguyen, K. B., Schieman, S., \u0026amp; Milkie, M. A. (2007). The Life-Course Origins of Mastery among Older People. \u003cem\u003eJournal of Health and Social Behavior\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(2), 164\u0026ndash;179. https://doi.org/10.1177/002214650704800205\u003c/li\u003e\n \u003cli\u003ePhelan, J. C., \u0026amp; Link, B. G. (2015). Is Racism a Fundamental Cause of Inequalities in Health? \u003cem\u003eAnnual Review of Sociology\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e, 311\u0026ndash;330. https://doi.org/10.1146/annurev-soc-073014-112305\u003c/li\u003e\n \u003cli\u003ePisano, V. D., Putnam, N. P., Kramer, H. M., Franciotti, K. J., Halpern, J. H., \u0026amp; Holden, S. C. (2017). The association of psychedelic use and opioid use disorders among illicit users in the United States. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(5), 606\u0026ndash;613. https://doi.org/10.1177/0269881117691453\u003c/li\u003e\n \u003cli\u003ePrizzia, R., \u0026amp; Mokuah, N. (1991). Mental health services for native Hawaiians: the need for culturally relevant services. \u003cem\u003eJournal of Health and Human Resources Administration\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 44\u0026ndash;61.\u003c/li\u003e\n \u003cli\u003eRadley, D. C., Baumgartner, J. C., Collins, S. R., \u0026amp; Zephyrn Lauri, C. (2023). \u003cem\u003e2023 Scorecard on State Health System Performance\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eSexton, J. D., Crawford, M. S., Sweat, N. W., Varley, A., Green, E. E., \u0026amp; Hendricks, P. S. (2019). Prevalence and epidemiological associates of novel psychedelic use in the United States adult population. \u003cem\u003eJournal of Psychopharmacology\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(9), 1058\u0026ndash;1067. https://doi.org/10.1177/0269881119827796\u003c/li\u003e\n \u003cli\u003eStorey, J. D. (2002). A Direct Approach to False Discovery Rates. \u003cem\u003eJournal of the Royal Statistical Society Series B: Statistical Methodology\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(3), 479\u0026ndash;498. https://doi.org/10.1111/1467-9868.00346\u003c/li\u003e\n \u003cli\u003eTran, A. G. T. T., Lee, R. M., \u0026amp; Burgess, D. J. (2010). Perceived discrimination and substance use in Hispanic/Latino, African-born Black, and Southeast Asian immigrants. \u003cem\u003eCultural Diversity and Ethnic Minority Psychology\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(2), 226\u0026ndash;236. https://doi.org/10.1037/a0016344\u003c/li\u003e\n \u003cli\u003eTynkkynen, L.-K., \u0026amp; Vrangb\u0026aelig;k, K. (2018). Comparing public and private providers: a scoping review of hospital services in Europe. \u003cem\u003eBMC Health Services Research\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), 141. https://doi.org/10.1186/s12913-018-2953-9\u003c/li\u003e\n \u003cli\u003eUmucu, E., Fortuna, K., Jung, H., Bialunska, A., Lee, B., Mangadu, T., Storm, M., Ergun, G., Mozer, D. A., \u0026amp; Brooks, J. (2022). A National Study to Assess Validity and Psychometrics of the Short Kessler Psychological Distress Scale (K6). \u003cem\u003eRehabilitation Counseling Bulletin\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(2), 140\u0026ndash;149. https://doi.org/10.1177/00343552211043261\u003c/li\u003e\n \u003cli\u003eVerdonk, P., Benschop, Y. W. M., de Haes, H. C. J. M., \u0026amp; Lagro-Janssen, T. L. M. (2009). From gender bias to gender awareness in medical education. \u003cem\u003eAdvances in Health Sciences Education\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 135\u0026ndash;152. https://doi.org/10.1007/s10459-008-9100-z\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2024a). Diminished Psychedelic Returns on Distress: Marital Status and Household Size. \u003cem\u003ePLoS ONE\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), 1\u0026ndash;23. https://doi.org/https://doi.org/10.1371/journal.pone.0293675\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2024b). Minorities\u0026rsquo; Diminished Psychedelic Returns: Cardio-Metabolic Health. \u003cem\u003eDrug Science, Policy and Law\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e, 1\u0026ndash;13. https://doi.org/doi.org/10.1177/20503245231225756\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2024c). Minorities\u0026rsquo; Diminished Psychedelic Returns: Gender, Perceived Stigma, and Distress. \u003cem\u003ePsychoactives\u0026nbsp;\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e, 303\u0026ndash;317. https://doi.org/10.3390/psychoactives3020019\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2024d). Minorities\u0026rsquo; Diminished Psychedelic Returns: Income and Educations Impact on Whites, Blacks, Hispanics, and Asians. \u003cem\u003eJournal of Race and Ethnic Health Disparities\u003c/em\u003e. https://doi.org/https://doi.org/10.1007/s40615-024-02023-y\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2024e). Religion, Psychedelics, Risky Behavior, and Violence. \u003cem\u003eJournal of Psychoactive Drugs\u003c/em\u003e, 1\u0026ndash;12. https://doi.org/10.1080/02791072.2024.2346132\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025a). American Indian Areas and Psychedelic Health Outcomes: A Test of the Minorities\u0026rsquo; Diminished Psychedelic Returns Theory. \u003cem\u003eJournal of Rural Mental Health\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e. https://doi.org/https://doi.org/10.1037/rmh0000302\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025b). Educational Moderation of Gender Disparities in Psychedelic Health Outcomes. \u003cem\u003eAcademia Mental Health and Well-Being\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(1). https://doi.org/10.20935/MHealthWellB7580\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025c). Minorities\u0026rsquo; diminished psychedelic returns: Depression, suicide, distress, and serious mental illness. \u003cem\u003eDrug Science, Policy and Law\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e. https://doi.org/10.1177/20503245251337357\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025d). Psychedelics and Mental Health Treatment Seeking Among Asians and Hawaiians.\u0026nbsp;\u003cem\u003ePsychoactives\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(32), 1\u0026ndash;15. https://doi.org/https://doi.org/10.3390/psychoactives4030032\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025e). Race and Gender Differences in the Moderating Relationship of Psychedelics on Stigma and Distress. \u003cem\u003ePsychedelic Medicine\u003c/em\u003e. https://doi.org/10.1089/psymed.2024.0021\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025f). The Medical Sociological and Social Epidemiological Psychedelics Paradigm (MSSEPP). \u003cem\u003eDrug Science, Policy and Law\u003c/em\u003e, \u003cem\u003eAccepted\u003c/em\u003e(Forthcoming).\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M. (2025g). The Relationships Between Healthcare Access, Gender, and Psychedelics and Their Effects on Distress. \u003cem\u003eHealthcare\u003c/em\u003e, \u003cem\u003e`1\u003c/em\u003e(10), 1158. https://doi.org/https://doi.org/10.3390/healthcare13101158\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M., \u0026amp; Stephens, A. L. (2023a). Minorities\u0026rsquo; diminished psychedelic returns. \u003cem\u003eDrug Science, Policy and Law\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e, 1\u0026ndash;19. https://doi.org/10.1177/20503245231184638\u003c/li\u003e\n \u003cli\u003eVi\u0026ntilde;a, S. M., \u0026amp; Stephens, A. L. (2023b). Psychedelics and workplace harm. \u003cem\u003eFrontiers in Psychiatry\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(JUNE), 1\u0026ndash;9. https://doi.org/10.3389/fpsyt.2023.1186541\u003c/li\u003e\n \u003cli\u003eWheaton, B. (2010). The Stress Process as a Successful Paradigm. In W. R. Avison, C. S. Aneshensel, S. Schieman, \u0026amp; B. Wheaton (Eds.), \u003cem\u003eAdvances in the Conceptualization of the Stress Process: Essays in Honor of Leonard I. Pearlin\u003c/em\u003e (pp. 231\u0026ndash;252). Springer. https://doi.org/10.1007/978-1-4419-1021-9\u003c/li\u003e\n \u003cli\u003eWilliams, M. T., Cabral, V., \u0026amp; Faber, S. (2023). Psychedelics and Racial Justice. \u003cem\u003eInternational Journal of Mental Health and Addiction\u003c/em\u003e. https://doi.org/10.1007/s11469-023-01160-5\u003c/li\u003e\n \u003cli\u003eZeifman, R. J., Singhal, N., Breslow, L., \u0026amp; Weissman, C. R. (2021). On the Relationship between Classic Psychedelics and Suicidality: A Systematic Review. In \u003cem\u003eACS Pharmacology and Translational Science\u003c/em\u003e (Vol. 4, Issue 2, pp. 436\u0026ndash;451). American Chemical Society. https://doi.org/10.1021/acsptsci.1c00024\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eTable 1. Descriptive Statistics for Dependent Variables, Independent Variables, and Controls (2008-2019) (weighted)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e% / min-max\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKey Predictor Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological Distress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e161,537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0-24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e484,732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo Health Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e63,390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e321,954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePublic Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e157,741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther Health Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9,635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLifetime Psychedelic Use\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34,224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsilocybin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38,475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAyahuasca\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePeyote/Mescaline\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13,091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35,666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClassic Psychedelic Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66,854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eControl Variables s\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e250,942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e484,732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1-24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFamily Income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e484,732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1-7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e134,007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e254,501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWidowed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28,908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDivorced/Separated\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67,316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChildren\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e484,043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0-3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e318,261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56,784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73,291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24,930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHawaiian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMulti-Racial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7,189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReligious Salience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e472,653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0-9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReligious Attendance in Days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e480,882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLifetime Drug Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCocaine\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78,221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStimulants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49,164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSedatives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40,022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTranquilizer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79,692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInhalants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42,851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePain Relievers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e174,374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHeroine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9,528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarijuana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e225,161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePCP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12,643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMDMA/ecstasy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44,156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTobacco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e277,750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge of First Alcohol Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e484,732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThrill Seeking Behavior\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e481,653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eSource: 2008-2019 National Survey of Drug Use and Health, \u003cem\u003en\u003c/em\u003e\u003cem\u003e=\u003c/em\u003e \u003cem\u003e484,732\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTable 2. Weighted Mean and Proportion Differences in Psychological Distress, Education, Health Insurance Coverage, and Lifetime Psychedelic Use by Insurance Status and Race/Ethnicity (White vs. Non-White; Black vs. Non-Black; Hispanic vs. Non-Hispanic; Asian vs. Non-Asian; NI/AN vs. Non-NI/AN; NHOPI vs. Non-NHOPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eNo Private Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003ePrivate Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNo Private Health Insurance (-) Private Health Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNo Public Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003ePublic Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNo Public Health Insurance (-) Public Health Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsychological Distress in Last Month (K6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e10.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(10.90-11.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(8.81-8.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.02-2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.44 - 9.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.70 - 9.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.43 - -0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eEducational Attainment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(2.26-2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.99-3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.74--0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.87 - 2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.47 - 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.38 - 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eHealth Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eUninsured\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.39-0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.39-0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.19 - 0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.19 - 0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePrivate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.77 - 0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.42 - 0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.34 - 0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePublic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.55-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.21-0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.34-0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eOther\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.06-0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06-0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03 - 0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03 - 0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLifetime Psychedelic Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.08-0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08 - 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04 - 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04 - 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsilocybin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.09-0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09-0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11 - 0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05 - 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05 - 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eAyahuasca\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePeyote/Mescaline\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.04-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04 - 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03 - 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00 - 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.11-0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10-0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01-0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11 - 0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.07 - 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04 - 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eClassic Psychedelics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.14-0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.14-0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.15 - 0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09 - 0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06 - 0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eNot White\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eWhite\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot White (-) White\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNot Black\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot Black (-) Black\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsychological Distress in Last Month (K6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e9.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e9.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e9.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e9.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(9.65-9.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.46-9.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11-0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.56-9.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.21-9.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.14-0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eEducational Attainment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(2.50-2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.87-2.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.37--0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.78-2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.49-2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.26-0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eHealth Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eUninsured\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.20-0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09-0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11-0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13-0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.16-0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.04--0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePrivate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.52-0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.73-0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.22--0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.68-0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.50-0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.16-0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePublic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.31-0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.33-0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.02--0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.31-0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.38-0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.08--0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eOther\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.03-0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03-0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.01--0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLifetime Psychedelic Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.05-0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08-0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.03--0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.07-0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03-0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsilocybin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.04-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.12-0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.08--0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10-0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08-0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00--0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eAyahuasca\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00-0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePeyote/Mescaline\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.02-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05-0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.04--0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03-0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.05-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13-0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.09--0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11-0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08-0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eClassic Psychedelics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.07-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.17-0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.11--0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.15-0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10-0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eNot Hispanic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHispanic \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot Hispanic (-) Hispanic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNot Asian\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot Asian (-) Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsychological Distress in Last Month (K6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e9.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e10.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(9.47\u0026ndash;9.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.90\u0026ndash;10.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.66\u0026ndash;\u0026ndash;0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.56\u0026ndash;9.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(8.93\u0026ndash;9.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.24\u0026ndash;0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eEducational Attainment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e2.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(2.84\u0026ndash;2.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.22\u0026ndash;2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.60\u0026ndash;0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.71\u0026ndash;2.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(3.32\u0026ndash;3.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.66\u0026ndash;\u0026ndash;0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eHealth Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eUninsured\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.28\u0026ndash;0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.18\u0026ndash;\u0026ndash;0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13\u0026ndash;0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09\u0026ndash;0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03\u0026ndash;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePrivate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.70\u0026ndash;0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.45\u0026ndash;0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.23\u0026ndash;0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.66\u0026ndash;0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.74\u0026ndash;0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.10\u0026ndash;\u0026ndash;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePublic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.33\u0026ndash;0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.27\u0026ndash;0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.33\u0026ndash;0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.19\u0026ndash;0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.12\u0026ndash;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eOther\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.01\u0026ndash;\u0026ndash;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.01\u0026ndash;\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLifetime Psychedelic Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsilocybin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eAyahuasca\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePeyote/Mescaline\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01\u0026ndash;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.11\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.11\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08\u0026ndash;0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eClassic Psychedelics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.15\u0026ndash;0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.08\u0026ndash;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.14\u0026ndash;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eNot NI/AN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNI/AN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot NI/AN (-)NI/AN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNot NHOPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003eNHOPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eNot NHOPI (-)NHOPI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsychological Distress in Last Month (K6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e9.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e11.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e10.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(9.53\u0026ndash;9.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(10.84\u0026ndash;11.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-2.31\u0026ndash;\u0026ndash;1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.54\u0026ndash;9.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(9.24\u0026ndash;10.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-1.19\u0026ndash;0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eEducational Attainment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(2.75\u0026ndash;2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.25\u0026ndash;2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.40\u0026ndash;0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.75\u0026ndash;2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(2.50\u0026ndash;2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eHealth Insurance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eUninsured\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.13\u0026ndash;0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13\u0026ndash;0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13\u0026ndash;0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.05\u0026ndash;\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePrivate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.66\u0026ndash;0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.35\u0026ndash;0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.26\u0026ndash;0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.66\u0026ndash;0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.56\u0026ndash;0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePublic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.32\u0026ndash;0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.40\u0026ndash;0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.13\u0026ndash;\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.32\u0026ndash;0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.28\u0026ndash;0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.03\u0026ndash;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eOther\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.13\u0026ndash;0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.15\u0026ndash;\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.02\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLifetime Psychedelic Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.01\u0026ndash;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.02\u0026ndash;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePsilocybin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.09\u0026ndash;0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09\u0026ndash;0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.03\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.09\u0026ndash;0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eAyahuasca\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.00\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003ePeyote/Mescaline\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.12\u0026ndash;0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.13\u0026ndash;\u0026ndash;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.04\u0026ndash;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.01\u0026ndash;0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.02\u0026ndash;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.10\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.05\u0026ndash;0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.02\u0026ndash;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eClassic Psychedelics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.14\u0026ndash;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.21\u0026ndash;0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(-0.13\u0026ndash;\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.14\u0026ndash;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.06\u0026ndash;0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e(0.03\u0026ndash;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eNote. Values are weighted means or proportions (95% confidence intervals in parentheses). Difference columns reflect first group minus second group, as labeled in the column headers. Post-estimation linear combination (LINCOM) tests were used to determine whether differences in group means or proportions were statistically significant (Long \u0026amp; Mustillo, 2018). This table presents a condensed summary of key sociodemographic differences; see Supplemental Tables 1\u0026ndash;4 for the full set of mean and proportion differences by insurance status and race/ethnicity, including additional substance use, marital status, income, age, religiosity, religious attendance, and other control variables.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSource: 2008-2019 National Survey of Drug Use and Health, n=\u003cem\u003e484,732\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e. Calculated with T-Tests\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e. Standard deviations in parentheses.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003ep \u0026lt; 0.10, \u003csup\u003e*\u003c/sup\u003ep \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003ep \u0026lt; 0.01, \u003csup\u003e***\u003c/sup\u003ep \u0026lt; 0.001 (two-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eTable 3. Weighted Ordinary Least Squares Regression Estimates of Mainline and Interaction Associations of Health Insurance and Psychedelic Use with Psychological Distress among the Total Population and by Race/Ethnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eMainline Associations\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePrivate Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePublic Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTwo-Way Interactions\u003c/p\u003e\n \u003cp\u003ePsychedelic (\u0026times;) Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThree-way Interactions\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eEducation (\u0026times;) Psychedelic (\u0026times;) Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTwo-Way Interactions\u003c/p\u003e\n \u003cp\u003ePsychedelic (\u0026times;) Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThree-way Interactions\u003c/p\u003e\n \u003cp\u003eEducation (\u0026times;) Psychedelic (\u0026times;) Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eTotal Population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.989***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.170**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.165*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.348**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.240*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.931***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.384*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.601***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.538*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.268**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.281*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.255*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.922***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e1.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;5.892*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.464***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.712*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.302*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.283*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.789***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eWhite, Non Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;1.166***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.357*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.081***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.0429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.446*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.888***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.516*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.345***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.328*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.061***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.362*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.547***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.528*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.756*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.273**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.358*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.893***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eBlack, Non-Hispanic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.884***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.319*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e1.608***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.658*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;2.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;1.084*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.330\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.634***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.0751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.573\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.485\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;11.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;4.666*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e2.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;20.21***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;3.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eAsian, Non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;1.145***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e1.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.0150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e8.965**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;6.434*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;3.056***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.589\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eNative Hawaiian or Pacific Islander (NHOPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e1.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.817**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;4.816*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e2.118*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.390*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;6.390**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;5.141**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.887**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.178*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.509*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;6.460*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026minus;3.219**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.713*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;3.700*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eNative Indian or Alaskan Native (NI/AN)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePublic insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eLCPU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.736\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eMDMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.419**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;4.425***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePsilocybin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eDMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;3.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eAyahuasca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePeyote/Mescaline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.534*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.092*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.890\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eLSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;2.349**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eNote: Table 3 reports selected coefficients from weighted ordinary least squares (OLS) models predicting psychological distress using data from the 2008\u0026ndash;2019 National Survey of Drug Use and Health (NSDUH). To conserve space and improve readability, the table presents key mainline associations and interaction terms only. Insurance mainline effects and LCPU coefficients are drawn from Model 2, while psychedelic mainline effects are drawn from Model 4 of the corresponding supplemental models. Interaction terms reflect the insurance \u0026times; psychedelic and insurance \u0026times; education \u0026times; psychedelic specifications.\u003c/p\u003e\n \u003cp\u003eAll coefficients shown were estimated in the underlying models. Blank cells indicate terms that were\u0026nbsp;\u003cem\u003enot estimable\u003c/em\u003e for a given subgroup or specification (e.g., due to limited cell size or model convergence), rather than omitted or excluded.\u003cbr\u003e\u0026nbsp;Full regression results\u0026mdash;including all estimated coefficients, standard errors, and model fit statistics\u0026mdash;are available in Supplemental Tables 5\u0026ndash;21.\u003c/p\u003e\n \u003cp\u003e*p \u0026lt; .05, **p \u0026lt; .01, ***p \u0026lt; .001 (two-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Medicine, race, ethnicity, psychedelics, inequality, distress","lastPublishedDoi":"10.21203/rs.3.rs-8483640/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8483640/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"While prior research suggests that healthcare context shapes the mental health correlates of psychedelic use, it remains unclear whether education can mitigate these disparities—particularly across racial and ethnic groups. This study examines whether educational attainment moderates the association between lifetime psychedelic use, health insurance context (public vs. private), and psychological distress, and whether these patterns vary by race/ethnicity. Using nationally representative data from the National Survey on Drug Use and Health (2008–2018; N = 484,732), we estimate ordinary least squares regression models stratified by racial and ethnic group. Results indicate that higher education is associated with lower psychological distress among psychedelic users primarily when paired with private insurance, a pattern observed most consistently among White respondents. In contrast, among individuals relying on public insurance, educational attainment offers little protection against elevated distress. A notable exception emerges among Native Hawaiian and Pacific Islander respondents, for whom higher education is associated with reduced distress despite public insurance coverage. Taken together, these findings suggest that education alone is insufficient to offset structurally patterned inequalities in healthcare and that the mental health correlates of psychedelic use remain contingent on institutional context.","manuscriptTitle":"Can Education Compensate for Poor Healthcare? Racial Inequalities in Psychedelic-Associated Psychological Distress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-14 12:41:51","doi":"10.21203/rs.3.rs-8483640/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cf6bf544-4eca-405e-a2f7-ec6bfb907ade","owner":[],"postedDate":"January 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-14T12:41:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-14 12:41:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8483640","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8483640","identity":"rs-8483640","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}