Black Men, Structural Racism, Cultural Barriers: Structural Equation Model With Cognitive-Behavioral Implications

The frequent police killings during the COVID-19 pandemic forced a reckoning among Americans from all backgrounds and propelled the Black Lives Matter movement into a global force. This manuscript addresses major issues to aid practitioners in the effective treatment of African Americans via the lens of Critical Race Theory and the Bioecological Model. We place the impacts of racism on Black families in historical context and outline the sources of Black family resilience. We critique structural racism embedded in all aspects of psychology and allied fields. We provide an overview of racial socialization and related issues affecting the parenting decisions in Black families, as well as a detailed overview of impacts of structural racism on couple dynamics. Recommendations are made for engaging racial issues in therapy, providing emotional support and validation to couples and families experiencing discrimination and racial trauma, and using Black cultural strengths as therapeutic resources.

2020 Rise to the challenge

Mental health care among marginalized populations in the United States

Perceived Effectiveness of Medications Among Mental Health Service Users With and Without Alcohol Dependence

Race-Ethnicity as a Predictor of Attitudes Toward Mental Health Treatment Seeking

Previous research on mental health disparities shows that persons from racial-ethnic minority groups have less access to mental health care, engage in less treatment, and receive poorer-quality treatment than non-Hispanic whites. Attitudes and beliefs about mental health treatment were examined to determine whether they contribute to these disparities. Data from the National Comorbidity Survey Replication (NCS-R) were analyzed to determine attitudes toward treatment-seeking behavior among people of non-Hispanic white, African-American, and Hispanic or Latino race-ethnicity. Additional sociodemographic variables were examined in relation to attitudes and beliefs toward treatment. African-American race-ethnicity was a significant independent predictor of greater reported willingness to seek treatment and lesser reported embarrassment if others found out about being in treatment. These findings persisted when analyses adjusted for socioeconomic variables. Hispanic or Latino race-ethnicity also was associated with an increased likelihood of willingness to seek professional help and lesser embarrassment if others found out, but these differences did not persist after adjustment for the effects of socioeconomic variables. Contrary to the initial hypothesis, African Americans and Hispanics or Latinos may have more positive attitudes toward mental health treatment seeking than non-Hispanic whites. To improve access to mental health services among racial-ethnic minority groups, it is crucial to better understand a broader array of individual-, provider-, and system-level factors that may create barriers to care.

Racism Is a Modifiable Risk Factor: Relationships Among Race, Ethnicity, and Colorectal Cancer Outcomes

Disproportionate Use of Psychiatric Emergency Services by African Americans

transfer, create conditions for the establishment of farmers' behavioral psychological contracts in the process of agricultural land transfers, and guide farmers to establish relationship psychological contracts. The second is to improve the market system, properly cultivate and develop agricultural land transfer intermediaries, reduce transaction costs, and reduce the probability of farmers' psychological contracts being broken. The third is to guide farmers to establish a positive agricultural land transfer psychology based on their resource endowments such as labor force quality and cultural quality, and encourage farmers to make agricultural land transfer decisions such as subcontracting, leasing, reselling, and interchanging.

This study assessed the prevalence, diagnosis, and treatment of major depressive disorder and generalized anxiety disorder among New York City adults. As part of the first community-specific Health and Nutrition Examination Survey in the United States, depression and anxiety were assessed in a representative sample of 1,817 noninstitutionalized adults in 2004. A total of 8% had major depressive disorder and 4% had generalized anxiety disorder. Respondents with depression were more likely to be formerly married, publicly insured, younger, and U.S. born. Only 55% of adults with depression were diagnosed, and 38% of those with depression or anxiety were in treatment; individuals with a diagnosis of depression were more likely to receive treatment than those without a diagnosis (61% versus 7%; p<.001). Immigrants with depression were 60% less likely to be diagnosed than their U.S.-born counterparts; immigrants arriving in this country ten or more years ago had slightly more anxiety than immigrants arriving less than ten years ago (3% versus 2%, not significant). Among respondents with anxiety, 23% reported disability compared with 15% of those with depression. Compared with adults with neither diagnosis, adults with depression or anxiety were twice as likely to smoke tobacco (p<.05), adults with depression were twice as likely to have diabetes (p<.01), and those with anxiety were twice as likely to have asthma (p<.01). Mental disorders are often disabling and inadequately diagnosed and treated. Foreign-born adults experience barriers to diagnosis and treatment despite having less depression; anxiety may increase with time since immigration. Increased awareness of and linkage to mental health services are needed, especially in larger, more diverse urban communities.

The purposes of this dissertation were to examine trends from 2008 to 2014 in mental health and substance use disorders and treatment receipt, and explore factors associated with treatment receipt in pregnant women aged 18-44 years in the United States. A systematic review showed that illicit drug use disorder increased in pregnant women over the past decade. Despite the increase in treatment admissions for these disorders from 1992 to 2012, the overall treatment admission rate for pregnant women remained relatively stable (4%). In a trend study, compared mental health and substance use disorders and treatment receipt across Matched groups of pregnant (n = 5,520) and non-pregnant women (n = 11,040) who participated in the 2008-2014 National Survey on Drug Use and Health (NSDUH) did not differ on mental health and substance use disorders and treatment receipt. Past-year anxiety disorder, past-month psychological distress, and illicit drug use disorder increased in the total sample from 2008 to 2014, whereas trends in treatment receipt did not change over time. Secondary analysis of data from the same survey was conducted with data from pregnant women (1,106 with mental health problems and 521 with substance use disorders). Predictors of mental health treatment receipt included: mental health problems, college education, health insurance, and White ethnicity. Predictors of substance use treatment receipt were: illicit drug abuse/dependence, alcohol dependence, comorbid anxiety/depression, White ethnicity, and urban residency. Compared to Whites, nonWhite pregnant women with mental health and/or substance use disorders had lower odds of receiving mental health treatment.

Race and measures of structural racism are associated with higher prevalence of diabetes at the census-tract level, but pathways and targets for intervention are unclear. To investigate the direct and indirect associations of race and 2 measures of structural racism (historic and contemporary) with prevalence of diabetes at the census-tract level. Cross-sectional study of 15 190 US census tracts across 157 counties within 50 states and Washington, DC conducted September 2025 to February 2026. Historic structural racism was defined as historic redlining using the Home Owners' Loan Corporation neighborhood grades (score between 1 = best and 4 = redlined) overlayed on present-day census tracts. Contemporary structural racism was defined using the structural racism effect index (SREI), a summary score of 9 domains (built environment, criminal justice, education, employment, housing, income and/or poverty, social cohesion, transportation, and wealth). African American or Black race was defined as proportion within a census tract based on American Community Survey 2019 data. Diabetes prevalence from the US Centers for Disease Control and Prevention Population Level Analysis and Community Estimates 2019 dataset was the main outcome. Structural equation modeling was used to investigate direct and indirect associations between race and both measures of structural racism. Analyses were completed using standardized estimates (β), which are interpreted as the change in SD associated with 1 SD increase in the variable. Among 15 190 census tracts, mean (SD) diabetes prevalence across census tracts was 11.8% (4.9%), and a mean (SD) of 26.7% (31.4%) of the population within census tracts was African American or Black. Both historic (β = 0.02; 95% CI, -0.05 to 0.08; P = .001) and contemporary (β = 0.56; 95% CI, 0.51 to 0.61; P < .001) measures of structural racism were directly associated with higher diabetes prevalence. Historic structural racism was indirectly associated with higher diabetes prevalence via the pathway of contemporary structural racism (β = 0.17; 95% CI, 0.15 to 0.20; P < .001). Contemporary structural racism showed a stronger association compared with historic structural racism for the pathway through which African American or Black race was associated with higher diabetes prevalence (β = 0.58; 95% CI, 0.52 to 0.63 vs β = 0.18; 95% CI, 0.14 to 0.22; both P < .001). African American or Black race, historic structural racism, and contemporary structural racism were associated with higher diabetes prevalence at the census-tract level in the US. Domains of contemporary structural racism as measured by the SREI are potential targets for future interventions.

On Structural Racism and Mental Illness

Finding a Medical Home for Perinatal Depression: How Can We Bridge the Postpartum Gap?

As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: (i) development of a previously created postpartum obesity modeling; (ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity. The most significant correlations obtained were between BMI and other substantial variables in the SEM analysis. The research framework included two categories of data related to postpartum women: living in urban and rural areas in Iran. The SEM output with the Bayesian estimator was 81.1%, with variations in the postpartum women’s BMI, which is related to their demographics, lifestyle, food intake, and mental health. Meanwhile, the variation based on SEM with partial least squares estimator was equal to 70.2%, and SEM with a maximum likelihood estimator was equal to 76.8%. On the other hand, the output of the root mean square error (RMSE), mean absolute error (MSE) and mean absolute percentage error (MPE) for the Bayesian estimator is lower than the maximum likelihood and partial least square estimators. Thus, the predicted values of the SEM with Bayesian estimator are closer to the observed value compared to maximum likelihood and partial least square. In conclusion, the higher values of R-square and lower values of MPE, RMSE, and MSE will produce better goodness of fit for SEM with Bayesian estimators.