A growing number of studies suggest that migrant and ethnic minority populations are at higher risk for being diagnosed with psychosis. However, the reasons why have been disputed. This study aims to explore different interpretations of the observed higher rates of psychosis diagnosis among immigrants and ethnic minorities in some parts of the world. We sought to examine these interpretations through a critical lens, acknowledging the social underpinnings of discourses and their power to shape real-world practices. Peer-reviewed editorials, commentaries and letters regarding the topics of interest were retrieved from database searches and subjected to a pattern-based critical discourse analysis. Across a 30-year span of literature, conceptualizations and explanations of higher psychosis rates amongst migrant and minoritized populations evolved in relation to the larger social context, at times opposing one another. Three discursive themes were identified, reflecting intersecting explanations: institutional racism in psychiatry; psychiatry as a scientific discipline that sees and treats all patients equally; and the social locus of high rates. Tensions surrounding psychiatry as a field, including issues of evidence, biological reductionism, and the conceptualization of psychiatric nosological categories have played out within the evolution of this discourse. Exploring how discursive constructions in relation to psychosis and minoritization have been shaped by historical and social factors, we consider the role of local and global dynamics of social power in favouring one explanatory model over another and how these may have affected efforts to prevent and better treat psychosis amongst immigrant and minoritized groups.

This paper introduces the Team Card (TC) as a protocol to address harmful biases in the development of clinical artificial intelligence (AI) systems by emphasizing the often-overlooked role of researchers' positionality. While harmful bias in medical AI, particularly in Clinical Decision Support (CDS) tools, is frequently attributed to issues of data quality, this limited framing neglects how researchers' worldviews-shaped by their training, backgrounds, and experiences-can influence AI design and deployment. These unexamined subjectivities can create epistemic limitations, amplifying biases and increasing the risk of inequitable applications in clinical settings. The TC emphasizes reflexivity-critical self-reflection-as an ethical strategy to identify and address biases stemming from the subjectivity of research teams. By systematically documenting team composition, positionality, and the steps taken to monitor and address unconscious bias, TCs establish a framework for assessing how diversity within teams impacts AI development. Studies across business, science, and organizational contexts demonstrate that diversity improves outcomes, including innovation, decision-making quality, and overall performance. However, epistemic diversity-diverse ways of thinking and problem-solving-must be actively cultivated through intentional, collaborative processes to mitigate bias effectively. By embedding epistemic diversity into research practices, TCs may enhance model performance, improve fairness and offer an empirical basis for evaluating how diversity influences bias mitigation efforts over time. This represents a critical step toward developing inclusive, ethical, and effective AI systems in clinical care. A publicly available prototype presenting our TC is accessible at https://www.teamcard.io/team/demo.

The Brief Jail Mental Health Screen (BJMHS) is one of the most well-known and frequently used tools to conduct routine mental health screening at jail intake. In prior research, the BJMHS results typically have been evaluated overall (i.e., yes/no positive screen). However, there is heterogeneity in symptom presentation and treatment histories among people with serious mental illness, and there are potential consequences of this heterogeneity for mental health administration and policy in jails. We conducted a latent class analysis of BJMHS item-level results using administrative data for 37,998 people booked into a southeastern, metropolitan, U.S. county jail over a 3.5-year period. A 4-class solution provided the best fitting and most interpretable model. The largest class (89.5%) comprised people unlikely to report symptoms or treatment histories (limited symptoms). The next class comprised people who were unlikely to report ongoing symptoms but reported medication and hospitalization (managed symptoms). The third class (2.5%) included people likely to report feeling useless/sinful, prior hospitalization, and current psychiatric medication (depressive symptoms). The fourth class (1.0%) comprised people likely to report thought control, paranoia, feeling useless/sinful, medication, and hospitalization (psychotic symptoms). Controlling for sociodemographic and booking characteristics, people in the managed, depressive, and psychotic symptoms classes had significantly longer jail stays compared to those in the limited symptoms class. People in the managed and depressive symptoms classes were at heightened risk of re-arrest compared to the limited symptoms class. Findings can inform case prioritization and the allocation of resources to support efficient and effective jail-based mental health services.

Mental illness is a significant public health concern prevalent in America. Over one in five U.S. adults are affected, yet less than half receive treatment. Among African Americans, only one in three seek treatment with statically lower rates among Black males. Therefore, an accurate diagnosis is crucial for appropriate treatment, while misdiagnosis leads to stigma, discrimination, and untreated illness. This paper examines the implications of misdiagnosing trauma responses in Black men, highlighting systemic biases that impede suitable care and perpetuate negative narratives. The authors propose a conceptual framework incorporating historical trauma, discrimination, and traumatic stress reactions, emphasizing the need for cultural competence and humility. This framework involves public narratives that influence perceptions and judgments, reviewing research evidence, advocating for competent trauma assessments, community empowerment, and future research directions. This paper underscores the importance of understanding and addressing the unique challenges Black men face in mental health diagnosis and treatment.

Neuropsychiatric symptoms (NPS) are nearly universal in dementia; some cross-sectional studies of NPS in dementia have found racial/ethnic differences, though it is unknown if NPS prevalence differs among racial/ethnic groups before and after dementia diagnosis.

Participants were followed annually at Alzheimer's Disease Centers and were assessed on the Neuropsychiatric Inventory-Questionnaire (NPI-Q) with at least one follow-up visit at which they were diagnosed with dementia. Descriptive statistics were generated by race/ethnicity. NPS were modeled over time as a function of race/ethnicity and with diagnosis date as the baseline.

NPS were present in 95% in at least one time point. After adjusting for covariates, there were no statistically significant differences in NPI-Q total scores among racial/ethnic groups at the time of and after dementia diagnosis.

Findings from our prospective cohort study suggest that when individuals are matched at the time of conversion to dementia, there are no racial/ethnic differences in NPS.

Neuropsychiatric symptoms of dementia are frequent and increase caregiver burden.Prior studies reported more neuropsychiatric symptoms (NPS) in Black compared to White individuals with dementia.National Alzheimer's Coordinating Center Black, White, and Hispanic participants did not differ in NPS at the time of dementia diagnosis.

Racial disparities in diagnosis and treatment are prevalent in child psychiatry, including disparate diagnosis rates of internalizing and externalizing disorders in Black and White children. However, limited research has investigated mechanisms that contribute to these disparities. This study examined child racial implicit associations in psychiatric clinicians and medical students to address this gap.

Psychiatrists and trainees completed an online survey including 2 race Implicit Association Tests (IATs) pairing child faces to words with either positive or negative valence, and words related to internalizing or externalizing behavioral problems. Psychiatrists and trainees' demographic predictors of implicit associations were also investigated.

Data were analyzed from 235 psychiatrists and trainees (112 child and adolescent psychiatrists and fellows) who met inclusion criteria. Psychiatrists and trainees demonstrated greater moderate-to-strong association between Black child faces and "bad" (ie, negatively valenced) words (44.3%) vs "good" (ie, positively valenced) words (6.4%), and between externalizing words (41.7%) vs internalizing words (7.2%). Psychiatrists and trainees' demographic characteristics including being female (β = -0.12; 95% CI = -0.23 to -0.01; p < .05), Black (β = -0.36; 95% CI = -0.54 to -0.18; p < .001), or an attending physician (β = -0.26; 95% CI = -0.45 to -0.06; p = .01) were significant predictors of decreased association between Black child faces and negative valence words. Being female was a significant predictor of decreased association between Black child faces and externalizing words (β = -0.26; 95% CI = -0.45 to -0.06; p = .01).

Participating psychiatrists and trainees demonstrated bias toward associating Black rather than White child faces with negative words and externalizing behavioral problems. Future research should examine the following: racial implicit associations in a more generalizable sample; the relationship between race IATs and provider behavior; and interventions to reduce racial inequities in psychiatry, including individual and systemic solutions.

We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper received support from a program designed to increase minority representation in science.

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.g., image, text, speech, genetic data, physiological signals) is imperative to facilitate a comprehensive disease analysis, a topic of burgeoning interest among both researchers and clinicians in recent times. Hence, there exists a pressing need to synthesize the latest strides in multi-modal data and AI technologies in the realm of medical diagnosis. In this paper, we narrow our focus to five specific disorders (Alzheimer's disease, breast cancer, depression, heart disease, epilepsy), elucidating advanced endeavors in their diagnosis and treatment through the lens of artificial intelligence. Our survey not only delineates detailed diagnostic methodologies across varying modalities but also underscores commonly utilized public datasets, the intricacies of feature engineering, prevalent classification models, and envisaged challenges for future endeavors. In essence, our research endeavors to contribute to the advancement of diagnostic methodologies, furnishing invaluable insights for clinical decision making.

Black Americans have lower rates of depression and anxiety than Whites, despite greater exposure to stressors known to negatively impact mental health, characterized as the Black-White mental health paradox. This study revisited the paradox during the coronavirus pandemic. Drawing on stress process theory, minority stress theory, and the rejection-identification model of discrimination, in-group identity, and well-being, we analyzed original survey data from a quota sample of African American and White adults (N = 594). The survey included a range of stressors and coping resources, including those relevant to the pandemic (e.g., COVID-19 illness) and race (e.g., witnessing anti-Black police violence). Results indicate that despite African Americans' greater exposure and vulnerability to racial discrimination, the Black-White mental health paradox holds, owing in part to protective effects of African American's higher self-esteem. Directions for future exploration of the paradox are presented based on this study's findings.

Under the Stop, Question, and Frisk (SQF) policy, New York City (NYC) police stopped Black Americans at more than twice the rate of non-Hispanic whites, after controlling for arrests and precinct differences. We examined whether police stops of Black Americans during SQF correspond positively with psychiatric emergency department (ED) visits among Black residents in NYC. We utilized as the exposure all police stops, stops including frisking, and stops including use of force among Black Americans in NYC between 2006 and 2015 from the New York City Police Department's New York City-Stop, Question, and Frisk database. We examined 938,356 outpatient psychiatric ED visits among Black Americans in NYC between 2006 and 2015 from the Statewide Emergency Department Database (SEDD). We applied Box-Jenkins time-series methods to control for monthly temporal patterns. Results indicate that all stops, frisking, and use of force of Black residents correspond with increased psychiatric ED visits among Black Americans in NYC (all stops-coef = 0.024, 95%CI = 0.006, 0.043; frisking-coef = 0.048, 95%CI = 0.015, 0.080; use of force-coef = 0.109, 95%CI = 0.028, 0.190). Our findings indicate that a one standard deviation increase in police stops equates to a 2.72% increase in psychiatric ED visits among Black residents in NYC. Use of force may have the greatest mental health consequences due to perceived threats of physical violence or bodily harm to other members of the targeted group. Racially biased and unconstitutional police encounters may have acute mental health implications for the broader Black community not directly involved in the encounter itself.

Extensive research has demonstrated racial disparities, particularly among Black individuals, in both presentation and course of psychosis spectrum disorders. Few studies, however, have examined racial differences in the clinical high-risk (CHR) phase of illness. It is unclear if functional deficits seen in association with CHR symptoms generalize to marginalized racial groups, or whether race may play a role in the link between symptoms and functioning. In a sample of youth at CHR (N = 46), the present study examined the effect of race (Black and White represented in this sample) on the relation between CHR symptoms and social/role functioning. Race had a moderating effect on the relation between CHR symptoms and social functioning for total positive symptom score (p < .04, f² = 0.10). Although positive symptoms were associated with worse social functioning for White participants, no association was found for Black participants. Follow up analyses indicated suspiciousness was a statistically significant predictor of social functioning for White participants but was unrelated to functioning for Black participants. Results may be indicative of phenomenon experienced by individuals within racial minority groups (e.g., "healthy suspiciousness") or potential measurement validity concerns. Findings further the understanding of racial differences in the CHR phase of illness among White and Black youth and highlight limitations of the existing CHR literature and assessment tools for diverse youth.

The Hierarchical Taxonomy of Psychopathology (HiTOP) uses factor analysis to group people with similar self-reported symptoms (i.e., like-goes-with-like). It is hailed as a significant improvement over other diagnostic taxonomies. However, the purported advantages and fundamental assumptions of HiTOP have received little, if any scientific scrutiny. We critically evaluated five fundamental claims about HiTOP. We conclude that HiTOP does not demonstrate a high degree of verisimilitude and has the potential to hinder progress on understanding the etiology of psychopathology. It does not lend itself to theory-building or taxonomic evolution, and it cannot account for multifinality, equifinality, or developmental and etiological processes. In its current form, HiTOP is not ready to use in clinical settings and may result in algorithmic bias against underrepresented groups. We recommend a bifurcation strategy moving forward in which the DSM is used in clinical settings while researchers focus on developing a falsifiable theory-based classification system.

Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses in stroke literature to assess the geographic distribution of datasets and patient cohorts used to train these models and compare them to stroke distribution to evaluate for disparities.

582 studies were identified on initial searching of the PubMed database. Of these studies, 106 full texts were assessed after title and abstract screening which resulted in 489 papers excluded. Of these 106 studies, 79 were excluded due to using cohorts from outside the United States or being review articles or editorials. 27 studies were thus included in this analysis.

Of the 27 studies included, 7 (25.9%) used patient data from California, 6 (22.2%) were multicenter, 3 (11.1%) were in Massachusetts, 2 (7.4%) each in Illinois, Missouri, and New York, and 1 (3.7%) each from South Carolina, Washington, West Virginia, and Wisconsin. 1 (3.7%) study used data from Utah and Texas. These were qualitatively compared to a CDC study showing the highest distribution of stroke in Mississippi (4.3%) followed by Oklahoma (3.4%), Washington D.C. (3.4%), Louisiana (3.3%), and Alabama (3.2%) while the prevalence in California was 2.6%.

It is clear that a strong disconnect exists between the datasets and patient cohorts used in training machine learning algorithms in clinical research and the stroke distribution in which clinical tools using these algorithms will be implemented. In order to ensure a lack of bias and increase generalizability and accuracy in future machine learning studies, datasets using a varied patient population that reflects the unequal distribution of stroke risk factors would greatly benefit the usability of these tools and ensure accuracy on a nationwide scale.

Racial and ethnic disparities are well documented in psychiatry, yet suboptimal understanding of underlying mechanisms of these disparities undermines diversity, inclusion, and education efforts. Prior research suggests that implicit associations can affect human behavior, which may ultimately influence healthcare disparities. This study investigated whether racial implicit associations exist among medical students and psychiatric physicians and whether race/ethnicity, training level, age, and gender predicted racial implicit associations.

Participants completed online demographic questions and 3 race Implicit Association Tests (IATs) related to psychiatric diagnosis (psychosis vs. mood disorders), patient compliance (compliance vs. non-compliance), and psychiatric medications (antipsychotics vs. antidepressants). Linear and logistic regression models were used to identify demographic predictors of racial implicit associations.

The authors analyzed data from 294 medical students and psychiatric physicians. Participants were more likely to pair faces of Black individuals with words related to psychotic disorders (as opposed to mood disorders), non-compliance (as opposed to compliance), and antipsychotic medications (as opposed to antidepressant medications). Among participants, self-reported White race and higher level of training were the strongest predictors of associating faces of Black individuals with psychotic disorders, even after adjusting for participant's age.

Racial implicit associations were measurable among medical students and psychiatric physicians. Future research should examine (1) the relationship between implicit associations and clinician behavior and (2) the ability of interventions to reduce racial implicit associations in mental healthcare.

Young Black gay/bisexual men (YBGBM) are a highly marginalized population across multiple health outcomes. Most research on YBGBM health has focused on HIV/sexual health, but there is a demonstrable need for research examining racism and psychosocial functioning among this population. Racialized Sexual Discrimination (RSD), also known as sexual racism, is an important but under-investigated phenomenon that may have implications for the psychological health and well-being of YBGBM. This paper provides an overview of empirical research on RSD as experienced by gay/bisexual men of color in online partner-seeking venues. First, the researchers discuss how racialized experiences are a documented online phenomenon, with a variety of manifestations, and identify the potential effects that this phenomenon may have on the psychosocial health of YBGBM, and gay/bisexual men of color as a whole. Second, the researchers synthesize the RSD literature with a broader literature examining psychological well-being across race and sexual orientation. Third, the researchers present a theoretically grounded conceptual model detailing the pathways between RSD and psychological well-being using a stress and coping framework. The paper concludes with recommendations for future research on this topic, including scale development and hypothesis testing.

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.

Many studies have attempted to discriminate patients with schizophrenia from healthy controls by machine learning using structural or functional MRI. We included both structural and diffusion MRI (dMRI) and performed random forest (RF) and support vector machine (SVM) in this study.

We evaluated the performance of classifying schizophrenia using RF method and SVM with 504 features (volume and/or fractional anisotropy and trace) from 184 brain regions. We enrolled 47 patients and 23 age- and sex-matched healthy controls and resampled our data into a balanced dataset using a Synthetic Minority Oversampling Technique method. We randomly permuted the classification of all participants as a patient or healthy control 100 times and ran the RF and SVM with leave one out cross validation for each permutation. We then compared the sensitivity and specificity of the original dataset and the permuted dataset.

Classification using RF with 504 features showed a significantly higher rate of performance compared to classification by chance: sensitivity (87.6% vs. 47.0%) and specificity (95.9 vs. 48.4%) performed by RF, sensitivity (89.5% vs. 48.0%) and specificity (94.5% vs. 47.1%) performed by SVM.

Machine learning using RF and SVM with both volume and diffusion measures can discriminate patients with schizophrenia with a high degree of performance. Further replications are required.

A decade has passed since the National Institute of Mental Health initiated its landmark Real Men Real Depression public education campaign. Despite increased awareness, depressed African American men continue to underutilize mental health treatment and have the highest all-cause mortality rates of any racial/ethnic group in the United States. We review a complex array of socio-cultural factors, including racism and discrimination, cultural mistrust, misdiagnosis and clinician bias, and informal support networks that contribute to treatment disparities. We identify clinical and community entry points to engage African American men. We provide specific recommendations for frontline mental health workers to increase depression treatment utilization for African American men. Providers who present treatment options within a frame of holistic health promotion may enhance treatment adherence. We encourage the use of multidisciplinary, community-based participatory research approaches to test our hypotheses and engage African American men in clinical research.

Screening for emotional distress is important, but not widely available. This study assesses the utility of the Refugee Health Screener 15 (RHS-15) in a public health setting. Refugee Health Screener 15 and diagnostic proxy (DP) instruments assessing anxiety, depression, and posttraumatic stress disorder were administered to refugees from 3 countries at their public health examination. Properties of the RHS-15 and its components were evaluated utilizing appropriate methods. Scale Cronbach α was 0.95, and a factor analysis identified 1 factor accounting for 66% of scale variance. Refugee Health Screener 15 scores and cases discriminated between refugee groups similar to DPs. Refugee Health Screener 15 case sensitivity and specificity to DPs were acceptable (≥0.87/0.77). A shorter, 13-item component had acceptable metric properties. The RHS-15 appears to be a valid screener for emotional distress of refugees. The 13-item scale may be more efficient and as efficacious for case identification. The critical public health need and recommendations for implementation are discussed.

Although blacks are more likely than whites to experience posttraumatic stress disorder (PTSD) after a natural disaster, the reasons for this disparity are unclear. This study explores whether race is associated with PTSD after adjusting for differences in preexisting vulnerabilities, exposure to stressors, and loss of social support due to Hurricane Katrina using a representative sample of 279 black and white adult current and past smokers who were present when Hurricane Katrina struck, and identified it as the most traumatic event in their lifetime. Multiple logistic regression models evaluated whether differential vulnerability (pre-hurricane physical and mental health functioning, and education level), differential exposure to hurricane-related stressors, and loss of social support deterioration reduced the association of race with PTSD. Blacks were more likely than whites to screen positive for PTSD (49 vs. 39 %, respectively, p = 0.030). Although blacks reported greater pre-hurricane vulnerability (worse mental health functioning and lower educational attainment) and hurricane-related stressor exposure and had less social support after the hurricane, only pre-hurricane mental health functioning attenuated the association of race with screening positive for PTSD. Thus, racial differences in pre-hurricane functioning, particularly poorer mental health, may partially explain racial disparities in PTSD after natural disasters, such as Hurricane Katrina. Future studies should examine these associations prospectively using representative cohorts of black and whites and include measures of residential segregation and discrimination, which may further our understanding of racial disparities in PTSD after a natural disaster.

Racial discrimination is related to depression, anxiety, and severe psychological distress, and evidence drawn from studies emanating from the United Kingdom and The Netherlands suggest racial discrimination is also related to clinical psychosis and subthreshold psychotic symptoms in racial and ethnic minority (REM) populations. The present study sought to determine the association between racial discrimination experiences and attenuated positive psychotic symptoms (APPS) in a United States (US) urban, predominantly immigrant and REM young adult population.

A cohort of 650 young adults was administered a self-report inventory for psychosis risk [i.e., Prodromal Questionnaire (PQ)], and the Experiences of Discrimination Questionnaire. The PQ allowed the dimensional assessment of APPS, as well as the categorical assessment of a potentially "high risk" group (i.e., 8 or more APPS endorsed as distressing), the latter of which was based on previous validation studies using the structured interview for prodromal syndromes. The relations between self-reported racial discrimination and APPS, and racial discrimination and "high" distressing positive PQ endorsement were determined, while accounting for anxiety and depression symptoms.

Racial discrimination was significantly associated with APPS and with significantly higher odds of endorsing eight or more distressing APPS, even after adjusting for anxiety and depression symptoms.

The present study provides preliminary evidence that racial discrimination among US ethnic minorities may be associated with APPS, as well as potentially higher risk for psychosis.

. To examine racial-ethnic differences in the endorsement and attribution of psychotic-like symptoms in a nationally representative sample of African-Americans, Asians, Caribbean Blacks, and Latinos living in the USA.

Data were drawn from a total of 979 respondents who endorsed psychotic-like symptoms as part of the National Latino and Asian American Study (NLAAS) and the National Survey of American Life (NSAL). We use a mixed qualitative and quantitative analytical approach to examine sociodemographic and ethnic variations in the prevalence and attributions of hallucinations and other psychotic-like symptoms in the NLAAS and NSAL. The lifetime presence of psychotic-like symptoms was assessed using the World Health Organization Composite International Diagnostic Interview (WMH-CIDI) psychotic symptom screener. We used logistic regression models to examine the probability of endorsing the four most frequently occurring thematic categories for psychotic-like experiences by race/ethnicity (n > 100). We used qualitative methods to explore common themes from participant responses to open ended questions on their attributions for psychotic-like symptoms.

African-Americans were significantly less likely to endorse visual hallucinations compared to Caribbean Blacks (73.7% and 89.3%, p < .001), but they endorsed auditory hallucinations symptoms more than Caribbean Blacks (43.1% and 25.7, p < .05). Endorsing delusions of reference and thought insertion/withdrawal were more prevalent for Latinos than for African-Americans (11% and 4.7%, p < .05; 6.3% and 2.7%, p < .05, respectively). Attribution themes included: supernatural, ghosts/unidentified beings, death and dying, spirituality or religiosity, premonitions, familial and other. Respondents differed by race/ethnicity in the attributions given to psychotic like symptoms.

Findings suggest that variations exist by race/ethnicity in both psychotic-like symptom endorsement and in self-reported attributions/understandings for these symptoms on a psychosis screening instrument. Ethnic/racial differences could result from culturally sanctioned beliefs and idioms of distress that deserve more attention in conducting culturally informed and responsive screening, assessment and treatment.

This study examined racial differences among male outpatients with severe mental illness on therapeutic support, mental health service utilization, and service satisfaction. A total of 530 participants (289 white, 179 black, and 62 of another race) across three large mental health centers (two state funded and one federally funded) in Connecticut were examined cross-sectionally. No racial differences were found in therapeutic support, and there were essentially no racial differences in service satisfaction. Black clients reported greater use of substance abuse inpatient services than White clients and clients of other racial minorities reported greater use of mental health inpatient services than White clients, but differences were small. These findings suggest there are few racial differences in the reported quality of mental health care and service utilization among male outpatients with severe mental illness. More research is needed on where and under what circumstances health disparities exist.

The clinical interview is critical in the diagnostic assessment undertaking in clinical settings, and cultural/ethnic influences have been shown to influence the outcome of this process. Specifically, a number of studies have reported that proportionally far more ethnic minorities than Caucasians are likely to be misdiagnosed when assessed for psychiatric disorders. This particularly is the case when open clinical interviews are used. Semistructured interviews, on the other hand, result in an increase in diagnostic accuracy with ethnic minorities. Parameters associated with bias in the clinical interview of ethnic minorities and its impact on assessment, diagnosis, and treatment decisions are examined. Although the current discussion focuses primarily on African Americans, many examples are provided that pertain to other ethnic groups. Strategies for addressing these issues are explored and recommendations for increasing cultural competence are made. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

Several studies have reported that ethnic differences influence psychiatric diagnoses. Some previous studies reported that African Americans and Hispanics are diagnosed with schizophrenia spectrum disorders more frequently than Caucasians, and that Caucasians are more likely to be diagnosed with affective disorders than other ethnic groups. We sought to identify associations between sociodemographic factors and psychiatric diagnosis.

We retrospectively examined the medical records of all psychiatric inpatients (ages over 18 years) treated at Kern county mental hospital (n=2,051) between July 2003 and March 2007 for demographic, clinical information, and discharge diagnoses.

African American and Hispanic males were more frequently diagnosed with schizophrenia spectrum disorders than Caucasians, whereas Caucasian females were more frequently diagnosed with affective disorders than females in the other ethnic groups, suggesting that patient ethnicity and gender may influence clinical diagnoses. Demographic variables, that is, a lower education, failure of marriage, homelessness, and low quality insurance, were found to be significantly associated with a diagnosis of schizophrenia spectrum disorders after adjusting for clinical variables. And, the presence of a family psychiatric history, failure of marriage, not-homelessness, and quality insurance were found to be associated with a diagnosis of affective disorders.

Our results show that these demographic factors, including ethnicity, have effects on diagnoses in psychiatric inpatients. Furthermore, these variables may help prediction of psychiatric diagnoses.

Robust screening measures that perform well in different populations could help improve the accuracy of diagnosis of pediatric bipolar disorder. Changes in sampling could influence the performance of items and potentially influence total scores enough to alter the predictive utility of scores. Additionally, creating a brief version of a measure by extracting items from a longer scale might cause differential functioning due to context effects. The authors of current study examined both sampling and context effects of a brief measure of pediatric mania. Caregivers of 813 youths completed the parent-reported version of the General Behavior Inventory (PGBI) at an academic medical center sample enriched for mood disorders. Caregivers of 481 youths completed the PGBI at a community mental health center. Caregivers of 799 youths completed 10 items extracted from the PGBI at a community setting. Caregivers of 159 youths completed both versions of the PGBI and a semistructured diagnostic interview. Differential item functioning indicated that across samples some items functioned differently; however, total observed scores were similar across all levels of mania. Receiver operating characteristic analysis indicated that the 10 extracted items discriminated bipolar disorder from nonbipolar behavior as well as when the items were embedded within the full measure. Findings suggest that the extracted items perform similarly to the embedded items in the community setting. Measurement properties appear sufficiently robust across settings to support clinical applications.

Racial differences in the clinical nature of major depressive disorder (MDD) could contribute to treatment disparities, but national data with large samples are limited. Our objective was to examine black-white differences in clinical characteristics and treatment for MDD from one of the largest, national community samples of US adults.

Non-Hispanic black and white adults (n=32752) from the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions produced data on 1866 respondents who met criteria for MDD based on the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) in the preceding 12 months. Outcome measures were depressive symptoms, comorbid psychiatric and medical disorders, disability, and treatment.

Blacks with MDD had significantly higher odds of initial insomnia, early-morning awakening, and restlessness than whites. Odds of hypertension (odds ratio [OR), 2.16; 95% confidence interval [CI], 1.48-3.14), obesity (OR, 1.98; 95% CI, 1.45-2.69), and liver disease (OR, 3.68; 95% CI, 1.20-11.30) were higher among blacks than whites. In unadjusted models, blacks had greater impairment than whites in social and physical functioning. However, adjusting for sociodemographic characteristics eliminated these differences. Blacks were less likely than whites to receive outpatient services (OR, 0.51; 95% CI, 0.36-0.72) and be prescribed medications for MDD, but were more likely to receive emergency room and inpatient treatment.

We found few racial differences in depressive symptoms, psychiatric comorbidity, and disability after adjusting for sociodemographic factors. Blacks' lower utilization of ambulatory treatment for MDD and greater medical comorbidity, emergency department use, and hospitalization suggests that management of MDD among blacks should be emphasized in primary care or other settings where treatment is more accessible.

The incidence of psychotic disorders is extremely high in several immigrant groups in Europe. This article describes the epidemiological evidence for increased incidence rates among immigrants compared with nonimmigrant populations and explores possible explanations for this excess risk. Potential causes not only involve factors acting at the level of the individual, but encompass the broader social context of neighborhoods and ethnic groups. Growing up and living in a disadvantaged ethnic minority position, characterized by a low social status, high degree of discrimination against the group and low neighborhood ethnic density, may lead to an increased risk of psychotic disorders, especially when individuals reject their minority status and when their social resources are insufficient to buffer the impact of adverse social experiences. Future research should refine measures of the social context, adopt a life-course perspective and should integrate social and neurobiological pathways.

To examine five types of child maltreatment and other risk correlates to establish associations with anxiety and/or depression confirmed or suspected in children investigated by child welfare services.

The present study used the data of a subsample of 10-15-year-olds (n = 4,381) investigated by child welfare services across Canada obtained from the Canadian Incidence Study of Reported Child Abuse and Neglect-2003. The analysis took into account the nested structure of the data by considering the variability existing among families and the clustering of siblings within them. Several models were analyzed for the construction of the presented hierarchical model. Striving for parsimony, we included only statistically significant variables in the final model.

The strongest associations were found with child substance abuse, substantiated emotional maltreatment, primary caregiver's mental health problems, and substantiated sexual abuse. Among the child maltreatment variables, substantiated physical abuse and substantiated exposure to domestic violence did not show any statistically significant associations with anxiety and/or depression in the model.

This analysis helped us in understanding child maltreatment and other adverse experiences in childhood that were related to anxiety and/or depression, which can further aid in the development of mental health and child welfare policies and programs.

The study aim was to identify and describe health consumer perspectives on social barriers to care for eating disorders in an ethnically diverse sample.

We conducted an exploratory secondary analysis of qualitative data comprising transcripts from semi-structured interviews with past and prospective consumers of eating disorder treatment (n = 32). Transcripts were inputted into NVivo 8 for coding, sorting, and quantifying thematic content of interest within strata defined by ethnic minority and non-minority participants. We then examined the influence of key social barriers-including stigma and social stereotypes-on perceived impact on care.

The majority of respondents (78%) endorsed at least one social barrier to care for an eating or weight concern. Perceived stigma (or shame) and social stereotyping-identified both within social networks and among clinicians-had adversely impacted care for 59% and 19% of respondents, respectively.

Social barriers to care for eating and weight related concerns may be prevalent in the U.S. and impact both ethnic minority and non-minority health care consumers.

Few studies have compared treatment outcomes of African-American, Hispanic, and non-Hispanic white patients with bipolar disorder. The U.S. Systematic Treatment Enhancement Program for Bipolar Disorder compared one-year outcomes for bipolar I or II disorder from each of these racial-ethnic groups.

African Americans (N=155) were retrospectively compared with a matched group of non-Hispanic whites (N=729), and Hispanics (N=152) were compared with a separate matched group of non-Hispanic whites (N=822). Response and recovery outcomes were examined. Survival analysis was used to compare time to treatment response for depression (Montgomery-Asberg Depression Rating Scale) and mania (Young Mania Rating Scale) as well as global assessment of functioning (Global Assessment of Functioning).

For manic and depressive symptoms, time to response and proportion of responders were similar across groups. Over the study year the proportion of days well was similar across groups. A smaller proportion of African Americans met criteria for improved global functioning. Depression response among African Americans with psychotic symptoms was slower than the response among African Americans without psychotic symptoms and among non-Hispanic whites with or without psychotic symptoms. No differences between Hispanics and non-Hispanic whites in response times and recovery were observed.

Results are consistent with U.S. clinical trials for other psychiatric disorders, which have reported similar outcomes for ratings of primary symptoms. Baseline psychotic symptoms are likely a significant contributor when African Americans with bipolar disorder are slow to recover. These results may be less generalizable to uninsured patients.

Compare the risk for schizophrenia in immigrants to countries of recent and longstanding immigration. Compare prevalence and incidence rates in black subjects under different conditions.

An electronic literature search was complemented by review articles and cross-references. Studies reporting standard diagnosis and incidence or prevalence rates were included.

Immigrants had an increased risk for schizophrenia in countries of longstanding immigration, but with lower risk ratios than in those of recent immigration. The risk was higher in black immigrants and the black population living in the United States. But incidence and prevalence rates in Africa and the Caribbean were similar to those of international studies.

Comparing the most recent generation of immigrants with descendants of previous ones may account for the lower risk ratios observed in countries of longstanding vs. recent immigration. Two neurobiological hypotheses are proposed to explain the epidemiological findings in black populations and in immigrants.

The authors detail the public health need for depression prevention research and the decisions made in designing an experiment testing problem solving therapy as "indicated" preventive intervention for high-risk older adults with subsyndromal depression. Special attention is given to the recruitment of African Americans because of well-documented inequalities in mental health services and depression treatment outcomes between races.

A total of 306 subjects (half white, half African American) with scores of 16 or higher on the Center for Epidemiological Studies of Depression Scale, but with no history of major depressive disorder in the past 12 months, are being recruited and randomly assigned to either problem solving therapy-primary care or to a dietary education control condition. Time to, and rate of, incident episodes of major depressive disorder are to be modeled using survival analysis. Level of depressive symptoms will be analyzed via a mixed models approach.

Twenty-two subjects have been recruited into the study, and to date eight have completed the randomly assigned intervention and postintervention assessment. Four of 22 have exited after developing major depressive episodes. None have complained about study procedures or demands. Implementation in a variety of community settings is going well.

The data collected to date support the feasibility of translating from epidemiology to RCT design and implementation of empirical depression prevention research in later life.

Ethnicity effects on diagnoses are frequently reported and have variably been attributed to diagnostic biases versus ethnic differences in environmental exposures, and other factors.

We compared best-estimate gold standard research diagnoses to clinical diagnoses (DSM-III-R and DSM-IV criteria) among 129 white, 57 African American, and 50 Hispanic patients with psychosis admitted to an inpatient research unit from 1990 to 2003.

Clinical and research diagnoses showed greater agreement in Hispanic than in African American patients (white patients were intermediate). Diagnostic agreement for paranoid schizophrenia was likewise the best in Hispanic patients. While paranoid schizophrenia tended to be overdiagnosed in African American patients, it was underdiagnosed in white patients. Patterns of diagnostic agreement for schizoaffective disorder and "other" diagnoses were similar among the 3 ethnic groups.

Diagnostic unreliability may explain the excess of paranoid schizophrenia reported for African Americans. Further research is needed to elucidate the influence of ethnicity on clinical diagnosis before other theories to explain group differences can be reasonably proposed and reliably tested.

This study describes the mental health status of community-living frail elders in Michigan and identifies subgroups of individuals who are vulnerable to mental health problems.

We analyzed the baseline assessment data collected from older adults who were admitted to two community-based long-term-care programs in Michigan (N = 18,939).

Results show that 40.5% of the individuals in the sample have recognized mental disorders, 39.6% use psychotropic medications, 24.5% have probable depression, and 1.4% have self-injury thoughts or attempts. Frail elders who are White, younger, and female - as well as those who experience more pain, disease burden, cognitive impairment, and limitations in instrumental activities of daily living - are more prone to psychological distress.

Mental health care is greatly needed by community-living frail elders.