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Hope and empowerment are key elements of recovery in the context of serious mental illnesses (SMI). We examined predictors of hope among individuals with SMI and tested a hypothesized path model in which perceived social status and perceived discrimination adversely impact hope, directly and through their impacts on depressive symptoms. Data from 232 individuals with SMI receiving care in public-sector settings were used in both a multiple linear regression (predicting Herth Hope Scale scores), and in path analyses examining both direct and indirect effects of perceived social status (Social Status Ladder) and perceived discrimination (Everyday Discrimination Scale). Depressive symptoms, perceived social status, and perceived discrimination were predictive of hope. Path analyses revealed that perceived social status has a direct effect on hope and empowerment but also impacts hope through its effects on depression. Similarly, perceived everyday discrimination affects hope and empowerment, though this effect is mediated through its effects on depression. Two alternative models and a trimmed hypothesized model did not fit the data or improve fit. These social determinants of mental health should provoke program and policy change to improve mental health and enhance recovery among persons with SMI.

The New York City Department of Health and Mental Hygiene (Health Department) has responded to an article that claimed their workforce discriminated against Asian restaurants during the early months of the COVID-19 pandemic. The Health Department conducted an investigation and found no evidence of bias against Asian restaurants in their inspectional data. They also criticized the authors of the article for using an incomplete dataset and not reaching out for assistance or collaboration. The Health Department presented their own analysis of inspection results, which showed no evidence of an uptick in violations among Asian restaurants. They concluded that the findings of the article are erroneous and rejected the accusations of discrimination. [Extracted from the article]

Aim: Premorbid substance use is widely recognized as a crucial factor in early psychosis. We explored the effects of childhood/adolescent adversity on premorbid tobacco, alcohol, and cannabis use. We hypothesized that adversity in childhood would be associated with an increased likelihood of use, and amount of intake, of tobacco, alcohol, and cannabis. We analysed which domains of adversity have the greatest impact. Methods: First‐episode psychosis patients were enrolled from six inpatient psychiatric units in Atlanta, Georgia and Washington, D.C. Premorbid substance use was thoroughly measured, and childhood/adolescent adversity was rated using 14 scales/subscales. Factor analysis was used to reduce these scales/subscales to the three domains of adversity (termed Violence and Environmental Adversity, Interpersonal Abuse, and Neglect and Lack of Connectedness). Regression analyses determined associations between adversity domains and premorbid substance use. Results: Our sample (n = 247) primarily consisted of African Americans (86.2%) and males (74.5%). Violence and Environmental Adversity was significantly associated with five of six substance use variables and marginally associated with the sixth. Interpersonal Abuse was unassociated with substance use, and Neglect and Lack of Connectedness was associated only with a lower likelihood cannabis use. When Violence and Environmental Adversity results were stratified by gender, effects on tobacco use and amount of tobacco use were stronger among females. Conclusions: Childhood/adolescent trauma and adversity have meaningful associations with premorbid substance use in first‐episode psychosis patients. First‐episode psychosis and clinical high‐risk treatment settings may benefit from expanding the assessment of childhood/adolescent adversity to include factors pertaining to violence exposure and adversities beyond abuse and neglect. [ABSTRACT FROM AUTHOR]

Background: Individuals with serious mental illness (SMI) are over-represented in the criminal justice system. One factor that impacts likelihood of incarceration is criminal thinking, and the Criminal Sentiments Scale – Modified (CSSM) has been shown to predict recidivism. However, no one has examined the CSS-M in outpatients with schizophrenia and other psychotic disorders, and little is known about what predicts high CSS-M scores. Methods: The data for the current investigation comes from a larger sample of individuals with SMI receiving services from outpatient mental health clinics who were enrolled in a randomized-controlled trial. The CSS-M was verbally administered to everyone during a baseline assessment. The 264 individuals in the sample all have a diagnosis of schizophrenia or another psychotic disorder, and all had been arrested in the last five years. We first explored the impact of demographic factors and adverse childhood experiences (ACE) on CSS-M scores. For the 258 participants with complete data for all five sub-scales (attitudes towards law, attitudes towards courts, attitudes towards police, tolerance for law violations, and identification with criminal others), we conducted a hierarchical analysis using Ward’s method to explore and define the number of clusters. We determined the number of clusters using the Elbow method. We then repeated the cluster analysis using a non-hierarchical method with the K-means technique and fixing the number of clusters to three. Results: The current sample exhibited considerably higher CSS-M scores than those previously published (mean = 32.0±14.4). The total CSS-M score demonstrated high reliability (alpha = 0.898), and four of the sub-scales exhibited moderate to high reliability (α,Law = 0.741; α,Courts = 0.808; α,Police = 0.762; α,TLV = 0.696). When controlling for age, race, gender, and ACE score, the multiple linear regression model accounted for 8.6% of the variability in total CSS-M score (p < 0.001), though only ACE score and age were significant predictors (β = 0.218, p = 0.001; β = -0.167, p = 0.008, respectively). The cluster analysis produced three clusters. Given that the ICO sub-scale had the lowest Cronbach’s alpha (α = 0.328), we repeated the cluster analysis process with the four other sub-scales, which confirmed the three clusters. An ANOVA with the four sub-scales and total CSS-M score showed that the three clusters could be defined as those with low, medium, and high scores on the scales. Confirming the results from the MLR, an ANOVA of the three clusters with ACE scores (F= 4.49, p = 0.012) and age (F = 3.77, p = 0.024) were both significant. Discussion: The average total CSS-M score is considerably higher than previous investigations. Both high ACE scores and younger age significantly predicted higher CSS-M scores. Because CSS-M scores have been shown to predict recidivism, it is critical to further understand the foundation of these negative attitudes towards the criminal justice system to prevent the continued over-representation of people with serious mental illness in the criminal justice system. [ABSTRACT FROM AUTHOR]

Problem/condition: Each year, state and local public health departments report hundreds of foodborne illness outbreaks associated with retail food establishments (e.g., restaurants or caterers) to CDC. Typically, investigations involve epidemiology, laboratory, and environmental health components. Health departments voluntarily report epidemiologic and laboratory data from their foodborne illness outbreak investigations to CDC through the National Outbreak Reporting System (NORS); however, minimal environmental health data from outbreak investigations are reported to NORS. This report summarizes environmental health data collected during outbreak investigations and reported to the National Environmental Assessment Reporting System (NEARS)., Period Covered: 2017-2019., Description of System: In 2014, CDC launched NEARS to complement NORS surveillance and to use these data to enhance prevention efforts. State and local health departments voluntarily enter data from their foodborne illness outbreak investigations of retail food establishments into NEARS. These data include characteristics of foodborne illness outbreaks (e.g., etiologic agent and factors contributing to the outbreak), characteristics of establishments with outbreaks (e.g., number of meals served daily), and food safety policies in these establishments (e.g., ill worker policy requirements). NEARS is the only available data source that collects environmental characteristics of retail establishments with foodborne illness outbreaks., Results: During 2017-2019, a total of 800 foodborne illness outbreaks associated with 875 retail food establishments were reported to NEARS by 25 state and local health departments. Among outbreaks with a confirmed or suspected agent (555 of 800 [69.4%]), the most common pathogens were norovirus and Salmonella, accounting for 47.0% and 18.6% of outbreaks, respectively. Contributing factors were identified in 62.5% of outbreaks. Approximately 40% of outbreaks with identified contributing factors had at least one reported factor associated with food contamination by an ill or infectious food worker. Investigators conducted an interview with an establishment manager in 679 (84.9%) outbreaks. Of the 725 managers interviewed, most (91.7%) said their establishment had a policy requiring food workers to notify their manager when they were ill, and 66.0% also said these policies were written. Only 23.0% said their policy listed all five illness symptoms workers needed to notify managers about (i.e., vomiting, diarrhea, jaundice, sore throat with fever, and lesion with pus). Most (85.5%) said that their establishment had a policy restricting or excluding ill workers from working, and 62.4% said these policies were written. Only 17.8% said their policy listed all five illness symptoms that would require restriction or exclusion from work. Only 16.1% of establishments with outbreaks had policies addressing all four components relating to ill or infectious workers (i.e., policy requires workers to notify a manager when they are ill, policy specifies all five illness symptoms workers need to notify managers about, policy restricts or excludes ill workers from working, and policy specifies all five illness symptoms requiring restriction or exclusion from work)., Interpretation: Norovirus was the most commonly identified cause of outbreaks reported to NEARS, and contamination of food by ill or infectious food workers contributed to approximately 40% of outbreaks with identified contributing factors. These findings are consistent with findings from other national outbreak data sets and highlight the role of ill workers in foodborne illness outbreaks. Although a majority of managers reported their establishment had an ill worker policy, often these policies were missing components intended to reduce foodborne illness risk. Contamination of food by ill or infectious food workers is an important cause of outbreaks; therefore, the content and enforcement of existing policies might need to be re-examined and refined., Public Health Action: Retail food establishments can reduce viral foodborne illness outbreaks by protecting food from contamination through proper hand hygiene and excluding ill or infectious workers from working. Development and implementation of policies that prevent contamination of food by workers are important to foodborne outbreak reduction. NEARS data can help identify gaps in food safety policies and practices, particularly those concerning ill workers. Future analyses of stratified data linking specific outbreak agents and foods with outbreak contributing factors can help guide the development of effective prevention approaches by describing how establishments' characteristics and food safety policies and practices relate to foodborne illness outbreaks., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were reported.