Predictors of mental health among U.S. adults during COVID-19 early pandemic, mid- pandemic, and post-vaccine eras.

BACKGROUND: A collective trauma like COVID-19 impacts individuals differently due to socio-contextual and individual characteristics. Younger adults, minorities, affiliates of certain political parties, and residents of some regions of the United States reported experiencing poorer mental health during the pandemic. Being diagnosed with COVID-19, or losing a friend/family to it, was related to more adverse mental health symptoms. While the negative impact of COVID-19 on health outcomes has been studied, mental health changes during this pandemic need further exploration. METHODS: In a study of 8,612 U.S. households, using three surveys collected from a nationally representative panel between May 2020 and October 2021, using a repeated cross-sectional design, a linear mixed effect regression model was performed to investigate factors associated with the mental health status, based on the Mental Health Inventory-5, of individuals throughout different phases of the COVID-19 pandemic, and whether an improvement over time, especially after vaccines became available, was observed. RESULTS: An overall improvement in mental health was observed after vaccines became available. Individuals with no COVID-related death in their household, those not wearing masks, those identifying as members of the Republican Party, race/ethnicities other than Asian, men, older adults, and residents of the South were less likely than others to report mental health challenges. CONCLUSIONS: Our results highlight the need for widespread mental health interventions and health promotion to address challenges during the COVID-19 pandemic and beyond. Due to the worse mental health observed among Asians, younger adults, women, low-income families, those with a higher level of concern for COVID-19, people who lost someone to COVID-19, and/or individuals with histories of opioid use disorder and criminal legal involvement, over the period of this study, targeted attention needs to be given to the mental health of these groups.

Recommended Mental Health Practices for Individuals Interacting With U.S. Police, Court, Jail, Probation, and Parole Systems.

OBJECTIVE: Tens of millions of individuals with mental health problems interact with the U.S. criminal legal system (including 911, police, jail detention and sentences, courts, and probation and parole) each year. The authors sought to identify recommended mental health practices for criminal legal system-involved individuals and report the percentages of U.S. counties and of the U.S. population living in counties in which each recommended practice is present. METHODS: Recommended practices for criminal legal-involved individuals with mental health problems were identified from meta-analyses, reviews, and best practice recommendations. Up to four respondents per county (i.e., jail, probation, community mental health, and community substance use treatment administrators) from 950 counties were asked whether each recommended practice was present for criminal legal-involved individuals. Weighted percentages of U.S. counties using recommended practices and of the U.S. population living in counties with each recommended practice are reported. RESULTS: Fifty-nine recommended practices, including general mental health approaches (e.g., permanent supportive housing, Medicaid continuity) and diagnosis-specific mental health treatments (including medications and psychotherapies), were identified. Weighted data from respondents (N=791 from 519 counties) indicated that each recommended practice was present for criminal legal-involved individuals in only 21.9%-43.0% of U.S. counties. CONCLUSIONS: These results inform implementation efforts by indicating the presence of recommended care practices for criminal legal-involved individuals with mental health problems in counties nationwide. Because supportive housing, access to Medicaid reactivation in jails, and psychosocial interventions for physical pain have low presence but high importance for recovery, implementation efforts might first target these approaches.

Impact of County-level health infrastructure on participation in a reform effort to reduce the use of jail for individuals with mental health disorders.

BACKGROUND: The national Stepping Up Initiative has attracted over 500 counties interested in reducing the use of jail for individuals with mental health disorders. This paper identifies socioeconomic, criminal legal, and health care factors that predict the likelihood of counties joining Stepping Up. RESULTS: After performing variable selection, logistic regression models were performed on 3,141 U.S. counties. Counties designated as medically underserved and/or mental health staffing shortage areas were less likely to participate in this initiative. Logistic regression models showed that larger counties (populations over 250,000) with better health care infrastructure, more mental health providers per capita, higher percent of Medicaid funded drug treatment services, and at least one medical school, were more likely to join Stepping Up. These counties had lower per capita jail populations, higher concentration of police resources, and higher pretrial incarceration rate. CONCLUSIONS: County-level health care delivery factors are major contributors to a county's likelihood, or willingness, of engaging in Stepping Up reform efforts to reduce jail population with mental health disorders issues. Therefore, improving availability and accessibility of medical and behavioral health care in different communities, may facilitate efforts to address the unnecessary incarceration of individuals with mental health disorders.

What Matters More in Explaining Drug Court Graduation and Rearrest: Program Features, Individual Characteristics, or Some Combination.

This study examines the program- and individual-level factors that impact the success of drug court clients in terms of: (1) graduation; and (2) not being arrested while participating in the court program. The data consist of 848 individuals in nine drug courts. This paper discusses how different individual- and program-level factors impact the success of drug court participants. The findings suggest that individual- and program-level factors are both important in predicting program graduation and arrest during drug court participation, while controlling for participant demographics. Clients' education, drug/alcohol usage, program staffing, and clinical standards impact program graduation while criminal history, drug/alcohol usage, number of program hours offered, program staffing, and use of rewards and sanctions predict in-program arrest. Models combining both program- and individual-level factors performed better than either alone, leading to recommendations that agencies should emphasize improving program quality while targeting clients' needs to achieve greater success.

The relationship between community public health, behavioral health service accessibility, and mass incarceration.

BACKGROUND: The relationship between healthcare service accessibility in the community and incarceration is an important, yet not widely understood, phenomenon. Community behavioral health and the criminal legal systems are treated separately, which creates a competing demand to confront mass incarceration and expand available services. As a result, the relationship between behavioral health services, demographics and community factors, and incarceration rate has not been well addressed. Understanding potential drivers of incarceration, including access to community-based services, is necessary to reduce entry into the legal system and decrease recidivism. This study identifies county-level demographic, socioeconomic, healthcare services availability/accessibility, and criminal legal characteristics that predict per capita jail population across the U.S. More than 10 million individuals pass through U.S. jails each year, increasing the urgency of addressing this challenge. METHODS: The selection of variables for our model proceeded in stages. The study commenced by identifying potential descriptors and then using machine learning techniques to select non-collinear variables to predict county jail population per capita. Beta regression was then applied to nationally available data from all 3,141 U.S. counties to identify factors predicting county jail population size. Data sources include the Vera Institute's incarceration database, Robert Wood Johnson Foundation's County Health Rankings and Roadmaps, Uniform Crime Report, and the U.S. Census. RESULTS: Fewer per capita psychiatrists (z-score = -2.16; p = .031), lower percent of drug treatment paid by Medicaid (-3.66; p < .001), higher per capita healthcare costs (5.71; p < .001), higher number of physically unhealthy days in a month (8.6; p < .001), lower high school graduation rate (-4.05; p < .001), smaller county size (-2.66, p = .008; -2.71, p = .007; medium and large versus small counties, respectively), and more police officers per capita (8.74; p < .001) were associated with higher per capita jail population. Controlling for other factors, violent crime rate did not predict incarceration rate. CONCLUSIONS: Counties with smaller populations, larger percentages of individuals that did not graduate high school, that have more health-related issues, and provide fewer community treatment services are more likely to have higher jail population per capita. Increasing access to services, including mental health providers, and improving the affordability of drug treatment and healthcare may help reduce incarceration rates.

Assessing the reliability and validity of the Risk-Need-Responsivity (RNR) program tool.

BACKGROUND: Fidelity assessment tools can assess whether a program embraces a core set of principles and performs well. A quality fidelity tool with valid scales can be a feedback loop to identify areas that need further work to improve the program. Using data collected from 1816 correctional and reentry programs in the United States in the construction sample and 761 programs in the confirmation sample, this study examined the internal consistency of the Risk-Need-Responsivity (RNR) Program Tool, an online resource to capture information about structural features of a program. RESULTS: The study reports on reliability statistics and factor analyses to highlight individual subscales. Six scales emerged and had acceptable to excellent levels of internal consistency. These scales are staffing, reward-and-sanction, clinical standards for programs, coaching, program duration, and risk-need assessment. CONCLUSIONS: This article discusses fidelity scales from the RNR Program Tool and provides guidance on the importance of tool development processes to ensure accurate, valid, and reliable scales. The purpose of the RNR Program Tool is to create a modern, online tool integrating both the empirical (research) literature on effective practices and clinical standards on quality programming. This process minimizes the need for consultants by giving program administrators the ability to gather information on their programs, score them, and receive instant and targeted feedback with recommendations for improvement to assess their programs against empirical standards in the field. Furthermore, it provides a standardized tool that administrators can use to examine what type of individuals fare better in their programs. The provided targeted feedback can give the programs the ability to seek technical assistance or guidance in specific areas that can strategically strengthen their program.

Substance use and firearm access among college freshmen.

OBJECTIVE: Examine the proportion of students with rapid firearm access and associations with recent alcohol and marijuana use. PARTICIPANTS: Cross-sectional data from college freshmen (n = 183) in 2020 who participated in the Mason: Health Starts Here study. METHODS: Using logistic regression, associations were examined between past 30-day substance use and access to firearms within 15-min. RESULTS: More than 10% of students could rapidly access a firearm, 53% of whom were current binge drinkers, compared to 13% of those who could not rapidly access firearms. Non-Hispanic White students (AOR = 4.1, 95%CI = 1.3,12.7) and past 30-day binge drinkers (AOR = 6.4, 95%CI = 2.1,19.7) had greater odds of having rapid firearm access. Age, sex, and past 30-day marijuana use were not associated with rapid access. CONCLUSIONS: A notable proportion of students had rapid firearm access, which was strongly associated with recent binge drinking. Campus prevention programs should consider how their alcohol and firearm policies could be enhanced to prevent violence/self-harm.

Drivers of County Engagement in Criminal Justice-Behavioral Health Initiatives.

Several large, county-level initiatives are underway to improve behavioral health care for justice-involved clients. Unfortunately, only about a quarter of counties participate in these efforts, leaving justice-involved populations at risk of poor mental health, substance use, and judicial outcomes. This study examined characteristics of 2,922 U.S. counties and county equivalents by whether they participated in these initiatives and found that crime and socioeconomic characteristics were not associated with participation. Participating counties had significantly more robust mental health and substance use care delivery systems. Nonparticipating counties may lack the expertise and basic delivery system prerequisites needed for participation in most national initiatives, further driving geographic disparities.

Protocol for the Mason: Health Starts Here prospective cohort study of young adult college students.

BACKGROUND: Young adulthood is a period of increasing independence for the 40% of young adults enrolled in U.S. colleges. Previous research indicates differences in how students' health behaviors develop and vary by gender, race, ethnicity, and socioeconomic status. George Mason University is a state institution that enrolls a highly diverse student population, making it an ideal setting to launch a longitudinal cohort study using multiple research methods to evaluate the effects of health behaviors on physical and psychological functioning, especially during the COVID-19 pandemic. RESULTS: Mason: Health Starts Here was developed as a longitudinal cohort study of successive waves of first year students that aims to improve understanding of the natural history and determinants of young adults' physical health, mental health, and their role in college completion. The study recruits first year students who are 18 to 24 years old and able to read and understand English. All incoming first year students are recruited through various methods to participate in a longitudinal cohort for 4 years. Data collection occurs in fall and spring semesters, with online surveys conducted in both semesters and in-person clinic visits conducted in the fall. Students receive physical examinations during clinic visits and provide biospecimens (blood and saliva). CONCLUSIONS: The study will produce new knowledge to help understand the development of health-related behaviors during young adulthood. A long-term goal of the cohort study is to support the design of effective, low-cost interventions to encourage young adults' consistent performance of healthful behaviors, improve their mental health, and improve academic performance.

Protocol for a quasi-experimental, 950 county study examining implementation outcomes and mechanisms of Stepping Up, a national policy effort to improve mental health and substance use services for justice-involved individuals.

BACKGROUND: The criminal justice system is the largest provider of mental health services in the USA. Many jurisdictions are interested in reducing the use of the justice system for mental health problems. The national Stepping Up Initiative helps agencies within counties work together more effectively to reduce the number of individuals with mental illness in jails and to improve access to mental health services in the community. This study will compare Stepping Up counties to matched comparison counties over time to (1) examine the effectiveness of Stepping Up and (2) test hypothesized implementation mechanisms to inform multi-agency implementation efforts more broadly. METHODS: The study will survey 950 counties at baseline, 18 months, and 36 months in a quasi-experimental design comparing implementation mechanisms and outcomes between 475 Stepping Up counties and 475 matched comparison counties. Surveys will be sent to up to four respondents per county including administrators of jail, probation, community mental health services, and community substance use treatment services (3800 total respondents). We will examine whether Stepping Up counties show faster improvements in implementation outcomes (number of justice-involved clients receiving behavioral health services, number of behavioral health evidence-based practices and policies [EBPPs] available to justice-involved individuals, and resources for behavioral health EBPP for justice-involved individuals) than do matched comparison counties. We will also evaluate whether engagement of hypothesized mechanisms explains differences in implementation outcomes. Implementation target mechanisms include (1) use of and capacity for performance monitoring, (2) use and functioning of interagency teams, (3) common goals and mission across agencies, and (4) system integration (i.e., building an integrated system of care rather than adding one program or training). Finally, we will characterize implementation processes and critical incidents using survey responses and qualitative interviews. DISCUSSION: There are few rigorous, prospective studies examining implementation mechanisms and their relationship with behavioral health implementation outcomes in justice and associated community behavioral health settings. There is also limited understanding of implementation mechanisms that occur across systems with multiple goals. This study will describe implementation outcomes of Stepping Up and will elucidate target mechanisms that are effective in multi-goal, multi-agency systems.

Learning Analytics to Assess Beliefs about Science: Evolution of Expertise as Seen through Biological Inquiry.

Epistemological beliefs about science (EBAS) or beliefs about the nature of science knowledge, and how that knowledge is generated during inquiry, are an essential yet difficult to assess component of science literacy. Leveraging learning analytics to capture and analyze student practices in simulated or game-based authentic science activities is a potential avenue for assessing EBAS. Our previous work characterized inquiry practices of experts and novices engaged in simulated authentic science inquiry and suggested that practices may reflect EBAS. Here, we extend our prior qualitative work to quantitatively examine differences in practices and EBAS between non-science majors, biology majors, and biology graduates. We observed that inquiry practices of non-science majors and biology graduates were similar to the novice and expert practices, respectively, in our prior work. However, biology majors sometimes appeared to act like their undergraduate peers (e.g., performing fewer planning actions) but other times were more similar to biology graduates (e.g., performing complex investigations). We noted that cognitive constructs like metacognition were also important for understanding which practices were most likely to be reflective of EBAS. This work advances how to assess EBAS using learning analytics and raises questions regarding the development of cognitive processes like EBAS among aspiring biologists.

Multilevel Matching in Natural Experimental Studies: Application to Stepping up Counties.

Among many approaches for selecting match control cases, few methods exist for natural experiments (Li, Zaslavsky & Landrum, 2007), especially when studying clustered or hierarchical data. The lack of randomization of treatment exposure gives importance to using proper statistical procedures that control for individual differences. In this natural experimental study, which has a hierarchical structure, we plan to evaluate the efforts of 455 counties across the United States to make targeted efforts to improve mental health services and reduce jail utilization over time. Nested within states, counties are clustered on health and social indicators, which affect the likelihood of making improvements in these areas. Similar to a randomized trial, prior to collecting survey data, it is necessary to identify matched control counties as study sites based on an array of state and county covariates. Accounting for the hierarchal structure of data, a blend of various probability-based models are presented to achieve this goal. Methods include multivariable models that control for observed differences among treatment and control groups, shrinkage based LASSO as a variable selection technique, and logistic models.

Predictive value of inflammatory markers for functional outcomes in patients with ischemic stroke.

Background: Inflammatory processes have been proposed in the pathophysiology of ischemic stroke. The present study was designed to evaluate the relationship between tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6), IL 1 beta (IL-1ß), and high sensitivity C-reactive protein (hsCRP) with the prognosis and functional outcome in patients with less severe ischemic stroke. Methods: We measured the level of IL-1ß, IL-6, hsCRP, and TNF-α on days 1 and 5 after stroke onset by enzyme-linked immunosorbent assay (ELISA). The infarct volume was assessed using Alberta Stroke Program Early CT Score (ASPECTS) and posterior circulation ASPECTS (pcASPECTS) score in brain computed tomography (CT) scan and magnetic resonance imaging (MRI). The severity of stroke was assessed by applying the National Institutes of Health Stroke Scale (NIHSS) and Modified Rankin Scale (MRS) in 24 hours on day 5 and after 3 months from stroke onset. Good outcome was defined as the third month MRS ≤ 2. The association of inflammatory markers and the course of stroke symptoms over time was examined. Results: Forty-four first-ever stroke patients without concurrent inflammatory diseases with a mean age of 65 years were included. The mean NIHSS and MRS in admission time were 6.5 ± 3.5 and 3.07, respectively. The day 1 and the day 5 levels of IL-1ß, IL-6, hsCRP, and TNF-α were not significantly different in good and poor outcome groups (all P-values > 0.05). In addition, they were not significantly associated with the ASPECTS, pcASPECTS, and changes of NIHSS and MRS over time. Conclusion: The levels of hsCRP, IL-1ß, IL-6, and TNF-α are not reliable predictors of functional outcomes in patients with less severe acute ischemic stroke (AIS).