Behavioral Health Risk Assessment and Estimation: Validating an Integrated, Multi-Risk Factor Approach aided by Technology

High rates of behavioral health problems in the U.S. require integrated, multi-dimensional approaches. The study of behavioral health risk assessment and estimation aided by technology has the potential to inform assessment and management of behavioral health problems toward the goal of reducing adverse outcomes. The objective of this study is to inform evidence-based behavioral health risk assessment and estimation. This research examines the U.S. Army Medical Command data within the Behavioral Health Risk Management module (BHRM) to explore behavioral health risk assessment and estimation aided by technology. Analyses are conducted on BHRM data from the records of 30,263 U.S. Army active duty, Guard and Reserve service members assigned to military medical units (U.S. Army Warrior Transition Units) between September 1, 2009 and November 12, 2013. To test risk assessment, responses on the BHRM intake tool (Behavioral Health Risk Assessment-Questionnaire / BHRA-Q) are used to test prevalence, associations, internal reliability and questionnaire’s factor group structure. To examine risk estimation, statistical tests are completed on the prevalence and correlations of risk estimates by the BHRM and clinical providers as well as the predictive properties of demographic variables toward risk estimation. Hypotheses are supported for significant relationships among behavioral health risk variables (r = .40); good fit of the data to the eight-factor group structure of the BHRA-Q (Comparative Fit Index = 0.969; Tucker-Lewis Fit Index = 0.967; Root Mean Square Error of Approximation = .029 [90% Confidence Interval 0.029 - 0.030]); significant correlations among BHRM and provider risk estimates (large or medium effect size of BHRM on provider estimates); and three significant demographic predictors of risk estimation (race, religion and military service component). Internal reliability of BHRA-Q is supported (Cronbach’s α = .897). This study tests data related to an integrated, multi-risk factor behavioral health risk assessment questionnaire (BHRA-Q) and risk estimation aided by technology (BHRM). Findings support behavioral health risk assessment and estimation using evidence-based / informed multi-risk factor assessment, aided by technology, to inform clinical decision making. Although demographic variables are not strong predictors of risk estimation, as grouped and tested, further study is recommended.Social Work, Graduate College o

Exploring the relationship between welfare participation in childhood and depression in adulthood in the United States

OBJECTIVE: Depression is a serious mental health disorder, and untangling its causal agents is a major public health priority in the United States. This study examines the relationship between participating in welfare programs during childhood and experiencing depression during young adulthood. METHOD: This study used wave I and IV data from the Add Health (N = 15,701). Multiple imputation is used to deal with missing data. Propensity score matching is used to reduce the selection bias, and then multiple regressions were used to examine the welfare participation and depression relationships. RESULTS: Overall, young adults from welfare-recipient families reported significantly higher depression scores, rather than the clinical diagnosis of depression. Subgroup analyses showed only the poor group had significantly higher depression scores, whereas only the near-poor group had a significantly diagnosed depression outcome. Additionally, significantly higher depression scores were found for female youth from welfare-recipient families. However, no significant differences were found between the gender groups regarding diagnosed depression. DISCUSSION: Using welfare participation as an economic marker, the subgroup analyses help to identify target populations for future intervention. Implications of this study will be of interest to policy makers and have value for informing policy decisions

The Role of Rural and Urban Geography and Gender in Community Stigma around Mental Illness

Empirical evidence describes the negative outcomes people with mental health disorders experience due to societal stigma. The aim of this study was to examine the role of gender and rural/urban living in perceptions about mental illness. Participants completed the Day’s Mental Illness Stigma Scale, a nationally validated instrument for measuring stigma. Directors of Chambers of Commerce in North Dakota distributed the electronic survey to their members. Additionally, distribution occurred through use of social media and other snowball sampling approaches. Analysis of data gathered from 749 participants occurred through examination of the difference in perceptions based on geography and gender. The ZIP codes of residence were sorted to distinguish between rural and urban participants. Application of weighting measures ensured closer alignment with the general population characteristics. Findings indicate that for the majority of the seven stigma measures the Day’s Mental Illness Stigma Scale examines, the coefficient of rural-gender interactions was positive and highly significant with higher levels of stigma in rural areas. Females exhibited lower stigma perceptions than males. However, women living in rural areas held higher degrees of stigma compared to urban residing females. Implications of the study include the need to advance mental health literacy campaigns for males and people residing in rural communities. Additional empirical studies that examine the role of geography and gender in understanding stigma towards people with mental health disorders will result in improved treatment outcomes due to increased and focused educational efforts

Exposure to substance use prevention messages among adolescents. Short report.

This issue of The CBHSQ Report examines adolescents' exposure to substance use prevention messages using US data from the 2002 to 2015 National Survey on Drug Use and Health (NSDUH). It also uses 2015 NSDUH data to examine exposure to prevention messages by key demographic characteristics. The 2015 estimates are based on a total sample size of 17,000 adolescents aged 12 to 17

Influencing Well-being: A Study of Childhood Risk Factors as Predictive Indicators for Future Mental Health Difficulties

Previous literature demonstrates common childhood characteristics of adults with mental health problems and children with internalizing and externalizing behavior challenges (Fatori et al., 2013; Jaffee et al., 2002; Koegel et al., 1995; Morrissey et al., 2014). Still, little research exists having associated school-based internalizing and externalizing behavior screening scores with the risk factors described in the literature (i.e., low socioeconomic status, office discipline referrals, homelessness, low academic achievement, low attendance rates, and ethnicity- and gender-based issues). This quantitative correlational study aimed to estimate the predictive value the childhood risk factors had on the results of the Student Risk Screening Scale – Internalizing and Externalizing (SRSS-IE) of elementary-aged students through a regression analysis of secondary data. The secondary data were taken from an urban school district in the Midwest. Guided by the life course theory and the age-graded theory of social control, this study explored the predictive value of several indicators. The findings show that the psychosocial risk factors pulled from the research hold predictive value when combined into a composite score with 45-60% accuracy and with 50-65% accuracy when the risk factors are considered individually. The results hold potential for identifying students who are at-risk for mental health difficulties before severe problems exist, allowing for the provision of early, targeted school- and community-based intervention in the areas of social, emotional, and behavioral wellness for students to reduce the likelihood of future mental health problems. The results, implications for schools, and recommendations for future research are discussed

Mental health and substance use disorders and treatment receipt among pregnant women in the United States, 2008-2014 : trend analysis, likelihood of treatment receipt, and ethnic disparities in mental health treatment.

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

The impact of prescription pain reliever misuse and heroin use on morbidity and mortality by level of urbanicity: 2002-2014

Non-medical use of prescription pain relievers (PPRs), heroin, and more recently fentanyl, continue to have major public health consequences in the United States. This article analyzes trends in PPR and heroin use, emergency department and hospital stays, substance use treatment services, and mortality to assess the relative impact of the opioid crisis on rural versus more urbanized counties in the United States. Our findings suggest that while more urbanized counties have had greater increases in opioid use, rural and less urbanized counties tended to be more negatively impacted than larger and non-rural counties. Disparities in service availability highlight the need for a serious discussion on how resources are allocated in counties that have lower tax bases. Based on these results, we conclude that rural and less urbanized counties can benefit from real increases in resources for substance use prevention and treatment services, including the expansion of prescribers trained to screen and treat opioid use. Understanding the unique challenges of rural and less urbanized counties may help decrease the disparity in consequences found in this study

Involuntary Termination from Substance Use Disorder Treatment: Unknown Phantoms, Red Flags, and Unexplained Medical Data

In the United States, all treatment programs receiving public funds are required by law to regularly submit admission and discharge data, inclusive of the forced/involuntary termination or administrative discharge of clients, to their local state authorities. In some states, this requirement even extends to programs not receiving public funds. The aim of collecting discharge data—collected under the auspices of the Substance Abuse and Mental Health Services Association [SAMHSA]—is to assist state and county authorities, funders, and accreditors to monitor recovery-focused program performance. However, investigation here undertaken shows that published discharge data from many state treatment settings are perennially and grossly underreported or misreported. This paper reports on evidence that point to systemic failure of regulatory supervision of treatment settings and the ethical breach in duty and consequent legal culpability in reporting medical data. Policy and practice implications are discussed

Medication-assisted treatment for opioid use disorder

"The opioid overdose epidemic continues to claim lives across the country with a record 47,600 overdose deaths in 2017. (This number represents 67.8% of the 70,237 overdose deaths from all drugs) [CDC 2018a]. More Americans now die every year from drug overdoses than in motor vehicle crashes [CDC 2016]. The crisis is taking an especially devastating toll on certain parts of the U.S. workforce. High rates of opioid overdose deaths have occurred in industries with high injury rates and physically demanding working conditions such as construction, mining, or fishing [Massachusetts Department of Public Health 2018; CDC 2018b]. Certain job factors such as high job demands, job insecurity, and lack of control over tasks have also been linked to opioid use [Kowalski-McGraw et al. 2017]. Medication-assisted treatment (MAT) (also known as medicationbased treatment*) has been shown to be effective for many people with opioid use disorder [SAMHSA 2015b; National Academies of Sciences, Engineering, and Medicine 2019]. In addition to providing general information about MAT, this document provides information for employers wishing to assist or support workers with opioid use disorder." - NIOSHTIC-2NIOSH no. 20055929Suggested citation: NIOSH [2019]. Medication-assisted treatment for opioid use disorder. By Howard J, Cimineri L, Evans T, Chosewood LC, Afanuh S. Washington, DC: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, DHHS (NIOSH) Publication No. 2019-133, https://doi.org/10.26616/NIOSHPUB2019133201910.26616/NIOSHPUB2019133659