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The number of nonfatal opioid-involved overdoses treated by health care providers has risen in the United States; the median number of emergency department (ED) visits for these overdoses was significantly higher during 2020 than during 2019 (1). ED visit data can underestimate nonfatal opioid-involved overdose incidence because, increasingly, persons experiencing a nonfatal opioid overdose are refusing transport to EDs by emergency medical services (EMS) (2). A study in Kentucky found that during a 6-month period, 19.8% of persons treated by EMS for an opioid overdose refused transport to an ED (2). Thus, EMS encounter data involving suspected nonfatal opioid-involved overdoses complement ED data and also allow for near real-time analysis (3). This report describes trends in rates of EMS encounters for nonfatal opioid-involved overdoses per 10,000 total EMS encounters (rates) by selected patient- and county-level characteristics during January 2018–March 2022 in 491 counties from 21 states using data from biospatial, Inc.* During this period, the nonfatal opioid-involved overdose rate increased, on average, 4.0% quarterly. Rates increased for both sexes and for most age groups. Rates were highest among non-Hispanic White (White) and non-Hispanic Native Hawaiian or other Pacific Islander (NH/OPI) persons, and increases were largest among non-Hispanic Black (Black), followed by Hispanic or Latino (Hispanic) persons. Rates increased in both urban and rural counties and for all quartiles of county-level characteristics (i.e., unemployment, education, and uninsured), except in counties with the lowest percentage of uninsured persons. Rates were highest and rate increases were largest in urban counties and counties with higher unemployment rates. This analysis of nonfatal opioid-involved overdose trends in EMS data highlights the utility of these data and the importance of addressing inequities that contribute to disproportionate overdose risk, such as through focused outreach to racial and ethnic minority groups, who disproportionately experience these inequities, and communities with higher levels of unemployment. EMS providers are in a unique position to engage in postoverdose response protocols and promote evidence-based overdose education and facilitate linkage to care and harm reduction services.†,§

Opioid overdose is a leading public health problem in the United States; however, national data on overdose deaths are delayed by several months or more.To build and validate a statistical model for estimating national opioid overdose deaths in near real time.In this cross-sectional study, signals from 5 overdose-related, proxy data sources encompassing health, law enforcement, and online data from 2014 to 2019 in the US were combined using a LASSO (least absolute shrinkage and selection operator) regression model, and weekly predictions of opioid overdose deaths were made for 2018 and 2019 to validate model performance. Results were also compared with those from a baseline SARIMA (seasonal autoregressive integrated moving average) model, one of the most used approaches to forecasting injury mortality.Time series data from 2014 to 2019 on emergency department visits for opioid overdose from the National Syndromic Surveillance Program, data on the volume of heroin and synthetic opioids circulating in illicit markets via the National Forensic Laboratory Information System, data on the search volume for heroin and synthetic opioids on Google, and data on post volume on heroin and synthetic opioids on Twitter and Reddit were used to train and validate prediction models of opioid overdose deaths.Model-based predictions of weekly opioid overdose deaths in the United States were made for 2018 and 2019 and compared with actual observed opioid overdose deaths from the National Vital Statistics System.Statistical models using the 5 real-time proxy data sources estimated the national opioid overdose death rate for 2018 and 2019 with an error of 1.01% and -1.05%, respectively. When considering the accuracy of weekly predictions, the machine learning-based approach possessed a mean error in its weekly estimates (root mean squared error) of 60.3 overdose deaths for 2018 (compared with 310.2 overdose deaths for the SARIMA model) and 67.2 overdose deaths for 2019 (compared with 83.3 overdose deaths for the SARIMA model).Results of this serial cross-sectional study suggest that proxy administrative data sources can be used to estimate national opioid overdose mortality trends to provide a more timely understanding of this public health problem.

We conducted systematic review and content analysis of measurement strategies related to child exposure to intimate partner violence (IPV). We searched nine electronic databases and supplementary sources for studies published between January 1984 and March 2016. Eligible studies were those that described a measurement strategy that was administered to children between, but not limited to, age 0 and 17, or administered to individuals who could report on youth of this age range. Measures were examined against a taxonomy of IPV exposure (direct involvement, direct eyewitness, and indirect exposure) and the four subtypes of IPV (sexual violence, physical violence, stalking, and psychological aggression). Twenty-eight measures met criteria for inclusion in the review; 18 measures were original, and 10 were modifications of the Conflict Tactics Scales. The majority of measures were published after 2008, demonstrating the considerable progress made in developing and substantially modifying measures over the last decade. Nonetheless, findings suggest important discrepancies in measurement strategies used in research efforts. Relatively few measures assess children's direct involvement in IPV, exposure to coercive control, and sexual violence. No measures found in our review examined children's exposure to stalking. The implications of these findings for research are discussed.

IntroductionThe drug overdose epidemic has worsened over the past decade; however, efforts have been made to better understand and track nonfatal overdoses using various data sources including emergency department and hospital admission data from billing and discharge files.Methods and findingsThe Centers for Disease Control and Prevention (CDC) has developed surveillance case definition guidance using standardised discharge diagnosis codes for public health practitioners and epidemiologists using lessons learnt from CDC’s funded recipients and the Council for State and Territorial Epidemiologists (CSTE) International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) Drug Poisoning Indicators Workgroup and General Injury ICD-10-CM Workgroup. CDC’s guidance was informed by health departments and CSTE’s workgroups and included several key aspects for assessing drug overdose in emergency department and hospitalisation discharge data. These include: (1) searching all diagnosis fields to identify drug overdose cases; (2) estimating drug overdose incidence using visits for initial encounter but excluding subsequent encounters and sequelae; (3) excluding underdosing and adverse effects from drug overdose incidence indicators; and (4) using codes T36–T50 for overdose surveillance. CDC’s guidance also suggests analysing intent separately for ICD-10-CM coding.ConclusionsCDC’s guidance provides health departments a key tool to better monitor drug overdoses in their community. The implementation and validation of this standardised guidance across all CDC-funded health departments will be key to ensuring consistent and accurate reporting across all entities.

Objectives: This study prospectively examined binge drinking's effect on prosocial bystander behavior and indicators of bystander behavior: intentions to intervene, self-efficacy to intervene, and positive outcome expectancies for intervening. Participants: College men were recruited from February to April 2010. Methods: Pre- and posttest surveys were administered as part of a randomized controlled trial (n = 743). Potential confounders were identified using Pearson product-moment correlations. Controlling for covariates, multiple linear regression was used to examine whether binge drinking was predictive of prosocial bystander behavior and indicators of bystander behavior. Results: Binge drinking was related to lower bystander behavior (p

This study examined the process by which a web-based sexual violence (SV) prevention program (i.e., RealConsent) prevents SV perpetration and increases bystander behaviors. Data from 743 college men who participated in a randomized controlled trial were analyzed. Simple and multiple-mediation models were estimated, using several theoretical constructs to assess the mechanisms through which RealConsent produced significant effects on SV perpetration and prosocial bystander or intervening behaviors. The results indicated that knowledge of effective consent for sex, hostility toward women, date rape attitudes, and hyper-gender male ideology significantly mediated the effects of RealConsent on SV perpetration in the multiple-mediator model. Furthermore, intentions to intervene significantly mediated the effects of RealConsent on prosocial bystander behaviors in the multiple-mediator model. The results show that the RealConsent program works to prevent SV perpetration and prosocial bystander behaviors via several theoretically proposed mediators central to the development and content of the program. The results also provide strong evidence that SV and bystander education for college men may benefit from including an explicit focus on decreasing negative norms related to women (e.g., hostility, date rape attitudes, hyper-gender ideology) and through increasing college men’s knowledge of consent and intentions to intervene.

INTRODUCTION: South Africa (SA) implemented the Global Youth Tobacco Survey (GYTS) four times between 1999 and 2011. Data from the four surveys indicated that downward trends in cigarette use among students may have stalled. Understanding the effect of school anti-smoking education on current smoking among students within schools and variability across schools may provide important insights into policies aimed at preventing or reducing tobacco use among students. Objective were to assess the student- and school-level effects of students’ exposure to school anti-smoking education on current cigarette use among the study population using the most recent wave of GYTS data in SA (2011). METHODS: an analytic sample of students 13-15 years of age was selected (n=3,068) from the SA GYTS 2011. A taxonomy of two-level logistic regression models was fit to assess the relationship of various tobacco use, control, and exposure predictor variables on current cigarette smoking among the study population. RESULTS: at the student-level in the full model, secondhand smoke (SHS) exposure, peer smoking, and ownership of a promotional item were significantly associated with higher risk of current smoking. At the school-level in the full model, average exposure to peer smoking was associated with significant increases in the prevalence of current cigarette use, while average family anti-smoking education was significantly associated with decreases in the outcome variable. School anti-smoking education was not a statistically significant predictor at the student- or school-levels. CONCLUSION: in this study, exposure to school anti-smoking education had no association with current cigarette smoking among the study population. Consistent with previous studies, having peers that smoked was highly associated with a student being a current smoker. Interestingly, at the school-level in the multilevel analysis, schools with higher rates of average family anti-smoking education had lower prevalence of current smoking. This finding has potential implications for tobacco control in SA, particularly if the school-level, family-centered protective effect can be operationalized as a prevention tool in the country’s tobacco control program.

To combat the high rates of sexual violence on college campuses, prevention programming should be theoretically driven, persuasive, and salient, and should provide messages that counter negative normative beliefs supportive of sexual violence. We describe qualitative formative research that identifies themes as a means to inform messages and content for a Web-based sexual violence prevention program. To illustrate the process, we used qualitative analysis of eight focus groups (N = 48) with male undergraduates from a large urban, public, Southeastern university. Analyses focused on how men interpret sexual interest, the meaning and methods of obtaining effective consent for sex, sexual encounters that involve alcohol, barriers to and facilitators of bystander intervention, and intervening techniques. We demonstrate how positive and negative themes identified in the analysis can be incorporated into programming segments.

BackgroundBystander intervention approaches offer promise for reducing rates of sexual violence on college campuses. Most interventions are in-person small-group formats, which limit their reach and reduce their overall public health impact. ObjectiveThis study evaluated the efficacy of RealConsent, a Web-based bystander approach to sexual violence prevention, in enhancing prosocial intervening behaviors and preventing sexual violence perpetration. MethodsA random probability sample of 743 male undergraduate students (aged 18 to 24 years) attending a large, urban university located in the southeastern United States was recruited online and randomized to either RealConsent (n=376) or a Web-based general health promotion program (n=367). Participants were surveyed online at baseline, postintervention, and 6-months postintervention. RealConsent was delivered via a password-protected Web portal that contained six 30-minute media-based and interactive modules covering knowledge of informed consent, communication skills regarding sex, the role of alcohol and male socialization in sexual violence, empathy for rape victims, and bystander education. Primary outcomes were self-reported prosocial intervening behaviors and sexual violence perpetration. Secondary outcomes were theoretical mediators (eg, knowledge, attitudes). ResultsAt 6-month follow-up RealConsent participants intervened more often (P=.04) and engaged in less sexual violence perpetration (P=.04) compared to controls. In addition, RealConsent participants reported greater legal knowledge of sexual assault (P