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BACKGROUND Adverse childhood experiences (ACEs), which include abuse and neglect and various household challenges such as exposure to intimate partner violence and substance use in the home, can have negative impacts on the lifelong health of affected individuals. Among various strategies for mitigating the adverse effects of ACEs is to enhance connectedness and social support for those who have experienced them. However, how the social networks of those who experienced ACEs differ from the social networks of those who did not is poorly understood. OBJECTIVE In this study, we used Reddit and Twitter data to investigate and compare social networks between individuals with and without ACE exposure. METHODS We first used a neural network classifier to identify the presence or absence of public ACE disclosures in social media posts. We then analyzed egocentric social networks comparing individuals with self-reported ACEs with those with no reported history. RESULTS We found that, although individuals reporting ACEs had fewer total followers in web-based social networks, they had higher reciprocity in following behavior (ie, mutual following with other users), a higher tendency to follow and be followed by other individuals with ACEs, and a higher tendency to follow back individuals with ACEs rather than individuals without ACEs. CONCLUSIONS These results imply that individuals with ACEs may try to actively connect with others who have similar previous traumatic experiences as a positive connection and coping strategy. Supportive interpersonal connections on the web for individuals with ACEs appear to be a prevalent behavior and may be a way to enhance social connectedness and resilience in those who have experienced ACEs.

Adverse childhood experiences (ACEs), which include abuse and neglect and various household challenges like exposure to intimate partner violence and substance use in the home can have negative impacts on lifelong health of affected individuals. Among various strategies for mitigating the adverse effects of ACEs is to enhance connectedness and social support for those who have experienced ACEs. However, how social networks of those who experienced ACEs differ from those who did not is poorly understood. In the present study, we use Reddit and Twitter data to investigate and compare social networks among individuals with and without ACEs exposure. We first use a neural network classifier to identify the presence or absence of public ACEs disclosures in social media posts. We then analyze egocentric social networks comparing individuals with self-reported ACEs to those with no reported history. We found that, although individuals reporting ACEs had fewer total followers in online social networks, they had higher reciprocity in following behavior (i.e., mutual following with other users), a higher tendency to follow and be followed by other individuals with ACEs, and a higher tendency to follow back individuals with ACEs rather than individuals without ACEs. These results imply that individuals with ACEs may try to actively connect to others having similar prior traumatic experiences as a positive connection and coping strategy. Supportive interpersonal connections online for individuals with ACEs appear to be a prevalent behavior and may be a way to enhance social connectedness and resilience in those who have experienced ACEs.

Illicit or ‘designer’ benzodiazepines are a growing contributor to overdose deaths. We employed natural language processing (NLP) to study benzodiazepine mentions over 10 years on 270 online drug forums (subreddits) on Reddit. Using NLP, we automatically detected mentions of illicit and prescription benzodiazepines, including their misspellings and non-standard names, grouping relative mentions by quarter. On a collection of 17 861 755 posts between 2012 and 2021, we searched for 26 benzodiazepines (8 prescription; 18 illicit), detecting 173 275 mentions. The rate of posts about both prescription and illicit benzodiazepines increased consistently with increases in deaths involving both drug classes, illustrating the utility of surveillance via Reddit.

Objective: The aim of this study was to assess associations of various content areas of Twitter posts with help-seeking from the US National Suicide Prevention Lifeline (Lifeline) and with suicides. Methods: We retrieved 7,150,610 suicide-related tweets geolocated to the United States and posted between 1 January 2016 and 31 December 2018. Using a specially devised machine-learning approach, we categorized posts into content about prevention, suicide awareness, personal suicidal ideation without coping, personal coping and recovery, suicide cases and other. We then applied seasonal autoregressive integrated moving average analyses to assess associations of tweet categories with daily calls to the US National Suicide Prevention Lifeline (Lifeline) and suicides on the same day. We hypothesized that coping-related and prevention-related tweets are associated with greater help-seeking and potentially fewer suicides. Results: The percentage of posts per category was 15.4% (standard deviation: 7.6%) for awareness, 13.8% (standard deviation: 9.4%) for prevention, 12.3% (standard deviation: 9.1%) for suicide cases, 2.4% (standard deviation: 2.1%) for suicidal ideation without coping and 0.8% (standard deviation: 1.7%) for coping posts. Tweets about prevention were positively associated with Lifeline calls ( B = 1.94, SE = 0.73, p = 0.008) and negatively associated with suicides ( B = −0.11, standard error = 0.05, p = 0.038). Total number of tweets were negatively associated with calls ( B = −0.01, standard error = 0.0003, p = 0.007) and positively associated with suicide, ( B = 6.4 × 10−5, standard error = 2.6 × 10−5, p = 0.015). Conclusion: This is the first large-scale study to suggest that daily volume of specific suicide-prevention-related social media content on Twitter corresponds to higher daily levels of help-seeking behaviour and lower daily number of suicide deaths. Preregistration: As Predicted, #66922, 26 May 2021.

Background Adverse childhood experiences (ACEs), which include abuse and neglect and various household challenges such as exposure to intimate partner violence and substance use in the home, can have negative impacts on the lifelong health of affected individuals. Among various strategies for mitigating the adverse effects of ACEs is to enhance connectedness and social support for those who have experienced them. However, how the social networks of those who experienced ACEs differ from the social networks of those who did not is poorly understood. Objective In this study, we used Reddit and Twitter data to investigate and compare social networks between individuals with and without ACE exposure. Methods We first used a neural network classifier to identify the presence or absence of public ACE disclosures in social media posts. We then analyzed egocentric social networks comparing individuals with self-reported ACEs with those with no reported history. Results We found that, although individuals reporting ACEs had fewer total followers in web-based social networks, they had higher reciprocity in following behavior (ie, mutual following with other users), a higher tendency to follow and be followed by other individuals with ACEs, and a higher tendency to follow back individuals with ACEs rather than individuals without ACEs. Conclusions These results imply that individuals with ACEs may try to actively connect with others who have similar previous traumatic experiences as a positive connection and coping strategy. Supportive interpersonal connections on the web for individuals with ACEs appear to be a prevalent behavior and may be a way to enhance social connectedness and resilience in those who have experienced ACEs.

Purpose Youth suicide clusters may be exacerbated by suicide contagion—the spread of suicidal behaviors. Factors promoting suicide contagion are poorly understood, particularly in the advent of social media. Using cross-sectional data from an ongoing youth suicide cluster in Ohio, this study examines associations between suicide cluster-related social media and suicidal behaviors. Methods We surveyed 7th- to 12th-grade students in northeastern Ohio during a 2017–2018 suicide cluster to assess the prevalence of suicidal ideation (SI), suicide attempts (SAs), and associations with potential contagion-promoting factors such as suicide cluster–related social media, vigils, memorials, news articles, and watching the Netflix series 13 Reasons Why before or during the cluster. Generalized estimating equations examined associations between potential contagion-promoting factors and SI/SA, adjusting for nonmodifiable risk factors. Subgroup analyses examined whether associations between cluster-related factors and SI/SA during the cluster varied by previous history of SI/SA. Results Among participating students, 9.0% (876/9,733) reported SI and 4.9% attempted suicide (481/9,733) during the suicide cluster. Among students who posted suicide cluster–related content to social media, 22.9% (267/1,167) reported SI and 15.0% (175/1,167) attempted suicide during the suicide cluster. Posting suicide cluster–related content was associated with both SI (adjusted odds ratio 1.7, 95% confidence interval 1.4–2.0) and SA during the cluster (adjusted odds ratio 1.7, 95% confidence interval 1.2–2.5). In subgroup analyses, seeing suicide cluster–related posts was uniquely associated with increased odds of SI and SA during the cluster among students with no previous history of SI/SA. Conclusions Exposure to suicide cluster–related social media is associated with both SI and SA during a suicide cluster. Suicide interventions could benefit from efforts to mitigate potential negative effects of social media and promote prevention messages.

Significance Rates of suicide in the United States have increased over recent decades. One modifiable risk factor for suicide is exposure to sensationalized media content about suicide. Health authorities have published guidelines for news media reporting on suicide; however, uptake of recommendations remains limited. We conducted a study to analyze adherence to the guidelines on news shared on Facebook and assessed how adherence affects reader engagement. Certain harmful elements were widely prevalent in news media while protective elements were limited; however, contrary to popular perception, articles which more closely adhered to safe-reporting practices were shared more often. Variability in scores exists across nations and publisher types with implications for journalists, public health organizations, social media companies, researchers, and lay readers., Rates of suicide in the United States are at a more than 20-y high. Suicide contagion, or spread of suicide-related thoughts and behaviors through exposure to sensationalized and harmful content is a well-recognized phenomenon. Health authorities have published guidelines for news media reporting on suicide to help prevent contagion; however, uptake of recommendations remains limited. A key barrier to widespread voluntary uptake of suicide-reporting guidelines is that more sensational content is perceived to be more engaging to readers and thus enhances publisher visibility and engagement; however, no empirical information exists on the actual influence of adherence to safe-reporting practices on reader engagement. Hence, we conducted a study to analyze adherence to suicide-reporting guidelines on news shared on social media and to assess how adherence affects reader engagement. Our analysis of Facebook data revealed that harmful elements were prevalent in news articles about suicide shared on social media while the presence of protective elements was generally rare. Contrary to popular perception, closer adherence to safe-reporting practices was associated with a greater likelihood of an article being reshared (adjusted odds ratio [AOR] = 1.19, 95% confidence interval [CI] = 1.10 to 1.27) and receiving positive engagement (“love” reactions) (AOR = 1.20, 95% CI = 1.13 to 1.26). Mean safe-reporting scores were lower in the US than other English-speaking nations and variation existed by publisher characteristics. Our results provide empirical evidence that improved adherence to suicide-reporting guidelines may benefit not only the health of individuals, but also support publisher goals of reach and engagement.

Introduction: The volume of new data that is created each year relevant to injury and violence prevention continues to grow. Furthermore, the variety and complexity of the types of useful data has also progressed beyond traditional, structured data. In order to more effectively advance injury research and prevention efforts, the adoption of data science tools, methods, and techniques, such as natural language processing and machine learning, by the field of injury and violence prevention is imperative. Method: The Centers for Disease Control and Prevention’s (CDC) National Center for Injury Prevention and Control has conducted numerous data science pilot projects and recently developed a Data Science Strategy. This strategy includes goals on expanding the availability of more timely data systems, improving rapid identification of health threats and responses, increasing access to accurate health information and preventing misinformation, improving data linkages, expanding data visualization efforts, and increasing efficiency of analytic and scientific processes for injury and violence, among others. Results: To achieve these goals, CDC is expanding its data science capacity in the areas of internal workforce, partnerships, and information technology infrastructure. Practical Application: These efforts will expand the use of data science approaches to improve how CDC and the field address ongoing injury and violence priorities and challenges.

Suicide is a growing public health problem in the United States, claiming approximately 47,000 lives in 2017 (1). However, deaths from suicide represent only a small part of a larger problem because each year millions of persons experience suicidal ideation and engage in suicidal and nonsuicidal self-directed violence, both risk factors for suicide (2). Emergency departments (EDs) are an important setting for monitoring these events in near real time (3-5). From 2001 to 2016, ED visit rates for nonfatal self-harm increased 42% among persons aged ≥10 years (1). Using data from CDC's National Syndromic Surveillance Program (NSSP), ED visits for suicidal ideation, self-directed violence, or both among persons aged ≥10 years during January 2017-December 2018 were examined by sex, age group, and U.S. region. During the 24-month period, the rate of ED visits for suicidal ideation, self-directed violence, or both increased 25.5% overall, with an average increase of 1.2% per month. Suicide prevention requires comprehensive and multisectoral approaches to addressing risk at personal, relationship, community, and societal levels. ED syndromic surveillance data can provide timely trend information and can support more targeted and prompt public health investigation and response. CDC's Preventing Suicide: A Technical Package of Policy, Programs, and Practices includes tailored suicide prevention strategies for health care settings (6).

BackgroundDespite recent increasing focus on fatal overdoses involving multiple substances, there is a paucity of knowledge about stimulant co-use patterns among people who use opioids (PWUO) or people being treated with medication for opioid use disorder (PTMOUD). This study examines stimulant co-mention trends among PWUO/PTMOUD on social media.MethodsWe collected publicly-available data from 14 prescription and illicit opioid and MOUD-related forums on Reddit (subreddits) between 2011-2020 and timelines comprising past posts from a sample of Reddit users (Redditors) on these forums. We applied natural language processing to detect mentions of opioids, opioid-related medications, and stimulants and described trends and patterns in co-mentions. ResultsPosts collected for 13,812 Redditors indicated 12,306 (89.1%) mentioned ≥1 opioid, opioid-related medication or stimulant. Analyses showed the number and proportion of Redditors mentioning both opioids and/or opioid-related medications and stimulants steadily increased over time. Relative rates of co-mentions of heroin and methamphetamine, substances most commonly co-mentioned, decreased in recent years while those of fentanyl and MOUD with methamphetamine increased. ConclusionData from Reddit reflect increasing mentions of stimulants, particularly methamphetamine, among PWUO/PTMOUD and closely resemble the growth in overdose deaths involving both opioids and stimulants. These findings are consistent with recent reports suggesting increasing stimulant use among people receiving treatment for opioid use disorder. These data offer insights on emerging trends in the overdose epidemic and underscore the importance of scaling efforts to address co-occurring opioid and stimulant use including harm reduction and comprehensive healthcare access spanning mental-health services and substance use disorder treatment.

ImportanceFirearm homicides are a major public health concern; lack of timely mortality data presents considerable challenges to effective response. Near real-time data sources offer potential for more timely estimation of firearm homicides.ObjectiveTo estimate near real-time burden of weekly and annual firearm homicides in the US.Design, Setting, and ParticipantsIn this prognostic study, anonymous, longitudinal time series data were obtained from multiple data sources, including Google and YouTube search trends related to firearms (2014-2019), emergency department visits for firearm injuries (National Syndromic Surveillance Program, 2014-2019), emergency medical service activations for firearm-related injuries (biospatial, 2014-2019), and National Domestic Violence Hotline contacts flagged with the keyword firearm (2016-2019). Data analysis was performed from September 2021 to September 2022.Main Outcomes and MeasuresWeekly estimates of US firearm homicides were calculated using a 2-phase pipeline, first fitting optimal machine learning models for each data stream and then combining the best individual models into a stacked ensemble model. Model accuracy was assessed by comparing predictions of firearm homicides in 2019 to actual firearm homicides identified by National Vital Statistics System death certificates. Results were also compared with a SARIMA (seasonal autoregressive integrated moving average) model, a common method to forecast injury mortality.ResultsBoth individual and ensemble models yielded highly accurate estimates of firearm homicides. Individual models’ mean error for weekly estimates of firearm homicides (root mean square error) varied from 24.95 for emergency department visits to 31.29 for SARIMA forecasting. Ensemble models combining data sources had lower weekly mean error and higher annual accuracy than individual data sources: the all-source ensemble model had a weekly root mean square error of 24.46 deaths and full-year accuracy of 99.74%, predicting the total number of firearm homicides in 2019 within 38 deaths for the entire year (compared with 95.48% accuracy and 652 deaths for the SARIMA model). The model decreased the time lag of reporting weekly firearm homicides from 7 to 8 months to approximately 6 weeks.Conclusions and RelevanceIn this prognostic study of diverse secondary data on machine learning, ensemble modeling produced accurate near real-time estimates of weekly and annual firearm homicides and substantially decreased data source time lags. Ensemble model forecasts can accelerate public health practitioners’ and policy makers’ ability to respond to unanticipated shifts in firearm homicides.

Key Points Question Are online risk factors measured using real-world online activity data associated with youth suicide-related behavior? Findings In this case-control study of 227 youths, having a severe suicide/self-harm alert in a school-based online safety monitoring program was associated with multiple online risk factors (including cyberbullying, violence, drug-related content, hate speech, profanity, sexual content, depression, and low-severity self-harm content). However, the greatest risk was found among youth having multiple types of online risk factors. Meaning This case-control study provides information that may help guide youth suicide prevention activities related to online risk factors., Importance The association between online activities and youth suicide is an important issue for parents, clinicians, and policy makers. However, most information exploring potential associations is drawn from survey data and mainly focuses on risk related to overall screen time. Objective To evaluate the association between a variety of online risk factors and youth suicide-related behavior using real-world online activity data. Design, Setting, and Participants A matched case-control study was conducted from July 27, 2019, to May 26, 2020, with the sample drawn from more than 2600 US schools participating in an online safety monitoring program via the Bark online safety tool. For 227 youths having a severe suicide/self-harm alert requiring notification of school administrators, cases were matched 1:5 to 1135 controls on location, the amount of follow-up time, and general volume of online activity. Exposures Eight potential online risk factors (cyberbullying, violence, drug-related, hate speech, profanity, sexual content, depression, and low-severity self-harm) through assessment of text, image, and video data. Main Outcomes and Measures Severe suicide/self-harm alert requiring notification of school administrators; severe suicide alerts are statements by youths indicating imminent or recent suicide attempts and/or self-harm. Results The 1362 participants had a mean (SD) age of 13.3 (2.41) years; 699 (51.3%) were male. All 8 online risk factors studied exhibited differences between case and control populations and were significantly associated with subsequent severe suicide/self-harm alerts when examining total direct and indirect pathways. These associations ranged from an adjusted odds ratio (aOR) of 1.17 (95% CI, 1.09-1.26) for drug-related content to an aOR of 1.82 (95% CI, 1.63-2.03) for depression-related content. When considering the total number of different types of online risk factors among the 8 measured, there was an exponentially larger risk of severe suicide/self-harm alerts; youths with 5 or more of the 8 risk factors present in their online activity had a more than 70-fold increased odds of subsequently having a severe suicide/self-harm alert (aOR, 78.64; 95% CI, 34.39-179.84). Conclusions and Relevance The findings of this study suggest that many discrete types of risk factors are identifiable from online data and associated with subsequent youth suicide-related behavior. Although each risk factor carries a specific association with suicide-related behavior, the greatest risk is evident for youths demonstrating multiple types of online risk factors., This case-control study examines the association between online risk factors and suicide-related behaviors in youths using a school-based online safety monitoring program.

Purpose Rates of suicide are increasing rapidly among youth. Social media messages and online games promoting suicide are a concern for parents and clinicians. We examined the timing and location of social media posts about one alleged youth suicide game to better understand the degree to which social media data can provide earlier public health awareness. Methods We conducted a search of all public social media posts and news articles on the Blue Whale Challenge (BWC), an alleged suicide game, from January 1, 2013, through June 30, 2017. Data were retrieved through multiple keyword search; sources included social media platforms Twitter, YouTube, Reddit, Tumblr, as well as blogs, forums, and news articles. Posts were classified into three categories: individual “pro”-BWC posts (support for game), individual “anti”-BWC posts (opposition to game), and media reports. Timing and location of posts were assessed. Results Overall, 95,555 social media posts and articles about the BWC were collected. In total, over one-quarter (28.3%) were “pro”-BWC. The first U.S. news article related to the BWC was published approximately 4 months after the first English language U.S. social media post about the BWC and 9 months after the first U.S. social media post in any language. By the close of the study period, “pro”-BWC posts had spread to 127 countries. Conclusions Novel online risks to mental health, such as prosuicide games or messages, can spread rapidly and globally. Better understanding social media and Web data may allow for detection of such threats earlier than is currently possible.

Identifying medical encounters that precede self-directed violence may allow for important prevention opportunities. This study examined the risk of self-directed violence after visiting the emergency department for a range of physical health conditions among youth.This retrospective cohort study used 2012-2013 statewide emergency department data from six states. Among patients aged 15-29 years, the exposure group included 2,192,322 emergency department visits for 16 selected conditions, coded by whether visits for those conditions were the first, second, or third or later visit for that condition. Emergency department visits for a minor infection served as the reference group (n=149,163). A Cox proportional hazard model was used to assess the risk of a self-directed violence event within 6 months for each condition. Analyses were conducted in 2017.Overall, 8,489 (0.4%) of all patients visited the emergency department for self-directed violence over a 6-month period. Initial visits for epilepsy or seizures conveyed a markedly elevated hazard ratio for subsequent self-directed violence at 6.0 and 5.7, respectively (p0.001). Initial visits for other conditions showed moderately elevated risk with hazard ratios primarily2. Second visits for various pain symptoms, syncope, vomiting, or non-self-directed violence injury also had a 3- to 5-fold increase in hazard ratios for subsequent self-directed violence. Hazard ratios for third or later visit increased to 8.8 for back pain, 6.9 for headache, about 5 for abdominal pain, dental complaints, and non-self-directed violence injury (p0.001).Young people presenting to the emergency department for certain medical conditions are at an increased risk of subsequent self-directed violence. An awareness of these patterns may help guide screening efforts for suicide prevention in clinical settings.

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.

BACKGROUND Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts. OBJECTIVE By adopting a multidisciplinary, mixed methods strategy, this paper aims to present machine learning and natural language analysis approaches to identify the characteristics and prevalence of web-based misinformation related to MOUD to inform future prevention, treatment, and response efforts. METHODS The team harnessed public social media posts and comments in the English language from Twitter (6,365,245 posts), YouTube (99,386 posts), Reddit (13,483,419 posts), and Drugs-Forum (5549 posts). Leveraging public health expert annotations on a sample of 2400 of these social media posts that were found to be semantically most similar to a variety of prevailing opioid use disorder–related myths based on representational learning, the team developed a supervised machine learning classifier. This classifier identified whether a post’s language promoted one of the leading myths challenging addiction treatment: that the use of agonist therapy for MOUD is simply replacing one drug with another. Platform-level prevalence was calculated thereafter by machine labeling all unannotated posts with the classifier and noting the proportion of myth-indicative posts over all posts. RESULTS Our results demonstrate promise in identifying social media postings that center on treatment myths about opioid use disorder with an accuracy of 91% and an area under the curve of 0.9, including how these discussions vary across platforms in terms of prevalence and linguistic characteristics, with the lowest prevalence on web-based health communities such as Reddit and Drugs-Forum and the highest on Twitter. Specifically, the prevalence of the stated MOUD myth ranged from 0.4% on web-based health communities to 0.9% on Twitter. CONCLUSIONS This work provides one of the first large-scale assessments of a key MOUD-related myth across multiple social media platforms and highlights the feasibility and importance of ongoing assessment of health misinformation related to addiction treatment.

Government policy responses to coronavirus disease 2019 (COVID-19), especially social distancing measures, have generated speculation on behavioral health effects, including interpersonal violence, domestic violence, and child abuse.1 We investigated the association between COVID-19 lockdown and emergency department (ED) visits for violence-related injuries in Cardiff, Wales, using detailed violence screening for all ED patients.2 We hypothesized that lockdown measures would decrease violence outside the home but would increase violence at home.

BACKGROUND Online communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers. OBJECTIVE This qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums. METHODS We designed a valid, reliable, and clinically grounded process for identifying risk and protective markers in social media data. This scheme draws on prior work on construct validity and the social sciences of measurement. We then applied the scheme to annotate 200 posts from r/SuicideWatch—a Reddit community focused on suicide crisis. RESULTS We documented our results on producing an annotation scheme that is consistent with leading public health information coding schemes for suicide and advances attention to protective factors. Our study showed high internal validity, and we have presented results that indicate that our approach is consistent with findings from prior work. CONCLUSIONS Our work formalizes a framework that incorporates construct validity into the development of annotation schemes for suicide risk on social media. This study furthers the understanding of risk and protective factors expressed in social media data. This may help public health programming to prevent suicide and computational social science research and investigations that rely on the quality of labels for downstream machine learning tasks.

BackgroundOnline communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers.ObjectiveThis qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums.MethodsWe designed a valid, reliable, and clinically grounded process for identifying risk and protective markers in social media data. This scheme draws on prior work on construct validity and the social sciences of measurement. We then applied the scheme to annotate 200 posts from r/SuicideWatch—a Reddit community focused on suicide crisis.ResultsWe documented our results on producing an annotation scheme that is consistent with leading public health information coding schemes for suicide and advances attention to protective factors. Our study showed high internal validity, and we have presented results that indicate that our approach is consistent with findings from prior work.ConclusionsOur work formalizes a framework that incorporates construct validity into the development of annotation schemes for suicide risk on social media. This study furthers the understanding of risk and protective factors expressed in social media data. This may help public health programming to prevent suicide and computational social science research and investigations that rely on the quality of labels for downstream machine learning tasks.

This study aims to quantify the prevalence of forced sex, pressured sex, and related pregnancy among adolescent girls and young women in five low- and middle-income countries. Nationally representative, cross-sectional household surveys were conducted in Haiti, Malawi, Nigeria, Zambia, and Uganda among girls and young women aged 13 to 24 years. A stratified three-stage cluster sample design was used. Respondents were interviewed to assess prevalence of sexual violence, pregnancy related to the first or most recent experience of forced or pressured sex, relationship to perpetrator, mean age at sexual debut, mean age at pregnancy related to forced or pressured sex, and prevalence of forced/coerced sexual debut. Frequencies, weighted percentages, and weighted means are presented. The lifetime prevalence of forced or pressured sex ranged from 10.4% to 18.0%. Among these adolescent girls and young women, the percentage who experienced pregnancy related to their first or most recent experience of forced or pressured sex ranged from 13.2% to 36.6%. In three countries, the most common perpetrator associated with the first pregnancy related to forced or pressured sex was a current or previous intimate partner. Mean age at pregnancy related to forced or pressured sex was similar to mean age at sexual debut in all countries. Preventing sexual violence against girls and young women will prevent a significant proportion of adverse effects on health, including unintended pregnancy. Implementation of strategies to prevent and respond to sexual violence against adolescent girls and young women is urgently needed.

Beyond alcohol retail establishments, most business and property types receive limited attention in studies of violent crime. We sought to provide a comprehensive examination of which properties experience the most violent crime in a city and how that violence is distributed throughout a city.For a large urban city, we merged violent incident data from police reports with municipal tax assessor data from 2012-2017 and tabulated patterns of violent crime for 15 commercial and public property types. To describe outlier establishments, we calculated the proportion of individual parcels within each property-type that experienced more than 5 times the average number of crimes for that property-type and also mapped the 25 parcels with the highest number of violent incidents to explore what proportion of violent crime in these block groups were contributed by the outlier establishments.While the hotel/lodging property-type experienced the highest number of violent crimes per parcel (2.72), each property-type had outlier establishments experiencing more than 5 times the average number of violent crimes per business. Twelve of 15 property-types (80%) had establishments with more than 10 times the mean number of violent incidents. The 25 parcels with the most violent crime comprised a wide variety of establishments, ranging from a shopping center, grocery store, gas station, motel, public park, vacant lot, public street, office building, transit station, hospital, pharmacy, school, community center, and movie theatre, and were distributed across the city. Eight of the 25 parcels with the highest amount of violent crime, accounted for 50% or more of the violent crime within a 400-meter buffer.All property-types had outlier establishments experiencing elevated counts of violent crimes. Furthermore, the 25 most violent properties in the city demonstrated remarkable diversity in property-type. Further studies assessing the risk of violent crime among additional property-types may aid in violence prevention.

ObjectivesViolence is a major public health problem in the USA. In 2016, more than 1.6 million assault-related injuries were treated in US emergency departments (EDs). Unfortunately, information about the magnitude and patterns of violent incidents is often incomplete and underreported to law enforcement (LE). In an effort to identify more complete information on violence for the development of prevention programme, a cross-sectoral Cardiff Violence Prevention Programme (Cardiff Model) partnership was established at a large, urban ED with a level I trauma designation and local metropolitan LE agency in the Atlanta, Georgia metropolitan area. The Cardiff Model is a promising violence prevention approach that promotes combining injury data from hospitals and LE. The objective was to describe the Cardiff Model implementation and collaboration between hospital and LE partners.MethodsThe Cardiff Model was replicated in the USA. A process evaluation was conducted by reviewing project materials, nurse surveys and interviews and ED–LE records.ResultsCardiff Model replication centred around four activities: (1) collaboration between the hospital and LE to form a community safety partnership locally called the US Injury Prevention Partnership; (2) building hospital capacity for data collection; (3) data aggregation and analysis and (4) developing and implementing violence prevention interventions based on the data.ConclusionsThe Cardiff Model can be implemented in the USA for sustainable violent injury data surveillance and sharing. Key components include building a strong ED–LE partnership, communicating with each other and hospital staff, engaging in capacity building and sustainability planning.

BACKGROUND: Upstream public health indicators of poor mental health in the United States (U.S.) are currently measured by national telephone-based surveys; however, results are delayed by 1–2 years, limiting real-time assessment of trends. AIM: The aim of this study was to evaluate associations between conversational topics on Twitter from 2018 to 2019 and mental distress rates from 2017 to 2018 for the 50 U.S. states and capital. METHOD: We used a novel lexicon, Empath, to examine conversational topics from aggregate social media messages from Twitter that correlated most strongly with official U.S. state-level rates of mental distress from the Behavioral Risk Factor Surveillance System. RESULTS: The ten lexical categories most positively correlated with rates of frequent mental distress at the state-level included categories about death, illness, or injury. Lexical categories most inversely correlated with mental distress included categories that serve as proxies for economic prosperity and industry. Using the prevalence of the 10 most positively and 10 most negatively correlated lexical categories to predict state-level rates of mental distress via a linear regression model on an independent sample of data yielded estimates that were moderately similar to actual rates (mean difference = 0.52%; Pearson correlation = 0.45, p < 0.001). CONCLUSION: This work informs efforts to use social media to measure population-level trends in mental health.

Identifying geographic areas and time periods of increased violence is of considerable importance in prevention planning. This study compared the performance of multiple data sources to prospectively forecast areas of increased interpersonal violence. We used 2011–2014 data from a large metropolitan county on interpersonal violence (homicide, assault, rape and robbery) and forecasted violence at the level of census block-groups and over a one-month moving time window. Inputs to a Random Forest model included historical crime records from the police department, demographic data from the US Census Bureau, and administrative data on licensed businesses. Among 279 block groups, a model utilizing all data sources was found to prospectively improve the identification of the top 5% most violent block-group months (positive predictive value = 52.1%; negative predictive value = 97.5%; sensitivity = 43.4%; specificity = 98.2%). Predictive modelling with simple inputs can help communities more efficiently focus violence prevention resources geographically.

Understanding factors that are associated with disclosure of sexual violence (SV) is important for the delivery of health services as well as developing strategies for prevention and response. The Violence Against Children Surveys were conducted in Malawi and Nigeria. We examined the prevalence of SV, help-seeking behaviors, and factors associated with disclosure among girls and young women aged 13 to 24. The self-reported prevalence of SV was similar in Nigeria (26%) and Malawi (27%). Among females who experienced SV, approximately one third (37%) in Nigeria and one half (55%) in Malawi ever disclosed their experience of SV. Females in Nigeria were significantly more likely to disclose to their parents (31.8%) than females in Malawi (9.5%). The most common reason for nondisclosure in Nigeria was not feeling a need or desire to tell anyone (34.9%) and in Malawi was embarrassment (29.3%). Very close relationships with one or both parents were significantly associated with disclosure among Nigerian females (odds ratio [OR] = 5.5, 95% confidence interval [CI] = [2.1, 14.6]) but were inversely associated with disclosure among Malawian females (OR = 0.05, 95% CI = [0.01, 0.33]). Reasons for nondisclosure of SV and factors associated with disclosure among females differ in the African nations studied. The stigma associated with shame of SV may prevent females from disclosing and thus receiving necessary support and health, social, and other services. This study demonstrates a need to reduce barriers for disclosure to improve the delivery of health, social, and other response services across African nations, as well as to develop culturally appropriate strategies for its response.

Background Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts. Objective By adopting a multidisciplinary, mixed methods strategy, this paper aims to present machine learning and natural language analysis approaches to identify the characteristics and prevalence of web-based misinformation related to MOUD to inform future prevention, treatment, and response efforts. Methods The team harnessed public social media posts and comments in the English language from Twitter (6,365,245 posts), YouTube (99,386 posts), Reddit (13,483,419 posts), and Drugs-Forum (5549 posts). Leveraging public health expert annotations on a sample of 2400 of these social media posts that were found to be semantically most similar to a variety of prevailing opioid use disorder–related myths based on representational learning, the team developed a supervised machine learning classifier. This classifier identified whether a post’s language promoted one of the leading myths challenging addiction treatment: that the use of agonist therapy for MOUD is simply replacing one drug with another. Platform-level prevalence was calculated thereafter by machine labeling all unannotated posts with the classifier and noting the proportion of myth-indicative posts over all posts. Results Our results demonstrate promise in identifying social media postings that center on treatment myths about opioid use disorder with an accuracy of 91% and an area under the curve of 0.9, including how these discussions vary across platforms in terms of prevalence and linguistic characteristics, with the lowest prevalence on web-based health communities such as Reddit and Drugs-Forum and the highest on Twitter. Specifically, the prevalence of the stated MOUD myth ranged from 0.4% on web-based health communities to 0.9% on Twitter. Conclusions This work provides one of the first large-scale assessments of a key MOUD-related myth across multiple social media platforms and highlights the feasibility and importance of ongoing assessment of health misinformation related to addiction treatment.

Substances involved in overdose deaths have shifted over time and continue to undergo transition. Early detection of emerging drugs involved in overdose is a major challenge for traditional public health data systems. While novel social media data have shown promise, there is a continued need for robust natural language processing approaches that can identify emerging substances. Consequently, we developed a new metric, the relative similarity ratio, based on diachronic word embeddings to measure movement in the semantic proximity of individual substance words to 'overdose' over time. Our analysis of 64,420,376 drug-related posts made between January 2011 and December 2018 on Reddit, the largest online forum site, reveals that this approach successfully identified fentanyl, the most significant emerging substance in the overdose epidemic, >1 year earlier than traditional public health data systems. Use of diachronic word embeddings may enable improved identification of emerging substances involved in drug overdose, thereby improving the timeliness of prevention and treatment activities.

This study identified sociodemographic, substance use, and multiple opioid prescriber and dispenser risk factors among drug overdose decedents in Rhode Island, in response to an increase in overdose deaths (ODs) involving fentanyl.This cross-sectional investigation comprised all ODs reviewed by Rhode Island's Office of the State Medical Examiners (OSME) during January 2012 to March 2014. Data for 536 decedents were abstracted from OSME's charts, death certificates, toxicology reports, and Prescription Monitoring Program (PMP) databases. Decedents whose cause of death involved illicit fentanyl (N = 69) were compared with decedents whose causes of death did not involve fentanyl (other drug decedents; N = 467).Illicit-fentanyl decedents were younger than other drug decedents (P = 0.005). While more other-drug decedents than illicit fentanyl decedents had postmortem toxicological evidence of consuming heroin (31.9% vs 19.8%, P 0.001) and various pharmaceutical substances (P = 0.002-0.027), third party reports indicated more recent heroin use among illicit fentanyl decedents (62.3% vs 45.6%, P = 0.002). Approximately 35% of decedents filled an opioid prescription within 90 days of death; of these, one-third had a mean daily dosage greater than 100 morphine milligram equivalents (MME/day). Most decedents' opioid prescriptions were filled at one to two dispensers (83.9%) and written by one to two prescribers (75.8%). Notably, 29.2% of illicit fentanyl and 10.5% of other drug decedents filled prescriptions for buprenorphine, which is used to treat opioid use disorders.Illicit-fentanyl deaths frequently involved other illicit drugs (e.g., cocaine, heroin). The proportion of all decedents acquiring greater than 100 MME/day prescription dosages written and/or filled by few prescribers and dispensers is concerning. To protect patients, prescribers and dispensers should review PMP records and substance abuse history prior to providing opioids.

Objective To describe epidemiological characteristics of emergency department (ED) visits related to suicidal ideation (SI) or suicidal attempt (SA) using syndromic surveillance data. Introduction Suicide is a growing public health problem in the United States. 1 From 2001 to 2016, ED visit rates for nonfatal self-harm, a common risk factor for suicide, increased 42%. 2–4 To improve public health surveillance of suicide-related problems, including SI and SA, the Data and Surveillance Task Force within the National Action Alliance for Suicide Prevention recommended the use of real-time data from hospital ED visits. 5 The collection and use of real-time ED visit data on SI and SA could support a more targeted and timely public health response to prevent suicide. 5 Therefore, this investigation aimed to monitor ED visits for SI or SA and to identify temporal, demographic, and geographic patterns using data from CDC’s National Syndromic Surveillance Program (NSSP). Methods CDC’s NSSP data were used to monitor ED visits related to SI or SA among individuals aged 10 years and older from January 1, 2016 through July 31, 2018. A syndrome definition for SI or SA, developed by the International Society for Disease Surveillance’s syndrome definition committee in collaboration with CDC, was used to assess SI or SA-related ED visits. The syndrome definition was based on querying the chief complaint history, discharge diagnosis, and admission reason code and description fields for a combination of symptoms and Boolean operators (for example, hang, laceration, or overdose), as well as ICD-9-CM, ICD-10-CM, and SNOMED diagnostic codes associated with SI or SA. The definition was also developed to include common misspellings of self-harm-related terms and to exclude ED visits in which a patient “denied SI or SA.” The percentage of ED visits involving SI or SA were analyzed by month and stratified by sex, age group, and U.S. region. This was calculated by dividing the number of SI or SA-related ED visits by the total number of ED visits in each month. The average monthly percentage change of SI or SA overall and for each U.S. region was also calculated using the Joinpoint regression software (Surveillance Research Program, National Cancer Institute). 6 Results Among approximately 259 million ED visits assessed in NSSP from January 2016 to July 2018, a total of 2,301,215 SI or SA-related visits were identified. Over this period, males accounted for 51.2% of ED visits related to SI or SA, and approximately 42.1% of SI or SA-related visits were comprised of patients who were 20-39 years, followed by 40-59 years (29.7%), 10-19 years (20.5%), and ≥60 years (7.7%). During this period, the average monthly percentage of ED visits involving SI or SA significantly increased 1.1%. As shown in Figure 1, all U.S. regions, except for the Southwest region, experienced significant increases in SI or SA ED visits from January 2016 to July 2018. The average monthly increase of SI or SA-related ED visits was 1.9% for the Midwest, 1.5% for the West (1.5%), 1.1% for the Northeast, 0.9% for the Southeast, and 0.5% for the Southwest. Conclusions ED visits for SI or SA increased from January 2016 to June 2018 and varied by U.S. region. In contrast to previous findings reporting data from the National Electronic Injury Surveillance Program – All-Injury Program, we observed different trends in SI or SA by sex, where more ED visits were comprised of patients who were male in our investigation. 2 Syndromic surveillance data can fill an existing gap in the national surveillance of suicide-related problems by providing close to real-time information on SI or SA-related ED visits. 5 However, our investigation is subject to some limitations. NSSP data is not nationally representative and therefore, these findings are not generalizable to areas not participating in NSSP. The syndrome definition may under-or over-estimate SI or SA based on coding differences and differences in chief complaint or discharge diagnosis data between jurisdictions. Finally, hospital participation in NSSP can vary across months, which could potentially contribute to trends observed in NSSP data. Despite these limitations, states and communities could use this type of surveillance data to detect abnormal patterns at more detailed geographic levels and facilitate rapid response efforts. States and communities can also use resources such as CDC’s Preventing Suicide: A Technical Package of Policy, Programs, and Practices to guide prevention decision-making and implement comprehensive suicide prevention approaches based on the best available evidence. 7 References 1. Stone DM, Simon TR, Fowler KA, et al. Vital Signs: Trends in State Suicide Rates — United States, 1999–2016 and Circumstances Contributing to Suicide — 27 States, 2015. Morb Mortal Wkly Rep . 2018;67(22):617-624. 2. CDCs National Center for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS). https://www.cdc.gov/injury/wisqars/index.html. Published 2018. Accessed September 1, 2018. 3. Mercado M, Holland K, Leemis R, Stone D, Wang J. Trends in emergency department visits for nonfatal self-inflicted injuries among youth aged 10 to 24 years in the United States, 2005-2015. J Am Med Assoc . 2017;318(19):1931-1933. doi:10.1001/jama.2017.13317 4. Olfson M, Blanco C, Wall M, et al. National Trends in Suicide Attempts Among Adults in the United States. JAMA Psychiatry . 2017;10032(11):1095-1103. doi:10.1001/jamapsychiatry.2017.2582 5. Ikeda R, Hedegaard H, Bossarte R, et al. Improving national data systems for surveillance of suicide-related events. Am J Prev Med . 2014;47(3 SUPPL. 2):S122-S129. doi:10.1016/j.amepre.2014.05.026 6. National Cancer Institute. Joinpoint Regression Software. https://surveillance.cancer.gov/joinpoint/. Published 2018. Accessed September 1, 2018. 7. Centers for Disease Control and Prevention. Preventing Suicide: A Technical Package of Policy, Programs, and Practices.

Abstract. Background: The dissemination of positive messages about mental health is a key goal of organizations and individuals. Aims: Our aim was to examine factors that predict increased dissemination of such messages. Method: We analyzed 10,998 positive messages authored on Twitter and studied factors associated with messages that are shared (re-tweeted) using logistic regression. Characteristics of the account, message, linguistic style, sentiment, and topic were examined. Results: Less than one third of positive messages (31.7%) were shared at least once. In adjusted models, accounts that posted a greater number of messages were less likely to have any single message shared. Messages about military-related topics were 60% more likely to be shared (adjusted odds ratio [AOR] = 1.6, 95% CI [1.1, 2.1]) as well as messages containing achievement-related keywords (AOR = 1.6, 95% CI [1.3, 1.9]). Conversely, positive messages explicitly addressing eating/food, appearance, and sad affective states were less likely to be shared. Multiple other message characteristics influenced sharing. Limitations: Only messages on a single platform and over a focused period of time were analyzed. Conclusion: A knowledge of factors affecting dissemination of positive mental health messages may aid organizations and individuals seeking to promote such messages online.

INTRODUCTION: Accurately identifying youth at highest risk of firearm violence involvement could permit delivery of focused, comprehensive prevention services. This study explored whether readily available city and state administrative data covering life events before youth firearm violence could elucidate patterns preceding such violence. METHODS: Four hundred twenty-one individuals arrested for homicide, attempted homicide, aggravated assault, or robbery with a firearm committed in Wilmington, Delaware, from January 1, 2009 to May 21, 2014, were matched 1:3 to 1,259 Wilmington resident controls on birth year and sex. In 2015, descriptive statistics and a conditional logistic regression model using Delaware healthcare, child welfare, juvenile services, labor, and education administrative data examined associations between preceding life events and subsequent firearm violence. RESULTS: In a multivariable adjusted model, experiencing a prior gunshot wound injury (AOR=11.4, 95% CI=2.7, 48.1) and being subject to community probation (AOR=13.2, 95% CI=5.7, 30.3) were associated with the highest risk of subsequent firearm violence perpetration, though multiple other sentinel events were informative. The mean number of sentinel events experienced by youth committing firearm violence was 13.0 versus 1.9 among controls (pCONCLUSIONS: Youth who commit firearm violence have preceding patterns of life events that markedly differ from youth not involved in firearm violence. This information is readily available from administrative data, demonstrating the potential of data sharing across city and state institutions to focus prevention strategies on those at greatest risk.Published by Elsevier Inc. Language: en

Objective To describe the Violence Against Children Surveys (VACS). The survey is a national, household survey that systematically measures the prevalence, nature and consequences of sexual, physical and emotional violence against children. Design This report provides information about the history, implementation, ethical protections, utility, results, limitations, and future directions of the VACS work. Results The study has been implemented in 11 countries in Africa, Asia and the Caribbean, providing each of these countries with baseline data and momentum to address violence against children as a public health and human rights priority. These data are novel in each country, and VACS is well poised to contribute to an existing surveillance system or be used as the basis of a periodic surveillance system. Conclusions Without ongoing surveillance to assess prevalence and the impact of policy, prevention and response programming, violence will likely continue to be overlooked as the linchpin public health crisis that it is, globally and in individual countries.

Key Points Question Can real-time streams of secondary information related to suicide be used to accurately estimate suicide fatalities in the US in real time? Findings In this national cross-sectional study, combining information from 8 data streams encompassing various health services and online data sources enabled accurate, real-time estimation of US suicide fatalities with meaningful correlation to week-to-week epidemiological trends and a less than 1% error compared with actual counts. Meaning These findings advance the first efforts to create a population-level system for enabling real-time epidemiological trend monitoring of suicide fatalities., This cross-sectional study uses machine learning to estimate weekly suicide fatalities in the US in near real time., Importance Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making. Objective To estimate weekly suicide fatalities in the US in near real time. Design, Setting, and Participants This cross-sectional national study used a machine learning pipeline to combine signals from several streams of real-time information to estimate weekly suicide fatalities in the US in near real time. This 2-phase approach first fits optimal machine learning models to each individual data stream and subsequently combines predictions made from each data stream via an artificial neural network. National-level US administrative data on suicide deaths, health services, and economic, meteorological, and online data were variously obtained from 2014 to 2017. Data were analyzed from January 1, 2014, to December 31, 2017. Exposures Longitudinal data on suicide-related exposures were obtained from multiple, heterogeneous streams: emergency department visits for suicide ideation and attempts collected via the National Syndromic Surveillance Program (2015-2017); calls to the National Suicide Prevention Lifeline (2014-2017); calls to US poison control centers for intentional self-harm (2014-2017); consumer price index and seasonality-adjusted unemployment rate, hourly earnings, home price index, and 3-month and 10-year yield curves from the Federal Reserve Economic Data (2014-2017); weekly daylight hours (2014-2017); Google and YouTube search trends related to suicide (2014-2017); and public posts on suicide on Reddit (2 314 533 posts), Twitter (9 327 472 tweets; 2015-2017), and Tumblr (1 670 378 posts; 2014-2017). Main Outcomes and Measures Weekly estimates of suicide fatalities in the US were obtained through a machine learning pipeline that integrated the above data sources. Estimates were compared statistically with actual fatalities recorded by the National Vital Statistics System. Results Combining information from multiple data streams, the machine learning method yielded estimates of weekly suicide deaths with high correlation to actual counts and trends (Pearson correlation, 0.811; P

Objectives To estimate the proportion of opioid misuse attributable to adverse childhood experiences (ACEs) among adolescents. Study design A cross-sectional survey was administered to 10 546 seventh-to twelfth-grade students in northeastern Ohio in Spring 2018. Study measures included self-reported lifetime exposure to 10 ACEs and past 30-day use of nonmedical prescription opioid or heroin. Using generalized estimating equations, we evaluated associations between recent opioid misuse, individual ACEs, and cumulative number of ACEs. We calculated population attributable fractions to determine the proportion of adolescents' recent opioid misuse attributable to ACEs. Results Nearly 1 in 50 adolescents reported opioid misuse within 30 days (1.9%); approximately 60% of youth experienced ≥1 ACE; 10.2% experienced ≥5 ACEs. Cumulative ACE exposure demonstrated a significant graded relationship with opioid misuse. Compared with youth with zero ACEs, youth with 1 ACE (aOR 1.9, 95% CI, 0.9-3.9), 2 ACEs (aOR, 3.8; 95% CI, 1.9-7.9), 3 ACEs (aOR, 3.7; 95% CI, 2.2-6.5), 4 ACEs (aOR, 5.8; 95% CI, 3.1-11.2), and ≥5 ACEs (aOR, 15.3; 95% CI, 8.8-26.6) had higher odds of recent opioid misuse. The population attributable fraction of recent opioid misuse associated with experiencing ≥1 ACE was 71.6% (95% CI, 59.8-83.5). Conclusions There was a significant graded relationship between number of ACEs and recent opioid misuse among adolescents. More than 70% of recent adolescent opioid misuse in our study population was attributable to ACEs. Efforts to decrease opioid misuse could include programmatic, policy, and clinical practice interventions to prevent and mitigate the negative effects of ACEs.

This study examined national trends in self-directed violence in the context of changes in opioid use and depression to better inform prevention measures. Using 2000–2015 National Inpatient Sample (NIS) data, we identified 625,064 hospitalizations for self-directed violence among persons aged ≥10 years in the United States. Based on whether co-listing opioid related diagnosis and depression, we categorized hospitalizations for self-directed violence into four comorbid categories as 1) related to opioids alone; 2) related to depression alone; 3) related to both opioids and depression; and 4) related to neither opioids nor depression. Census population estimates served as the denominator for calculating hospitalization rates for self-directed violence. Hospitalization rates for self-directed violence related to opioids doubled from 5.1 per 100,000 persons in 2000 to 11.0 in 2015. The rate of increase was highest for self-directed violence related to both opioids and depression, which increased 9.4% annually during 2000–2011 and then decreased 4.3% annually during 2011–2015. Hospitalizations for self-directed violence related to depression alone remained the predominant category, accounting for approximately 60% of hospitalizations for self-directed violence; the rates among females aged 10–24 years were the highest among all subgroups, and rose 7.8% annually since 2011 reaching 93.2 per 100,000 persons in 2015. These findings highlight the importance of assessing the risk for self-directed violence among patients misusing opioids and the importance of treating opioid use disorder and depression, particularly when they co-occur. Prevention and treatment of depression is especially important for young females.

Sexual violence against children is a significant global public health problem, yet limited studies exist from low-resource settings. In Haiti we conducted the country’s first, nationally representative survey focused on childhood violence to help inform the development of a national action plan for violence against children. The Haiti Violence Against Children Survey was a household-level, multistage, cluster survey among youth age 13–24. In this analysis we sought to determine whether sexual violence sentinel events (unwanted sexual touching or unwanted attempted sex) were predictive of later unwanted, completed, penetrative sex in Haiti. We also sought to explore characteristics of sentinel events and help-seeking behavior among Haitian children. Multivariable logistic regression was used to test associations between sentinel events and later unwanted, completed, penetrative sex. Overall, 1,457 females reported on experiences of sexual violence occurring in childhood (before age 18). A sentinel event occurred in 40.4% of females who experienced subsequent unwanted completed sex. Females experiencing a sentinel event were approximately two and a half times more likely to experience later unwanted completed sex (adjusted odds ratio = 2.40, p = .004) compared to individuals who did not experience a sentinel event. The mean lag time from first sentinel event to first unwanted completed sex was 2.3 years. Only half (54.6%) of children experiencing a sentinel event told someone about their experience of sexual violence. Among children, sentinel events occur frequently before later acts of completed unwanted sex and may represent a useful point of intervention. Reporting of sexual violence by children in Haiti is low and can be improved to better act on sentinel events.

Naloxone administration is an important component of resuscitation attempts by emergency medical services (EMS) for opioid drug overdoses. However, EMS providers must first recognize the possibility of opioid overdose in clinical encounters. As part of a public health response to an outbreak of opioid overdoses in Rhode Island, we examined missed opportunities for naloxone administration and factors potentially influencing EMS providers’ decision to administer naloxone. We reviewed medical examiner files on all individuals who died of an opioid-related drug overdose in Rhode Island from January 1, 2012 through March 31, 2014, underwent attempted resuscitation by EMS providers, and had records available to assess for naloxone administration. We evaluated whether these individuals received naloxone as part of their resuscitation efforts and compared patient and scene characteristics of those who received naloxone to those who did not receive naloxone via chi-square, t-test, and logistic regression analyses. One hundred and twenty-four individuals who underwent attempted EMS resuscitation died due to opioid overdose. Naloxone was administered during EMS resuscitation attempts in 82 (66.1%) of cases. Females were nearly three-fold as likely not to receive naloxone as males (OR 2.9; 95% CI 1.2–7.0; p-value 0.02). Additionally, patients without signs of potential drug abuse also had a greater than three-fold odds of not receiving nalox-one (OR 3.3; 95% CI 1.2–9.2; p-value 0.02). Older individuals, particularly those over age 50, were more likely not to receive naloxone than victims younger than age 30 (OR 4.8; 95% CI 1.3–17.4; p-value 0.02). Women, older individuals, and those patients without clear signs of illicit drug abuse, were less likely to receive naloxone in EMS resuscitation attempts. Heightened clinical suspicion for opioid overdose is important given the recent increase in overdoses among patients due to prescription opioids.

Policing and public health have largely been perceived by clinicians, researchers, and policy makers as 2 entirely separate approaches to reducing violence. This long-standing tradition, reinforced by the different languages of criminal justice systems (eg, deterrence, culpability, victimhood, and offending) and public health systems (eg, injury, risk factors, and epidemiology), has perhaps contributed to limited collaboration between local law enforcement agencies and public health to prevent violence. It has also probably limited collaboration between criminologists and population health researchers relative to other cross-discipline areas such as road traffic safety, prisoner health, and prevention of substance abuse.

Interpersonal firearm violence among youth is a substantial public health problem, and emergency department (ED) physicians require a clinical screening tool to identify high-risk youth.To derive a clinically feasible risk index for firearm violence.24-month prospective cohort study.Urban, level 1 ED.Substance-using youths, aged 14 to 24 years, seeking ED care for an assault-related injury and a proportionately sampled group of non-assault-injured youth enrolled from September 2009 through December 2011.Firearm violence (victimization/perpetration) and validated questionnaire items.A total of 599 youths were enrolled, and presence/absence of future firearm violence during follow-up could be ascertained in 483 (52.2% were positive). The sample was randomly split into training (75%) and post-score-construction validation (25%) sets. Using elastic-net penalized logistic regression, 118 baseline predictors were jointly analyzed; the most predictive variables fell predominantly into 4 domains: violence victimization, community exposure, peer influences, and fighting. By selection of 1 item from each domain, the 10-point SaFETy (Serious fighting, Friend weapon carrying, community Environment, and firearm Threats) score was derived. SaFETy was associated with firearm violence in the validation set (odds ratio [OR], 1.47 [95% CI, 1.23 to 1.79]); this association remained (OR, 1.44 [CI, 1.20 to 1.76]) after adjustment for reason for ED visit. In 5 risk strata observed in the training data, firearm violence rates in the validation set were 18.2% (2 of 11), 40.0% (18 of 45), 55.8% (24 of 43), 81.3% (13 of 16), and 100.0% (6 of 6), respectively.The study was conducted in a single ED and involved substance-using youths. SaFETy was not externally validated.The SaFETy score is a 4-item score based on clinically feasible questionnaire items and is associated with firearm violence. Although broader validation is required, SaFETy shows potential to guide resource allocation for prevention of firearm violence.National Institute on Drug Abuse R01024646.