Bullying as a Longitudinal Predictor of Adolescent Dating Violence

One suggested approach to preventing adolescent dating violence is to prevent behavioral precursors to dating violence, such as bullying. However, no longitudinal study has examined bullying as a behavioral precursor to dating violence. In this study, longitudinal data were used to examine (1) whether direct and indirect bullying perpetration in the sixth grade predicted the onset of physical dating violence perpetration by the eighth grade and (2) whether the associations varied by sex and race/ethnicity of the adolescent

An RCT of dating matters:Effects on teen dating violence and relationship behaviors

Introduction Teen dating violence is a serious public health problem with few effective prevention strategies. This study examines whether the Dating Matters comprehensive prevention model, compared with a standard of care intervention, prevented negative relationship behaviors and promoted positive relationship behaviors. Study design This longitudinal, cluster-RCT compared the effectiveness of Dating Matters with standard of care across middle school. Standard of care was an evidence-based teen dating violence prevention curriculum (Safe Dates) implemented in eighth grade. Setting/participants Forty-six middle schools in high-risk urban neighborhoods in four U.S. cities were randomized. Schools lost to follow-up were replaced with new schools, which were independently randomized (71% school retention). Students were surveyed in fall and spring of sixth, seventh, and eighth grades (2012–2016). The analysis sample includes students from schools implementing Dating Matters or standard of care for >2 years who started sixth grade in the fall of 2012 or 2013 and had dated (N=2,349 students, mean age 12 years, 49% female, and 55% black, non-Hispanic, 28% Hispanic, 17% other). Intervention Dating Matters is a comprehensive, multicomponent prevention model including classroom-delivered programs for sixth to eighth graders, training for parents of sixth to eighth graders, educator training, a youth communications program, and local health department activities to assess capacity and track teen dating violence–related policy and data. Main outcome measures Self-reported teen dating violence perpetration and victimization, use of negative conflict resolution strategies, and positive relationship skills were examined as outcomes. Imputation and analyses were conducted in 2017. Results Latent panel models demonstrated significant program effects for three of four outcomes; Dating Matters students reported 8.43% lower teen dating violence perpetration, 9.78% lower teen dating violence victimization, and 5.52% lower use of negative conflict resolution strategies, on average across time points and cohorts, than standard of care students. There were no significant effects on positive relationship behaviors. Conclusions Dating Matters demonstrates comparative effectiveness, through middle school, for reducing unhealthy relationship behaviors, such as teen dating violence and use of negative conflict resolution strategies, relative to the standard of care intervention

Relationship Characteristics Associated with Teen Dating Violence Perpetration

Teen dating violence (TDV) is unstable across dating relationships, suggesting that characteristics of the relationship could be related to TDV. Few empirical studies have examined these links. This study examined associations between relationship characteristics and TDV perpetration among teens and sex differences in those associations. Relationship characteristics examined include tactics used to manipulate partners; ways of responding to relationship problems; relationship duration; exclusivity of the relationship; age difference between partners; and history of sexual intercourse with partner. Data were drawn from 667 teens in a current relationship (62.5% female and 81.4% white) enrolled in the 11(th) or 12(th) grade in 14 public schools in a rural US state. Bivariate and multivariable regression analyses examined proposed associations. 30.1% and 8.2% of teens reported controlling and physical TDV perpetration, respectively. In multivariable models, frequent use manipulation tactics increased risk for controlling or physical TDV perpetration. Teens dating a partner two or more years younger were at significantly increased risk for both controlling and physical perpetration. A significant interaction emerged between sex and exit/neglect accommodation for physical TDV. Characteristics of a current dating relationship play an important role in determining risk for controlling and physical TDV perpetration

Examining explanations for the link between bullying perpetration and physical dating violence perpetration: Do they vary by bullying victimization?

This short-term longitudinal study examined whether the association between bullying perpetration and later physical dating violence perpetration and mediators of that association (via anger, depression, anxiety, and social status), varied depending on level of bullying victimization. Differences have been noted between those who bully but are not victims of bullying, and those who are both bullies and victims. These differences may influence dating violence risk and the explanations for why bullying leads to dating violence. Data were from dating adolescents in three rural counties who completed self-administered questionnaires in the fall semester of grades 8-10 and again in the spring semester. The sample (N = 2,414) was 44.08% male and 61.31% white. Bullying perpetration in the fall semester predicted physical dating violence perpetration in the spring semester when there was no bullying victimization, but not when there was any bullying victimization. Bullying perpetration was positively associated with anger at all levels of bullying victimization and with social status when there was no or low amounts of victimization; it was negatively associated with social status at high levels of victimization. Bullying victimization was positively associated with anger, depression, and anxiety at all levels of bullying perpetration. Anger mediated the association between bullying perpetration and dating violence, regardless of level of victimization; depression, anxiety, and social status did not mediate the association at any level of bullying victimization. The findings have implications for dating violence prevention efforts and for future research on the link between bullying and dating violence

Estimating weekly national opioid overdose deaths in near real time using multiple proxy data sources.

Importance: 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. Question: Can proxy data sources be used to estimate national opioid overdose mortality trends in near real time? Finding: In this cross-sectional time series analysis, signals from 5 overdose-related, proxy data sources encompassing health, law enforcement, and online data from 2014 to 2019 in the US were combined via a statistical model that was able to demonstrate that these data can be used to estimate national opioid overdose death rates with an approximate 1% error. Meaning: This study suggests that it may be possible to enable a more timely understanding of national opioid overdose mortality trends through the use of near–real-time proxy data sources

Monitoring suicide-related events using National Syndromic Surveillance Program data

ObjectiveTo describe epidemiological characteristics of emergency department (ED) visits related to suicidal ideation (SI) or suicidal attempt (SA) using syndromic surveillance data.IntroductionSuicide 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).MethodsCDC’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).6ResultsAmong 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.ConclusionsED 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.7References1. 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.2017.133174. 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.2017.25825. 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.2014.05.0266. 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.

Using Syndromic Surveillance Data to Study the Impact of Media Content on Self-harm

ObjectiveTo describe national-level trends in nonfatal self-harm and suicidal ideation among 10-19 year old youth from January 2016 through December 2017 and examine the impact of popular entertainment on suicidal behavior.IntroductionIn 2016, a half million people were treated in U.S. emergency departments (EDs) as a result of self-harm. 1 Not only is self-harm a major cause of morbidity in the U.S., but it is also one of the best predictors of suicide. Given that approximately 40% of suicide decedents visited an ED in the year prior to their death and that the majority of medically-serious self-harm patients are treated in EDs2, EDs serve as a critical setting in which to monitor rates and trends of suicidal behavior.To date, the majority of ED data for self-harm are generally two to three years old and thereby can only be used to describe historical patterns in suicidal behavior. Thus, in 2018, a syndrome definition for suicide attempts and suicidal ideation (SA/SI) was developed by the International Society for Disease Surveillance (ISDS) Syndrome Definition Committee in conjunction with Centers for Disease Control and Prevention (CDC) staff, allowing researchers to better monitor recent trends in medically treated suicidal behavior using data from the CDC’s National Syndromic Surveillance Program (NSSP). These data serve as a valuable resource to help detect deviations from typical patterns of SA/SI and can help drive public health response if atypical activity, such as geospatial or temporal clusters of SA/SI, is observed. Such patterns may be indicative of suicide contagion (i.e., exposure to the suicide or suicidal behavior of a friend or loved one, or through media content, that may put individuals at increased risk of suicidal behavior).Research has demonstrated that suicide contagion is a real phenomenon. 3 13 Reasons Why is a Netflix series focused on social, school, and family-related challenges experienced by a high school sophomore; each episode in the 13-episode series describes a problem faced by the main character, which she indicates contributed to her decision to die by suicide. The series premiered March 31, 2017 and is rated TV-MA by TV Parental Guidelines4 (may be unsuitable for those under age 18 years due to graphic content). Nevertheless, the series has become popular among youth under 18 years of age. Of note, in the final episode, the main character’s suicide by wrist laceration is graphically depicted. Following the premiere of the series, researchers and psychologists across the U.S. expressed concern that this graphic depiction of suicide could result in a contagion effect, potentially exacerbating suicidal thoughts and behavior among vulnerable youth viewers. To date, the only empirical data demonstrating the potential iatrogenic effects of this graphic portrayal of suicide comes from a study of Google Trends data demonstrating an increase in online suicide queries in the weeks following the show, with most of the queries focusing on suicidal ideation (e.g., “how to commit suicide,” “how to kill yourself”).5 However, there has been no study to examine changes in nonfatal self-harm trends following the series debut.MethodsNSSP data were aggregated at the national level from January 2016 through December 2017 to examine weekly trends in the percentage of ED visits that involved SA/SI among all ED visits for youth aged 10-19. Google Trends data were also used to examine suicide-related online searches conducted during this period. Additional sensitivity analyses to explore these findings will be conducted by HHS region using NSSP data.ResultsPreliminary results suggest an increase in ED visits due to SA/SI among 10-19 year old youth across the U.S. beginning about two weeks after the premiere of 13 Reasons Why (April 16, 2017) and lasting a total of six weeks before weekly percentages of SA/SI ED visits returned to their endemic levels during the week of May 28-June 3, 2017. The peak of the increase represented a 26% increase in SA/SI compared to the highest weekly percentage of these visits in the previous 15 weeks in 2017. Additionally, this peak coincided with marked peaks in online searches for phrases including “13 Reasons Why” from March 26-June 3, 2017, “how to kill yourself” from April 16-June 3, 2017, and “how to slit wrists” from April 2-June 3, 2017 as demonstrated by Google Trends data.ConclusionsThis study demonstrates the utility of syndromic surveillance data for tracking SA/SI at the national level and for detecting atypical fluctuations in trends over time. Using syndromic surveillance data for this purpose could help spark public health response to emerging health threats. However, it is important to note that NSSP data are subject to some limitations; for instance, although about 60% of ED visits in the U.S. are captured in NSSP, the system is not nationally representative and thus, these findings are not generalizable to areas not participating in NSSP. Additionally, our definition may under- or over-estimate SA/SI based on differences in chief complaints or discharge diagnosis data between jurisdictions. Further, hospital participation in NSSP can vary across months–a factor that could contribute to trends observed in NSSP data. Finally, these analyses explored the concurrent trends in SA/SI among youth and the popularity of only one television series. Although these analyses point to an association between the increases in SA/SI and the time period in which the series reached its peak popularity as evidenced by Google Trends, there may have been other sociocultural factors that impacted SA/SI trends during the study period. Still, preliminary findings suggest that media content containing graphic depictions of suicide viewed by youth audiences may contribute to increases in ED visits for self-harm and suicidal ideation, as well as greater interest in searching for information about suicidal behavior online. While it is impossible to assess causation, these results are consistent with the phenomenon of suicide contagion. It is also possible that the series or related media coverage during this time increased help-seeking among some youth or their families that contributed to the increases observed. Regardless of the underlying mechanism, entertainment content creators may consider referring to the Recommendations for Reporting on Suicide (www.reportingonsuicide.org), which can help reduce the risk of suicide among vulnerable individuals and avoid contributing to suicide contagion while promoting suicide prevention messages. Finally, ongoing surveillance of suicidal behavior using NSSP data could help reduce the burden of nonfatal self-harm by catalyzing the implementation of prevention efforts.Results1. Center for Disease Control and Prevention, National Center for Injury Prevention and Control. (2018). Web-based Injury Statistics Query and Reporting System (WISQARS). Available from www.cdc.gov/ncipc/wisqars. Accessed 10-3-2018.2. Ahmedani BK, Simon GE, Stewart C et al. (2014) Health care contacts in the year before suicide death. J Gen Intern Med, 29, 870-877.3. Gould, M., Jamieson, P., & Romer, D. (2003). Media contagion and suicide among the young. American Behavioral Scientist, 46(9), 1269-1284.4. The TV Parental Guidelines. (2018). Available from http://tvguidelines.org/. Accessed 10-3-2018.5. Ayers, J. W., Althouse, B. M., Leas, E. C., Dredze, M., & Allem, J. P. (2017). Internet searches for suicide following the release of 13 Reasons Why. JAMA internal medicine, 177(10), 1527-1529.