Officer-Involved Killings of Unarmed Black People and Racial Disparities in Sleep Health.

Importance: Racial disparities in sleep health may mediate the broader health outcomes of structural racism. Objective: To assess changes in sleep duration in the Black population after officer-involved killings of unarmed Black people, a cardinal manifestation of structural racism. Design, Setting, and Participants: Two distinct difference-in-differences analyses examined the changes in sleep duration for the US non-Hispanic Black (hereafter, Black) population before vs after exposure to officer-involved killings of unarmed Black people, using data from adult respondents in the US Behavioral Risk Factor Surveillance Survey (BRFSS; 2013, 2014, 2016, and 2018) and the American Time Use Survey (ATUS; 2013-2019) with data on officer-involved killings from the Mapping Police Violence database. Data analyses were conducted between September 24, 2021, and September 12, 2023. Exposures: Occurrence of any police killing of an unarmed Black person in the state, county, or commuting zone of the survey respondent's residence in each of the four 90-day periods prior to interview, or occurence of a highly public, nationally prominent police killing of an unarmed Black person anywhere in the US during the 90 days prior to interview. Main Outcomes and Measures: Self-reported total sleep duration (hours), short sleep (<7 hours), and very short sleep (<6 hours). Results: Data from 181 865 Black and 1 799 757 White respondents in the BRFSS and 9858 Black and 46 532 White respondents in the ATUS were analyzed. In the larger BRFSS, the majority of Black respondents were between the ages of 35 and 64 (99 014 [weighted 51.4%]), women (115 731 [weighted 54.1%]), and college educated (100 434 [weighted 52.3%]). Black respondents in the BRFSS reported short sleep duration at a rate of 45.9%, while White respondents reported it at a rate of 32.6%; for very short sleep, the corresponding values were 18.4% vs 10.4%, respectively. Statistically significant increases in the probability of short sleep and very short sleep were found among Black respondents when officers killed an unarmed Black person in their state of residence during the first two 90-day periods prior to interview. Magnitudes were larger in models using exposure to a nationally prominent police killing occurring anywhere in the US. Estimates were equivalent to 7% to 16% of the sample disparity between Black and White individuals in short sleep and 13% to 30% of the disparity in very short sleep. Conclusions and Relevance: Sleep health among Black adults worsened after exposure to officer-involved killings of unarmed Black individuals. These empirical findings underscore the role of structural racism in shaping racial disparities in sleep health outcomes.

Evaluating the impact of a street outreach intervention on participant involvement in gun violence.

The past several years have witnessed increased calls for community violence interventions (CVIs) that address firearm violence while centering local expertise and avoiding the criminal legal system. Currently, little evidence exists on CVI effectiveness at the individual level. This study presents an evaluation of the impact of a street outreach-based CVI [Chicago CRED (Create Real Economic Destiny)] on participant involvement in violence. We used a quasiexperimental design with a treatment sample of 324 men recruited by outreach staff from 2016 to 2021 and a balanced comparison sample of 2,500 men from a network of individuals arrested in CRED's service areas. We conducted a Bayesian survival analysis to evaluate CRED's effect on individual violence-related outcomes on three levels of treatment: All enrolled participants, a subsample that made it through the initial phase, and those who completed programming. The intervention had a strong favorable effect on the probability of arrest for a violent crime for those completing the program: After 24 mo, CRED alumni experienced an 11.3 percentage point increase in survival rates of arrest for a violent crime relative to their comparisons (or, stated differently, a 73.4% reduction in violent crime arrests). The other two treatment levels experienced nontrivial declines in arrests but did not reach statistical significance. No statistically significant reduction in victimization risk was detected for any of the treatment levels. Results demonstrate that completion of violence intervention programming reduces the likelihood of criminal legal involvement for participants, despite the numerous systemic and environmental factors that impede personal success.

"We know what's going on in our community": A qualitative analysis identifying community assets that deter gun violence.

Communities of color are disproportionately impacted by gun violence. Unlocking potential community-led solutions could be the key to quelling the gun violence epidemic and its impact on these communities. In this qualitative study, we explored community perspectives on local assets that may prevent and mitigate gun violence. We conducted semi-structured, in-depth interviews (n = 45) among individuals not directly involved in gun violence (i.e., shooting victim or perpetrator) despite having a high probability of being involved in gun violence in New Haven, CT. Participants were asked to describe social structures that may deter local gun violence. Here, we report emergent themes to preventing gun violence across multiple levels, including role models (interpersonal), social cohesion and home ownership (neighborhood), and community-based organizations (organizational). Our findings suggest that investments in stable housing, efforts to build social cohesion, access to community-based mental health services, and youth activities are needed to curb the drivers of community gun violence.

Exposure to gun violence among the population of Chicago community violence interventionists.

Gun violence is a leading cause of premature death and a driver of racial disparities in life expectancy in the United States. Community-based interventions are the foremost policy strategy for reducing gun violence without exacerbating harm associated with criminal justice approaches. However, little is known about the interventionist workforce. In 2021, we used a researcher-guided survey to obtain a near-census of Chicago violence interventionists (n = 181, 93% response rate). Workers were mostly male (84%) and Black (80.9%), with a mean age of 43.6 years. Interventionists commonly experienced work-related exposure to violence and direct victimization. A total of 59.4% witnessed someone being shot at, whereas 32.4% witnessed a victim struck by gunfire. During work hours, 19.6% were shot at, while 2.2% were nonfatally shot. Single-year rates of gun violence victimization exceeded those of Chicago police. Results suggest that investment in community violence intervention should prioritize improving worker safety and reducing violence exposure while developing support for vulnerable frontline practitioners.

The experience of secondary traumatic stress among community violence interventionists in Chicago.

Community violence intervention strategies are rising in prominence as promising alternatives to traditional criminal justice responses to gun violence. Although such approaches may offer policy advantages and yield societal benefits, the costs to the practitioners of this work-owing to the intimate proximity to violence required by the job-have generally been overlooked. Using a first of its kind survey of nearly the entire population of community-based violence interventionists in Chicago, Illinois (United States), this study assesses the extent to which violence intervention workers experience Secondary Traumatic Stress (STS). Responses to a series of 17 items on a Secondary Traumatic Stress Scale revealed alarmingly high levels of STS among violence interventionists: 94% of workers reported at least one STS indicator in the past 7 days and a full 50% reported experiencing 9 out of the 17 STS items. Our analysis further showed that the STS responses of interventionists were impacted by on-the-job traumatic experiences, particularly the death of a client. These results offer an important first systematic analysis of the trauma and mental health risks associated with community violence intervention practice and suggest that policymakers and practitioners should monitor and address worker risk of traumatic stress within this important public health profession.

Identifying misconduct-committing officer crews in the Chicago police department.

Explanations for police misconduct often center on a narrow notion of "problem officers," the proverbial "bad apples." Such an individualistic approach not only ignores the larger systemic problems of policing but also takes for granted the group-based nature of police work. Nearly all of police work is group-based and officers' formal and informal networks can impact behavior, including misconduct. In extreme cases, groups of officers (what we refer to as, "crews") have even been observed to coordinate their abusive and even criminal behaviors. This study adopts a social network and machine learning approach to empirically investigate the presence and impact of officer crews engaging in alleged misconduct in a major U.S. city: Chicago, IL. Using data on Chicago police officers between 1971 and 2018, we identify potential crews and analyze their impact on alleged misconduct and violence. Results detected approximately 160 possible crews, comprised of less than 4% of all Chicago police officers. Officers in these crews were involved in an outsized amount of alleged and actual misconduct, accounting for approximately 25% of all use of force complaints, city payouts for civil and criminal litigations, and police-involved shootings. The detected crews also contributed to racial disparities in arrests and civilian complaints, generating nearly 18% of all complaints filed by Black Chicagoans and 14% of complaints filed by Hispanic Chicagoans.

Complaints about excessive use of police force in women's neighborhoods and subsequent perinatal and cardiovascular health.

There are substantial, unexplained racial disparities in women's health. Some of the most pronounced involve elevated rates of preterm delivery (PTD) and cardiovascular disease (CVD) among Black women. We hypothesized that stress associated with excessive use of force by police may contribute to these disparities. In two prospective cohorts derived from electronic health records (pregnancy cohort, N = 67,976; CVD cohort, N = 6773), we linked formal complaints of excessive police force in patients' neighborhoods with health outcomes. Exposed Black women were 1.19 times as likely to experience PTD [95% confidence interval (CI): 1.04 to 1.35] and 1.42 times as likely to develop CVD (95% CI: 1.12 to 1.79), even after adjustment for neighborhood disadvantage and homicide. The excess risks of PTD were also observed in maternal fixed-effects analyses comparing births to the same woman. These findings suggest police violence may be an unrecognized contributor to health inequity for Black women.

Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions.

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g., wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health, leading to the goal of precise phenotypic correlates for genotypes. Even though treatments and interventions are becoming more specific and datasets more abundant, measuring the causal impact of health interventions requires careful considerations of complex covariate structures, as well as knowledge of the temporal and spatial properties of the data. Thus, interpreting biomedical sensor data needs to make use of specialized statistical models. Here, we show how the Bayesian structural time series framework, widely used in economics, can be applied to these data. This framework corrects for covariates to provide accurate assessments of the significance of interventions. Furthermore, it allows for a time-dependent confidence interval of impact, which is useful for considering individualized assessments of intervention efficacy. We provide a customized biomedical adaptor tool, MhealthCI, around a specific implementation of the Bayesian structural time series framework that uniformly processes, prepares, and registers diverse biomedical data. We apply the software implementation of MhealthCI to a structured set of examples in biomedicine to showcase the ability of the framework to evaluate interventions with varying levels of data richness and covariate complexity and also compare the performance to other models. Specifically, we show how the framework is able to evaluate an exercise intervention's effect on stabilizing blood glucose in a diabetes dataset. We also provide a future-anticipating illustration from a behavioral dataset showcasing how the framework integrates complex spatial covariates. Overall, we show the robustness of the Bayesian structural time series framework when applied to biomedical sensor data, highlighting its increasing value for current and future datasets.

Bad apples and incredible certitude.

Research summary: Chalfin and Kaplan attend to the problem of police misconduct with a series of simulation analyses that leverage data on complaints and uses of force in the Chicago Police Department. They conclude that incapacitating officers has minimal effects on misconduct and that, given political constraints, policy makers may prefer broader reforms around accountability and management to removing "bad apples". In this comment, we argue that this conclusion and its policy implications are characterized by "incredible certitude" driven by a selective focus on a subset of their full simulation results and inadequate incorporation of network spillovers into their analysis. Policy implications: Contrary to CK's conclusions, their preferred estimates of the effect of incapacitating "bad apples" on misconduct are squarely within the range of other interventions aimed at reducing police complaints and use of force. Once network spillovers are accounted for, estimates are up to five times as large. We conclude with a discussion of how even small reductions in misconduct can have outsized benefits as measured in both dollars and human suffering, and argue that the removal of problem officers is a normative good that should be pursued on moral grounds.

Building community resilience to prevent and mitigate community impact of gun violence: conceptual framework and intervention design.

INTRODUCTION: The USA has the highest rate of community gun violence of any developed democracy. There is an urgent need to develop feasible, scalable and community-led interventions that mitigate incident gun violence and its associated health impacts. Our community-academic research team received National Institutes of Health funding to design a community-led intervention that mitigates the health impacts of living in communities with high rates of gun violence. METHODS AND ANALYSIS: We adapted 'Building Resilience to Disasters', a conceptual framework for natural disaster preparedness, to guide actions of multiple sectors and the broader community to respond to the man-made disaster of gun violence. Using this framework, we will identify existing community assets to be building blocks of future community-led interventions. To identify existing community assets, we will conduct social network and spatial analyses of the gun violence episodes in our community and use these analyses to identify people and neighbourhood blocks that have been successful in avoiding gun violence. We will conduct qualitative interviews among a sample of individuals in the network that have avoided violence (n=45) and those living or working on blocks that have not been a location of victimisation (n=45) to identify existing assets. Lastly, we will use community-based system dynamics modelling processes to create a computer simulation of the community-level contributors and mitigators of the effects of gun violence that incorporates local population-based based data for calibration. We will engage a multistakeholder group and use themes from the qualitative interviews and the computer simulation to identify feasible community-led interventions. ETHICS AND DISSEMINATION: The Human Investigation Committee at Yale University School of Medicine (#2000022360) granted study approval. We will disseminate study findings through peer-reviewed publications and academic and community presentations. The qualitative interview guides, system dynamics model and group model building scripts will be shared broadly.

The influence of firearms trafficking on gunshot injuries in a co-offending network.

Individuals at the greatest risk of gunshot victimization are often prohibited from legally acquiring guns in the U.S. due to prior felony convictions or other disqualifications. Prohibited persons often rely on others - such as friends, family members, fellow gang members, and gun brokers - to acquire firearms. This study examines whether the sources of guns recovered from high-risk individuals differ relative to the sources of guns recovered more generally in a major U.S. city, and whether illegally-diverted guns are associated with increased gunshot victimization risk. Using official data, we recreate the co-offending network of individuals in Boston who were arrested or contacted by the police with at least one other person between 2007 and 2014. Firearms trace data are then used to develop measures of the shortest distance between individuals and firearms in their immediate network. Results suggest guns with markers of illegal diversion are more likely to be recovered in the highest risk sector of the network and that the probability of gunshot victimization increases with decreased distance to an individual linked to firearms with markers of illegal trafficking.

Procedural justice training reduces police use of force and complaints against officers.

Existing research shows that distrust of the police is widespread and consequential for public safety. However, there is a shortage of interventions that demonstrably reduce negative police interactions with the communities they serve. A training program in Chicago attempted to encourage 8,480 officers to adopt procedural justice policing strategies. These strategies emphasize respect, neutrality, and transparency in the exercise of authority, while providing opportunities for civilians to explain their side of events. We find that training reduced complaints against the police by 10.0% and reduced the use of force against civilians by 6.4% over 2 y. These findings affirm the feasibility of changing the command and control style of policing which has been associated with popular distrust and the use of force, through a broad training program built around the concept of procedurally just policing.

Modeling the origin of urban-output scaling laws.

Urban outputs often scale superlinearly with city population. A difficulty in understanding the mechanism of this phenomenon is that different outputs differ considerably in their scaling behaviors. Here, we formulate a physics-based model for the origin of superlinear scaling in urban outputs by treating human interaction as a random process. Our model suggests that the increased likelihood of finding required collaborations in a larger population can explain this superlinear scaling, which our model predicts to be non-power-law. Moreover, the extent of superlinearity should be greater for activities that require more collaborators. We test this model using a novel dataset for seven crime types and find strong support.

Reducing gunshot victimization in high-risk social networks through direct and spillover effects.

More than 60,000 people are victimized by gun violence each year in the United States. A large share of victims cluster in bounded and identifiable social networks. Despite a growing number of violence reduction programmes that leverage networks to broaden programmatic effects, there is little evidence that reductions in victimization are achieved through spillover effects on the peers of participants. This study estimates the direct and spillover effects of a gun violence field intervention in Chicago. Using a quasi-experimental design, we test whether a desistance-based programme reduced gunshot victimization among 2,349 participants. The study uses co-arrest network data to further test spillover effects on 6,132 non-participants. Direct effects were associated with a 3.2-percentage point reduction in victimization among seeds over two years, while potential spillover was associated with a 1.5-percentage point reduction among peers. Findings suggest that peer influence and the structure of networks might be leveraged to amplify gun violence reduction efforts.

Hot spots policing of small geographic areas effects on crime.

Background: In recent years, crime scholars and practitioners have pointed to the potential benefits of focusing crime prevention efforts on crime places. A number of studies suggest that there is significant clustering of crime in small places, or "hot spots," that generate half of all criminal events. Researchers have argued that many crime problems can be reduced more efficiently if police officers focused their attention to these deviant places. The appeal of focusing limited resources on a small number of high-activity crime places is straightforward. If crime can be prevented at these hot spots, then citywide crime totals could be reduced. Objectives: To assess the effects of focused police crime prevention interventions at crime hot spots. The review also examined whether focused police actions at specific locations result in crime displacement (i.e., crime moving around the corner) or diffusion (i.e., crime reduction in surrounding areas) of crime control benefits. Search Methods: A keyword search was performed on 15 abstract databases. Bibliographies of past narrative and empirical reviews of literature that examined the effectiveness of police crime control programs were reviewed and forward searches for works that cited seminal hot spots policing studies were performed. Bibliographies of past completed Campbell systematic reviews of police crime prevention efforts were reviewed and hand searches of leading journals in the field were completed. Experts in the field were consulted and relevant citations were obtained. Selection Criteria: To be eligible for this review, interventions used to control crime hot spots were limited to police-led prevention efforts. Suitable police-led crime prevention efforts included traditional tactics such as directed patrol and heightened levels of traffic enforcement as well as alternative strategies such as aggressive disorder enforcement and problem-oriented policing. Studies that used randomized controlled experimental or quasiexperimental designs were selected. The units of analysis were limited to crime hot spots or high-activity crime "places" rather than larger areas such as neighborhoods. The control group in each study received routine levels of traditional police crime prevention tactics. Data Collection and Analysis: Sixty-five studies containing 78 tests of hot spots policing interventions were identified and full narratives of these studies were reported. Twenty-seven of the selected studies used randomized experimental designs and 38 used quasiexperimental designs. A formal meta-analysis was conducted to determine the crime prevention effects in the eligible studies. Random effects models were used to calculate mean effect sizes. Results: Sixty-two of 78 tests of hot spots policing interventions reported noteworthy crime and disorder reductions. The meta-analysis of key reported outcome measures revealed a small statistically significant mean effect size favoring the effects of hot spots policing in reducing crime outcomes at treatment places relative to control places. The effect was smaller for randomized designs but still statistically significant and positive. When displacement and diffusion effects were measured, a diffusion of crime prevention benefits was associated with hot spots policing. Authors' Conclusions: The extant evaluation research suggests that hot spots policing is an effective crime prevention strategy. The research also suggests that focusing police efforts on high-activity crime places does not inevitably lead to crime displacement; rather, crime control benefits may diffuse into the areas immediately surrounding the targeted locations.

Closer to Guns: the Role of Street Gangs in Facilitating Access to Illegal Firearms.

Criminal offenders often turn to social networks to gain access to firearms, yet we know little about how networks facilitate access to firearms. This study conducts a network analysis of a co-offending network for the City of Chicago to determine how close any offender may be to a firearm. We use arrest data to recreate the co-offending network of all individuals who were arrested with at least one other person over an eight-year period. We then use data on guns recovered by the police to measure potential network pathways of any individual to known firearms. We test the hypothesis that gangs facilitate access to firearms and the extent to which such access relates to gunshot injury among gang members. Findings reveal that gang membership reduces the potential network distance (how close someone is) to known firearms by 20% or more, and regression results indicate that the closer gang members are to guns, the greater their risk of gunshot victimization.

Modeling Contagion Through Social Networks to Explain and Predict Gunshot Violence in Chicago, 2006 to 2014.

Importance: Every day in the United States, more than 200 people are murdered or assaulted with a firearm. Little research has considered the role of interpersonal ties in the pathways through which gun violence spreads. Objective: To evaluate the extent to which the people who will become subjects of gun violence can be predicted by modeling gun violence as an epidemic that is transmitted between individuals through social interactions. Design, Setting, and Participants: This study was an epidemiological analysis of a social network of individuals who were arrested during an 8-year period in Chicago, Illinois, with connections between people who were arrested together for the same offense. Modeling of the spread of gunshot violence over the network was assessed using a probabilistic contagion model that assumed individuals were subject to risks associated with being arrested together, in addition to demographic factors, such as age, sex, and neighborhood residence. Participants represented a network of 138 163 individuals who were arrested between January 1, 2006, and March 31, 2014 (29.9% of all individuals arrested in Chicago during this period), 9773 of whom were subjects of gun violence. Individuals were on average 27 years old at the midpoint of the study, predominantly male (82.0%) and black (75.6%), and often members of a gang (26.2%). Main Outcomes and Measures: Explanation and prediction of becoming a subject of gun violence (fatal or nonfatal) using epidemic models based on person-to-person transmission through a social network. Results: Social contagion accounted for 63.1% of the 11 123 gunshot violence episodes; subjects of gun violence were shot on average 125 days after their infector (the person most responsible for exposing the subject to gunshot violence). Some subjects of gun violence were shot more than once. Models based on both social contagion and demographics performed best; when determining the 1.0% of people (n = 1382) considered at highest risk to be shot each day, the combined model identified 728 subjects of gun violence (6.5%) compared with 475 subjects of gun violence (4.3%) for the demographics model (53.3% increase) and 589 subjects of gun violence (5.3%) for the social contagion model (23.6% increase). Conclusions and Relevance: Gunshot violence follows an epidemic-like process of social contagion that is transmitted through networks of people by social interactions. Violence prevention efforts that account for social contagion, in addition to demographics, have the potential to prevent more shootings than efforts that focus on only demographics.

Promises and pitfalls of data sharing in qualitative research.

The movement for research transparency has gained irresistible momentum over the past decade. Although qualitative research is rarely published in the high-impact journals that have adopted, or are most likely to adopt, data sharing policies, qualitative researchers who publish work in these and similar venues will likely encounter questions about data sharing within the next few years. The fundamental ways in which qualitative and quantitative data differ should be considered when assessing the extent to which qualitative and mixed methods researchers should be expected to adhere to data sharing policies developed with quantitative studies in mind. We outline several of the most critical concerns below, while also suggesting possible modifications that may help to reduce the probability of unintended adverse consequences and to ensure that the sharing of qualitative data is consistent with ethical standards in research.

The Transmission of Gun and Other Weapon-Involved Violence Within Social Networks.

Fatal and nonfatal injuries resulting from gun violence remain a persistent problem in the United States. The available research suggests that gun violence diffuses among people and across places through social relationships. Understanding the relationship between gun violence within social networks and individual gun violence risk is critical in preventing the spread of gun violence within populations. This systematic review examines the existing scientific evidence on the transmission of gun and other weapon-related violence in household, intimate partner, peer, and co-offending networks. Our review identified 16 studies published between 1996 and 2015 that suggest that exposure to a victim or perpetrator of violence in one's interpersonal relationships and social networks increases the risk of individual victimization and perpetration. Formal network analyses find high concentrations of gun violence in small networks and that exposure to gun violence in one's networks is highly correlated with one's own probability of being a gunshot victim. Physical violence by parents and weapon use by intimate partners also increase risk for victimization and perpetration. Additional work is needed to better characterize the mechanisms through which network exposures increase individual risk for violence and to evaluate interventions aimed at disrupting the spread of gun and other weapon violence in high-risk social networks.