Melissa Schaefer Morabito

Improving police response to persons with mental illness: a multi-level conceptualization of CIT.

The large numbers of people with mental illness in jails and prisons has fueled policy concern in all domains of the justice system. This includes police practice, where initial decisions to involve persons in the justice system or divert them to mental health services are made. One approach to focus police response in these situations is the implementation of Crisis Intervention Teams (CIT). The CIT model is being implemented widely, with over 400 programs currently operating. While the limited evidence on CIT effectiveness is promising, research on CIT is limited in scope and conceptualization-much of it focusing on officer characteristics and training. In this paper we review the literature on CIT and present a conceptual model of police response to persons with mental illness that accounts for officer, organizational, mental health system and community level factors likely to influence implementation and effectiveness of CIT and other approaches. By moving our conceptualizations and research in this area to new levels of specificity, we may contribute more to effectiveness research on these interventions.

Understanding Community Policing as an Innovation: Patterns of Adoption

In the 1980s and 1990s, community policing was viewed by many as a radical innovation in the field of policing, with the vast majority of police agencies reporting to have adopted the approach. Despite its overwhelming popularity, most police agencies did not adopt the central elements of community policing. This study examines patterns of community policing adoption of 474 police departments across the United States. Using an innovations framework, a model was developed that measures the extent to which community characteristics, organizational complexity, and organizational commitment can explain differences in the adoption of community policing. Findings suggest that the innovations approach can explain some variation in the adoption of community policing and should be considered in future police research.In the 1980s and 1990s, community policing was viewed by many as a radical innovation in the field of policing, with the vast majority of police agencies reporting to have adopted the approach. Despite its overwhelming popularity, most police agencies did not adopt the central elements of community policing. This study examines patterns of community policing adoption of 474 police departments across the United States. Using an innovations framework, a model was developed that measures the extent to which community characteristics, organizational complexity, and organizational commitment can explain differences in the adoption of community policing. Findings suggest that the innovations approach can explain some variation in the adoption of community policing and should be considered in future police research.

Crisis Intervention Teams and People With Mental Illness Exploring the Factors That Influence the Use of Force

The Crisis Intervention Team (CIT) program was first developed to reduce violence in encounters between the police and people with mental illness as well as provide improved access to mental health services. Although there is overwhelming popular support for this intervention, scant empirical evidence of its effectiveness is available—particularly whether the program can reduce the use of force. This investigation seeks to fill this gap in the literature by exploring the factors that influence use of force in encounters involving people with mental illness and evaluating whether CIT can reduce the likelihood of its use.

Defying Negative Expectations: Dimensions of Fair and Respectful Treatment by Police Officers as Perceived by People with Mental Illness

Programs to improve police interactions with persons with mental illness are being initiated across the country. In order to assess the impact of such interventions with this population, we must first understand the dimensions of how police encounters are experienced by consumers themselves. Using procedural justice theory as a sensitizing framework, we used in-depth semi-structured interviews to explore the experiences of twenty persons with mental illness in 67 encounters with police. While participants came into contact with police in a variety of ways, two main themes emerged. First, they feel vulnerable and fearful of police, and second, the way police treated them mattered. Findings elaborate on dimensions of procedural justice theory and are informative for police practice and mental health services.

Gendered institutions and gender roles: understanding the experiences of women in policing

Men are disproportionately represented in many institutions including law, politics, the academy, and the economy. Women have made great strides in increasing representation in many of these professions with the exception of policing; where police departments have had difficulty hiring, retaining, and promoting female officers. The available literature on women in policing, however, is largely atheoretical and does not thoroughly address advancement barriers and the retention of women. To address this gap in the literature, this article utilizes Acker’s theory of gendered institutions to provide a historical review of women’s experiences in law enforcement. Acker’s four gendered processes are used to organize the existing literature regarding women’s experiences as well as coping and adaptation strategies in the gendered institution of policing. Finally, implications are explored and an agenda for future research is discussed.

Crime hotspot mapping using the crime related factors--a spatial data mining approach

The technique of Hotspot Mapping is widely used in analysing the spatial characteristics of crimes. The spatial distribution of crime is considered to be related with a variety of socio-economic and crime opportunity factors. But existing methods usually focus on the target crime density as input without utilizing these related factors. In this study, we introduce a new crime hotspot mapping tool—Hotspot Optimization Tool (HOT). HOT is an application of spatial data miming to the field of hotspot mapping. The key component of HOT is the Geospatial Discriminative Patterns (GDPatterns) concept, which can capture the differences between two classes in a spatial dataset. Experiments are done using a real world dataset from a northeastern city in the United States and the pros and cons of utilizing related factors in hotspot mapping are discussed. Comparison studies with the Hot Spot Analysis tool implemented by Esri ArcMap 10.1 validate that HOT is capable of accurately mapping crime hotspots.

The adoption of police innovation: the role of the political environment

Purpose – The purpose of this paper is to understand the role of the political environment in the implementation of community policing, using a model informed by the innovations perspective in addition to the criminal justice literature.Design/methodology/approach – Using archival data, this paper draws a national sample of 428 police jurisdictions. Multivariate models are estimated to determine the influence of reform governments as indicated by city managers, non‐partisan and at‐large elections, on community policing.Findings – This paper finds evidence to suggest that reform governments have a limited but significant influence on the adoption of community policing. Form of government and the type of municipal elections do directly influence community policing. Results demonstrate that the innovations literature does explain some variation in community policing adoption across municipalities.Research limitations/implications – The findings of the study should have implications for understanding the exte...

Explaining the IPV Arrest Decision: Incident, Agency, and Community Factors

Over the last half century in the United States, we have seen the criminal system become increasingly aggressive in its response to violence against intimate partners. Although policies have been implemented to encourage arrest, police continue to maintain discretion over whether or whom to arrest in cases of intimate partner violence (IPV). Using data from three national data sets, we examined the contributions of incident, agency, and community factors on the police arrest decisions, independently considering atypical cases of women arrested and dual arrest. The findings from this study reveal that incident factors account for the majority of the variance in arrest for single arrest cases, more so than factors associated with the particular police agency or the community in which the alleged crime occurred. The frequency of dual arrest is affected more by community factors. The findings from this study can be used to guide police training and local policies as well as to inform legislation designed to prevent variance in arrest based on sociodemographic and other extralegal factors.

Police Encounters, Mental Illness, and Injury: An Exploratory Investigation

Police encounters are believed to be particularly dangerous for people with mental illness and police officers. Despite widespread concern among advocates, researchers, and police professionals, little is known about the details of these interactions, including the occurrence of injuries. In the current study, we explore injuries to people with mental illness and officers to determine the extent to which situational and individual factors predict injuries. Findings suggest that injuries during police calls involving persons with mental illness are infrequent and rarely require medical attention. Predictors of injuries in these calls are similar to those in police encounters with the general population.

Understanding the spatial distribution of crime based on its related variables using geospatial discriminative patterns

Crime tends to cluster geographically. This has led to the wide usage of hotspot analysis to identify and visualize crime. Accurately identified crime hotspots can greatly benefit the public by creating accurate threat visualizations, more efficiently allocating police resources, and predicting crime. Yet existing mapping methods usually identify hotspots without considering the underlying correlates of crime. In this study, we introduce a spatial data mining framework to study crime hotspots through their related variables. We use Geospatial Discriminative Patterns (GDPatterns) to capture the significant difference between two classes (hotspots and normal areas) in a geo-spatial dataset. Utilizing GDPatterns, we develop a novel model—Hotspot Optimization Tool (HOT)—to improve the identification of crime hotspots. Finally, based on a similarity measure, we group GDPattern clusters and visualize the distribution and characteristics of crime related variables. We evaluate our approach using a real world dataset collected from a northeast city in the United States.