The Use of a Brief Mental Health Screener to Enhance the Ability of Police Officers to Identify Persons with Serious Mental Disorders

Police agencies in Canada and elsewhere have received much criticism over how they respond to persons with serious mental disorders. The adequacy of training provided to police officers on mental health issues and in particular on recognizing indicators of serious mental disorders has been a major concern. 

This paper describes the process that led to the development of a new brief mental health screener (interRAI Brief Mental Health Screener, BMHS) designed to assist police officers to better identify persons with serious mental disorders. The interRAI BMHS was developed in collaboration with interRAI, an international, not-for-profit consortium of researchers. The government of Ontario had previously partnered with interRAI to develop and implement the Resident Assessment Instrument for Mental Health (RAI-MH), the assessment system mandated for use on all persons admitted into inpatient psychiatric care in the province. Core items on the interRAI BMHS were obtained through analysis (N=41,019) of RAI-MH data together with input from representatives from health care, police services, and patient groups. 

Two police services in southwestern Ontario completed forms (N=235) on persons thought to have a mental disorder. Patient records were later accessed to determine patient disposition. The use of summary and inferential statistics revealed that the variables significantly associated with being taken to hospital by police included performing a self-injurious act in the past 30days, and others being concerned over the person's risk for self-injury. Variables significantly associated with being admitted included abnormal thought process, delusions, and hallucinations. 

The results of the study indicate that the 14-variable algorithm used to construct the interRAI BMHS is a good predictor of who was most likely to be taken to hospital by police officers and who was most likely to be admitted. The instrument is an effective means of capturing and standardizing police officer observations enabling them to provide more and better quality information to emergency department (ED) staff. 

Teaching police officers to use the form constitutes enhanced training on major indicators of serious mental disorders. Further, given that items on the interRAI BMHS are written in the language of the health system, language acts as common currency between police officers and ED staff laying the foundation for a more collaborative approach between the systems.

Full article at:   http://goo.gl/4FA5EB

By:  Hoffman R1, Hirdes J2, Brown GP3, Dubin JA4, Barbaree H5.

• 1Ministry of Community Safety and Correctional Services, Ontario Police College, 10716 Hacienda Road, Aylmer, Ontario N5H 2T2, Canada; Faculty of Applied and Professional Studies, School of Criminology and Criminal Justice, Nipissing University, 100 College Drive, Box 5002, North Bay, Ontario P1B 8L, Canada. Electronic address: Ron.Hoffman@sympatico.ca.
• 2School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada.
• 3Faculty of Applied and Professional Studies, School of Criminology and Criminal Justice, Nipissing University, 100 College Drive, Box 5002, North Bay, Ontario P1B 8L7, Canada.
• 4Department of Statistics and Actuarial Science, School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada.
• 5Division of Forensic Psychiatry, Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R, Canada; Waypoint Centre for Mental Health Care, 500 Church Street, Penetanguishene, Ontario L9M 1G3, Canada. 
• Int J Law Psychiatry. 2016 Apr 1. pii: S0160-2527(16)30044-9. doi: 10.1016/j.ijlp.2016.02.031.

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Does Predictive Policing Encourage Racial Profiling?

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Police Decision-Making in the Gray Zone: The Dynamics of Police–Citizen Encounters with Mentally Ill Persons

Research finds mentally ill persons have higher rates of police contacts, arrests, and criminal charges for minor offenses and noncriminal behavior. It remains unclear whether the decision-making process and factors affecting discretion reflect a procedural bias that criminalizes the mentally ill. 

Using observational data from a Canadian police service, the findings suggest higher odds for criminal charges with serious offenses, males, older citizens, a prior criminal record, being under the influence of alcohol or drugs, and being uncooperative with requests for information and compliance. The odds of a citation are higher for proactive calls, more serious offenses, older citizens, mentally ill persons, those under the influence, or with a disrespectful demeanor. 

The overall findings suggest an indirect procedural bias exists due to situational constraints, a disjuncture between policy and police culture, and limited mental health resources that lead to response strategies that contribute to criminalization of the mentally ill.

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By:  Jennifer L. Schulenberg

Jennifer L. Schulenberg, Department of Sociology and Legal Studies, University of Waterloo, Waterloo, ON, N2L 3G1, Canada; e-mail: jlschule@uwaterloo.ca.

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Characteristics of Officer-Involved Vehicle Collisions in California

PURPOSE:

The purpose of this paper is to examine the situational and individual officer characteristics of officer-involved vehicle collisions that result in fatality, injury, and non-injury outcomes.

DESIGN/METHODOLOGY/APPROACH:

Data on 35,840 vehicle collisions involving law enforcement officers in California occurring between January 2000 and December 2009 are examined. A descriptive analysis of collision characteristics is presented.

FINDINGS:

There were 39 officers killed by collisions over this study period and 7,684 officers who received some type injury. Incidents involving officers on motorcycles represented 39 percent of officer fatalities and 39 percent of severe injuries. In the case of fatalities, 33 percent of officers were reported as wearing seatbelts, 38 percent were not wearing a seatbelt, and seatbelt use was not stated in 29 percent of car fatalities.

RESEARCH LIMITATIONS/IMPLICATIONS:

The findings only represent one state and the analysis is based on an estimated 86 percent of collisions that occurred during the study period due to missing data. Nonetheless, the results are based on a robust sample and address key limitations in the existing literature.

PRACTICAL IMPLICATIONS:

During the study period in California the estimated financial impact of collisions reached into the hundreds of millions of dollars when considering related fatality, injury, and vehicle damage costs combined. These impacts highlight the need for the law enforcement community to give greater attention to this issue.

ORIGINALITY/VALUE:

At the time of this writing there was no published independent research that compares the situational and officer characteristics across fatality, injury, and non-injury outcomes in these events. The findings reported here will help inform emerging interest in this issue within the law enforcement, academic, and policy-making communities.

Frequency of officer-involved traffic collisions, injuries, and fatalities during the observation period

Year	Officer-involved collisions n	Officer injuries n	Officer fatalities n	% of collisions that resulted in injurya	% of collisions that resulted in fatalitya
2000	3,622	825	3	22.6	0.1
2001	3,668	829	3	22.2	0.1
2002	3,456	788	3	22.6	0.1
2003	3,508	822	7	23.2	0.2
2004	3,417	779	6	22.6	0.2
2005	3,353	732	5	21.7	0.1
2006	3,376	694	3	20.4	0.1
2007	3,893	756	4	19.1	0.1
2008	3,691	716	3	19.1	0.1
2009	3,856	743	2	19.0	0.1
Total	35,840	7,684	39	21.2	0.1

Note:

aPercentages are calculated by dividing the number of collisions that had at least one officer injury/fatality by the total number of officer-involved collisions in each year

Weather and road conditions during officer-involved traffic collisions during the observation period

	n	%
Weather
Clear	28,918	80.7
Cloudy	5,161	14.4
Raining	1,202	3.4
Snowing	99	0.3
Fog	202	0.6
Other	59	0.1
Not stated	199	0.6
Road surface conditions
Dry	31,992	89.3
Wet	2,928	8.2
Snowy or icy	285	0.8
Slippery (muddy, oily, etc.)	285	0.8
Not stated	350	1.0
Lighting
Daylight	21,163	59.0
Dusk or dawn	1,091	3.0
Dark – street lights	10,368	28.9
Dark – no street lights	2,929	8.2
Dark – street lights not functioning	91	0.3
Not stated	198	0.6

Factors surrounding officer-involved traffic collisions during the observation period

	n	%
Location of collision
Intersection	8,661	24.2
Non-intersection	26,830	74.9
Missing	349	1.0
Type of collision
Head-on	1,140	3.2
Sideswipe	6,838	19.1
Rear end	10,879	30.4
Broadside	8,054	22.5
Hit object	5,833	16.3
Overturned	438	1.2
Vehicle/pedestrian	445	1.2
Other	2,030	5.7
Not stated	183	0.5
Number of vehicles involved
Single vehicle	8,416	23.5
Multiple vehicle	27,424	76.5
Driving under the influence a
Had not been drinking	35,650	98.0
Had been drinking, under influence	29	0.1
Had been drinking, not under influence	33	0.1
Had been drinking, impairment unknown	8	< 0.1
Impairment unknown	69	0.2
Not applicable	243	0.7
Not stated	349	1.0
Officer at-fault a
Single-vehicle collision
Yes	6,366	75.6
No	2,050	24.4
Multiple-vehicle collision
Yes	10,402	37.2
No	17,563	62.8

Note:

aThis information is derived from the “party/officer level” data file and, therefore, the frequencies sum to greater than the total number of collisions because multiple officer vehicles could be involved in single collision

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By:  Wolfe SE1, Rojek J2, Alpert G1, Tiesman H3, James S4.

• 1Department of Criminology and Criminal Justice, University of South Carolina, Columbia, South Carolina, USA.
• 2Department of Criminal Justice, University of Texas at El Paso, El Paso, Texas, USA.
• 3Centers for Disease Control, National Institute for Occupational Safety and Health, Morgantown, West Virginia, USA.
• 4Department of Criminology and Criminal Justice, Washington State University, Pullman, Washington, USA.
• Policing. 2015;38(3):458-477. 

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Experiences of Intimate Partner Violence and Subsequent Police Reporting among Lesbian, Gay, Bisexual, Transgender, and Queer Adults in Colorado: Comparing Rates of Cisgender and Transgender Victimization

Research indicates that lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals are at high risk of victimization by others and that transgender individuals may be at even higher risk than their cisgender LGBQ peers. 

In examining partner violence in particular, extant literature suggests that LGBTQ individuals are at equal or higher risk of partner violence victimization compared with their heterosexual peers. As opposed to sexual orientation, there is little research on gender identity and partner violence within the LGBTQ literature. 

In the current study, the authors investigated intimate partner violence (IPV) in a large sample of LGBTQ adults (N = 1,139) to determine lifetime prevalence and police reporting in both cisgender and transgender individuals. 

Results show that more than one fifth of all participants ever experienced partner violence, with transgender participants demonstrating significantly higher rates than their cisgender peers. Implications focus on the use of inclusive language as well as future research and practice with LGBTQ IPV victims.

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By:  Langenderfer-Magruder L1, Whitfield DL2, Walls NE2, Kattari SK2, Ramos D3.

• 1University of Denver (http://www.du.edu/), CO, USA llangen2@du.edu.
• 2University of Denver, CO, USA.
• 3One Colorado, Denver, CO, USA. 
• J Interpers Violence. 2016 Mar;31(5):855-71. doi: 10.1177/0886260514556767. 

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Black and Hispanic Men Perceived to Be Large Are at Increased Risk for Police Frisk, Search, and Force

Social justice issues remain some of the most pressing problems in the United States. One aspect of social justice involves the differential treatment of demographic groups in the criminal justice system. 

While data consistently show that Blacks and Hispanics are often treated differently than Whites, one understudied aspect of these disparities is how police officers' assessments of suspects' size affects their decisions. Using over 3 million cases from the New York Police Department (NYPD) Stop, Question, and Frisk (SQF) Database, 2006-2013, this study is the first to explore suspects' race, perceived size, and police treatment. 

Results indicate that tall and heavy black and Hispanic men are at the greatest risk for frisk or search. Tall and heavy suspects are at increased risk for experiencing police force, with black and Hispanic men being more likely to experience force than white men across size categories.

Below:  The adjusted odds ratios for the suspect being frisked or searched by race, height, and weight category compared to white suspects with weight 141–204 pounds and 66–72” in height, controlling for stop characteristics. The blue circle denotes white (W) suspects, the red diamond denotes black (B) suspects, and the green square denotes Hispanic (H) suspects. Error bars indicate the 99% confidence interval for the group estimates.

Below:  The adjusted odds ratios for the suspect having force used on them by race, height, and weight category compared to white suspects with weight 141–204 lbs. and 66–72” in height, controlling for stop characteristics.  The blue circle denotes white (W) suspects, the red diamond denotes black (B) suspects, and the green square denotes Hispanic (H) suspects. Error bars indicate the 99% confidence interval for the group estimates.

Below:  The adjusted odds ratios for the suspect being frisked or searched (top) or having force used on them (bottom) by race and BMI category compared to normal weight white suspects, controlling for stop characteristics. The blue circle denotes white suspects, the red diamond denotes black suspects, and the green square denotes Hispanic suspects. Error bars indicate the 99% confidence interval for the group estimates.

Full article at:   http://goo.gl/L48OrV

By:  Milner AN1,2,3,4, George BJ2,5,6, Allison DB2,5,6.

• 1Department of Sociology, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America.
• 2Nutrician Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America.
• 3Minority Health and Health Disparities Research Center, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America.
• 4Center for the Study of Community Health, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America.
• 5School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America.
• 6Office of Energetics, University of Alabama at Birmingham, Birmingham, AL 35294, United States of America
• PLoS One. 2016 Jan 19;11(1):e0147158. doi: 10.1371/journal.pone.0147158. 

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