Abstract
This study examines whether clinical classification schemes from general suicide research are applicable for cases of suicide by cop (SbC) and whether there are indicators as to why the police might be engaged in the suicide. Using archival law enforcement data, 13 clinical risks were examined among 68 cases of SbC using exploratory factor analysis and k–means cluster analysis. Three subtypes of SbC cases emerged: Mental Illness, Criminality, and Not Otherwise Specified. The subtypes varied significantly on their levels of mental illness, substance use, and criminal activity. Findings suggest that reducing fragmentation between law enforcement and mental health service providers might be a crucial goal for suicide intervention and prevention, at least among cases of SbC.
Acknowledgments
The authors would like to express their gratitude to the FBI's Behavioral Science Unit for coordinating access to the data used in this paper. Authors’ opinions, statements and conclusions should not be considered an endorsement by the FBI for any policy, program or service. The data for this research were taken from closed, fully adjudicated state and local cases that were contributed from law enforcement agencies from around the country for the purpose of research. All identifiers, including names of victims, suspects, offenders, officers, departments, correctional agencies, are removed. Only aggregate data are reported.
The authors would like to acknowledge Keith Markus and Wen Gu for their early review and feedback, as well as John Jarvis of the Behavioral Science Unit, FBI for his thorough review and comments on the manuscript.
Joanna Fava is now at Center for Cognitive and Dialectical Behavior Therapy, located in Lake Success, New York. Elizabeth Arias is now at Psychiatry Department, Bellevue Hospital Center, New York University School of Medicine. Anthony Pinizzotto has retired from the FBI and is currently in private practice as the president of Clinical Forensic Psychology Associates, located in Virginia.
Notes
Note. Principal Component Analysis with Varimax rotation. Factor loadings >.40 are in boldface.
Note. Chi-Square tests were conducted as follow up analyses to detect differences between clusters on the frequencies of clinical risk variables.