Hostname: page-component-76fb5796d-x4r87 Total loading time: 0 Render date: 2024-04-25T20:26:02.096Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment of aggression in inpatient settings

Published online by Cambridge University Press:  17 June 2014

Barbara E. McDermott  and
Brian J. Holoyda
Barbara E. McDermott*
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, California, 95817, USA
Brian J. Holoyda
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, California, 95817, USA
*
*Address for correspondence: Barbara E. McDermott, PhD, Professor of Clinical Psychiatry, Department of Psychiatry and Behavioral Sciences, Division of Psychiatry and the Law, UC Davis School of Medicine, 2230 Stockton Blvd. Sacramento, CA, 95817, USA. (Email: bemcdermott@ucdavis.edu)
Get access Rights & Permissions [Opens in a new window]

Abstract

The threat of violence is a major concern for all individuals working or receiving treatment in an inpatient psychiatric setting. One major focus in forensic psychology and psychiatry over the past several decades has been the development of risk assessments to aid in the identification of those individuals most at risk of exhibiting violent behavior. So-called second- and third-generation risk assessments were developed to improve the accuracy of decision making. While these instruments were developed for use in the community, many have proven to be effective in identifying patients more likely to exhibit institutional aggression. Because the purpose of risk assessment is the reduction of violence, dynamic factors were included in third-generation risk instruments to provide opportunities for intervention and methods for measuring change. Research with these instruments indicates that both static factors (second-generation) and dynamic factors (third-generation) are important in identifying those patients most likely to engage in institutional aggression, especially when the aggression is categorized by type (impulsive/reactive, organized/predatory/instrumental, psychotic). Recent research has indicated that developing a typology of aggressive incidents may provide insight both into precipitants to assaults as well as appropriate interventions to reduce such aggression. The extant literature suggests that both static and dynamic risk factors are important, but may be differentially related to the type of aggression exhibited and the characteristics of the individuals exhibiting the aggression.

Keywords

Imminent aggressioninstitutional aggressioninterventionsrisk assessmenttypology of aggression
Type
Review Articles
Information
CNS Spectrums , Volume 19 , Issue 5 , October 2014 , pp. 425 - 431
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Quintal, SA. Violence against psychiatric nurses: an untreated epidemic? J Psychosoc Nurs Ment Health Serv. 2002; 40(1): 46–53.Google Scholar
2. Silver, JM, Yudofsky, SC. Documentation of aggression in the assessment of the violent patient. Psychiatric Annals. 1987; 17(6): 375–384.Google Scholar
3. Duhart, DT. Violence in the Workplace, 1993–99 (December 2001, NCJ 190076). Washington, DC: U.S. Department of Justice, Office of Justice Programs; 2001.Google Scholar
4. Hunter, M, Carmel, H. The cost of staff injuries from inpatient violence. Hosp Community Psychiatry. 1992; 43(6): 586–588.Google ScholarPubMed
5. Duxbury, J, Whittington, R. Causes and management of patient aggression and violence: staff and patient perspectives. J Adv Nurs. 2005; 50(5): 469–478.CrossRefGoogle ScholarPubMed
6. Skeem, JL, Monahan, J. Current directions in violence risk assessment. Current Directions in Psychological Science. 2011; 20(1): 38–42.Google Scholar
7. Monahan, J. The Clinical Prediction of Violent Behavior. Crime and Delinquency Issues: A Monograph Series. Washington, DC: US Government Printing Office; 1981.CrossRefGoogle Scholar
8. Hart, SD, Michie, C, Cooke, DJ. Precision of actuarial risk assessment instruments: evaluating the “margins of error” of group v. individual predictions of violence. Br J Psychiatry. 2007; 190(Suppl. 49): s60–s65.Google Scholar
9. Mossman, D, Sellke, T. Avoiding error about “margins of error. ” Br J Psychiatry. 2007; 191(6): 561.Google Scholar
10. Harris, GT, Rice, ME, Quinsey, VL. Violent recidivism of mentally disordered offenders: the development of a statistical prediction instrument. Criminal Justice and Behavior. 1993; 20(4): 315–335.Google Scholar
11. Hanson, RK. The Development of a Brief Actuarial Scale for Sexual Offense Recidivism. Ottawa, Ontario: Department of the Solicitor General; 1997.Google Scholar
12. Hare, RD. The Hare Psychopathy Checklist—Revised Manual, 2nd ed. Toronto, Ontario: Multi-Health Systems; 2003.Google Scholar
13. Bloom, H, Webster, C, Hucker, S, DeFreitas, K. The Canadian contribution to violence risk assessment: history and implications for current psychiatric practice. Can J Psychiatry. 2005; 50(1): 3–11.Google Scholar
14. Hart, SD. The role of psychopathy in assessing risk for violence: conceptual and methodological issues. Legal and Criminological Psychology. 1998; 3(1): 121–137.Google Scholar
15. Quinsey, VL, Harris, GT, Rice, ME, Cormier, CA. Violent Offenders: Appraising and Managing Risk, 2nd ed. Washington, DC: American Psychological Association; 2006.Google Scholar
16. Rice, ME, Harris, GT, Lang, C. Validation of and revision to the VRAG and SORAG: the violence risk appraisal guide-revised (VRAG-R). Psychol Assess. 2013; 25(3): 951–965.Google Scholar
17. Hodgkinson, P. The use of seclusion. Med Sci Law. 1985; 25(3): 215–222.Google Scholar
18. Maguire, T, Young, R, Martin, T. Seclusion reduction in a forensic mental health setting. J Psychiatr Ment Health Nurs. 2012; 19(2): 97–106.CrossRefGoogle Scholar
19. Edens, JF, Buffington-Vollum, JK, Keilen, A, Roskamp, P, Anthony, C. Predictions of future dangerousness in capital murder trials: Is it time to “disinvent the wheel?” Law Hum Behav. 2005; 29(1): 55–86.Google Scholar
20. Guy, LS, Edens, JF, Anthony, C, Douglas, KS. Does psychopathy predict institutional misconduct among adults? A meta-analytic investigation. J Consult Clin Psychol. 2005; 73(6): 1056–1064.CrossRefGoogle ScholarPubMed
21. Douglas, KS, Skeem, JL. Violence risk assessment: getting specific about being dynamic. Psychology, Public Policy, and Law. 2005; 11(3): 347–383.Google Scholar
22. Campbell, MA, French, S, Gendreau, P. The prediction of violence in adult offenders: a meta-analytic comparison of instruments and methods of assessment. Criminal Justice and Behavior. 2009; 36(6): 567–590.CrossRefGoogle Scholar
23. Edens, JF, Otto, RK. Release decision making and planning. In: Ashford JB, Sales BD, Reid WH, eds. Treating Adult and Juvenile Offenders with Special Needs. Washington, DC: American Psychological Association; 2001: 335–371.Google Scholar
24. Walters, GD. Risk-appraisal versus self-report in the prediction of criminal justice outcomes: a meta-analysis. Criminal Justice and Behavior. 2006; 33(3): 279–304.Google Scholar
25. Hare, RD, McPherson, LM. Violent and aggressive behavior by criminal psychopaths. Int J Law Psychiatry. 1984; 7(1): 35–50.CrossRefGoogle ScholarPubMed
26. Hill, CD, Rogers, R, Bickford, ME. Predicting aggressive and socially disruptive behavior in a maximum security forensic psychiatric hospital. J Forensic Sci. 1996; 41(1): 56–59.Google Scholar
27. Walters, GD. Predicting institutional adjustment and recidivism with the Psychopathy Checklist factor scores: a meta-analysis. Law Hum Behav. 2003; 27(5): 541–558.Google Scholar
28. Webster, CD, Douglas, KS, Eaves, D, Hart, S. HCR-20: Assessing Risk for Violence (Version 2). Burnaby, BC, Canada: Mental Health, Law, and Policy Institute, Simon Fraser University; 1997.Google Scholar
29. McNiel, D, Gregory, A, Lam, J, Binder, RL, Sullivan, GR. Utility of decision support tools for assessing acute risk of violence. J Consult Clin Psychol. 2003; 71(5): 945–953.Google Scholar
30. Kroner, DG, Mills, JF. The accuracy of five risk appraisal instruments in predicting institutional misconduct and new convictions. Criminal Justice and Behavior. 2001; 28(4): 471–489.Google Scholar
31. Doyle, M, Dolan, M, McGovern, J. The validity of North American risk assessment tools in predicting in-patient violent behaviour in England. Legal and Criminological Psychology. 2002; 7(2): 141–154.Google Scholar
32. McDermott, BE, Edens, JF, Quanbeck, CD, Busse, D, Scott, CL. Examining the role of static and dynamic risk factors in the prediction of inpatient violence: variable and person-focused analyses. Law Hum Behav. 2008; 32(4): 325–338.CrossRefGoogle ScholarPubMed
33. Vitacco, MJ, Gonsalves, V, Tomony, J, Smith, BER, Lishner, DA. Can standardized measures of risk predict inpatient violence? Combining static and dynamic variables to improve accuracy. Criminal Justice and Behavior. 2012; 39(5): 589–606.Google Scholar
34. Leistico, AMR, Salekin, RT, DeCoster, J, Rogers, R. A large-scale meta-analysis relating the Hare measures of psychopathy to antisocial conduct. Law Hum Behav. 2008; 32(1): 28–45.Google Scholar
35. Mills, JF, Kroner, DG. Anger as a predictor of institutional misconduct and recidivism in a sample of violent offenders. J Interpers Violence. 2003; 18(3): 282–294.Google Scholar
36. Mills, JF, Kroner, DG, Forth, A. Novaco Anger Scale: reliability and validity within an adult criminal sample. Assessment. 1998; 5(3): 237–248.Google Scholar
37. Monahan, J, Steadman, H, Silver, E, etal. Rethinking Risk Assessment: The MacArthur Study of Mental Disorder and Violence. New York: Oxford University Press; 2001.CrossRefGoogle Scholar
38. Monahan, J, Steadman, H, Appelbaum, P, etal. Classification of Violence Risk (COVR) Professional Manual. Lutz, FL: Psychological Assessment Resources, Inc.; 2002.Google Scholar
39. Ullrich S, Keers R, Coid JW. Delusions, anger, and serious violence: new findings from the MacArthur Violence Risk Assessment Study. Schizophr Bull. In press. DOI: doi: 10.1093/schbul/sbt126.Google Scholar
40. Fehon, D, Grilo, C, Lipschitz, D. A comparison of adolescent inpatients with and without a history of violence perpetration: impulsivity, PTSD, and violence risk. J Nerv Ment Dis. 2005; 193(6): 405–411.Google Scholar
41. Wang, EW, Diamond, PM. Empirically identifying factors related to violence risk in corrections. Behav Sci Law. 1999; 17(3): 377–389.Google Scholar
42. Barratt, E. Impulsiveness and aggression. In: Monahan J, Steadman H, eds. Violence and Mental Disorder: Developments in Risk Assessment. Chicago: University of Chicago Press; 1994: 61–79.Google Scholar
43. Nolan, KA, Czobor, P, Roy, BB, etal. Characteristics of assaultive behavior among psychiatric patients. Psychiatr Serv. 2003; 54(7): 1012–1016.Google Scholar
44. Quanbeck, CD, McDermott, BE, Scott, CL, etal. Categorization of assaultive acts committed by chronically aggressive state hospital patients. Psychiatr Serv. 2007; 58(4): 521–528.Google Scholar
45. Cornell, DG, Warren, J, Hawk, G, etal. Psychopathy in instrumental and reactive violent offenders. J Consult Clin Psychol. 1996; 64(4): 783–790.Google Scholar
46. Porter, S, Woodworth, M. Psychopathy and aggression. In: Patrick CJ, ed. Handbook of Psychopathy. New York: Guilford Press; 2006: 481–494.Google Scholar
47. Vitacco, MJ, Van Rybroek, GJ, Rogstad, J, etal. Predicting short-term institutional aggression in forensic patients: a multi-trait method for understanding subtypes of aggression. Law Hum Behav. 2009; 33(4): 308–319.Google Scholar
48. McDermott, BE, Quanbeck, CD, Busse, D, Yastro, K, Scott, CL. The accuracy of risk assessment instruments in the prediction of impulsive versus predatory aggression. Behav Sci Law. 2008; 26(6): 759–777.Google Scholar
49. Woods, P, Almvik, R. The Brøset violence checklist (BVC). Acta Psychiatr Scand Suppl. 2002; 106(412): 103–105.Google Scholar
50. McNiel, J, Binder, R. Screening for risk of inpatient violence: validation of an actuarial tool. Law Hum Behav. 1994; 18(5): 579–586.Google Scholar
51. Almvik, R, Woods, P, Rasmussen, K. The Brøset Violence Checklist: sensitivity, specificity, and interrater reliability. J Interpers Violence. 2000; 15(12): 1284–1296.Google Scholar
52. Ogloff, JR, Daffern, M. The dynamic appraisal of situational aggression: an instrument to assess risk for imminent aggression in psychiatric patients. Behav Sci Law. 2006; 24(6): 799–813.CrossRefGoogle Scholar
53. Grann, M, Belfrage, H, Tengstrom, A. Actuarial assessment of risk for violence: predictive validity of the VRAG and the historical part of the HCR-20. Criminal Justice and Behavior. 2000; 27(1): 97–114.CrossRefGoogle Scholar
54. Johnson, ME. Violence on inpatient psychiatric units: state of the science. Journal of the American Psychiatric Nurses Association. 2004; 10(3): 113–121.Google Scholar
55. Douglas, KS, Hart, S, Webster, C, Belfrage, H. HCR-20 (Version 3): Assessing Risk for Violence. Burnaby, BC, Canada: Mental Health, Law, and Policy Institute, Simon Fraser University; 2013.Google Scholar