An Examination of Personality Profiles based on Psychological Assessments of Violent and Nonviolent Offenders

Erica Hoover, MADoctoral Candidate

Aldwin Domingo, PhD Mark Hume, PhD Clinical Research Project Committee Chair Committee Member

American School of Professional Psychology at Argosy University, Southern California

The need to better understand these individuals and their behavior is great.

Psychologists often emphasize treatment of these offenders, especially when they also have a mental illness.

Gaining more information about their personality characteristics and behavior can help clinicians create beneficial intervention strategies and inform appropriate management of these offenders (Craig, Browne, Beech, & Stringer, 2006).

Use psychological assessments to

differentiate between violent and

nonviolent offenders. Incorporating various types of assessment into a

complete personality structure of an individual can yield invaluable information.

Understanding an individual from many perspectives, such as how they think, feel, and interact with the world, is essential in order to create an integrative picture of their personality.

Archival data was collected from the California Institution for Men (CIM) in Chino California. CIM is a men’s prison facility that opened in 1941 and

currently holds over 5000 inmates. The archival data consisted of previous testing

batteries that have been performed on inmates from 2008-2012.

The subjects were all part of the mental health system at CIM and their primary clinician referred them to have a psychological assessment completed on them by a psychodiagnositc practicum student working at the facility.

The cognitive measure: the Wechsler Adult Intelligence Scale (WAIS-IV)

The objective measure: the Personality Assessment Inventory (PAI)

The projective measure: the Rorschach Inkblot test using the Rorschach Performance Assessment System (R-PAS) to score and interpret the results.

Violent crimes, or crimes against persons: involve force or the threat of force, and are comprised of

the following offenses: Murder Manslaughter Robbery Assault Sex offenses Kidnapping

Non-violent crimes include property crimes such as: Burglary Theft Or drug offenses

Descriptive Statistics: sample size: 36 subjects Ages of subjects ranged from 18 to 77 years old,

with an average age of 37. 38.9% Caucasian, 30.1% African American,

27.8% Hispanic, 2.8% Biracial Completed education levels ranged from 4th grade

to 4-year college degree, average completed education level of 11th grade.

23 Violent Offenders, 13 Nonviolent Offenders

37 personality factors across three assessment measures were statistically analyzed using a Binary Logistic Regression.

The alpha level of statistical significance was set at 0.05. The best resulting BLR model to categorize between

violent and nonviolent offenders involved the combination of:

Variables in the BLR equation for this model:

The resulting BLR regression equation is:

(-0.123)(PRI)+(-0.128)(DOM)+(-0.06)(PHR)+22.7

This model correctly classified 20 of the 23 violent offenders resulting in 87% correctly classified.

9 of the 13 nonviolent offenders were correctly classified, corresponding to 69.2%.

The model demonstrated an overall correct classification of 80.6%.

Multivariate analysis of variance (MANOVA):

Trait Offense Mean Std. Deviation Sig.

FSIQViolent 83.2174 14.89038

.090Nonviolent 75.2308 9.28398

PRIViolent 90.7391 16.42674

.080Nonviolent 81.7692 9.31087

DominanceViolent 55.2609 13.03219

.022Nonviolent 44.8462 11.59631

Diffuse Shading (Y)Violent 97.8696 14.53930

.068Nonviolent 89.7692 6.80874

A combination of PRI, DOM, and PHR is able to correctly classify an offender as violent or nonviolent 80% of the time, and can correctly classify violent offenders 87% of the time.

The mean scores for PRI were marginally significantly different, violent offenders’ scores were higher.

The mean scores on the DOM scale were significantly different, violent offenders’ scores were higher.

The mean scores on the PHR scale were not statistically significantly different, (violent offenders: M=106.61, nonviolent offenders: M=101.15). Adding the PHR scale to the BLR model improved the overall

correct classification rate by 5%. The mean scores on the Diffuse Shading (Y) scale were

marginally statistically significant But not included in the BLR equation

Factors that may be related to an individual’s score include:

(Sattler & Ryan, 2009)

Violent offenders scored higher than nonviolent offendersM=90.7Nonviolent offenders: M=81.8

Larger PRI vs VCI split with violent offendersVCI was 4 points lower (on average) for violent1 point lower for nonviolent

(Sattler & Ryan, 2009, p. 134)

Violent offenders: M=83.2 >1 SD below the mean (“low average”)

Nonviolent offenders: M=75.2 Almost 2 SD below the mean (“borderline”)

Better understanding of violent offenders Prominent features that differentiate this population

from nonviolent offenders are related to interpersonal characteristics, and reasoning and problem solving skills

Prone to using nonverbal problem solving and reasoning More dominant and controlling

*Based on self-report Problematic understanding of self and others

This understanding can guide treatment planning toward more interpersonal/social skills and adaptively understanding and interacting with others

especially during conflictual encounters and those that require healthy problem solving

Small sample size (especially nonviolent offenders) Generalizability

Only inmates within the mental health system at one prison Not representative of general prison population

Inter-rater reliability Tests were scored by various examiners

Standard validity concerns for each assessment measure Effort, motivation, performing at optimal level, self-

reporting, defensiveness, impression management, rapport with examiner, administration, nature of setting/environment, etc.

Comparative characteristics and styles of those prone to harm others directly vs other crimes in a small sample

This is preliminary research -there is much more we can do! Gather more assessment data Study how these results can affect treatment of

violent offenders to reduce future violent crime and increase their likelihood of success while incarcerated and when released into the community

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