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The PCL-R, PAI, and Rorschach as Predictors of Institutional Misconduct with Incarcerated Women


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Managing the incarcerated population is the primary task within correctional settings. Using psychological assessment to predict institutional behavior, the psychologist has a unique set of skills essential to the management of prisoners. PCL-R, PAI, and Rorschach data were compared with institutional infractions (total, physical, verbal, non-aggressive) among 126 incarcerated women. Multiple binary logistic regression analyses were used which found significant correlations between PCL-R total score, PAI scales (BOR, ANT, VPI), and Rorschach variables (ROD, EGOI, TCI, AgPot, AgPast, SumV, SumC’, MOR) with total, verbal, physical, and nonviolent incident reports. Each of these measures adds incrementally to the assessment and understanding of institutional misbehavior for incarcerated women. Clinical implications of the findings were presented.
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Women & Criminal Justice
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The PCL-R, PAI, and Rorschach as Predictors of
Institutional Misconduct with Incarcerated Women
Jason M. Smith, Carl B. Gacono & Ted B. Cunliffe
To cite this article: Jason M. Smith, Carl B. Gacono & Ted B. Cunliffe (2021): The PCL-R, PAI,
and Rorschach as Predictors of Institutional Misconduct with Incarcerated Women, Women &
Criminal Justice, DOI: 10.1080/08974454.2021.1976699
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Published online: 04 Oct 2021.
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The PCL-R, PAI, and Rorschach as Predictors of Institutional
Misconduct with Incarcerated Women
Jason M. Smith
, Carl B. Gacono
, and Ted B. Cunliffe
Maverick Psychology Training and Consultation PLLC, Lewisburg, WV, USA;
Maverick Psychology Training
and Consultation PLLC, Asheville, NC, USA;
Maverick Psychology Training and Consultation PLLC, Albizu
University, Miami, FL, USA
Managing the incarcerated population is the primary task within correc-
tional settings. Using psychological assessment to predict institutional
behavior, the psychologist has a unique set of skills essential to the man-
agement of prisoners. PCL-R, PAI, and Rorschach data were compared with
institutional infractions (total, physical, verbal, non-aggressive) among 126
incarcerated women. Multiple binary logistic regression analyses were used
which found significant correlations between PCL-R total score, PAI scales
(BOR, ANT, VPI), and Rorschach variables (ROD, EGOI, TCI, AgPot, AgPast,
SumV, SumC, MOR) with total, verbal, physical, and nonviolent incident
reports. Each of these measures adds incrementally to the assessment and
understanding of institutional misbehavior for incarcerated women. Clinical
implications of the findings were presented.
Correctional settings;
incarcerated women;
institutional misconduct;
psychopathy; Rorschach
Within the United States, approximately 7% of the incarcerated population is women (Carson,
2020). With a significantly lower population of women incarcerated than men, states typically
house all incarcerated women within one prison. For example, Kentucky like most states, house
all the women in one prison while there are 13 male facilities. Within a female prison, it is highly
likely that all security levels will be housed in one institution, while in male prisons, there is a
better chance that the inmates will contain only one type of security level. A medium-security
prison for women may house minimum, low, medium, and perhaps high depending on the need,
while a medium-security level prison for men is more likely to have just medium-security males.
Therefore, male and female prisons are not equivalent and is not recommended to expect the
security level to provide what institutional misconduct may be present with women (i.e., violence
in a medium-security female prison may not be equal to the violence in a male medium-secur-
ity prison).
Institutional misconduct is rarely studied with incarcerated women (Steiner & Wooldredge,
2014). Like most prisoner research, research with males is generalized to females disregarding the
many differences between the genders and constituents a form of bias (Cunliffe et al., 2021; Reidy
et al., 2017; Smith et al., 2021). Institutional misconduct research is no exception and therefore,
there is a need for a better understanding of why misconduct in these women occurs.
Research that has focused on incarcerated womens institutional misconduct has found that
women commit less violent and serious infractions than men (Reidy et al., 2017). However, it has
ß2021 Taylor & Francis Group, LLC
CONTACT Jason M. Smith Maverick Psychology Training and Consultation PLLC, Lewisburg,
been found women with longer sentences and those that have been incarcerated for a longer
period tend to commit violent offenses (Drury & DeLisi, 2010). Psychopathy may be a factor
related to institutional misconduct (Smith et al., 2021).
Studies with incarcerated women that explored the relationship between personality vulnerabil-
ities and misbehavior indicated that women adjust better to prison than men and engage in less
violence and other serious infractions (Celinska & Sung, 2014; Chen et al., 2014; Craddock, 1996;
Harer & Langan, 2001; Jiang & Winfree, 2006; McClellan, 1994; Smith et al., 2021; Thompson &
Loper, 2005; Warren et al., 2004). Women were also less likely to lose privileges (telephone,
email, visitation, etc.) and be remanded to confinement units (put in segregation) than incarcer-
ated men (Smith et al., 2021). Further, female institutional misconduct has been related to being
younger, the amount of time served in prison, a criminal history, self-directed violence, and their
custody level (Gover et al., 2008; Leigey, 2019; Reidy et al., 2017). Impulsivity within incarcerated
women has also been associated with institutional violence (Camlibel et al., 2021).
Identification of institutional management risk, including types of behaviors, is essential to the
management and treatment of incarcerated populations. Institutional misconduct helps prison
administrators make decisions about classification, programming, and visitation (Leigey, 2019).
Mostly deemphasized within institutional settings, psychological assessment aids in assessing and
understanding men and women at risk for institutional misconduct (Baity & Hilsenroth, 2002;
Buffington-Vollum et al., 2002; Edens et al., 2002; Gacono, 2016; Hare et al., 2020; Smith et al.,
2021). Assessment data can both inform and expand clinical judgment providing a clear depiction
of how the personality of the prisoner provides a blueprint for their future behavior (Gacono,
2016; Meyer et al., 2001).
A thorough understanding of personality functioning allows the clinician to describe why a
behavior occurred and provides a picture of the circumstances and potential for future behavior.
In this study, Psychopathy Checklist-Revised (PCL-R), Personality Assessment Inventory (PAI),
and Rorschach data were used to elucidate the dynamics that contribute to receiving institutional
infractions among incarcerated women.
Psychopathy is an essential construct to consider when attempting to understand a prisoners
past behaviors or constructing a blueprint for future ones (Gacono, 2016; Hare, 2003; Hare et al.,
2020; Smith et al., 2021). The construct of psychopathy includes affective (lack of remorse, guilt,
and empathy), interpersonal (conning/manipulation, lying), as well as impulsive and antisocial
behaviors. It is measured in a reliable or valid manner with the PCL-R (Hare, 2003)or
Psychopathy Checklist: Youth Version (PCL: YV; Forth et al., 2003) and therefore, can be utilized
for determining and comparing psychopathic versus non-psychopathic groups (Gacono, 2016;
Hare, 2003; Neumann et al., 2016; Smith et al., 2021).
The PCL-R is a 20-item measure that has been found to contain a two factor, four facet struc-
ture (Hare, 2003; scored by a 0, 1, or 2 per item): Factor 1 (Interpersonal/affective); Factor 2
(Lifestyle/antisocial); facet 1 (Interpersonal); facet 2 (Affective); facet 3 (Lifestyle); and facet 4
(Antisocial). Self-report measures (i.e., Psychopathic Personality Inventory-Revised [PPI-R;
Lilienfeld & Widows, 2005]) or the Psychopathy Checklist: Screening Version (PCL:SV; Hart et
al., 1995) have not been appropriate for creating psychopathic or non-psychopathic groups
(Cunliffe et al., 2021; Gacono et al., 2001; Hare, 2003; Smith et al., 2014,2018). A total PCL-R
score of 30 or higher has been suggested for an appropriate categorical psychopathic group for
both males and females (Cunliffe et al., 2016; Gacono, 2016; Hare, 2003; Nørbech et al., 2018;
Smith et al., 2021). Numerous forensic studies with male and female populations have noted the
predictive power of the PCL-R total score related to both violent and nonviolent crimes and
infractions (Gray & Snowden, 2016; Hare et al., 2020; Kennealy et al., 2010; Olver et al., 2020;
Warren et al., 2005; Smith et al., 2021).
While male and female antisocial personality disordered individuals share a common border-
line or psychotic personality organization (Gacono & Meloy, 1994; Smith et al., 2021), important
gender differences between male and female psychopaths have emerged (Forouzan & Cooke,
2005; Gacono, 2016; Gacono & Meloy, 1994; Hare, 2003; Kreis & Cooke, 2011,2012; Smith et al.,
2021). Pathological narcissism characterized the male psychopath (narcissistic self-focus; grandios-
ity) as they tend to be cold, detached, and non-emotional (Gacono & Meloy, 1994). Female psy-
chopaths presented with a malignant hysterical style (borderline/histrionic traits), and they tend
to want interpersonal contact for admiration/manipulation, presented with more emotional labil-
ity, and with a pathological self-focus characterized by self-criticism (Cunliffe & Gacono, 2005,
2008; Cunliffe et al., 2016; Forouzan & Cooke, 2005; Gacono & Meloy, 1994; Kreis & Cooke,
2011,2012; Smith et al., 2021).
Psychopathic women have been found to be more prone to engage in affective (a lack of emo-
tional control) rather than predatory violence as evidenced by their higher base rates of violence
toward intimates (Cunliffe & Gacono, 2005,2008; Cunliffe et al., 2016; Hicks et al., 2010; Meloy,
2006; Smith et al., 2021). Women with higher PCL-R
scores displayed more verbal relational/
affective violence (a form of indirect violence) driven by revenge/jealousy (de Vogel & Lancel,
2016; Mansfield-Green, 2017; Selenius et al., 2016; Thomson et al., 2019). Psychopathic women
(PCL-R 30) also displayed high rates of a range of different types of prison misconduct (i.e.,
high [e.g., assaults], medium [e.g., engaging in sexual behaviors], & low [e.g., insolence]), new
convictions while incarcerated, more violence, and increased recidivism rates than non-psycho-
pathic women (Carabellese et al., 2018; Loucks & Zamble, 2000; Richards et al., 2003; Salekin et
al., 1998; Sellbom et al., 2017; Smith et al., 2021; Vitale et al., 2002).
While the PAI cannot determine psychopathy level, it has several scales that add to our under-
standing of the prisoners personality functioning and aggressive behavior (Conn et al., 2010;
Edens et al., 2001; Edens & Ruiz, 2005; Morey & Quigley, 2002; Skopp et al., 2007; Smith et al.,
2020b). The Antisocial Features (ANT) scale correlated with the PCL-R total score especially in
forensic male samples (r¼0.50; Douglas et al., 2007; Edens et al., 2000). Elevated ANT
scores (T 70) suggested egocentricity, lack of empathy, need for stimulation, and proneness to
engage in antisocial behaviors. Incarcerated men who scored higher on the ANT scale and the
Violence Potential Index (VPI; violence risk) committed more institutional infractions (Edens et
al., 2002; Reidy et al., 2016). The PAI Aggression (AGG
; attitudes and behaviors related to hos-
tility, anger, and aggression) scale has been found to be related to institutional misbehavior and
infractions (Edens et al., 2002).
Elevations on the ANT (T 70) and AGG (T 70) scales correlated with recidivism (Morey &
Quigley, 2002). In mixed forensic samples of males and females, PCL-R total scores correlated
with ANT and AGG scale scores (Blonigen et al., 2010; Poythress et al., 2010). Higher total PCL-
R scores in females correlated with elevated ANT, AGG, and DOM (dominance; self-assured,
Rater biases may play a role in the assessment of women including using the PCL-R (e.g., gender bias, affective heuristic,
availability heuristics, etc., see Cunliffe et al. (2021) for a full discussion on biases present for assessing women; also see
Grann, 2000; Verona & Vitale, 2018). Specifically, if the representative heuristic is present, the rater of the PCL-R has the
prototypic male psychopath as their frame of reference, which will result in missing information pertinent to women. This
may be an artifact related to the PCL-R being normed on males and using male pronouns throughout the PCL-R manual
(Hare, 2003).
It is composed of three subscales, Antisocial Behaviors (ANT-A), Egocentricity (ANT-E), and Stimulus-Seeking (ANT-S).
It contains three subscales, Aggressive Attitude (AGG-A), Verbal Aggression (AGG-V), and Physical Aggression (AGG-P).
confident, forceful) scales (Conn et al., 2010; Edens et al., 2000; Kimonis et al., 2010; Salekin et
al., 1997,1998; Smith, Gacono, Kivisto, et al., 2019; Smith et al., 2020b,2021) and female inmates
scoring higher on the AGG, VPI, and ANT scales had more violent and nonviolent incident
reports (Davidson et al., 2016). This suggested that those women who have institutional miscon-
duct had more aggressive and antisocial attitudes, hostility, and stimulus-seeking behaviors.
Two other PAI scales, Borderline features (BOR
) and Paranoia (PAR
) have been correlated
with higher PCL-R total scores and increased institutional incident reports (Davidson et al., 2016;
Smith et al., 2020b). Psychopathic females (PCL-R 30) expressed more problems with aggression
(AGG and its subscales), acknowledged more antisocial behaviors (ANT & ANT-A), and exhibited
a dominant interpersonal style (DOM) with an increased potential for violence (VPI; Smith et al.,
2020b). Skopp et al. (2007) found significant correlations with the PAI scales of ANT, BOR, VPI,
DOM, and ARD-T (traumatic stress) with general/aggressive institutional misconduct in women.
Rorschach Comprehensive System (CS; Exner, 2003) findings have added to our understanding of
forensic participants (Cunliffe & Gacono, 2005,2008; Erard & Evans, 2017; Gacono & Evans,
2008; Gacono & Meloy, 1994; Gacono & Smith, 2021; Meloy, 1988; Smith et al., 2021). Forensic
research with the CS has resulted in the analysis and presentation of over 2,000 administered pro-
tocols available as group data (Gacono & Evans, 2008; Gacono & Smith, 2021; Smith et al., 2021).
Rorschach imagery has effectively aided in mapping the vicissitudes and role of aggression in
borderline, narcissistic, antisocial, and psychopathic personalities (Gacono & Meloy, 1994;
Huprich, 2006; Nørbech et al., 2018; Smith et al., 2020a). Response patterns highlighted an ego-
dystonic (unacceptable to the person, causing internal stress) relationship to aggression for bor-
derline personality disordered individuals, and an ego-syntonic (acceptable to the person, does
not cause internal stress) one for antisocial and psychopathic individuals (Gacono & Meloy, 1994;
Gacono et al., 2008; Meloy & Gacono, 1992; Smith et al., 2020a). Borderline individuals tended to
be distressed by their aggression while antisocial ones, particularly those suffering from primary
psychopathy, gained relief by acting on their aggression and experienced distress when they are
forced to contain it (Gacono & Meloy, 1994).
In the Comprehensive System (CS, Exner, 2003) the aggressive movement response (AG) is
scored solely for aggressive movement occurring in the present. In forensic populations where
behavioral aggression is ubiquitous, AG does not occur frequently enough to be useful (Gacono,
1988). In fact, it is produced more often in non-patient samples (Exner, 2003,2007; Gacono et
al., 2008; Gacono & Meloy, 1994). Additionally, in an inpatient sample, elevations of AG score
(>3) indicated less physical and verbal aggression (Baity & Hilsenroth, 2002).
Largely in response to the failure of AG to capture the aggressive imagery produced by anti-
social and psychopathic prisoners, and based on the research observations of Gacono (1988) and
Heaven (1989), four Rorschach aggressive scores were developed which have been found to be
scored reliably (Extended Aggression Scores; Baity et al., 2000; Gacono, 1988,1990; Gacono &
Meloy, 1994; Meloy & Gacono, 1992; Gacono et al., 2008; Mihura et al., 2003; Smith et al.,
2020a): (1) Aggressive Content (AgC), (2) Aggressive Potential (AgPot), (3) Aggressive Past
(AgPast), and (4) Sado-Masochism (SM).
AgC applied to percepts that most people would perceive as predatory, dangerous, malevolent,
injurious, or harmful(Meloy & Gacono, 1992, p. 105). Elevated AgC scores have been associated
with physical/verbal aggression, DSM Antisocial Personality Disorder criteria (ASPD; American
BOR contains four subscales: Affective Instability (BOR-A), Identity Problems (BOR-I), Negative Relationships (BOR-N), and Self-
Harm (BOR-S).
PAR has Hypervigilance (PAR-H), Persecution (PAR-P), and Resentment (PAR-R) subscales.
Psychiatric Association, 2013), and the MMPI-2 Antisocial Practices (ASP) scale (Baity & Hilsenroth,
1999,2002). AgPot is coded for those responses where an aggressive act was about to occur
(Gacono, 1988), related to sadism (Meloy & Gacono, 1992), and identification with predatory objects
or a preoccupation with predation (Gacono & Meloy, 1994).TheSMresponseisscored
devalued, aggressive, or morbid content is accompanied by pleasurable effects and correlates with
both psychopathy and sexual homicide behavior (Gacono & Meloy, 1994; Huprich et al., 2004).
AgPast is coded for any response in which an aggressive act has occurred, or the object has been the
target of aggression (Gacono, 1988,1990). AgPast responses relate to self-damage, masochism, or an
early traumatic experience of having been aggressed against (Gacono & Meloy, 1994). In antisocial
participants, these indices frequently represented a marker for adopting a victim stance and the
entitlement that supported their rightto then victimize others. It has been found to be related to
the MMPI-2 scale of Anger (ANG; Baity & Hilsenroth, 1999).
Female psychopaths (PCL-R 30) produced greater frequencies of AgC, AgPast, and AgPot
responses than non-psychopathic females (Smith et al., 2020a). Rorschach aggression indices sug-
gested that the violence and potential violence (AgPot) in psychopathic women stemmed from
their identification with aggression (AgC) and pervasive feelings of entitlement (AgPast).
Elevations on these variables suggested ego-syntonic aggression (Smith et al., 2020a), a finding
consistent with their behavioral histories. Additionally, AgC, AgPast, AgPot, and SM were all sig-
nificantly correlated to the PCL-R total score (Smith et al., 2020a). Though not significant, there
was a higher frequency of AG scores in the non-psychopathic women (46%) than the psycho-
pathic women (35%), but less than a non-patient sample (56%; Exner, 2007).
Interpersonal aspects of these women played a role in both aggressive and non-aggressive acts
(Cunliffe et al., 2016;deVogel&Lancel,2016; Greenfeld & Snell, 1999;Mansfield-Green,2017;
Selenius et al., 2016; Thomson et al., 2019).TheRorschachhasbeenvaluabletounderstandthese
interpersonal difficulties. For example, these women tend to have maladaptive neediness (COP; ROD
[Masling et al., 1967]), have a poor understanding of others (PHR), and poor boundaries (DQv)
making it more likely they will aggress against others (Cunliffe & Gacono, 2005;Smithetal.,2021).
High levels of borderline traits have been found within incarcerated women (Conn et al., 2010;
Smith et al., 2021), therefore reality testing may be poor with possible trauma intrusions/dissoci-
ation (Trauma Content Index [TCI]; Armstrong & Loewenstein, 1990). The White Space response
with poor form quality (S-; inability to think clearly when angry; Exner, 2003) may also be
important to examine within incarcerated women. Egocentricity has been identified as the hall-
mark of the psychopathic personality (Cleckley, 1988; Gacono 2016; Hare, 2003). However, unlike
men, women tend to produce fewer reflections (narcissism and arrogance; also Personalized
[PER] responses) and more pair responses in the Egocentricity Index (EGOI; Cunliffe & Gacono,
2005; Cunliffe et al., 2016). Nevertheless, the variable remains an important one to consider in
the examination of misconduct in prison (Smith et al., 2019). Finally, due to affective instability,
negative or painful affect, and a damaged sense of self, that may drive misconduct which can be
studied on the Rorschach with the Achromatic Color (SumC), Vista (SumV), and Morbid
(MOR) variables.
Findings have revealed a convergence between Rorschach and PAI data (Appel, 2016; Charnas
et al., 2010; Hopwood & Evans, 2017; Klonsky, 2004; Mihura et al., 2003; Morey & McCredie,
2019; Petrosky, 2005; Smith et al., 2019,2021).
Sadistic attribution and personalization of sadistic activity in the percept also relates to sadism and does not require the
examinee to directly express pleasurable affect (Gacono et al., 2008).
We anticipated that PCL-R, PAI, and Rorschach variables would significantly predict the total
amount of institutional misconduct for women. Due to the nature of female misconduct, the inci-
dent reports would be categorized as physical aggression, verbal aggression, and nonviolent (see
Buffington-Vollum et al., 2002). We predicted that these three sub-categories would also be sig-
nificantly correlated with the PCL-R, PAI, and Rorschach variables. No specific hypotheses will
be offered; however, all variables placed into the regression equations have been found to relate
to aggressive or illegal behaviors. For each of the measures, the following variables will be used
PCL-R (total); PAI (BOR, ANT, PAR, AGG, PAR, DOM, DRG, VPI, ARD-T); Rorschach (TCI,
ROD, AG, AgC, AgPast, AgPot, SM, S-, DQv, SumC, EGOI, COP, PHR, MOR, SumV, PER).
Participants were 241 women who were incarcerated in a USA medium-security
facility. A subset of these women (n¼126) was used because not all had completed all three
measures (PCL-R, PAI, Rorschach) or they met exclusion criteria
on the measures. They were
incarcerated for sex offenses (20%), fraud (13%), theft (18%), drug offenses (42%), violent
offenses (25%), or other crimes (28%). The mean age was 35.98 (SD ¼9.57; range ¼2167)
while 56% were white, 36% black, 6% Hispanic, 2% Native American, and 1% Asian. Mean IQ
was average (M¼92.22, SD ¼9.10, range ¼80116) and consistent with their educational levels
(M¼11.70, SD ¼2.39, range ¼620). Half of the sample was psychopathic (PCL-R total score
30; n¼64, 51%). All participants signed informed consent to participate in the study and the
research was approved by the local University, IRB boards, and the correctional institution.
The PCL-R (Hare, 2003) was used to determine psychopathy level. This measure contains 20
items and is administered via a file review and a semi-structured interview. Prior to the interview,
all medical, legal, psychiatric, and pertinent institutional files were reviewed. During the interview,
the personality characteristics and antisocial behaviors were evaluated on a three-point ordinal
scale (0, 1, 2 or omit) with a total score range of 040. Gaconos(2005)Clinical and Forensic
Interview Schedule (CFIS) was used to administer the PCL-R (conducting the interview, organiz-
ing all records, & interview information). Doctoral-level psychologists scored all PCL-R protocols.
The inter-rater (Spearman Rho) for PCL-R ratings were 0.98 for total PCL-R score, 0.93 for
Factor 1, 0.92 for Factor 2, and 0.87 for facets and PCL-R items. To limit multicollinearity in
the binary logistic regressions, only PCL-R total score was used (see Table 1).
The Personality Assessment Inventory (PAI; Morey, 1991) is a 344-item self-report measure of
personality and psychopathology. It contains 22 non-overlapping full scales, including four valid-
ity, 11 clinical, 5 treatment considerations, and 2 interpersonal scales, as well as 30 subscales. The
As noted above, female prisons tend to house different security levels due to the total number of female prisons. Therefore,
it is not recommended the findings be compared to males in medium-security prisons.
Protocols were excluded for PAI scores of INF >74, ICN >73, and/or NIM >76 (Morey, 1991) or on the Rorschach, low IQ
(<80) and/or less than 14 responses (Exner, 2003; Smith, Gacono, Fontan et al., 2018; Smith et al., 2020). One was removed
for an extreme number of Rorschach responses (R ¼90).
PAI was standardized on adult samples from the community (n¼1,000) and in mental health
treatment (n¼1,265). Though many PAI scales have subscales (e.g., ANT has ANT-A, ANT-E,
and ANT-S), to limit multicollinearity, only the full scales (no subscales) were used in the data
analyses. PAI scales used were BOR, PAR, ANT, AGG, DRG, DOM, VPI, and ARD-T (only sub-
scale used as full scale was not used) (see Table 2).
All Rorschach protocols were administered and scored per the Exner Comprehensive System (CS)
guidelines (Exner, 2003) by doctoral level (Ph.D. or Psy.D.) clinicians. Protocols were scored by
two raters and inter-rater reliability was calculated from these protocols. Kappa coefficients
ranged from 0.75 to 1.00 (all in the excellent range). The following Rorschach variables were
included in the data analyses: TCI, ROD, AG, AgC, AgPast, AgPot, SM, S-, DQv, SumC, EGOI,
COP, PHR, MOR, SumV, PER (see Table 3).
Disciplinary Offenses
Seventy-five offenses were classified within three different categories of severity: high (i.e., escape),
medium (i.e., substance use), and low (i.e., not attending their work assignment). Using similar
procedures as Edens et al. (2002) and Buffington-Vollum et al. (2002), the individual infractions
were classified as (1) Physical Aggression (fighting, assault, injuring another, bodily harm); (2)
Verbal Aggression (threatening harm, insolence, refusing an order, verbal threats); (3) Nonviolent
(any other incident not classified in the other two categories to include substance use, escape,
mail abuse, etc.).
Personality measures (PCL-R, PAI, Rorschach) were collected as part of an approved research
study. Five years after completing the research, institutional disciplinary files were reviewed for
incident reports received by the participant.
Table 1. Descriptive statistics for the PCL-R scores for entire sample (n¼126).
MSD Range
PCL-R Total Score 28.61 5.80 11.638.9
PCL-R Factor 111.27 3.13 119
PCL-R Factor 214.33 3.58 4.420
PCL-R Facet 15.93 1.67 08
PCL-R Facet 25.26 1.68 18
PCL-R Facet 37.76 1.69 310
PCL-R Facet 46.39 2.58 010
Note. : not used in regressions; M: mean; SD: standard deviation; PCL-R: Psychopathy Checklist-Revised.
Table 2. Descriptive statistics for the PAI scales for entire sample (n¼126).
MSD Range
PAI BOR 76.56 11.28 44100
PAI PAR 71.67 11.28 46100
PAI ANT 70.13 13.24 37105
PAI AGG 64.45 14.89 3297
PAI DOM 50.33 13.99 1774
PAI VPI 84.62 19.22 43125
PAI DRG 85.19 19.64 42114
PAI ARD-T 81.59 12.77 4899
Note. M: mean; SD: standard deviation; PAI: Personality Assessment Inventory; BOR: borderline features; PAR: paranoia; ANT:
antisocial features; AGG: aggression; DOM: dominant style; VPI: violence potential index; DRG: drug; ARD-T: traumatic stress.
Data Analyses
The Statistical Package for Social Sciences (SPSS) version 27 was used for all calculations. For the
PAI (T scores), Rorschach, and PCL-R, the data were analyzed for means, standard deviations,
and ranges. Binary logistic regression analyses (backward) were completed for the personality
measures and the categories of incident reports. Due to the lack of total amount of incident
reports for these women, each incident report category (total, physical, verbal, non-aggressive)
was converted to binominal values (0 ¼no; 1 ¼yes). These were then used in the regression anal-
yses instead of totals for each category (Skopp et al., 2007).
Looking at the number of incident reports, these women had a low number of incident reports
with physical aggression being relatively rare (see Table 4). The psychopathic (PCL-R 30)
women had significantly higher rates of total (t¼2.912; p¼0.005; Cohensd¼0.50) and non-
aggressive (t¼2.638; p¼0.01; Cohensd¼0.42) incident reports than non-psychopathic women
(PCL-R 24) did. Additionally, psychopathic women (PCL-R 30) engaged in significantly more
high (i.e., assaults; psychopaths; M¼0.39, SD ¼0.78; non-psychopaths; M¼0.10, SD ¼0.50),
medium (i.e., sexual behaviors; psychopaths; M¼1.6, SD ¼3.94; non-psychopaths; M¼0.41, SD
¼0.68), and low (i.e., insolence; psychopaths; M¼4.44,
SD ¼11.63; non-psychopaths; M¼1.59, SD ¼3.45) risk infractions. Though in the sample,
assault and possessing substances were present, a lot of the incident reports were phone abuse
Table 3. Descriptive statistics for the Rorschach variables for entire sample (n¼126).
MSD Range Frequency (%)
Responses22.55 8.77 1455 126 (100%)
Lambda0.84 0.73 0.096.00 126 (100%)
AG 0.45 0.74 03 41 (32%)
AgC 4.36 2.94 014 124 (98%)
AgPast 2.40 2.60 017 95 (75%)
AgPot 0.43 0.82 04 36 (29%)
SM 0.48 0.84 04 41 (32%)
S- 1.55 1.69 08 86 (68%)
EGOI 0.39 0.20 0.041.59 126 (100%)
PHR 4.18 3.19 015 117 (93%)
ROD 0.25 0.13 00.57 121 (96%)
TCI 0.29 0.20 00.96 120 (95%)
SumC2.31 2.16 010 100 (79%)
DQv 4.99 4.01 021 122 (97%)
COP 0.66 0.90 04 56 (44%)
SumV 1.71 1.78 09 90 (71%)
PER 3.48 3.56 021 103 (82%)
MOR 3.24 2.83 016 107 (85%)
Note.: not used in regression analyses. M: mean; SD: standard deviation; AG: aggressive movement; AgC: aggressive content;
AgPast: aggressive past; AgPot: aggressive potential; SM: sadomasochistic; S: white space; EGOI: egocentricity index; PHR:
poor human response; ROD: Rorschach oral dependency; TCI: trauma content index; C: achromatic color; DQv: developmen-
tal quality vague; COP: cooperative movement; V: vista; PER: personalized response; MOR: morbid.
Table 4. Descriptive statistics for incident reports for entire sample (n¼126).
MSD Range
Total # of incident reports 0.78 1.33 07
Total # of physical aggressive reports 0.11 0.38 03
Total # of verbal aggressive reports 0.33 0.75 04
Total # of nonviolent incident reports 0.33 0.90 07
Note. #: number; M: mean; SD: standard deviation.
(i.e., giving another woman access to their phone), insolence, refusing an order, having unauthor-
ized items, not reporting to their assignment, and misusing medication.
Though not specifically explored in any model, being younger was significantly related to
physically aggressive incident reports (age; v
;1,n¼126; 6.664, p¼0.01, Nagelkerke R
true R-Squared ¼0.04 [low; Cohen, 1992]). Age was not significant with any other category of
incident reports. Additionally, the amount of time incarcerated at the time of the assessment and
sentence length was not significant compared to any of the incident report categories.
Total Incident Reports
The regression model (see Table 5) for the total number of incident reports with the three per-
sonality measures was significant (v
; 10, n¼126; 30.571, p<0.001, Nagelkerke R
¼0.295; true
¼0.213 [medium, Cohen, 1992]). In the model, ten variables were used from the PCL-R, PAI,
and Rorschach. Total PCL-R score, PAI BOR scale, PAI ANT scale (lower scores), Rorschach TCI
(lower scores), Rorschach ROD, and Rorschach AgPot (lower scores) were significant in this
model (Table 5).
Table 5. Final logistic regression models predicting prison misconduct using the PCL-R, PAI, and Rorschach.
Infraction Type B
SE Wald df p OR
Constant 2.536 1.926 1.734 1 0.188 0.079
PCL-R TS 0.154 0.053 8.519 1 0.004 1.167
PAI PAR 0.048 0.027 3.065 1 0.080 0.954
PAI BOR 0.065 0.031 4.332 1 0.037 1.067
PAI ANT 0.080 0.028 8.196 1 0.004 0.923
PAI AGG 0.034 0.019 3.071 1 0.080 1.035
TCI 3.135 1.275 6.050 1 0.014 0.044
ROD 4.983 2.100 5.629 1 0.018 145.865
AgPot 0.708 0.316 5.021 1 0.025 0.493
EGOI 2.477 1.272 3.792 1 0.051 0.084
COP 0.515 0.271 3.621 1 0.057 1.674
Constant 3.563 2.042 3.046 1 0.081 0.028
PAI DRG 0.029 0.019 2.397 1 0.122 0.971
PAI VPI 0.046 0.020 5.257 1 0.022 1.047
ROD 6.101 2.846 4.596 1 0.032 446.293
EGOI 5.992 2.625 5.209 1 0.022 0.002
Constant 4.757 2.025 5.521 1 0.019 0.009
PAI BOR 0.069 0.030 5.299 1 0.021 1.071
PAI ANT 0.054 0.025 4.810 1 0.028 0.947
PAI DOM 0.035 0.018 3.811 1 0.051 1.035
TCI 4.861 2.150 5.111 1 0.024 0.008
ROD 4.512 2.227 4.106 1 0.043 91.105
AgPast 0.648 0.231 7.862 1 0.005 0.523
SumV 0.439 0.206 4.553 1 0.033 0.645
MOR 0.762 0.237 10.337 1 0.001 2.143
Constant 7.303 2.708 7.272 1 0.007 0.001
PCL-R TS 0.375 0.093 16.238 1 <0.001 1.455
PAI BOR 0.080 0.037 4.766 1 0.029 1.083
PAI ANT 0.147 0.045 10.757 1 0.001 0.863
AgPot 0.836 0.410 4.160 1 0.041 0.434
SumC0.395 0.166 5.645 1 0.018 1.484
SumV 0.429 0.231 3.444 1 0.063 0.651
EGOI 5.019 2.193 5.239 1 0.022 0.007
COP 0.556 0.305 3.329 1 0.068 1.744
Note. OR: odds ratio; TS: total score. For abbreviations see Tables 2-4.
Unstandardized regression coefficients.
Physically Aggressive Incident Reports
A significant regression model (see Table 5) for the physically aggressive reports and the three
personality measures produced was found (v
;4,n¼126; 16.506, p¼0.002, Nagelkerke R
0.264; true R
¼0.088 [low, Cohen, 1992]). In the model, four variables were included but only
one PAI scale (VPI) and two Rorschach variables (ROD & EGOI [lower scores]) were significant
in the model.
Verbally Aggressive Incident Reports
There was a significant regression model (see Table 5) for verbally aggressive misconduct and
the three personality measures (v
;8,n¼126; 23.579, p¼0.003, Nagelkerke R
¼0.265; true
¼0.181 [medium, Cohen, 1992]). In the model, eight variables were included with PAI
BOR, PAI ANT (lower scores), Rorschach TCI (lower scores), Rorschach ROD, AgPast (lower
scores), Rorschach SumV, and Rorschach MOR being significant.
Non-Violent Aggressive Incident Reports
The regression model (see Table 5) for the non-aggressive reports with the three personality
measures was significant (v
;8,n¼126; 37.073, p<0.001, Nagelkerke R
¼0.417; true R
0.309 [high, Cohen, 1992]). In the model, eight variables were included. The significant variables
were PCL-R total score, PAI BOR, PAI ANT (lower scores), Rorschach AgPot (lower scores),
Rorschach C, and Rorschach EGOI (lower scores).
Supplemental Analyses
To gain added understanding of psychopathy, psychopaths (n¼64; PCL-R 30) were also
compared to non-psychopaths (n¼30; PCL-R score 24). With the PAI scales, the psycho-
paths had significantly higher means than non-psychopaths on all PAI scales studied (BOR,
PAR,ANT,AGG,DRG,VPI,DOM,p<0.05, d0.60) except for ARD-T (non-significant).
On the Rorschach, the psychopathic females had significantly more ROD, AgPot, SumV, PHR
(p<0.05, effect size >0.29) scores than the non-psychopathic females.
To add to the construct validity of the PAI AGG-P (Physical Aggression) and PAI AGG-V
(Verbal Aggression) scales, correlational analyses were done with verbal and physical aggressive
incident reports. AGG-P was significantly correlated with physical aggression (r¼0.207) but not
verbal aggression reports. AGG-V was significantly correlated with verbal aggression (r¼0.151)
but not physical aggression.
This study has many strengths including comparisons with three distinct categories for incident
reports (physical, verbal, nonviolent) rather than one inclusive category (Buffington-Vollum et al.,
2002; Edens et al., 2002; Skopp et al., 2007). Rather than looking at the data retrospectively, we
looked at incident reports after a five-year period when the psychological data was collected help-
ing eliminate criterion contamination and questionable generalizability. These women completed
personality measures first and then were behaviorally assessed five years later. For example, when
an incarcerated woman had a high ROD score on the Rorschach did that mean anything later
while incarcerated? In this case, yes, those who produced high ROD scores had significantly more
incident reports in general and more physically (i.e., fights) and verbally (i.e., insolence, refusing
orders, and threatening others) aggressive incident reports. This is important because having
measures that can help identify incarcerated women at risk for different offenses can help with
better management strategies (closer supervision, higher security if available, etc.). Therefore, the
measures can be valuable tools in keeping the prison safe.
The use of three different measures allows for a more thorough understanding of why these
women misbehave. This multi-method approach provides a template for understanding the valid-
ity of each measure and in combination with one another. Failure to use a multi-method
approach for the sake of time may give the psychologist an incomplete picture of the prisoners
predicted behavior that is not as valuable as the three in combination (Buffington-Vollum et al.,
2002; Gacono, 2016; Smith et al., 2021).
For the PAI, it appears that Borderline Features scale (BOR; positive relationships in the mod-
els) rather than Antisocial Features scale (ANT; negative relationships in the models) was the
driving force behind the incident reports in these women unlike those described by Buffington-
Vollum et al. (2002). High incidences of borderline personality disorder within female correc-
tional settings have been found (Conn et al., 2010) and the underlying personality style of female
psychopathy appears to be malignant hysteria (borderline/histrionic traits; Gacono & Meloy,
1994; Cunliffe & Gacono, 2005; Kreis & Cooke, 2011; Smith et al., 2021). This may account for
these findings. Further, affective instability, self-harming behaviors, identity disturbance, and
negative relationships appeared to be related to their misconduct (BOR scale). Identifying these
important characteristics of these women can help better assist in diagnosing and providing
appropriate mental health care.
In terms of aggression, it has been found that relational and affective aggression against close
acquaintances were common in women (de Vogel & Lancel, 2016; Mansfield-Green, 2017;
Selenius et al., 2016; Thomson et al., 2019). The findings of physical aggression being tied to rela-
tionships (Rorschach ROD) suggested that the women were engaging in a form of relational
aggression. The verbal aggression incidents may also account for this style of aggression (PAI
DOM; ROD) in a sample where gossiping, ostracizing, and criticizing has been highly prevalent
(women; Crick & Grotpeter, 1995; Crick et al., 2006). Additionally, many of the incident reports
that the women had received included a social component (phone abuse, insolence, refusing
orders, etc.) suggesting the importance of relationships in their misconduct.
Traumatic events tend to be ubiquitous to incarcerated women (DeCou et al., 2017;
MacDonald, 2013). It appears having less traumatic intrusions/dissociation (Rorschach TCI)
resulted in more incident reports for these women (total and verbal) speaking to more personality
characteristics rather than environmental events (experiencing traumatic events). The PAI ARD-T
(traumatic events) scale was not added to any model. Due to the high rates of trauma sympto-
mology among incarcerated women (non-significant between psychopathic and non-psychopathic
women), the presence of traumatic events may not be helpful in predicting institutional miscon-
duct (unlike Skopp et al., 2007).
EGOI was negatively related to physical aggression suggesting that lower self-esteem or self-
view was related to engaging in physical aggression. Incarcerated women tend to have poor self-
images, and this coupled with perhaps the criminal thinking error of zero states (Yochelson &
Samenow, 1977) may allow her to feel she has nothing left to lose and therefore, engages in phys-
ical aggression to take back some form of power. Additionally, an affective (immature) need for
others (ROD) appears related to the physical aggression in these women.
Psychopathic women (PCL-R 30) in comparison to the non-psychopathic women, showed
more self-critical attitudes (SumV), aggressive potential (AGG, VPI, AgPot), borderline sympto-
mology (BOR), higher rates of antisocial attitudes and behaviors (ANT), drug use (DRG), para-
noia (PAR), and dominant maladaptive interpersonal interactions (DOM, ROD, PHR). This adds
to our understanding of psychopathic women displaying malignant hysteria (borderline/histrionic
traits) with affective instability and poor interpersonal relations leading to antisocial behaviors
which can be related to their entitlement and impulsivity.
Despite the relatively low frequency of total incident reports among the incarcerated women
(M¼0.78), especially physically aggressive incidents (M¼0.11) significant patterns emerged along
expected theoretical lines. For example, perhaps in part due to their impulsivity and entitlement,
the psychopathic women had significantly higher rates of total and non-aggressive incident
reports than the non-psychopathic women did.
Examining the PCL-R, Rorschach, and PAI scores with these incarcerated women suggested
that they committed any type of infraction due to high levels of psychopathy (PCL-R; like
Buffington-Vollum et al., 2002), affective instability (PAI BOR), negative views of relationships
(PAI BOR; Rorschach ROD), low levels antisocial attitudes/paranoia (PAI ANT and PAR), less
traumatic intrusions/dissociation (Rorschach TCI), and less aggressive potential (Rorschach
AgPot). It appears that their inability to regulate their emotions and high rates of impulsivity
(Camlibel et al., 2021) coupled with poor interpersonal boundaries were personal vulnerabilities
leading to poor real-world decisions and behaviors; in this case, maladjustment while incarcer-
ated. These were the same vulnerabilities that produced offenses in the community (Smith et
al., 2021).
Exploring physical aggression within the sample, though rare, there were some important
insights into these women. As expected with theory, being younger did have some relationship to
physical aggression (Gover et al., 2008; Leigey, 2019; Reidy et al., 2017). It has been postulated
that as age increases, the amount of energy to engage in physical aggression decreases resulting in
less violent acts (Ulmer & Steffensmeier, 2014). That may be the case with this sample and it is
an important aspect to consider when classifying incarcerated women.
Examining the personality measures, the women who received physical aggression incident
reports tended to have the potential for violence (PAI VPI) with maladaptive neediness
(Rorschach ROD), and negative views of self (low Rorschach EGOI). This suggested that these
self-concept and interpersonal difficulties resulted in more fights and assaults for these women in
prison. Similarly, those that had more verbal incident reports such as insolence, refusing orders,
or threatening staff and other inmates, tended to display self-concept (Rorschach SumV and
MOR) and interpersonal difficulties (PAI DOM and Rorschach ROD). However, those with more
verbal incident reports also showed affective instability and impulsivity (PAI BOR), less antisocial
attitudes (PAI ANT), less traumatic intrusions/dissociation and an identification as victims of
aggression (Rorschach TCI and AgPast).
When non-aggressive incident reports such as using illicit substances, abusing phone privi-
leges, and having sexual encounters were considered, more patterns emerged. PCL-R total score
was related to non-aggressive incident reports. Past research has found psychopathy to be related
to acting out with women (Smith et al., 2021). Additionally, borderline symptomology including
affective instability,self-harming behaviors (BOR),lower antisocial attitudes (PAI ANT), and low
levels of aggressive potential (Rorschach AgPot) contributed to their nonviolence misconduct.
SumCwas related to nonviolent incident reports indicating that these womens internal painful
affect may induce them to engage in non-effective behaviors. This would also be linked to their
low scores on the EGOI (low self-worth).
Based on the previous literature (Appel, 2016; Charnas et al., 2010; Hopwood & Evans, 2017;
Klonsky, 2004; Mihura et al., 2003; Morey & McCredie, 2019;Petrosky,2005; Smith et al., 2019,2021),
it was not surprising to see a convergence between the three measures in the models (see Table 5).
Specifically, PCL-R total score, PAI scales, and Rorschach variables helped explain the variance in total
and nonviolent incident reports while PAI scales and Rorschach variables helped explain physical and
verbal incident reports. Though the measures were not as good at predicting physical aggression, total,
verbal, and especially non-aggressive incident reports were better predicted by the PCL-R, PAI,
and Rorschach.
As mentioned previously (Buffington-Vollum et al., 2002; Edens et al., 2002; Skopp et al.,
2007), though the PAI ANT scale has some features in common with the PCL-R and had a high
correlation here (r¼0.54) it is not recommended that one designate psychopathy based on the
PAI score but rather the PCL-R score. Additionally, the fact that scoring lower on the ANT scale
contributed to committing misconduct for these women suggested it may not be as useful as the
PCL-R total score. Adding to the validity of the PAI, as expected, physically aggressive acts were
related to the PAI scale measuring physical aggression (AGG-P) and not verbal aggression. The
expected result was also found for the verbal aggression PAI scale (AGG-V) with it being related
to verbal but not physical aggression.
The results should be encouraging to psychologists working in correctional settings.
Empirically driven data can help inform decisions and better educate correctional staff and
administrators to help manage the correctional facility. The data can provide important insights
to help with differential diagnosis, provide recommendations for adequate mental health treat-
ment, and help put in place security and safety measures with these women. For example, a
woman who scores high on PAI BOR and Rorschach ROD with a low Rorschach EGOI coupled
with higher psychopathy scores (PCL-R) is likely at risk for misconduct possibly toward staff and
other inmates. This data can help reclassify her to a different security level, increase her supervi-
sion within the prison, or allow for a discussion on an interdepartmental safety plan.
Additionally, it will provide important guidance on mental health treatment including offering
anger management, Dialectical Behavior Therapy (DBT), and criminal thinking groups that might
mitigate her personality vulnerabilities related to committing institutional misconduct.
This type of in-depth assessment only adds value to having psychologists as vital members of
the treatment team providing a service, psychological assessment, no other member can provide
(Gacono, 2016). Therefore, assessment, when conducted properly, is crucial to the correctional
setting (Gacono, 2002,2016). We are mindful of the demands of working in these settings which
may encourage shortcuts where a psychologist may forgo testing and rely solely on clinical judg-
ment. However, this is short-sighted and can lead to biased judgments (Smith et al., 2021). We
advocate for only using measures that are efficient and add clinical value which we have found to
be the PCL-R, PAI, and Rorschach. Using a self-report measure of psychopathy would not pro-
vide the results one is looking for and would be a waste of time and resources for both the
inmate and the psychologist (Gacono, 2016). We also warn of the dangers of over-relying on
computer-generated interpretive reports. Although, they are without a doubt valuable, especially
in the case of the PAI and Rorschach where a computer program greatly assists with making sure
the test is properly scored. However, the clinician is encouraged to consider how the test scores
(group data) relate to the person being evaluated (idiographic data) and all assessments and clin-
ical reports should be a careful integration of all the data available (clinical interviews, test data,
record review, and other collateral information).
While this study did not focus exclusively on theories related to misconduct while in prison
(importation, deprivation, gendered importation, and threat appraisal and coping; Camlibel et al.,
2021; Leigey, 2019), the results can be used by researchers to explore how they can be integrated
into them. While accurately reflecting the recorded behaviors of the women in this sample, the
total number of incident reports (especially physical aggression; probably related to the low vari-
ance found) is less than ideal for the number of comparisons made. While the overall patterns
that we discovered are likely accurate, our clinical interactions with these women suggest that
they committed more institutional infractions than have been recorded. Additionally, this is just
one female sample in the United States so this may limit the generalizability. More research into
incarcerated women with psychological measures is needed as is more research looking at the
convergence between the PCL-R, PAI, and the Rorschach. Recently, a new version of the PAI was
released (PAI Plus; Morey, 2020) which included new validity scales and refocused the assessment
upon how different variables interact and coalesce (i.e., PAI Cluster scores) to increase its eco-
logical validity and clinical utility. Future studies with these scales forensically are encouraged.
Gender and racial bias may be present during psychological assessments (Cunliffe et al., 2021).
Though there have been researches to suggest that the instruments themselves are not biased in
this manner, rather it is how the clinician applies the findings that lead to bias (Cunliffe et al.,
2021). There is a need for all clinicians and researchers to be cognizant of and take steps to elim-
inate bias in their professional work especially working with incarcerated women. Examiners
must be on guard and adopt an objective, professional, neutral, and factual mindset when inter-
acting with or conducting evaluations with these women (Cunliffe et al., 2021).
If identifying institutional misconduct risk is a major goal of prison settings, the PCL-R, PAI,
and Rorschach measures provide valuable information for clinicians working with incarcerated
women. It is imperative clinicians attempt to better understand the underlying misconduct behav-
iors of these women to offer better management and treatment of these prisoners and provide
other correctional workers with scientific insights.
We would like to thank Dr. Les Morey for the article idea and Charles Reshenberg for helping with
data collection.
Jason M. Smith
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Full-text available
It is essential to understand that CS validity research does not translated directly to the R-PAS. In this article we dicuss essential issues to consider prior to using the R-PAS in an applied context.
Full-text available
Between 1980 and 2018, the number of incarcerated women increased by more than 750%, rising from a total of 26,378 to 225,345. Managing and treating these women can be challenging. Understanding Female Offenders: Psychopathy, Criminal Behavior, Assessment, and Treatment provides a guide for meeting these challenges. In addition to providing a sound conceptualization for both psychopathic and non-psychopathic women, the text includes suggestions for interviewing, assessing, managing, and treating them. Throughout this text, clinical caveats and case examples enliven the application of research to practice. Consistent with the scientist-practitioner model, clinical experience and research guide the authors’ formulations which are translated for direct application. Additionally, guidelines are provided for identifying bias and interpreting the female offender literature. This is the first in-depth resource of its kind.
Full-text available
Mihura’s (2019) recent commentary on Smith et al.’s (2018) article, “A Scientific Critique of Rorschach Research: Revisiting Exner’s Issues and Methods in Rorschach Research (1995)” raised several issues surrounding our internal validity criteria and our approach to validating Rorschach research. Mihura also conducted additional statistical analyses that failed to address important, critical issues. In this article, we further clarify the importance of refining internal validity criteria for Rorschach research and Rorschach meta-analytic studies (our 2018 article). We offer this information and analysis to guide the Rorschach consumer toward a better understanding of how to assess the validity of Rorschach data and empirical findings. Criticisms of our criteria for evaluating Rorschach research (inter-rater reliability, IQ/Education level, Rorschach Responses, Lambda/F%, sample size) and our recommendation to include descriptive data for critical variables in all published Rorschach studies contradict accepted standards for Rorschach research. Mihura stated that “the associations between the Rorschach and self-report measures were not used to determine the validity of Rorschach variables” (p. 171) in her meta-analyses. Consequently, we applied our methodological criteria to only Mihura’s externally assessed criteria studies (removing self-report studies; 67%) and found that 91% had three or more problems related to internal validity (13 had counter-intuitive findings). In addition, other central issues related to meta-analyses, application/validation studies, and counter-intuitive findings regarding the Rorschach were discussed.
The Personality Assessment Inventory (PAI; Morey, 1991) and Rorschach Inkblot Method (RIM; Rorschach, 1921) are two of the most commonly used and well-validated instruments used in forensic settings (see Gacono & Evans, 2008, Morey & Meyer, 2013). Both instruments have been found to meet standards necessary for use in court (PAI: Mullen & Edens, 2008; Rorschach: McCann & Evans, 2008, Meloy, 2008, Erard, 2012). Furthermore, several aspects of these tests make them highly complementary for clinical and forensic assessment. However, thus far there are currently few resources in the literature on how to combine these instruments for clinical practice (Charnas, Hilsenroth, Zodan, & Blais, 2010; Klonsky, 2004), let alone forensic practice. In this chapter, we first review the PAI in terms of its development, validity, and interpretation in forensic settings. We will then discuss a case example highlighting the value of synthesizing PAI and Rorschach data in forensic practice. We will conclude with the integration of the PAI with the Rorschach for forensic personality assessment.
Long before psychology, bias has existed in science. From the beginning, concerns have been raised about the reliability, validity, and accuracy of social science research (Meehl, 1954). In this chapter, we define and discuss the origins of bias and how it can erode the scientific method. We focus specifically on bias in psychological research, theory, assessment, and treatment. We discuss the range of common misconceptions and misinformation that permeates the female offender literature. Finally, we conclude with ten myths about female offenders and offer guidelines for identifying bias and how to avoid it.
In this chapter, we provide a theoretical and empirically based understanding of antisocial and psychopathic women. We begin by clarifying the differences between psychopathy, sociopathy, and ASPD, and then provide a historical perspective of hysteria. While the underlying personality of the female psychopath is paranoid, malignant hysteria is their predominant personality style (Gacono & Meloy, 1994). Overviews of the Hare Psychopathy Checklist-Revised (PCL-R), Personality Assessment Inventory (PAI), and Rorschach are offered as a refresher for those experienced clinicians and as a resource for those that are not. Finally, we present group PAI and Rorschach data (also Trauma Symptom Inventory-2 [TSI-2]) for 337 female offenders including subsets of psychopathic (N = 124) and non-psychopathic (N = 57) females. We make note of the differences between female and male psychopaths.
The present study compared predictors of violence as suggested by the importation and deprivation models and the newly utilized threat appraisal and coping models. Participants included 290 female and 472 male inmates in Wisconsin state prisons who completed anonymous surveys to report seven characteristics they import to prison and to report three social stressors experienced during the deprivation and powerlessness of the prison experience. Multiple regression revealed that for both female and male inmates, violence was associated with the imported characteristics of younger age and impulsivity and with in-prison stressors from correctional staff and family. Years of incarceration was a significant predictor of violence only for males. As suggested from past research, the personality pattern of hostility was associated with violence, particularly in male inmates, and internal locus of control was associated with violence, particularly in female inmates.