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The human brain The human brain argumentatively is the human brain – it remains relatively the same and is not subject to sudden leaps in evolution. In 150

September 13, 2021

The human brain The human brain argumentatively is the human brain – it remains relatively the same and is not subject to sudden leaps in evolution. In 1500 words, do the following:

Explain if      there are still pathways to be explored in our understanding of the human brain.

Analyze how      the field of computer science could aide psychopathologist in      understanding the human mind.

Describe      tools that could aide or treat those suffering from deviant or even      criminal psychological conditions that you anticipate seeing in the      future.

Provide six peer-reviewed sources to support your claims.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. Understanding Persons With Mental Illness Who Are and Are Not
Criminal Justice Involved: A Comparison of Criminal Thinking and

Psychiatric Symptoms

Nicole R. Gross and Robert D. Morgan
Texas Tech University

Research has begun to elucidate that persons with mental illness become involved in the criminal justice
system as a result of criminality and not merely because of their mental illness. This study aims to clarify
the similarities and differences in criminal thinking and psychiatric symptomatology between persons
with mental illness who are and are not criminal justice involved. Male and female (n � 94) participants
admitted to an acute psychiatric facility completed measures to assess criminal thinking (i.e., Psycho-
logical Inventory of Criminal Thinking Styles and Criminal Sentiments Scale–Modified) and psychiatric
symptomatology (Millon Clinical Multiaxial Inventory–Third Edition). In addition to the inpatient
sample, 94 incarcerated persons with mental illness from a previously conducted study were selected
based on their match with the current sample on several key demographic and psychiatric variables. The
results of this study indicated that hospitalized persons with mental illness with a history of criminal
justice involvement evidenced similar thinking styles to persons with mental illness who were incarcer-
ated. Persons with mental illness without criminal justice involvement evidenced fewer thinking styles
supportive of a criminal lifestyle than the incarcerated sample. Furthermore, the persons with mental
illness sample with no history of criminal justice involvement showed significantly lower levels of
psychopathology shown to be risk factors for criminal justice involvement (e.g., antisocial personality,
drug dependence, alcohol dependence). These findings have implications for offender-type classification,
development of targeted treatment interventions, and program placement.

Keywords: criminal thinking, offender, criminal justice involvement, mental illness

Persons with mental illness (PMI) are 3 times more likely to be
incarcerated than admitted to a psychiatric facility (Abramsky &
Fellner, 2003; Torrey, Kennard, Eslinger, Lamb, & Pavle, 2010).
Consequently, correctional institutions have become the largest
providers of mental health treatment in the United States (Abram-
sky & Fellner, 2003). Notably, 14.5% of male and 31% of female
offenders in jails have a serious mental illness (i.e., schizophrenia
spectrum disorder; schizoaffective disorder; schizophreniform disor-
der; brief psychotic disorder; delusional disorder; psychotic disorder
not otherwise specified [NOS]; bipolar disorder I, II, and NOS; major
depressive disorder; and depressive disorder NOS; Steadman, Osher,
Robbins, Case, & Samuels, 2009). PMI are disproportionally repre-
sented in correctional institutions because less than 6% of the general
population is estimated to suffer from a severe mental illness (Amer-
ican Psychiatric Association, 2000; Kessler, Chiu, Demler, & Walters,
2005). It appears that PMI are involved in and affected across criminal
justice (CJ) and mental healthcare systems; however, it remains un-
clear how PMI involved in the mental healthcare system compare to
PMI involved in the CJ system.

When compared to offenders without mental illness, PMI who are
placed in community supervision (i.e., probation and parole) after
being released from a correctional facility are significantly more likely
to recidivate (continued criminal behavior resulting in arrest and
reincarceration; Messina, Burdon, Hagopian, & Prendergast, 2006).
Likewise, it is estimated that 37–53% of PMI released from mental
health facilities psychiatrically recidivate (decompensate and are con-
sequently readmitted to a mental health facility) within 1 year of being
discharged (Hillman, 2001; Segal & Burgess, 2006). Commonalities
such as high criminal recidivism and psychiatric hospitalization rates
between PMI who are and are not CJ involved may indicate common
risk factors such as criminal thinking, poverty, homelessness, and
unemployment (Draine, Salzer, Culhane, & Hadley, 2002; Mgust-
shini, 2010) between the two groups. Such results would identify a
neglected treatment area for PMI regardless of setting (CJ or mental
health) that, if addressed, may improve treatment outcomes (e.g.,
symptom reduction, reduced criminal recidivism, and psychiatric hos-
pitalizations). Investigating the role of mental illness in the provoca-
tion and exacerbation of criminal behavior is thus warranted. PMI
who are CJ involved may have unique mental health needs and
criminal risk factors when it comes to offending behavior. Addition-
ally, similarities in criminal thought patterns may affect psychological
functioning and mental health recovery (e.g., symptom management,
rehospitalization) of PMI who are not CJ involved.

Although it may seem plausible that PMI enter the CJ system as
a result of their mental health symptoms, it has been suggested that
some PMI have comorbid criminal dispositions that result in their

This article was published Online First October 29, 2012.
Nicole R. Gross and Robert D. Morgan, Department of Psychology,

Texas Tech University.
Correspondence concerning this article should be addressed to Robert D.

Morgan, Department of Psychology, Texas Tech University, Box 42051,
Lubbock, TX 79409-2051. E-mail: robert.morgan@ttu.edu

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Law and Human Behavior © 2012 American Psychological Association
2013, Vol. 37, No. 3, 175–186 0147-7307/13/$12.00 DOI: 10.1037/lhb0000013

175

mailto:robert.morgan@ttu.edu

http://dx.doi.org/10.1037/lhb0000013

CJ involvement (Hiday, 1999). Elbogen and Johnson (2009) found
that severe mental illness did not predict future violence if not
paired with historical, clinical, and dispositional contextual factors
(e.g., past violence, unemployment, low socioeconomic status,
victimization; Draine et al., 2002). Although violence does not
necessarily result in CJ involvement, the aforementioned contex-
tual factors that are related to the prediction of violence are also
commonly associated with crime in general. Furthermore, Draine
and colleagues (2002) noted that the relationship between mental
illness and crime is weak, and they suggest that poverty, lack of
education, unemployment, and limited prosocial relationships
likely serve as moderating variables in this relationship. Mental
illness appears to predispose individuals to reside in environments
that foster criminal behavior (Draine et al., 2002; Fisher, Silver, &
Wolff, 2006). For example, offenders and PMI often live in low-
income areas, are single, have limited social and family support,
and have a history of unemployment (Fisher et al., 2006). Home-
lessness and a family history of incarceration have been found to
be more prevalent among PMI who are CJ involved than offenders
without mental illness (Ditton, 1999). Additionally, PMI who are
CJ involved were more likely to be unemployed before their arrest
when compared with offenders without mental illness (Ditton,
1999), and male PMI with substance abuse disorders were twice as
likely to have a criminal record as those without a substance abuse
disorder. This is likely due to the role of substance abuse as a
prominent risk factor for criminal behavior (Andrews & Bonta,
2006). Among a sample of hospitalized veterans, substance abuse
accounted for most of the variance in the risk of incarceration
despite the presence or absence of mental illness (Erickson, Rosen-
heck, Trestman, Ford, & Desai, 2008). Additionally, the link
between mental illness and violent behavior was weak if the
individual did not have comorbid substance use issues (Elbogen &
Johnson, 2009; Swartz et al., 1998).

PMI appear to experience multiple risk factors that strongly
influence CJ involvement. With regards to the number and inten-
sity of risk factors experienced by PMI, Girard and Wormith
(2004) found that PMI evidenced higher scores on the Levels of
Service Inventory/Case Management Inventory (LSI/CMI; a com-
monly used measure of risk assessment for predicting criminal
recidivism) than persons without mental illness, suggesting that
PMI experience more criminal risk factors than individuals with-
out mental illness. Many of these criminal risk factors measured by
the LSI (e.g., education, employment, housing, substance abuse)
correspond to poverty, joblessness, and other factors that Draine
and colleagues (2002) identified as factors that predispose PMI to
engage in criminal behavior. The criminal risk factors measured by
the LSI/CMI are positively correlated with criminal recidivism. In
a study examining PMI perceived risk for psychiatric rehospital-
ization, individuals endorsed risk factors such as unemployment,
lack of education, lack of housing, and economic difficulties
(Mgustshini, 2010) that correspond to those used in the prediction
of criminal behavior. Thus, it is reasonable to suggest that criminal
risk factors may also play a role in the frequency of psychiatric
hospitalizations. These predisposing environmental factors are im-
portant in terms of treatment and recidivism (criminal and psychi-
atric) given that they increase the potential for the presence of
criminal attitudes and thought patterns in PMI, even if they are not
currently engaging in criminal behavior.

Carr and colleagues (2009) examined criminal thinking styles in
a sample of civil psychiatric patients and compared the results to
findings from a previously published study using offenders with-
out mental illness. Results indicated that the civil psychiatric
patients scored significantly higher on five of eight criminal think-
ing style scales. Morgan and colleagues (2010) examined criminal
thinking and psychiatric symptomatology in a sample of 416
incarcerated PMI. It was found that incarcerated PMI exhibited
criminal thinking patterns similar to those of incarcerated offend-
ers without mental illness. Additionally, the psychiatric symptom-
atology of the incarcerated PMI was similar to that of inpatient
psychiatric samples. These comparisons were made with preva-
lence rates known from other published samples of offenders
without mental illness (criminal thinking comparison) and nonof-
fender psychiatric patients (psychiatric symptomatology compari-
son). Furthermore, a recent study conducted with 4,204 incarcer-
ated male and female participants found results consistent with
Carr and colleagues (2009) and Morgan et al. (2010) such that
incarcerated PMI evidenced similar criminal thinking styles when
compared with those without mental illness (Wolff, Morgan, Shi,
Fisher, & Huening, 2011). Additionally, those with severe mental
illness (i.e., schizophrenia or bipolar disorder) displayed higher
levels of criminal thinking than those without mental illness and
those with less severe mental illness (i.e., depression, posttrau-
matic stress disorder, and anxiety; Wolff et al., 2011). Although
these three studies provided valuable information for understand-
ing PMI that are and are not CJ involved, significant research
design and methodological problems limited conclusive interpre-
tations. Specifically, Carr and colleagues (2009) and Morgan and
colleagues (2010) lacked a direct comparison group, and Wolff et
al. (2011) was limited in that there was no mental health sample
that was not CJ involved as a control. The proposed study aims to
extend these prior studies by examining criminal thinking with
PMI who are and are not CJ involved and provide a direct com-
parison group for Morgan et al. (2010).

Results from Morgan et al. (2010) suggested that PMI who are
CJ involved may have different psychiatric needs and features
when compared with PMI who are not CJ involved. Furthermore,
general criminal thinking has been shown to partially mediate the
relationship between mental illness and institutional violence for
incarcerated PMI (Walters, 2011), suggesting that the behavior of
PMI who act violently should be considered a product of more
than mental illness. It appears that PMI who are CJ involved are
not merely criminals because of their mental illness but are “crim-
inals who happen to be mentally ill” (Morgan et al., 2010). This
assertion has important implications for PMI who are CJ involved,
but the applicability of these results to PMI who are not CJ
involved has yet to be empirically examined. Thus, the exploration
of criminal thinking in PMI is warranted. If criminal thought
patterns are found within PMI, or a subset of PMI, who are not CJ
involved, what effects do such dispositions have on other aspects
of functioning (e.g., mental health functioning)? To expand on
Morgan et al. (2010), criminal thinking and psychiatric symptom-
atology data from PMI admitted to a short-term psychiatric facility
were gathered to examine potential differences between this group
and incarcerated PMI. Because mental illness and criminal pro-
pensities are conceptualized as comorbid disorders (Morgan et al.,
2010; Wolff et al., 2011), the presentation and effects of such
comorbidity may manifest differently in PMI who are not CJ

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176 GROSS AND MORGAN

involved. Additionally, the data collected from PMI who are not
CJ involved will allow for the examination of criminal thinking as
a risk factor in predicting the number of psychiatric hospitaliza-
tions and relapse.

The purpose of this study was to further examine differences
and similarities in psychiatric symptoms and criminal thinking
between PMI who are incarcerated and psychiatric inpatients. The
aim of the proposed study was to identify distinguishing features
of PMI who are and are not CJ involved. It was hypothesized that
all three groups would evidence similar overall levels of psychi-
atric symptomatology and produce similar symptom profiles. Such
results would coincide with the results from Morgan et al. (2010).
It was hypothesized that PMI admitted to the short-term psychi-
atric hospital without a history of CJ involvement would evidence
less criminal thinking, as measured by the Psychological Inventory
of Criminal Thinking Styles (PICTS) and the Criminal Sentiments
Scale–Modified (CSS-M), than the PMI who were incarcerated or
admitted to the short-term psychiatric facility with a history of CJ
involvement. Lastly, it was expected that criminal thinking would
be positively correlated with psychiatric hospitalizations such that
those evidencing higher levels of criminal thinking would also
have a greater number of lifetime psychiatric hospitalizations.

Methods

The following method section is a replication of that found in
Morgan et al. (2010). The procedure and all measures used,
with the exception of a modified demographic form, are the same
as those used in Morgan et al. (2010). This replication was nec-
essary to allow for a direct comparison between the PMI sample
admitted to a short-term psychiatric hospital in this study with the
incarcerated PMI sample in Morgan et al. (2010).

Participants

Participants consisted of 94 short-term psychiatric male (n � 53,
56.4%) and female (n � 41, 43.6%) patients from an acute
psychiatric hospital located in West Texas. Participants were at
least 18 years old (M � 38.55, SD � 11.35) and were admitted to
the facility for at least 5 days (M � 8.24, SD � 7.02). We
incorporated a 5-day minimum for the length of time admitted to
the facility to increase the likelihood that the participant would be
experiencing chronic and enduring psychiatric problems and not
transient, crisis-type issues. Over half of the sample (n � 51,
54.3%) had been convicted of a crime in the past; for that reason,
the inpatient sample was split into two groups (i.e., with and
without past CJ involvement) for the completion of data analysis.
Approximately 80% (n � 76) of the inpatients had been admitted
to a psychiatric facility before their admission at the time of
participation.

Additionally, the Structured Clinical Interview for DSM–IV
Axis I Disorders (SCID-I) was administered by a doctoral-level
counseling psychology student (who received supervision and
training from a licensed psychologist) to approximately 20% of the
sample to assess the reliability of the participant’s diagnosis as
reported by the institutional file. It appears that the institutional file
provided a reliable diagnosis for the participants because there was
a 77.8% agreement rate between the diagnosis found in the insti-
tutional file and the diagnosis determined by the administration of

the SCID-I. On the basis of the diagnoses recorded for each
participant from institutional records, the inpatient sample had a
primary Axis I diagnosis of bipolar disorders (n � 37, 39.4%)
followed by major depressive disorder (n � 24, 25.5%), schizo-
phrenia (n � 11, 11.7%), schizoaffective disorder (n � 9, 9.6%),
other mood disorders (e.g., drug-induced, NOS; n � 8, 8.5%),
adjustment disorder (n � 2, 2.1%), psychosis NOS (n � 1. 1.1%),
acute stress disorder (n � 1. 1.1%), and Asperger’s syndrome (n �
1. 1.1%).

Participants were also drawn from those who participated in the
Morgan et al. (2010) study. This sample was composed of 94
incarcerated male (n � 53, 56.4%) and female (n � 41, 43.6%)
adults with mental illness. Participants were selected based on their
match with participants in our sample on sex, Axis I diagnosis,
age, ethnicity, years of formal education, and relationship status
when possible. Analyses revealed no significant differences among
significant demographic characteristics of Axis I diagnosis, age,
race, and relationship status. However, the two groups differed
significantly with regards to the number of years of formal edu-
cation completed, t � 2.81, p � .005, with the inpatient mental
health sample having completed more years of formal education
(M � 12.46, SD � 2.13) than the incarcerated mental health
sample (M � 11.52, SD � 2.44).

Demographic characteristics of both groups along with the
results of the between-group analyses of the demographics of each
sample are shown in Table 1.

Materials

A written informed consent form was used to inform potential
participants of the purpose of the study, the potential risks, confi-
dentiality, and their rights as human subjects. A self-report demo-
graphic form was used to gather information regarding age, eth-
nicity, relationship status, time hospitalized, CJ involvement,
psychiatric history (e.g., treatment, number of hospitalizations),
mental health diagnoses, employment status, and public assistance
received.

The PICTS (Walters, 1995), a self-report measure composed of
80 items and designed to assess thought patterns associated with
criminal behavior (Walters, 2006), was used. For example, the
PICTS contains items such as “The more I got away with crime the
more I thought there was no way the police or authorities would
ever catch up with me”; “The way I look at it, I’ve paid my dues
and am therefore justified in taking what I want”; and “I have
justified selling drugs, burglarizing homes, or robbing banks by
telling myself that if I didn’t do it someone else would.” Responses
to the items on the PICTS are provided using a 4-point Likert scale
(1 � disagree, 4 � strongly agree; Walters, 2006). The PICTS
produces two content scales (i.e., Current Criminal Thinking and
Historical Criminal Thinking), two composite scales (i.e., Proac-
tive Criminal Thinking and Reactive Criminal Thinking), eight
thinking style scales (i.e., Mollification, Cutoff, Entitlement,
Power Orientation, Sentimentality, Superoptimism, Cognitive In-
dolence, and Discontinuity), and five Factor and Special Scales
(i.e., Problem Avoidance, Interpersonal Hostility, Self-Assertion,
Denial of Harm, and Fear of Change; Walters, 2006). There are no
cutoff scores distinguishing the presence or absence of each of the
eight criminal thinking scales, but guidelines are provided for
interpreting the criminal thinking style T-scores as low (�40),

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177UNDERSTANDING PERSONS WITH MENTAL ILLNESS

average (�40, �60), high (�60, �70), and very high (�70;
Walters, 2006). The PICTS has acceptable validity when compared
with other means of assessing criminality (i.e., criminal history such
as arrests, diversity of offenses, age of first offense, and psychopathy)
(Walters, 2006; Walters & Schlauch, 2008). The PICTS has demon-
strated moderate to high levels of internal consistency and test-retest
reliability in offender samples. The internal consistency for the sub-
scales ranged from .54 to .88 for male and female offenders (Walters,
1995; Walters, Elliott, & Miscoll, 1998). Test-retest reliability was
.68 –.85 after 2 weeks and .57–.72 after 12 weeks (Walters, 1995;
Walters et al., 1998). The PICTS has not been normed on a clinical
sample. The internal consistency for the PICTS in this study was high,
yielding a Cronbach’s � of .95.

The CSS-M (Simourd, 1997), a self-report measure composed
of 41 items, designed to assess “attitudes, values, and beliefs
related to criminal behavior” (Wormith & Andrews, 1984), was
used. The CSS-M measures the content of criminal thoughts
whereas the PICTS measures the process of criminal thinking
(Simourd & Olver, 2002). For example, the CSS-M contains items
such as “The police are as crooked as the people they arrest,”
“Pretty well all laws deserve our respect,” and “You cannot get
justice in court.” Responses to the items on the CSS-M are pro-
vided using a 3-point Likert-type scale (Simourd, 1997; Simourd
& Olver, 2002). The CSS-M yields a total score and five subscale
scores (attitude toward the law [Law], attitude toward the court
[Court], attitude toward the police [Police], tolerance for law
violations [TLV], and identification with criminal others [ICO];
Simourd, 1997; Simourd & Olver, 2002; Simourd & van de Ven,
1999). The Law, Court, and Police subscales are then combined to
form the Law-Court-Police (LCP) subscale that assesses the level
of respect an individual has for the criminal and legal system

(Simourd & Olver, 2002). Additionally, the TLV subscale assesses
the degree to which an individual justifies their criminal behavior,
and the ICO subscale assesses how the individual perceives the
criminal behavior of others (Simourd & Oliver, 2002). Scores
greater than 19 indicate clinical significance whereas scores of 30
or higher are considered “high” (Simourd, 1997). The CSS-M has
not been normed on a clinical sample; however, it has been shown
to be a valid and reliable measure with offender populations
(Andrews, Wormith, & Kiessling, 1985; Roy & Wormith, 1985;
Wormith & Andrews, 1984). Internal consistency ranged from .73
to .91 (Simourd, 1997; Simourd & Olver, 2002). Additionally,
when compared with other criminal risk assessment measures (i.e.,
Hare Psychopathy Checklist–Revised and Level of Service
Inventory–Revised), the convergent validity ranged from .25 to .37
(Simourd, 1997). The internal consistency for the CSS-M in this
study was high, yielding a Cronbach’s � of .88.

The Millon Clinical Multiaxial Inventory–Third Edition
(MCMI-III; Millon, 1994) was used. MCMI-III is a self-report
measure composed of 175 true/false items, providing an integrated
understanding of a respondent’s personality and clinical syn-
dromes (Millon, 1994). The MCMI-III yields 14 Personality Dis-
order Scales that coincide with Diagnostic and Statistical Manual–
4th Edition (DSM–IV; American Psychiatric Association, 1994)
Axis II disorders, and there are 10 Clinical Syndrome Scales that
coincide with DSM–IV Axis I disorders (Millon, 1994). A Correc-
tion Scale detects careless or random responding, and the Modi-
fying Indices and the Validity Index assess validity and response
style (Millon, 1994). MCMI-III is strongly correlated with the
MCMI-II, with correlations ranging from .59 to .88 (Millon, Davis,
& Millon, 1997). The MCMI-III has been designed for use with
clinical populations and has been normed on a clinical population.

Table 1
Between-Sample Comparison of Demographic Results

Psychiatric inpatient
sample

Morgan et al., (2010)
sample

�2 pn % n %

Ethnicity 10.16 0.07
Caucasian 54 58.1 51 54.3
Hispanic 20 21.5 13 13.9
African American 8 8.6 22 23.4
Asian 1 1.1 0 0.0
American Indian 1 1.1 0 0.0
Other 9 9.7 8 8.5

Diagnosis 0.57 0.90
Schizophrenia/Other Psychotic Disorder 21 22.3 20 21.3
Bipolar I and II 38 40.4 38 40.4
MDD/Other Mood Disorder 29 30.9 32 34.0
Other Mental Health Disorder 6 6.4 4 4.3

Relationship Status 8.15 0.15
Single 34 42.5 43 45.7
Partnered/Common Law 5 6.3 4 4.3
Divorced 21 26.3 23 24.5
Separated 8 10.0 9 9.6
Married 7 8.8 15 15.9
Widowed 5 6.3 0 0.0

M SD M SD t p

Age 38.55 11.35 36.83 10.61 1.08 0.28
Education (Years) 12.46 2.13 11.52 2.443 2.81 0.005

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178 GROSS AND MORGAN

Validity of the MCMI-III with relation to the diagnostic determi-
nation from clinicians was low to moderate, and the correlations
ranged from .07 to .37 (Millon, 1994). Internal consistency reli-
ability ranged from .66 to .90 whereas test–retest reliability ranged
from .82 to .86 at 5–14 days from the original test date (Millon,
1994). The internal consistency for the MCMI-II in this study was
high, yielding a Cronbach’s � of .92.

SCID-I (First, Spitzer, Gibbon, & Williams, 1997), a semistruc-
tured interview used to assist in diagnosing DSM–IV Axis I dis-
orders that is composed of six modules that assess mood episodes,
mood disorders, psychotic symptoms, psychotic disorders, sub-
stance abuse disorders, and anxiety and other disorders (First et al.,
1997), was used in this study. During administration, various
questions regarding mental health symptoms are posed to the
examinee, and on the basis of their response the examiner deter-
mines the presence or absence of the symptom (First et al., 1997).
The positive and negative ratings of symptoms within a diagnostic
category are combined to determine if DSM–IV diagnostic criteria
for the disorder have been satisfied (First et al., 1997). In terms of
Kappa ratings, interrater reliability for the SCID-I ranges from .57
to 1.0, and test–retest reliability over a 7- to 10-day period ranges
from .35 to .78 (Zanarini, et al., 2000). SCID-I has been developed
as a means of improving the diagnostic accuracy of clinicians;
thus, most comparisons with unstructured interviews or the best
estimate diagnosis procedure have demonstrated superior validity
for the SCID-I (Basco et al., 2000).

Procedure

Individuals admitted to the psychiatric hospital were identified
and recruited for participation in this study using a bed locator
sheet (an updated record that identified the names, admission
dates, cautionary ratings, and room assignments for all current
inpatients). Consumers were considered eligible for participation if
they had been admitted to the facility for a minimum of 5 days,
were able to communicate in English, were not admitted to the
facility after being adjudicated not competent to stand trial and
not restorable, were not receiving competency restoration ser-
vices, and were at least 18 years of age. Participants were
selected in the order of their presentation on the bed locator
sheets such that the first available consumer (e.g., met inclusion
criteria, had not already participated or refused participation)
was contacted by a research assistant for recruitment into the
study presented here. Research assistants approached the iden-
tified consumers either in the day room of the facility or in their
assigned rooms and asked them to meet with a research assis-
tant regarding participation.

During this meeting, consumers were verbally informed about
the purpose of the study, the tasks they would be asked to com-
plete, and of their rights as a research participant (i.e., confiden-
tiality, right to withdraw) should they decide to participate. Addi-
tionally, risks and benefits of participation were also verbally
explained. Consumers willing to participate were provided with a
written informed …

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