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External Validity of the Personality Assessment Inventory (PAI) in a Clinical
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External Validity of the Personality Assessment
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a
a
a
a
Jenelle Slavin-Mulford , Samuel Justin Sinclair , Michelle Stein , Johanna Malone ,
b
Iruma Bello & Mark A. Blais
a
a
Psychological Evaluation and Research Laboratory (PEaRL), Massachusetts General Hospital
and Harvard Medical School
b
Department of Psychiatry, New York University, Langone Medical Center and School of
Medicine
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A. Blais (2012): External Validity of the Personality Assessment Inventory (PAI) in a Clinical Sample, Journal of Personality
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DOI: 10.1080/00223891.2012.681817
External Validity of the Personality Assessment Inventory (PAI)
in a Clinical Sample
JENELLE SLAVIN-MULFORD,1 SAMUEL JUSTIN SINCLAIR,1 MICHELLE STEIN,1 JOHANNA MALONE,1 IRUMA BELLO,2 AND
MARK A. BLAIS1
Downloaded by [Augusta State University], [Jenelle Slavin-Mulford] at 08:16 14 February 2013
1
Psychological Evaluation and Research Laboratory (PEaRL), Massachusetts General Hospital and Harvard Medical School
2
Department of Psychiatry, New York University, Langone Medical Center and School of Medicine
This study contributes to the ongoing construct validation of the Personality Assessment Inventory (PAI; Morey, 1991, 2007) by identifying
nontest life-event correlates of the PAI full scales and subscales in a sample of psychiatric patients. The life-event data used in this study included
education, marital status, and employment, as well as a history of suicide attempts, psychiatric hospitalizations, trauma, medical problems,
hallucinations, paranoid ideation, drug abuse, alcohol abuse, and arrest. Correlations were calculated to explore the convergent and discriminant
validity of the PAI scales relative to the life-event data. The results showed that the majority of the PAI scales (11 of 13) had meaningful correlations
with at least 1 life-event variable. The PAI BOR scale had the greatest number of correlations and was associated with 8 life-event variables. In
contrast, the PAI ANX and MAN scales had no correlations above a predetermined threshold (r ≥.21). These findings add to the growing body of
empirical correlates of the PAI and generally provide support for the construct validity of the PAI scales.
The Personality Assessment Inventory (PAI; Morey, 1991) is
a modern broadband self-report measure of psychopathology.
The test contains 22 nonoverlapping scales that measure validity, response style, and a wide range of psychological constructs.1 The PAI was developed through the construct validation framework (e.g., Loevinger, 1957). This approach to test
development emphasizes measuring constructs that have both
substantial theoretical articulation and empirical support. In addition, the PAI uses a 4-point item response format along with
a low reading level to achieve an acceptable balance between
user burden and range of scale measurement (Blais, Baity, &
Hopwood, 2010; Morey, 1996). These practical features, combined with the focus on construct validation, resulted in the PAI
being rapidly adopted across diverse settings and populations including mental health (Morey, 2000), forensic (Edens & Ruiz,
2005), and personnel selection (Roberts, Thompson, & Johnson,
2000).
Since the introduction of the PAI, the body of empirical
evidence supporting its validity and clinical utility has shown
steady and consistent growth (Blais et al., 2010; Morey, 1996).
For example, there is a substantial body of research exploring
the PAI’s ability to detect faking or feigning among a variety
of populations (Baity, Siefert, Chambers, & Blais, 2007; Blanchard, McGrath, Pogge, & Khadivi, 2003; Eakin, Weathers,
Benson, Anderson, & Funderburk, 2006; Rogers, Sewell,
Cruise, Wang, & Ustad, 1998; Wang et al., 1997). There is also
research exploring the PAI’s concurrent validity and diagnostic
utility. Findings from these studies have been encouraging and,
in general, suggest that the PAI full scales and subscales have
Received September 2, 2011; Revised February 15, 2012.
Address correspondence to Jenelle Slavin-Mulford, Massachusetts General
Hospital and Harvard Medical School, Psychological Evaluation and Research
Laboratory (PEaRL), One Bowdoin Square, 7th Floor, Boston, MA 02114;
Email: jenelle.slavin@gmail.com
1Throughout this article, abbreviations for the scales are used. Please see
Appendix for a listing of all scale abbreviations used in this article.
diagnostic utility in a variety of populations, including college
students (McDevitt-Murphy, Weathers, Flood, Eakin, & Benson,
2007), inmates (Edens & Ruiz, 2008), psychiatric outpatients
(Jacobo, Blais, Baity, & Harley, 2007; Stein, Pinsker-Aspen, &
Hilsenroth, 2007), psychiatric inpatients (Klonsky, 2004), and
medical patients (Corsica, Azarbad, McGill, Wool, & Hood,
2010; Wagner, Wymer, Topping, & Pritchard, 2005).
Other research has examined the convergent and discriminant
validity of the PAI scales relative to other measures (Bradley,
Hilsenroth, Guarnaccia, & Westen, 2007; Douglas, Guy, Edens,
Boer, & Hamilton, 2007; Morey, 1991; Stein et al., 2007;
Walters & Geyer, 2005; Wang et al., 1997). These comparisons
have been made both with other self-report tests (e.g., Walters
& Geyer, 2005; Wang et al., 1997) and with clinician-rated
measures (e.g., Bradley et al., 2007; Stein et al., 2007). For
example, the PAI ANT subscales have been found to positively
correlate with the self-reported Psychological Inventory of
Criminal Thinking Styles (Walters & Geyer, 2005) as well
as with the clinician-rated SWAP–200 Antisocial subscale
(Bradley et al., 2007) and the clinician-rated Psychopathology
Checklist Revised (Douglas et al., 2007).
Although the growth in PAI research is impressive, the construct validation process requires instruments to be studied
broadly using data from multiple sources including life-space
or life-event data (Block & Block, 1980). Life-event data is objective information associated with major life outcomes such
as education level, marital status, employment, health status,
and legal history. This information can be obtained fairly objectively from an individual’s life history or from formal historical
records (John & Soto, 2007). At present, the PAI life-event research base seems limited in terms of the scales and samples
studied (e.g., Cherepon & Prinzhorn, 1994). In fact, the majority of these studies have used forensic or substance abuse
samples (e.g., Boccaccini, Murrie, Hawes, Simpler, & Johnson,
2010; Caillouet, Boccaccini, Davis, & Rostow, 2007; Patry, Magaletta, Diamond, & Weinman, 2011; Salekin, 2008; Walters,
Duncan, & Geyer, 2003).
593
SLAVIN-MULFORD ET AL.
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594
For example, the PAI AGG scale has been shown to predict subsequent disciplinary action (Walters et al., 2003) and
recidivism (Boccaccini et al., 2010) in correctional samples. In
addition, Wang and colleagues (1997) found that the PAI SUI
and Suicide Potential Index (SPI) were positively related (.31
and .20, respectively) with suicidal gestures in a correctional
psychiatric inpatient sample. Hopwood, Baker, and Morey
(2008) found that for inpatient substance abusers, AGG was
related to assault history, SUI and SPI positively correlated with
a history of suicide attempts, ANT predicted rule infractions,
and Treatment Process Index (TPI) predicted treatment completion. Finally, Ruiz and Edens (2008) organized the scales into
internalizing and externalizing factors. They found that in a corrections sample, the internalizing factor was associated with a
history of physical health problems and diagnoses of an internalizing disorder, but it was unrelated or negatively related to
disinhibited behaviors (e.g., institutional misconduct, history of
driving under the influence). In contrast, the externalizing factor
was correlated with disinhibited behaviors, but it was unrelated
or negatively related to a history of health problems or an internalizing disorder. This work provides important information
about the construct validity of the PAI, but its generalizability
is limited to specific samples and PAI scales.
This study sought to expand this line of research by examining the convergent and discriminant validity of 13 PAI scales
(all the clinical scales and two treatment consideration scales)
with a wide range of life-space data using a large, diagnostically diverse psychiatric sample. The construct validity of these
PAI scales should be evident in their pattern of convergent and
discriminant correlations with the life-event variables. For example, the externalizing PAI scales ALC, DRG, and ANT (Hopwood & Moser, 2011; Ruiz & Edens, 2008) should be strongly
correlated with life-event variables associated with externalizing behaviors (e.g., arrest, drug abuse). Similarly, strong correlations would be expected for the PAI scales measuring realityimpairing conditions (PAR and SCZ) and life events related to
severe psychopathology (a history of paranoid ideation or hallucinations). The goal of this study is to explore such relationships
by examining correlations of the 11 PAI clinical scales, as well
as the SUI and AGG treatment scales, with a wide range of
life-event variables.
METHOD
Participants
A pool of 451 potential participants (301 outpatients and 150
inpatients) was identified from a record review of patients who
completed the PAI as part of a clinical assessment at a large
teaching hospital in the Northeast within a 2-year period. After evaluating the PAI profiles, 48 potential participants were
eliminated due to having invalid profiles based on Morey’s recommended cutoff scores (Morey, 1991, 2007). The remaining
403 participants (270 outpatients and 133 inpatients) were included in the study. The sample was 55% (221) male with a
mean age of 41.95 years (SD = 14.82, range = 16–83). The
racial composition was reported as 89% White, 4% Asian, 5%
Hispanic, and 2% African American. The vast majority of participants had completed high school (91%); however, approximately 53% were unemployed. Moreover, approximately 53%
reported at least one prior psychiatric hospitalization.
All participants were referred by a mental health professional
for a psychological evaluation. These evaluations included measures of personality, psychopathology, and neuropsychological
functioning. As part of the evaluation process, relevant clinical and historical information was obtained from the referring
professional and the medical record. The diagnoses at the time
of evaluation included depressive disorders (61%), anxiety disorders (45%), bipolar disorder (18%), substance abuse (14%),
cognitive disorders (11%), and psychotic disorders (7%). In addition, the majority of participants (67%) had some form of
medical comorbidity (either an active or recent medical illness
listed among the patient’s problem by the referring clinician).
Our assessment clinic maintains a data repository approved by
the institutional review board containing all assessment data
and extensive demographic information for all evaluations conducted. This study used PAI and life-event data from this data
repository.
Measures
The PAI (Morey, 1991, 2007) is a self-report multiscale personality measure used to assess psychopathology, substance
abuse, treatment-related issues, and interpersonal style. It contains 344 items making up 22 nonoverlapping scales: 4 validity
scales, 11 clinical scales, 5 treatment scales, and 2 interpersonal
scales. Norms for the PAI were developed from three separate
samples: a census-matched sample (N = 1,000), a college sample (N = 1,051), and a clinical sample (N = 1,246). In this
study, we examined the following PAI full scales: SOM, ANX,
ARD, DEP, MAN, PAR, SCZ, BOR, ANT, ALC, DRG, SUI,
and AGG. Ten of these PAI scales also contain subscales (ALC,
DRG, and SUI do not have subscales) that were also explored in
the study. Previous research by our group has shown that the PAI
maintains adequate psychometric properties when administered
to clinical samples (Siefert, Sinclair, Kehl-Fie, & Blais, 2009).
Procedures
All patients completed the PAI as part of a clinical evaluation.
The assessments were conducted by licensed psychologists or by
postdoctoral fellows and predoctoral psychology interns under
supervision. All assessment evaluations began with a semistructured clinical interview designed by one of the authors (Mark A.
Blais). The interview aimed to systematically capture clinically
relevant information regarding a patient’s current functioning
along with his or her psychiatric, developmental, educational,
relational, occupational, medical, and legal history. When available, medical records were also reviewed as part of the clinical
information-gathering process. The PAI was administered after
the interview along with other measures (the other measures varied based on the needs of the individual assessment). Given that
the PAI was always administered after the interview, interviewers were blind to the PAI results when conducting the interview.
After each assessment, approximately 45 nontest variables (obtained from the semistructured interview or medical record) and
all psychological and neuropsychological test scores were entered into the data repository. These data were entered either by
the evaluating clinician or a research assistant.
For this study, 12 life-event variables were selected as external validity targets for the PAI scales. They included education
level, marital status, employment status, history of suicide attempt, past psychiatric hospitalization, history of physical or
sexual trauma, current medical problems, history of hallucinations, paranoid ideation, drug abuse, alcohol abuse, and arrests.
These variables were selected because they represented a wide
range of meaningful life events, were relatively complete in the
EXTERNAL CORRELATES
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database, and were judged to have a high degree of objectivity.
Together they formed four broad categories including positive
life outcomes (education, employment, and marriage), markers of psychiatric severity (hallucinations, paranoid ideation,
trauma, suicide attempts, and hospitalization), physical health
status (medical problems), and negative life outcomes (alcohol
abuse, drug abuse, and arrest).
Retest Reliability Analyses
A review of the database identified 20 patients who had been
evaluated twice by different clinicians within a 1-year period
(mean evaluation–reevaluation interval was 6.4 months). For the
majority of cases (18 of 20), this reflects an inpatient evaluation
followed by an outpatient evaluation. Given that the same data
fields from the semistructured interview are coded for inpatient
and outpatient evaluations, these 20 cases allowed us to assess
the reliability of the life-event variables. Kappa coefficients were
computed to determine retest reliability for the dichotomously
coded variables. The kappa coefficients ranged from .61 (past
psychiatric hospitalization) to .85 (suicide attempt). Education
level was coded as four categories (<12 years, 12 years, 13–15
years, and ≥16 years) and the reliability was computed as a
Spearman rank-order correlation (rs = .85). See Table 1 for a
complete listing of the kappa coefficients.
Data Analyses
Table 2 presents the means and standard deviations for the
13 PAI scales. Bivariate correlations were then computed to explore the associations among the PAI scales and life-event data.
First, we ran the correlations for the PAI full scales and the 12
life-event variables. Next, we ran the correlations for the PAI
subscales (31 in total) and the life-event variables. Consistent
with their construct validation development, the PAI scales and
subscales were used as continuous variables (i.e., they were not
dichotomized) in all analyses. To ensure clinically meaningful
results and to partially control for family-wise error, a significance level of r ≥.21 (absolute value) was set for interpretation. With a sample of 330 (the smallest N for the correlations
presented), a correlation ≥.21 is significant at p <.0002. This
corrects the alpha level (p = .05) for 100 correlations (.05/100
= .0005). In addition, the 95% CI for r = .21 is .10 to .32,
which correspond to an effect size range in the Cohen’s d metric
of .20 and .67. The use of r ≥.21 as a threshold for clinical
significance is consistent with previous research exploring the
empirical correlates of multiscaled psychological instruments
in clinical samples (Arbisi, Sellbom, & Ben-Porath, 2008).
RESULTS
Table 3 presents the correlations for the 13 PAI full scales
and the 12 criterion variables. Overall, 11 of the 13 PAI scales
were significantly associated with one or more of the criterion
variables. Only the ANX and MAN scales had no correlations
that reached the threshold of .21. The number of meaningful
correlations ranged from eight for the BOR scale to two for
SOM and DEP.
Table 3 reveals that most PAI scales have multiple meaningful
associations to the life-event variables. Four scales (ANT, PAR,
SUI, and ARD) were meaningfully associated with five lifeevent variables, and two scales (DRG and SCZ) were associated
with four criterion variables each. PAI scales AGG and ALC
595
TABLE 1.—Retest reliability for the life data codes.
Life Dataa
Manner of Coding and
Frequencies of Each Variable
0 = Less than 12 years education
(n = 36)
1 = 12 years of education (n = 94)
2 = 13–15 years education (n =
88)
3 = 16 or more years education (n
= 181)
Relationship
0 = Not currently married (n =
N = 383
260)
1 = Currently married (n = 123)
Work
0 = Unemployed (n = 207)
N = 393
1 = Employed (full or part time)
or retired (n = 186)
Suicide attempt 0 = No history of a suicide
N = 380
attempt (n = 268)
1 = A history of a suicide attempt
(n = 112)
Psychiatric
0 = No history of psychiatric
hospitalizahospitalization (n = 174)
tion
N = 370
1 = History of psychiatric
hospitalization (n = 196)
Trauma
0 = No history of physical or
N = 333
sexual abuse (n = 246)
1 = History of physical and/or
sexual abuse (n = 87)
Medical
0 = No history of medical
problems
problems (n = 127)
N = 381
1 = History of medical problems
(n = 254)
Hallucinations 0 = No history of auditory or
N = 374
visual hallucinations (n = 322)
1 = History of auditory and/or
visual hallucinations (n = 52)
Paranoid
0 = No history of paranoid
ideation
ideation (n = 315)
N = 365
1 = History of paranoid ideation
(n = 50)
Drug abuse
0 = No history of drug abuse (n =
N = 378
243)
1 = History of drug abuse (n =
135)
Alcohol abuse 0 = No history of alcohol abuse (n
N = 381
= 219)
1 = History of alcohol abuse (n =
162)
Arrest
0 = No history of arrest (n = 277)
N = 330
1 = History of arrest (n = 53)
Education
N = 399
N for
Reliability
Statisticb
Kappa
19
.85c
19
.75
19
.77
20
.85
19
.61
16
.65
20
.73
19
.77
19
.75
19
.82
19
.77
16
.63
a
The Ns for the life data indicate the number of participants that had available data. b20
cases were rerated, however, the Ns vary slightly due to missing data. cThe reliability for
education level is presented as a Spearman rank-order correlation.
were positively correlated with three criterion variables, and
DEP and SOM were correlated with two life event variables.
Data present in the columns of Table 3 (the life-event variables) provide evidence of convergent validity for nine of the
PAI full scales. For example, the DRG scale had its strongest
association with a history of drug abuse, ALC with a history of
alcohol abuse, SOM with medical illnesses, SUI with a history
of suicide attempts, SCZ with a history of hallucinations, ARD
with a history of trauma, and DEP with history of psychiatric
hospitalizations. Similarly, the PAI ANT scale had its second
highest association with a history of arrest, and the AGG scale
SLAVIN-MULFORD ET AL.
596
TABLE 2.—Means and standard deviations for the clinical and treatment scales.
SOM
ANX
ARD
Downloaded by [Augusta State University], [Jenelle Slavin-Mulford] at 08:16 14 February 2013
DEP
MAN
PAR
SCZ
BOR
ANT
ALC
DRG
AGG
SUI
Mean clinical
elevation
Setting
M
SD
N
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
Outpatient
Inpatient
Total
61.35
62.47
61.72
64.42
65.15
64.66
59.75
60.47
59.99
68.71
72.98
70.12
49.82
49.16
49.60
54.75
56.50
55.33
59.60
58.85
59.35
61.71
62.21
61.87
52.81
53.05
52.89
54.53
54.32
54.46
58.01
56.75
57.60
51.03
50.74
50.94
60.64
70.89
64.03
58.61
58.94
58.72
13.00
13.15
13.04
13.53
14.19
13.74
14.20
13.78
14.05
15.84
17.09
16.36
10.99
10.73
10.89
12.35
13.56
12.77
12.86
14.80
13.52
13.15
12.89
13.05
12.20
12.34
12.23
13.57
16.01
14.40
16.63
15.22
16.17
12.75
12.16
12.54
18.07
21.53
19.85
8.99
9.17
9.04
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
270
133
403
showed equal associations with a history of drug abuse and a
history of arrests.
Table 4 presents the correlations between the PAI subscales
and the 12 criterion variables. The correlations in Table 4 provide evidence of the unique construct variance of the PAI subscales. For example, of the three SOM subscales, SOM-H had
the highest correlation with current medical problems. In contrast, SOM-C had the smallest correlation with medical problems, and was also correlated with hallucinations. Likewise,
ARD-T had the highest correlation with a history of trauma of
any PAI subscale. The SCZ subscales also showed a differential
pattern of correlations. SCZ-P was the only SCZ subscale to
correlate with a history of hallucinations and paranoid ideation.
Conversely, SCZ-S was not significantly correlated with any
criterion variable and SCZ-T had its only significant correlation
with drug abuse. Finally, among the ANT subscales, ANT-A
had the highest correlations with drug abuse, arrest, and alcohol
abuse. Likewise, AGG-P had higher positive correlations with a
history of drug abuse and arrest than either AGG-A or AGG-V.
AGG-P was also the only AGG subscale to have a significant
negative correlation with educational level.
DISCUSSION
This study explored the relationship of PAI scales to objective life-event data. Our findings revealed a pattern of life-event
correlations that seem to support the construct validity of the
majority of PAI scales used in this study. Of the 13 PAI scales
investigated, 11 demonstrated significant and meaningful correlations to multiple life-event variables. Only the PAI MAN
and ANX scales failed to show meaningful correlations (≥.21)
with our life-event variables. Moreover, nine of the PAI scales
had their highest or second highest correlation to life events that
appear highly related to the scale’s underlying construct. For example, a history of arrest had its highest correlation with ANT, a
history of alcohol abuse had its highest correlation with ALC, a
history of drug abuse with DRG, a history of hallucinations with
SCZ, a history of physical or sexual trauma with ARD, a history of suicide attempt with SUI, and current medical problems
with SOM. Furthermore, nine of the PAI scales (SOM, ARD,
TABLE 3.—Empirical correlates of the clinical scales and treatment scales.
SOM
ANX
ARD
DEP
SUI
MAN
PAR
SCZ
BOR
ANT
ALC
DRG
AGG
Ed
Rln
Work
SA
Hosp
Trauma
Med
Hallu
PI
Drug
Alc
Arrest
–.22
–.17
–.22
–.13
–.04
–.04
–.26
–.25
–.22
–.21
–.06
–.30
–.21
–.03
–.18
–.15
–.14
–.22
–.13
–.21
–.11
–.26
–.29
–.04
–.12
–.10
–.19
–.12
–.23
–.15
–.25
–.06
–.13
–.13
–.18
–.14
.01
–.17
–.12
.13
.18
.18
.20
.33
–.08
.12
.04
.22
.07
.14
.08
.07
.20
.20
.21
.26
.29
–.09
.14
.14
.21
.06
.11
.12
.05
.12
.17
.29
.14
.14
.03
.16
.13
.24
.04
.09
.08
.15
.37
.03
.03
.09
.00
–.08
–.02
.02
.01
–.09
–.07
.06
.01
.16
.08
.12
.06
.11
.15
.16
.28
.10
.09
–.04
–.01
.12
.11
.07
.18
.10
.12
.11
.25
.27
.11
.10
.04
.07
.13
.17
.19
.23
.21
.21
.19
.24
.26
.44
.49
.37
.65
.33
.13
.17
.15
.14
.12
.13
.18
.18
.27
.39
.59
.41
.20
.12
.08
.19
.05
.00
.19
.28
.16
.25
.44
.29
.30
.33
Note. Sample sizes vary from 330 to 399 due to missing data. Correlations at or above .21 are shown in bold. Ed = educational level; Rln = relationship status (married); Work =
employed; SA = suicide attempts; Hosp = past psychiatric hospitalizations; Trauma = history of physical or sexual abuse; Med = current medical problems; Hallu = auditory or visual
hallucination; PI = paranoid ideation; Drug = history of drug abuse; Alc = history of alcohol abuse; Arrest = history of arrest.
EXTERNAL CORRELATES
597
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TABLE 4.—Empirical correlates for Personality Assessment Inventory clinical subscales.
SOM-C
SOM-S
SOM-H
ANX-C
ANX-A
ANX-P
ARD-O
ARD-P
ARD-T
DEP-C
DEP-A
DEP-P
MAN-A
MAN-G
MAN-I
PAR-H
PAR-P
PAR-R
SCZ-P
SCZ-S
SCZ-T
BOR-A
BOR-I
BOR-N
BOR-S
ANT-A
ANT-E
ANT-S
AGG-A
AGG-V
AGG-P
Ed
Rln
Work
SA
Hosp
Trauma
Med
Hallu
PI
Drug
Alc
Arrest
–.20
–.16
–.18
–.11
–.13
–.20
–.12
–.18
–.17
–.16
–.06
–.15
–.03
.01
–.06
–.22
–.24
–.19
–.25
–.15
–.17
–.10
–.16
–.27
–.15
–.26
–.15
–.07
–.16
–.14
–.22
–.06
–.02
.00
–.19
–.16
–.14
–.04
–.15
–.16
–.18
–.13
–.04
–.13
–.08
–.10
–.24
–.15
–.16
–.14
–.02
–.11
–.17
–.18
–.27
–.22
–.20
–.29
–.28
–.10
–.08
–.11
–.19
–.14
–.17
–.07
–.13
–.16
–.15
–.13
–.23
–.13
–.11
–.16
–.04
–.01
–.10
–.14
–.17
–.06
–.13
–.12
–.08
–.12
–.14
–.18
–.14
–.18
–.10
–.07
–.11
–.07
–.16
.17
.13
.05
.13
.19
.18
.03
.19
.18
.16
.17
.18
.02
–.16
.01
.12
.03
.14
–.04
.10
.02
.20
.13
.19
.16
.10
.01
.05
.11
.01
.05
.19
.12
.21
.19
.19
.17
.04
.15
.25
.19
.24
.24
.00
–.17
.00
.14
.14
.10
.04
.14
.11
.19
.19
.20
.10
.05
.04
.07
.10
–.01
.05
.19
.09
.05
.10
.19
.18
.14
.15
.32
.12
.09
.17
.12
–.09
.08
.15
.12
.15
.04
.09
.14
.20
.21
.22
.13
.10
–.04
.01
.17
.09
.13
.24
.34
.37
–.03
.04
.08
.02
.00
.03
.02
.03
.19
–.06
–.12
–.02
–.02
–.04
.02
.01
–.01
.04
.01
–.01
.03
–.03
–.04
–.10
–.13
.04
–.03
.00
.21
.06
.13
.03
.08
.12
–.01
.11
.15
.06
.04
.04
.14
.07
.11
.13
.20
.07
.39
.12
.18
.08
.09
.13
.03
.03
.11
.12
.12
.04
.15
.12
.08
.09
.06
.07
.06
.07
.12
.19
.08
.10
.07
.02
.08
.12
.20
.31
.16
.31
.20
.14
.11
.08
.16
.01
.11
.08
.07
.11
.05
.16
.15
.16
.13
.16
.17
.20
.04
.17
.26
.23
.18
.13
.25
.01
.21
.24
.17
.21
.16
.17
.25
.36
.30
.30
.46
.52
.27
.41
.28
.22
.37
.13
.12
.09
.12
.18
.15
–.02
.11
.19
.13
.13
.10
.14
–.01
.16
.22
.11
.14
.11
.13
.15
.25
.17
.18
.26
.39
.28
.29
.18
.13
.19
.11
.06
.09
.03
.07
.11
.09
.06
.22
.03
.05
.06
.14
.09
.17
.23
.23
.26
.15
.10
.12
.22
.12
.24
.22
.47
.25
.35
.29
.17
.38
Note. Sample sizes vary from 330 to 399 due to missing data. Correlations at or above .21 are shown in bold. Ed = educational level; Rln = relationship status (married); Work =
employed; SA = suicide attempts; Hosp = past psychiatric hospitalizations; Trauma = history of physical or sexual abuse; Med = current medical problems; Hallu = auditory or visual
hallucination; PI = paranoid ideation; Drug = history of drug abuse; Alc = history of alcohol abuse; Arrest = history of arrest.
SUI, PAR, SCZ, BOR, ANT, DRG, and AGG) evidenced both
meaningful positive associations with negative life outcomes
or psychiatric events and meaningful negative associations with
positive life events (education, marital status, and employment).
Together, the overall pattern of findings provides solid convergent and discriminant support for the construct validity for the
PAI SOM, ARD, SUI, PAR, SCZ, BOR, ANT, DRG, and AGG
scales.
Out of all the PAI scales studied, BOR had the greatest number
of meaningful correlations to the life-event variables. In fact,
the BOR full scale and subscales were related to the majority
(67%) of the life-event variables. This finding is consistent with
the growing evidence that patients with borderline personality
disorder experience meaningful difficulties across a wide range
of life domains (e.g., Jørgensen et al., 2009).
In contrast, the MAN full scale had no meaningful correlations with the life-event variables. This unexpected finding
might reflect limitations in the life-event variables we employed,
problems with the MAN scale (Siefert et al., 2009), or the fact
that few of the patients with bipolar disorder were actively
manic at the time they completed the PAI. External validity
studies of other broadband multiscale instruments, like the Minnesota Multiphasic Personality Inventory–2 (MMPI–2; Butcher,
Dahlstrom, Graham, Tellegen, & Kaemmer, 1989), have also reported mixed findings for scales tapping hypomanic symptoms
(Ben-Porath & Tellegen, 2008). For example, Arbisi and colleagues (2008) found that the MMPI–2 RC9 scale (Hypomanic
Activation) was only associated with cocaine use in a sample
of psychiatric inpatients. Interestingly, the MAN-I and MAN-A
subscales were associated with a history of drug abuse in our
study. Overall, these findings suggest that continued research
is needed to better understand the MAN scale and its nontest
correlates. Future research in this area might benefit from including more “mania”-relevant life-event criteria (e.g., financial
problems related to impulsive spending).
Similarly, neither the ANX full scale nor any of the ANX
subscales were correlated above our preset criteria with the
life-event variables. Other authors have reported significant correlations between ANX and external criteria (see Ruiz & Edens,
2008), but the correlations reported were well below the significance threshold applied in this study. The lack of meaningful
associations between ANX and the life-event data was unexpected. However, Arbisi and colleagues (2008) also reported
no meaningful associations for the MMPI–2 RC7 (Dysfunctional Negative Emotions) scale with external criteria related to
anxiety (worry, panic, rumination, or obsession). Clearly further
research regarding the external correlates of the PAI ANX scales
is needed.
The SOM scale was associated with active medical problems.
This finding is consistent with research showing that SOM correlates strongly with other measures of physical functioning
(Morey, 1996) and that SOM generally has the highest elevation among the PAI scales in general medical populations (Osborne, 1994). Furthermore, of the three SOM subscales, SOM-H
Downloaded by [Augusta State University], [Jenelle Slavin-Mulford] at 08:16 14 February 2013
598
(health concerns) had the strongest correlation with currently
diagnosed medical problems, whereas the SOM-C (unusual
medical symptoms) had the lowest correlation with this criterion
measure.
The ARD, DEP, and SUI scales were associated with the lifeevent data in ways that fit with theoretical expectations. First,
ARD’s association with a history of trauma was driven by a
single subscale, ARD-T (see Table 4), which is a measure of
symptoms related to traumatic experiences. Our finding is consistent with past research showing that ARD correlates strongly
with other measures of PTSD (Morey, 1996) and that ARDT differentiates women psychiatric patients with a history of
childhood abuse from those with no such history (Cherepon &
Prinzhorn, 1994). Second, the positive association of both SUI
and DEP with a history of hospitalization is also consistent with
research showing that depression (Thompson et al., 2004) and
suicide risk (Doerfler, Moran, & Hannigan, 2010; Ziegenbein,
Anreis, Brüggen, Ohlmeier, & Kropp, 2006) are among the most
common reasons for psychiatric admission.
The reality impairing scales (PAR and SCZ) also had correlations that support their construct validity. First, as would be
expected, PAR and SCZ were the only two scales related to a history of paranoid ideation. Moreover, SCZ was the only full scale
related to a history of hallucinations and the SCZ-P (Psychotic
Experiences) subscale appears responsible for this association.
Interestingly, PAR and all three of the PAR subscales were also
positively correlated with a history of arrest. Although we did
not characterize the nature of the arrest charges in this study
(e.g., violent crime, drug charge, etc.), this is consistent with
the finding that paranoid personality disorder is among the most
common personality disorders encountered in correctional settings (Coid, 2005).
The PAI scales measuring externalizing psychopathology,
ANT, ALC, and DRG (Hopwood & Moser, 2011), produced
associations that generally fit with expectations. First, ANT and
the ANT subscales were associated with a history of drug abuse,
alcohol abuse, and arrest. This is in line with research showing
that antisocial personality disorder is the most common personality disorder in correctional settings (Coid, 2005) and research
showing high levels of comorbidity between antisocial personality disorder and substance abuse disorders (Cloninger, Bayon,
& Przybeck, 1997; Waldman & Slutske, 2000). Our finding that
ALC’s second highest correlation was with a history of drug
abuse and DRG’s second highest correlation was with a history of alcohol abuse is consistent with the known high rates
of comorbidity between these conditions (Stinson et al., 2005).
The association of DRG and ALC with a history of arrests is
also consistent with research linking drug and alcohol abuse
with crime and violence (Cantor, 1999; Chermack et al., 2008;
Farabee, Joshi, & Anglin, 2001).
Exploring discriminant validity, we expected positive lifeevent data to be negatively or at least uncorrelated with the
PAI scales. This pattern was observed. Education level was
negatively related to the majority of the PAI scales and had its
strongest negative association with DRG. This fits with research
linking substance abuse to decreased educational achievement
(e.g., Hawkins, Catalano, & Miller, 1992). Marital status was
negatively correlated with SUI, PAR, BOR, and ANT. Given
that PAR, BOR, and ANT scales all measure aspects of problematic relational styles, such a finding was not surprising. The
negative relationship of SUI and marital status was not expected,
SLAVIN-MULFORD ET AL.
but it seems to be in line with research showing that marriage
is generally a protective factor against suicide (e.g., Kposowa,
2000; Kreitman, 1988). Finally, we found only ARD and SUI to
have meaningful associations with unemployment. This was unexpected given that unemployment is known to have a negative
impact on mental health (Paul & Moser, 2009).
In sum, despite a few exceptions (e.g., few relationships with
employment and no meaningful significant correlations with
MAN and ANX), the pattern of correlations obtained for the
PAI scales and the life-event variables was generally consistent
with expectations and past research. Moreover, the correlations
found for the PAI subscales help to establish the unique contribution that these more homogeneous subscales can make in
personality assessment and research (see Smith, McCarthy, &
Zapolski, 2009). However, it is important to note some limitations in this study. First, all patients came from one hospital,
the patients were primarily White, and very few of the patients
had less than a high school education. As such, it will be important for future research to examine the empirical correlates
of these PAI scales in more demographically diverse clinical
groups. Second, although it is a strength of this study that criterion variables constituted objective information that is primarily
factual in nature (e.g., years of education, marital status), there
are limitations associated with such variables. For example,
marital status does not provide information about the quality
of a person’s relationship, years of education does not provide
information about the degree of educational success (grades obtained) or quality of the institution(s) attended, and employment
status does not provide information about the person’s level of
functioning in the workplace. Thus, it will be important for future research to include subjective measures of these objective
variables (e.g., marital satisfaction questionnaire, ratings from
employers about participants’ performance on the job). Further,
all of the criterion variables were either concurrent or retrospective. Therefore, these findings do not provide insight into
the predictive validity of the PAI. For example, although our
study shows that the SUI and BOR scales are correlated with
a history of suicide attempts, it does not show that SUI and
BOR predict future suicide attempts. Thus, continued research
is needed to provide further evidence for the predictive validity
of the measure. Still, our findings provide additional support
for the validity for the PAI scales SOM, ARD, SUI, PAR, SCZ,
BOR, ANT, DRG, and AGG and contribute to an understanding
of their nomological networks (Cronbach & Meehl, 1955).
ACKNOWLEDGMENT
An earlier version of this article was presented at the annual
meeting of the Society for Personality Assessment, Boston, MA,
March 2011.
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APPENDIX A.—Personality Assessment Inventory key.
Full Scale
Symbol
Somatic
Complaints
SOM
Anxiety
ANX
Anxiety-Related
Disorders
ARD
Depression
DEP
Mania
MAN
Paranoia
PAR
Schizophrenia
SCZ
Borderline
Features
BOR
Antisocial
Features
ANT
Alcohol Problems ALC
Drug Problems
DRG
Aggression
AGG
Suicidal Ideation
SUI
Subscale
Conversion
Somatization
Health Concerns
Cognitive
Affective
Physiological
Obsessive–Compulsive
Disorder
Phobia
Traumatic Stress
Cognitive
Affective
Physiological
Activity Level
Grandiosity
Irritability
Hypervigilance
Persecution
Resentment
Psychotic Experience
Social Detachment
Thought Disorder
Affective Instability
Identity Disturbance
Negative Relationships
Self-Harm
Antisocial Behaviors
Egocentricity
Stimulus-Seeking
None
None
Aggressive Attitude
Verbal Aggression
Physical Aggression
None
Symbol
SOM-C
SOM-S
SOM-H
ANX-C
ANX-A
ANX-P
ARD-O
ARD-P
ARD-T
DEP-C
DEP-A
DEP-P
MAN-A
MAN-G
MAN-I
PAR-H
PAR-P
PAR-R
SCZ-P
SCZ-S
SCZ-T
BOR-A
BOR-I
BOR-N
BOR-S
ANT-A
ANT-E
ANT-S
ALC
DRG
AGG-A
AGG-V
AGG-P
SUI