Comparing the Dependability and Associations With Functioning .docx

Comparing the Dependability and Associations With
Functioning of the
DSM–5 Section III Trait Model of Personality Pathology and
the DSM–5
Section II Personality Disorder Model
Michael Chmielewski
Southern Methodist University
Camilo J. Ruggero
University of North Texas
Roman Kotov
Stony Brook University
Keke Liu
University of North Texas
Robert F. Krueger
University of Minnesota
Two competing models of personality psychopathology are
included in the fifth edition of the Diagnostic
Statistical Manual of Mental Disorders (DSM–5; American
Psychiatric Association, 2013); the tradi-
tional personality disorder (PD) model included in Section II
and an alternative trait-based model
included in Section III. Numerous studies have examined the
validity of the alternative trait model and
its official assessment instrument, the Personality Inventory for
DSM–5 (PID-5; Krueger, Derringer,

Markon, Watson, & Skodol, 2012). However, few studies have
directly compared the trait-based model
to the traditional PD model empirically in the same dataset.
Moreover, to our knowledge, only a single
study (Suzuki, Griffin, & Samuel, 2015) has examined the
dependability of the PID-5, which is an
essential component of construct validity for traits
(Chmielewski & Watson, 2009; McCrae, Kurtz,
Yamagata, & Terracciano, 2011). The current study directly
compared the dependability of the DSM-5
traits, as assessed by the PID-5, and the traditional PD model,
as assessed by the Personality Diagnostic
Questionnaire-4 (PDQ-4�), in a large undergraduate sample. In
addition, it evaluated and compared their
associations with functioning, another essential component of
personality pathology. In general, our
findings indicate that most DSM–5 traits demonstrate high
levels of dependability that are superior to the
traditional PD model; however, some of the constructs assessed
by the PID-5 may be more state like. The
models were roughly equivalent in terms of their associations
with functioning. The current results
provide additional support for the validity of PID-5 and the
DSM–5 Section III personality pathology
model.
Keywords: dependability, PID-5, functioning, personality
disorders, DSM–5 Section III
The fifth edition the Diagnostic Statistical Manual of Mental
Disorders (DSM–5; American Psychiatric Association [APA],
2013) includes two competing models of personality pathology:
the traditional categorical personality disorder (PD) model from
DSM–IV and an alternative trait-based model in Section III.
Prob-

lems with the traditional PD model have been extensively re-
viewed (Clark, 2007; Widiger & Samuel, 2005; Widiger &
Trull,
2007). They include extreme heterogeneity (Chmielewski &
Wat-
son, 2008; Johansen, Karterud, Pedersen, Gude, & Falkum,
2004),
high rates of diagnostic comorbidity (Oldham et al., 1992), arbi-
trary boundaries with normality (Widiger & Samuel, 2005), low
interrater reliability (Tyrer et al., 2007), poor
convergent/discrim-
inant validity (Clark, Livesley, & Morey, 1997), excessive not
otherwise specified diagnosis (Verheul & Widiger, 2004), and
low
diagnostic stability (Shea et al., 2002; Skodol et al., 2005).
Considerable research has been conducted on the DSM–5 alter-
native model and the official assessment instrument for the trait
aspect of the model, the Personality Inventory for DSM–5 (PID-
5;
Krueger, Derringer, Markon, Watson, & Skodol, 2012).
Numerous
studies have demonstrated the structural validity of the PID-5
(De
Fruyt et al., 2013; Krueger et al., 2012; Wright et al., 2012;
Zimmermann et al., 2014). Moreover, the DSM–5 traits capture
the
variance within the traditional PD model (Hopwood, Thomas,
Markon, Wright, & Krueger, 2012; Miller, Few, Lynam, &
MacK-
This article was published Online First September 12, 2016.
Michael Chmielewski, Department of Psychology, Southern
Methodist
University; Camilo J. Ruggero, Department of Psychology,

University of
North Texas; Roman Kotov, Department of Psychiatry and
Behavioral
Sciences, Stony Brook University; Keke Liu, Department of
Psychology,
University of North Texas; Robert F. Krueger, Department of
Psychology,
University of Minnesota.
Robert Krueger has served as a paid consultant to preValio
LLC,
developers of psychological reports based on the Personality
Inventory for
DSM-5 (PID-5).
Correspondence concerning this article should be addressed to
Michael
Chmielewski, Department of Psychology, Southern Methodist
University,
PO Box 75275-0442, Dallas, TX 75275. E-mail:
[email protected]
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Personality Disorders: Theory, Research, and Treatment © 2016
American Psychological Association
2017, Vol. 8, No. 3, 228 –236 1949-2715/17/$12.00
http://dx.doi.org/10.1037/per0000213

228
mailto:[email protected]
illop, 2015; Samuel, Hopwood, Krueger, Thomas, & Ruggero,
2013), are strongly associated with other models of personality
and
personality pathology (Anderson et al., 2012; Ashton, Lee, de
Vries, Hendrickse, & Born, 2012; De Fruyt et al., 2013; Gore &
Widiger, 2013; Hopwood et al., 2012; Miller et al., 2015;
Quilty,
Ayearst, Chmielewski, Pollock, & Bagby, 2013; Samuel et al.,
2013;
Suzuki, Griffin, & Samuel, 2015; Thomas et al., 2012;
Zimmermann
et al., 2014), and have meaningful ties to other clinical
constructs
(Hopwood et al., 2013; Zimmermann et al., 2014).
The accumulated research provides support for the validity of
the DSM–5 trait model and the PID-5; nevertheless, important
gaps
remain regarding their construct validity. First, few data exist
regarding the dependability of the DSM–5 trait model and the
PID-5. Second, only a handful of studies have examined the
association between DSM–5 traits and functioning. Third, very
few
studies have directly compared the DSM–5 traits to the
traditional
PDs by simultaneously examining the performance of both
models
in the same dataset.

Dependability, Transient Error, and Stability
Cattell, Eber, and Tatsuoka (1970, p. 30) defined dependability
“as the correlation between two administrations of the same test
when the lapse of time is insufficient for people themselves to
change.” Dependability correlations are the primary method of
assessing transient measurement errors, which are systematic
mea-
surement errors caused by fluctuations in participants’
psycholog-
ical state on any particular day (Cattell et al., 1970;
Chmielewski
& Watson, 2009; Gnambs, 2014; McCrae, Kurtz, Yamagata, &
Terracciano, 2011; Schmidt, Le, & Ilies, 2003; Watson, 2004).
Because transient errors produce consistent responses during the
same assessment session but inconsistent responses across
differ-
ent assessment sessions they cannot be detected using indices of
reliability computed from a single administration (e.g., internal
consistency, Cronbach’s �). Importantly, transient errors can
mas-
querade as true trait change, making it difficult to determine the
stability of the construct that a scale assesses (see Anusic,
Lucas,
& Donnellan, 2012; Chmielewski & Watson, 2009; Gnambs,
2014; McCrae et al., 2011).
As noted in the DSM–5, personality pathology must have “an
enduring pattern” and be “stable over time” (APA, 2013, p.
645).
One of the many limitations of the traditional DSM PD model is
that PDs demonstrate, at best, modest stability (Grilo et al.,
2004;
Lenzenweger, 1999; McGlashan et al., 2005; Shea et al., 2002;
Zanarini, Frankenburg, Reich, & Fitzmaurice, 2012). To our
knowledge, only a single study (Wright et al., 2015) has

examined
the stability of DSM–5 traits. They reported a mean PID-5
domain
stability of r � .73 (range: r � .62 to .75) and a median facet
stability of r � .68 (range: r � .41 to.78) over a 1.4-year
interval
in 93 outpatients. Wright et al. (2015) concluded that the DSM–
5
traits were “highly stable over the course of the study” (p. 202).
However, this broad statement overshadows substantial differ-
ences in stability (r � .41 to .78) among the various PID-5
traits.
Because a measure’s dependability sets an upper limit on its
stability, it is possible that the observed differences are due to
differential levels of transient error (i.e., differential
dependability)
across the PID-5 scales. Moreover, it is possible that transient
error
is responsible for the poor stability of the traditional DSM PD
model. In fact, Zimmerman (1994) concluded that state effects
(i.e., transient error) substantially influence assessments of the
traditional PD model.
Transient errors can also distort associations with other con-
structs, result in failures to replicate research, and substantially
alter study outcomes (Chmielewski, Sala, Tang, & Baldwin,
2016;
Chmielewski & Watson, 2009). Moreover, they may lead to an
overinclusion of “false positives” and exclusion of “false nega-
tives” in clinical samples (Chmielewski & Watson, 2009).
Despite
the potential influence of transient error, to our knowledge only
a
single study has examined the dependability of the PID-5.
Suzuki

et al. (2015) reported a mean domain dependability of .83
(range �
.81 to .83) and a mean facet dependability of .78 (range � .66 to
.86), which was similar to values for the Revised NEO
Personality
Inventory (NEO-PI-R) in the sample. Although these findings
pro-
vide initial evidence for the dependability of the PID-5, some of
the
facet dependabilities were low, suggesting that transient error
may be
a concern. Moreover, their sample (N � 266) was below recom-
mended cutoffs (N � 300) for examining dependability
(Watson,
2004). Given the importance of transient error, replication of
these
findings in a larger sample is necessary.
Personality Pathology and Functioning
The traditional PD model and the alternative model (Criterion
A) both include functional impairment (American Psychiatric
As-
sociation, 2013). The traditional PD model is associated with
functioning across various domains, including work, social rela-
tionships, and leisure (Miller, Campbell, & Pilkonis, 2007;
Skodol
et al., 2005). To our knowledge, only three studies have
examined
associations between the DSM–5 traits and functioning. Wright
et
al. (2015) reported that the DSM–5 traits predicted psychosocial
functioning 1.4 years later in a patient sample. Ackerman and
Corretti (2015) found that higher levels of detachment in
college
students lead to their roommates feeling less close to them.

Keeley,
Flanagan, and McCluskey (2014) demonstrated that the DSM–5
traits concurrently explained variance in several functioning do-
mains in student and patient samples.
Results from these studies have generally reflected impairments
(e.g., interpersonal relationships) aligned with Criterion A of
the
alternative model. However, several unexpected findings
emerged,
including significant associations with impairments in mobility
and self-care (Keeley et al., 2014). Moreover, Risk Taking,
Atten-
tion Seeking, and Manipulativeness were not associated with
func-
tioning in the student sample (Keeley et al., 2014). Given the
importance of functioning for personality pathology, replication
of
these counterintuitive findings is necessary. Finally, is worth
not-
ing that Keeley et al. (2014) hypothesized transient errors could
have influenced their results and called for further research
regard-
ing this issue.
Current Study
The current study was designed to provide evidence regarding
the construct validity of the DSM–5 traits and the PID-5. First,
we
examined the dependability of the PID-5 in a sample large
enough
(i.e., minimum N � 300; Watson, 2004) to provide precise de-
pendability estimates. Second, we examined the concurrent
asso-
ciations of the DSM–5 traits with functional impairment across

a
wide range of domains. Finally, we directly compared the
DSM–5
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229DSM–5 TRAITS AND TRADITIONAL PD MODEL
trait (PID-5) and traditional PD (PDQ-4�) models empirically
in
the same sample. Although the alternative model was created to
address limitations inherent in the traditional PD model, only
two
studies have directly tested these models against each other in
the
same sample. They found that the models had similar
associations
with psychopathology and normal personality (Fossati et al.,
2015;
Miller et al., 2015). As Chmielewski and Watson (2009, p. 199)
note, “consideration of transient error could help determine
which
PD models are more valid and reliable” making the current anal-
yses very relevant in comparing the two models. Finally, we
categorically and dimensionally examined traditional PDs

because
(a) dimensional representations are more valid and reliable than
categorical ones (Markon, Chmielewski, & Miller, 2011) and
(b)
dimensional representations have been suggested as an
alternative
model of traditional PDs (Oldham & Skodol, 2000).
Method
Participants and Procedures
Participants were undergraduate students (N � 572; 68.3%
female, 71.8% Caucasian, 12.4% African American, 18.3% His-
panic, mean age � 21.9 years) who completed all measures
online.
Approximately 2 weeks later all participants were invited to
com-
plete the PID-5 a second time, 382 of whom did, allowing for
precise dependability estimates (see Watson, 2004). The Person-
ality Diagnostic Questionnaire-4 (PDQ-4�) was later added to
the
second assessment, resulting in a subset of participants (N �
202
of the 382) who also completed it twice. Participants who com-
pleted both assessments scored higher on PID-5 Separation
Inse-
curity and lower on Callousness, Manipulativeness, Risk
Taking,
and Irresponsibility than those completing one assessment.
Those
who completed both assessments also scored lower on the
PDQ-4� Antisocial symptoms and World Health Organization
Disability Assessment Schedule 2.0 (WHODAS) Life Activities.
Measures

PID-5. The PID-5 (Krueger et al., 2012) is the official mea-
sure of the DSM–5 dimensional trait-based model of personality
pathology. It includes 25 lower order traits and 5 higher order
domains. Facet scores were calculated as item means; domain
scores were calculated based on APA guidelines in which each
domain score is the mean of three facet scales. Several studies
previously reviewed have documented the validity of the PID-5.
PDQ-4�. The PDQ-4� (Hyler, 1994) maps directly onto the
traditional DSM PD model and is one of the most widely used
measures of the model (Widiger & Coker, 2002). The PDQ-4�
demonstrates high sensitivity and moderate specificity
(Davison,
Leese, & Taylor, 2001). The PDQ-4� was examined
categorically
and dimensionally (i.e., by summing symptoms for each PD).
WHODAS. The WHODAS was completed during the first as-
sessment. It assesses functioning across six domains: Cognition,
Mo-
bility, Self-Care, Getting Along (i.e., interpersonal
relationships), Life
Activities, and Participation in Society.1 Internal consistency
esti-
mates range from .94 to .96 and dependability estimates range
from
.93 to .96 (Üstün et al., 2010). The WHODAS is also included
in
Section III of the DSM–5 as a replacement for the Global
Assessment
of Functioning scale and is the same measure used by Keeley et
al.
(2014), allowing for a direct comparison with their findings.

Results
Cronbach’s �s for the PID-5 (see Table 1) were at least
adequate
(e.g., �.70; Nunnally, 1978), with 88% being considered good
(e.g., �.80; Clark & Watson, 1995). Average interitem correla-
tions (AICs) for most PID-5 scales were generally within
recom-
mendations, suggesting that the scales assess homogenous con-
structs (see Clark & Watson, 1995). However, some scales
demonstrated higher than optimal AICs, especially considering
the
breadth of the constructs they assess. This was particularly true
for
Eccentricity, which demonstrated a very high AIC at both
assess-
ments (i.e., .65 and .72), suggesting that it contains items that
could be considered redundant in this sample. In contrast, none
of
the �s for the PDQ-4� dimensional symptom counts were
above
.80. Moreover, 85% were below .70, and the AICs were quite
low
1 The Mobility and Self-Care domains were added as the study
was in
progress and therefore completed by a subset (N � 275) of the
sample.
Table 1
PID Internal Consistency and Dependability
Scale
Time 1 Time 2

Dependability� AIC � AIC
Domains
Negative Affectivity .94 .41 .95 .45 .91
Detachment .93 .36 .93 .36 .89
Psychoticism .95 .37 .96 .42 .88
Antagonism .91 .33 .92 .35 .86
Disinhibition .92 .34 .93 .38 .86
PID-5 Domain Mean .93 .36 .94 .39 .88
Facets
Withdrawal .91 .49 .92 .54 .89
Depressivity .93 .49 .94 .52 .88
Eccentricity .96 .65 .97 .72 .88
Emotional Lability .89 .53 .92 .61 .88
Anxiousness .91 .51 .91 .53 .88
Separation Insecurity .86 .47 .88 .52 .86
Hostility .86 .38 .88 .43 .85
Risk Taking .87 .33 .88 .34 .85
Anhedonia .87 .45 .89 .51 .84
Restricted Affect .83 .40 .85 .45 .84
Deceitfulness .87 .41 .89 .44 .84
Intimacy Avoidance .83 .44 .83 .44 .84
Callousness .86 .31 .88 .33 .84
Distractibility .91 .52 .92 .56 .84
Attention Seeking .89 .50 .91 .55 .84
Manipulativeness .83 .50 .87 .57 .83
Rigid Perfectionism .91 .51 .92 .53 .83
Perceptual Dysregulation .84 .30 .85 .32 .80
Unusual Beliefs .77 .29 .84 .39 .80
Irresponsibility .74 .29 .77 .32 .80
Impulsivity .86 .51 .86 .50 .79
Perseveration .87 .43 .89 .48 .78
Submissiveness .80 .51 .85 .59 .77
Suspiciousness .71 .26 .72 .26 .76
Grandiosity .76 .34 .79 .38 .76

PID facet mean .85 .44 .87 .47 .83
Note. N T � 572, T2 � 382. Italic values represents mean of the
scales.
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230 CHMIELEWSKI, RUGGERO, KOTOV, LIU, AND
KRUEGER
(see Table 2). These results reflect the heterogeneity of
symptoms
included within the traditional PD constructs.
Dependability
It is highly unlikely that true changes in personality pathology
would have occurred over the short 2-week dependability
interval;
therefore, any dependability coefficients (see Table 1) below
1.0
indicate the presence of measurement error. The PID-5 domains
demonstrated high levels of dependability that approach 1.0
(e.g.,
r � .86 to .91, mean domain r � .88).2 However, there was

considerable variability across the PID-5 facets (mean
dependabil-
ity; r � .83), with some approaching 1.0 (e.g., Withdrawal; r �
.89) and others being appreciably lower (e.g., Grandiosity and
Suspiciousness; r � .76).
In sharp contrast, the dependability of the PDQ-4� symptom
count scales (see Table 2) were well below 1.0, ranging from r
�
.68 (Narcissistic) to r � .82 (Avoidant) with a mean of only r �
.75. This low level of dependability indicates a substantial
amount
of measurement error. The PDQ-4� categorical PDs
demonstrated
even poorer dependability (� � .36 to .72; mean � � .57),
demonstrating that a substantial portion of their variance is due
to
measurement error. These results are in line with past evidence
indicating that categorical representations of psychopathology
are
less reliable and valid than dimensional ones (Markon et al.,
2011).
Unexpectedly, strong correlations emerged between
dependability
and Cronbach’s � (PID-5: domain mean r � .62, facet mean r �
.77; PDQ-4�: mean r � .82).
Next, we conducted significance tests (Pearson Filon for non-
overlapping variables from the same sample) comparing the
PID-5
and PDQ-4� symptom count scales, which were more
dependable
than the PDQ-4� categories, in the subsample (N � 202) that
completed both measures twice. The PID-5 domains were
signif-
icantly more dependable than the PDQ-4� scales in 94% of the

comparisons and the facets were significantly more dependable
in
63% of comparisons. The PDQ-4� scales were never more de-
pendable than the PID-5 scales.
Associations With Functioning
Because Criterion A of the trait model includes dysfunction in
identity, self-direction, empathy, and intimacy, we would expect
stronger associations with certain WHODAS domains (e.g., get-
ting along with others) and weaker associations with others
(e.g.,
self-care, mobility). Nearly every PID-5 scale was significantly
associated with poorer functioning across every WHODAS do-
main (see Table 3).3 Many of these associations were medium
in
size; however, certain traits (e.g., Grandiosity and
Manipulative-
ness) appear to be less strongly associated with functioning than
others. A notable exception was that Risk Taking was not
signif-
icantly associated with any WHODAS domain, which replicates
previous counterintuitive findings (Keeley et al., 2014). In this
regard, Crego and Widiger (2014) suggested that reverse-keyed
items underperform when assessing psychopathy-related traits.
Given the high percentage of reverse-keyed items in the Risk
Taking scale (43%), we created two risk-taking composites (one
using reverse-keyed items and one using nonreverse-keyed
items).
These two composites correlated r � .50 with each other; how-
ever, the nonreverse-keyed composite demonstrated small
positive
associations (mean r � .13) and the reverse-keyed composite
demonstrated small negative associations (mean r � �.15) with
the WHODAS. Next, we conducted separate multiple regression
analyses for the PID-5 domains and facets to determine the

amount
of variance each explained in the WHODAS. The weakest PID-5
associations were with mobility (domain R2 � .12, facet R2 �
.17)
and self-care (domain R2 � .21, facet R2 � .28), domains hypo-
thetically less related to Criterion A, suggesting that the PID-5
demonstrates evidence of specificity. The PDQ-4� symptom
count scales (see Table 4) demonstrated significant associations
(R2 � .21 to .47) with all WHODAS functioning domains. How-
ever, the PDQ-4� scales were more broadly associated with
functioning in that the PDQ-4� associations with Mobility (R2
�
.22) and Self-Care (R2 � .28) were not as differentiated from
associations with the other WHODAS domains.
The incremental ability of each personality pathology measure
to predict concurrent functioning was examined using
hierarchical
regressions analyses (see Table 5). In Step 1, the PDQ-4�
symp-
tom count scores were entered, then in Step 2 the PID-5
domains
(or facets) were entered. The order of entry was then reversed.
The
PID-5 domains and facets added incremental prediction beyond
the PDQ-4� for all areas of functioning except Mobility and
Self-Care. For most areas of functioning the additional variance
was modest; however, it was more substantial for life activities
(domain � 6.6%, facet � 14.8%), cognition (domain � 8.9%,
facet � 15.7%), and overall functioning (domain � 3.2%, facet
�
11.1%). Likewise, the PDQ-4� symptom counts added
incremen-
tal validity beyond the PID-5 domains (�4 –13%) and facets
(�4 –11%) for all functioning domains, with the greatest incre-
mental validity (10 –12% additional variance) for Mobility and

Self-Care. Moreover, the PDQ-4� added approximately 10%
pre-
2 The dependability the PID-5 Brief Form, scored from the full
PID-5,
ranged from .78 to .83 with a mean of .80.
3 Associations between the PID-5 Brief Form and functioning
were very
similar.
Table 2
PDQ-4 Internal Consistency and Dependability
Time 1 Time 2 Dependability
Scale � AIC � AIC Sym. Cat.
Avoidant .77 .32 .78 .34 .82 .63
Borderline .67 .18 .65 .17 .81 .72
Paranoid .65 .21 .70 .25 .78 .63
Schizotypal .62 .15 .68 .19 .78 .44
Antisocial .56 .14 .50 .11 .74 .70
Dependent .68 .21 .66 .20 .73 .52
Schizoid .54 .14 .51 .13 .73 .62
Histrionic .56 .14 .59 .15 .72 .56
Obs. Comp. .47 .10 .50 .11 .69 .53
Narcissistic .55 .12 .52 .11 .68 .36
Mean .61 .17 .61 .18 .75 .57
Note. T1 N � 572, T2 N � 202. Sym. � symptom count; Cat. �
categorical scoring; Obs. Comp. � Obsessive Compulsive.
Dependability
statistic for categorical scoring is �. We also computed
dependability for
the categorical scoring as intraclass correlations, and results

were essen-
tially identical. Italic values represents mean of the scales.
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dictive utility for overall functioning, regardless of if the PID-5
domains or facets were included in the model.
Discussion
The current study adds to the evidence supporting the DSM–5
alternative model of personality pathology and the PID-5. To
our
knowledge, it is only the second study to examine the
dependabil-
ity of the PID-5 and the first to use a sample large enough to
meet
recommendations (Watson, 2004). It is also one of a few studies
examining the association between DSM–5 pathological
personal-
ity traits and functioning. Finally, only two other studies
(Fossati
et al., 2015; Miller et al., 2015) directly tested the alternative

model against the traditional PD model in the same dataset,
neither
of which addressed the current issues.
Dependability
High levels of dependability are essential for the construct
validity of trait measures and models (Chmielewski & Watson,
2009; Gnambs, 2014; McCrae et al., 2011; Watson, 2004). Al-
though measurement error is present to some degree in all PID-5
scales, the dependability of the PID-5 domains approached 1.0
(mean domain dependability r � .88), indicating relatively low
levels of transient error. However, there was considerable
variabil-
ity among the PID-5 facet scales (mean r � .83), with depend-
abilities ranging from high (e.g., r � .89) to relatively low (e.g.,
r � .76). The current dependabilities appear higher than those
reported by Suzuki et al. (2015; domain M � .83, range � .81 to
.83; facet M � .78, range � .66 to .86). Despite the differences
in
magnitude, the correlation of dependability coefficients across
the
Table 3
PID-5 Relationship to WHODAS Functioning
Scale Cognition Mobility Self-Care Get Along Life Act Society
Overall
NA .49 .26 .36 .42 .39 .49 .52
Anxiousness� .45 .21 .29 .38 .37 .43 .48
Depressivity .48 .33 .40 .50 .42 .45 .56
Emot. Labil.� .44 .29 .36 .36 .34 .43 .51
Perseveration .51 .22 .23 .39 .39 .43 .46
Rigid Perfect. .20 .11 .07 .20 .15 .27 .24
Sep. Insecur.� .35 .16 .26 .33 .27 .37 .34

Submissive. .32 .14 .18 .27 .28 .29 .28
Suspicious. .41 .25 .26 .42 .32 .40 .42
Detachment .40 .20 .21 .50 .33 .35 .42
Anhedonia� .39 .22 .23 .46 .39 .38 .43
Intim. Av.� .23 .14 .12 .29 .17 .16 .28
Restrict Aff .15 .05 .02 .21 .13 .13 .14
Withdrawal� .34 .15 .18 .46 .25 .31 .35
Antagonism .18 .15 .15 .17 .18 .22 .20
Att. Seeking .18 .10 .13 .06 .16 .15 .13
Callousness .16 .15 .17 .26 .14 .18 .20
Deceit.� .27 .20 .19 .24 .20 .27 .24
Hostility .31 .24 .26 .34 .24 .36 .38
Grandiosity� .10 .11 .08 .08 .08 .11 .15
Manipulat.� .10 .09 .11 .11 .16 .18 .12
Disinhibition .51 .32 .36 .37 .42 .38 .53
Distract� .55 .27 .30 .34 .46 .34 .51
Impulsivity� .29 .21 .27 .21 .23 .24 .32
Irresponsib.� .43 .36 .38 .38 .36 .36 .52
Risk Taking �.01 .02 .06 �.04 �.02 �.02 .02
Psychoticism .47 .27 .29 .40 .37 .41 .50
Eccentricity� .37 .18 .20 .36 .31 .32 .41
Perc. Dys.� .52 .32 .37 .41 .36 .44 .55
Unsl. Beliefs� .37 .23 .23 .30 .31 .35 .39
R2
Domains .37 .12 .17 .33 .24 .28 .39
Facets .44 .21 .28 .37 .32 .34 .49
Brief Domains .31 .10 .16 .27 .18 .25 .33
Adjusted R2

Domains .37 .10 .16 .32 .23 .28 .38
Facets .42 .14 .20 .34 .29 .31 .43
Brief Domains .31 .08 .14 .26 .17 .24 .32
Note. N � 561–570 for Cognition, Getting Along with Others,
Engaging in Life Activities, and Participation in
Society; N � 265–275 for Mobility, Self-Care, and Overall
Functioning. Underline � p .05. bold � p .01. � �
scales scored in the PID-5 domains. Emot. Labil. � Emotional
Lability; Rigid Perfect. � Rigid Perfectionism; NA �
Negative Affect; Schizd � Schizoid; STPD � Schizotypal PD;
Antisoc � Antisocial; Sep. Ins. � Separation
Insecurity; Submissive. � Submissiveness; Suspicious. �
Suspiciousness; Intim. Av. � Intimacy Avoidance; Restrict
Aff. � Restricted Affect; Att. Seeking � Attention Seeking;
Deceit. � Deceitfulness; Manipulat. � Manipulative-
ness; Irresponsib. � Irresponsibility; Perc. Dys. � Perceptual
Dysregulation; Unsl. Belfs. � Unusual Beliefs; Get
Along � Getting Along; Life Act � Life Activities; Society �
Participation in Society.
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KRUEGER

two studies was high (r � .66), indicating that the relative
depend-
ability of these PID-5 scales was similar across the studies. In
other
words, some PID-5 scales are consistently more dependable
than
others are.
Overall, the dependability results from the current study and
those from Suzuki et al. (2015) compare favorably to
dependability
estimates for “normal” personality traits in similar samples
(Chmielewski et al., 2016; Chmielewski & Watson, 2009;
Suzuki
et al., 2015). Nevertheless, it should be noted that dependability
estimates in the .75 range represent a high level of measurement
error (e.g., �25% error variance) and that even fairly low levels
of
transient error can have substantial effects on study outcomes
(see
Chmielewski & Watson, 2009). Therefore, we echo previous
calls
in the literature for further research into the causes of transient
error. This is especially important because previous
explanations
for transient error, such as item formats, response formats, or
instruction sets (see Chmielewski & Watson, 2009; Watson,
2004),
cannot explain the differences in dependability across PID-5
scales.
The current results suggest that some of the constructs assessed
by the PID-5 may, instead of representing traits, be best concep-
tualized as more transient and state like. This interpretation is

in
line with past suggestions that personality pathology may
subsume
both traits and acute symptoms (Clark, 2007; McGlashan et al.,
2005; Oldham & Skodol, 2000). More recently, Wright et al.
(2015) raised this as a possible explanation for the differential
Table 4
PDQ-4 Symptom Count Relationship to Functioning
Scale Cognition Mobility Self-Care Get Along Life Act Society
Overall
Paranoid .30 .25 .26 .33 .31 .36 .39
Schizoid .29 .30 .29 .39 .22 .27 .40
Schizotypal .43 .38 .34 .45 .36 .45 .52
Antisocial .21 .18 .31 .19 .20 .28 .29
Borderline .46 .33 .42 .46 .36 .50 .58
Histrionic .32 .34 .36 .23 .26 .32 .40
Narcissistic .25 .20 .19 .17 .24 .24 .27
Avoidant .43 .29 .35 .53 .35 .42 .53
Dependent .46 .31 .38 .43 .38 .42 .53
Obs. Comp .28 .17 .19 .25 .22 .31 .32
R2 .32 .22 .28 .38 .21 .34 .47
Adjusted R2 .31 .19 .25 .37 .20 .32 .45
Engaging in Life Activities, and Participation
in Society; N � 265–275 for Mobility, Self-Care, and Overall
Functioning. Underline � p .05. bold � p
.01. Obs. Comp � Obsessive Compulsive; Get Along � Getting
Along; Life Act � Life Activities; Society �
Table 5
Hierarchical Regression Analyses Predicting Functioning

PID-5 incremental validity PDQ-4 incremental validity
WHODAS
R2
F p
R2
F p
Domain level
Cognition .089 16.86 .000 .041 3.90 .000
Mobility .022 1.50 .191 .126 4.35 .000
Self-Care .011 .83 .533 .114 4.13 .000
Getting Along .026 4.78 .000 .079 7.33 .000
Life Activities .066 9.94 .000 .038 2.85 .002
Society .023 3.99 .001 .075 6.49 .000
Overall .032 3.18 .008 .109 5.40 .000
Facet level
Cognition .157 6.48 .000 .037 3.86 .000
Mobility .100 1.43 .091 .109 3.86 .000
Self-Care .100 1.52 .058 .100 3.82 .000
Getting Along .048 1.80 .011 .058 5.35 .000
Life Activities .148 4.86 .000 .043 3.51 .000
Society .057 1.99 .003 .053 4.66 .000
Overall .111 2.42 .000 .090 4.91 .000
Engaging in Life Activities, and Participation
in Society; N � 265–275 for Mobility, Self-Care, and Overall
Functioning; Significant estimates are bolded.
Columns 2, 3, and 4 present results of the model where the
PDQ-4� was entered in the first block and then the
PID-5 (domains or facets) in the second block; Columns 5, 6,
and 7 present results of the model where the PID-5
(domains or facets) was entered in the first block and then the

PDQ-4� entered in the second block. Society �
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1.4-year stability of the PID-5 scales, arguing that it was
essential
for future research to address this issue. The current research,
combined with that of Suzuki et al. (2015), provides further
evidence for this possibility. Nevertheless, it is worth noting
that
there was a significant association between the number of items
a
facet contained and its dependability (r � .49), suggesting that
scale length may have influenced the dependability of the PID-5
facets. As such, additional research is necessary to determine
which constructs included within the PID-5 are best conceptual-
ized as acute states.
Our dependability results suggest that the PID-5 outperforms
the
PDQ-4� regardless of whether the latter was categorically or
dimensionally assessed. Because dependability analyses provide

a
metric for comparing models of personality pathology
(Chmielewski & Watson, 2009), the current results empirically
demonstrate the superiority of the alternative DSM–5 model
over
the traditional PD model, at least as assessed by these
commonly
used measures. It is worth noting that the PID-5 Brief Form,
which
contains only 25 items (compared with 99 items in the PDQ-
4�),
demonstrated as strong if not stronger dependabilities than the
PDQ-4�, indicating that the PID-5’s higher dependability is not
solely due to it having more items than the PDQ-4�. Our results
also highlight that the categorical nature of traditional DSM
PDs
makes them far more susceptible to transient error, suggesting
that
transient error is at least partially responsible for the poor
stability
of the traditional categorical PD model (Chmielewski &
Watson,
2009; Clark et al., 1997; Skodol et al., 2005; Zimmerman,
1994).
Taken together, these results add to the large body of research
indicating that dimensional representations of psychopathology
are
superior to categorical ones (Markon et al., 2011). It is worth
noting that interview assessments of PDs have lower stability
than
do self-report measures (Samuel et al., 2011). Moreover, past
research has documented poor dependability for interviewer-
assessed mood and anxiety disorders (Chmielewski, Clark,
Bagby,
& Watson, 2015), suggesting that dependability of interviewer-
based PD assessments would likely be lower than self-report PD

assessments.
Functioning
The PID-5 scales demonstrated broad associations with multiple
functioning domains. In line with previous research (Keeley et
al.,
2014), the DSM–5 traits appear to be more strongly associated
with
functioning domains conceptually aligned with personality
pathol-
ogy (e.g., getting along with others) than more distal domains
(e.g.,
mobility, self-care). With one notable exception, the current
asso-
ciations were very similar to those reported by Keeley et al.
(2014); the current results align very strongly with results from
their student sample for five of the WHODAS domains (mean
cross study correlation of the PID-5 associations with
functioning
was r � .83, range r � .71 to .91). However, a major
discrepancy
emerged for Participation in Society; in the current study nearly
every PID-5 scale was significantly associated with
Participation
in Society (domain mean r � .28, facet mean r � .34), whereas
no
PID-5 scales were in the Keeley et al. (2014) student sample
(domain mean r � .00, facet mean r � .01). We note that
significant correlations did emerge in their clinical sample.
Finally,
we replicated Keeley et al.’s (2014) finding of no association
between PID-5 Risk Taking and functioning. It is interesting to
note that Wright et al. (2015) also found no association between
Risk Taking and functioning in their longitudinal study. Keeley

et
al. (2014) suggested that the self-report nature of the PID-5
might
have led to this unexpected finding, and we would add that the
high number of reverse-keyed items in this scale may have
influ-
enced the results (Crego & Widiger, 2014)
Despite demonstrating lower dependability, the PDQ-4� was
associated with functioning at least as strongly as the PID-5
was.
Although this finding may seem counterintuitive, it is in line
with
previous studies demonstrating that the traditional PDs and the
alternative model have similar associations with
psychopathology
and normal personality (Fossati et al., 2015; Miller et al.,
2015).
This equivalence may be due, in part, to the fact that the models
share a considerable amount of variance and cover the same
basic
content organized in a different manner (Hopwood et al., 2012;
Miller et al., 2015; Samuel et al., 2013). In addition, the PID-5
specifically assesses the trait component of the model (Criterion
B)
and not the dysfunction component (Criterion A), whereas the
PDQ-4� does not explicitly make such a distinction. It is worth
noting that the PID-5 Brief Form demonstrated similar associa-
tions to the full PID-5, suggesting that scale length was not a
major
factor. Finally, the PID-5 and PDQ-4� provided significant
incre-
mental validity over each other for various functioning domains.
The PID-5 provided the most incremental validity for the
Cogni-
tion domain whereas the PDQ-4� had its greatest incremental

validity for Mobility and Self-Care. These results suggest that
the
two models differ in their specificity in regards to functioning,
with the traditional PD model linked to a broader range of func-
tioning and the DSM–5 trait model demonstrating more specific
links.
Limitations, Future Directions, and Conclusions
Despite its strengths, there are some limitations to the current
study. First, although the PID-5 is the APA’s official instrument
for assessment of the DSM–5 traits and the PDQ-4� is a widely
used measure specifically created to assess traditional PDs,
differ-
ent self-report measures assessing these models, informant
reports,
or clinician ratings may lead to different results, which is an
important direction for future research. Second, the strong
associ-
ation between dependability and � is in contrast to previous
studies
(Chmielewski et al., 2016; Chmielewski & Watson, 2009;
Gnambs, 2014; McCrae et al., 2011), including those of the
PID-5
(Suzuki et al., 2015). The reasons for the high correlation in the
current sample, as well as for the differences in magnitude of
PID-5 dependabilities between the current study and that of
Suzuki
et al. (2015), are unclear, especially considering that past
studies
have used similar samples and test administration techniques.
Third, it is unclear if the current student results would replicate
in
community or clinical samples. Additional dependability studies
of
the PID-5 using large samples are required to address these

issues.
However, previous evidence suggests that the relative level of
dependability is consistent across different samples
(Chmielewski
& Watson, 2009).
In conclusion, the current study provides evidence regarding the
dependability, a crucial component of construct validity for trait
measures, of the PID-5. In general, the results indicate the
DSM–5
traits are highly dependable and outperform the traditional PD
model in this regard. However, some constructs assessed by the
T
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ol
og
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al
A
ss
oc
ia
ti
on
or
on
e
of

it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so

le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
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us
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an
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to
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em
in
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br
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y.
KRUEGER
PID-5 may be best conceptualized as more state like. In
addition,
the current results replicate previous studies demonstrating
impor-
tant associations between the DSM–5 traits and functioning. It
is
worth noting that both the traditional PD and alternative models

demonstrated similar associations with functioning, suggesting
that the DSM–5 traits capture the important aspects of the tradi-
tional PD model.
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http://dx.doi.org/10.1521/pedi_2014_28_130Comparing the
Dependability and Associations With Functioning of the DSM–5
Section III Tr ...Dependability, Transient Error, and
StabilityPersonality Pathology and FunctioningCurrent
StudyMethodParticipants and ProceduresMeasuresPID-5PDQ-
4+WHODASResultsDependabilityAssociations With
FunctioningDiscussionDependabilityFunctioningLimitations,
Future Directions, and ConclusionsReferences
Running head: IDEAL STRATEGY 1
IDEAL Strategy

EDU 372 – Educational Psychology
IDEAL STRATEGY 2
IDEAL Strategy
The IDEAL strategy consists of five steps: Identify problems,
Define goals, Explore
possible strategies, Anticipate outcomes and Act, and Look back
and Learn. Identifying
problems can be more than just what we see in our text. As a
matter of fact, our text tells us that

these are usually more than questions that are given to us and
incorporate challenges that we face
on a day to day basis (LeFrançois, 2011). In a classroom,
educators may face problems such as
the child who wants to act out, or the one who really just
doesn’t understand the material. Once
we have identified the problem, we need to know what our goal
is. By defining goals and
representing the problem, we eliminate any useless information
while determining what our end-
state will be. For educators, this can involve identifying that
some students who aren’t getting
the material will require more help. Exploring possible
strategies involves looking at different
ways in which we can get from point A to point B. Educators
will need to explore different ways
in which they will be able to help their students. Anticipating
outcomes generally means to
conduct a hypothesis (LeFrançois, 2011). Educators will have
to guess whether or not their
selected strategies will be useful. Once they’ve drawn their
hypothesis, they will have to
implement it and put their strategy into action. Finally, looking
back and learning can be one of

the most useful steps of the IDEAL strategy. “It’s important to
evaluate the appropriateness of
each and by so doing, learn things that might be useful in the
future,” (LeFrançois, 2011, para
6.7). You can take everything that you have learned during
your previous issues and apply it to
new problems that arise.
Solving the Problem and Reflection
The problem seems simple; Bobby doesn’t like group activities.
Since he is bright and is
able to fully engage in assignments independently, we can draw
a record of his work. This is
IDEAL STRATEGY 3
important because we see that he can complete tasks as an
individual, but not so much in a group
setting. This record may be useful if we need to approach his
parents or utilize some other sort
of intervention in the future (Nunn & McMahan, 2000).
Obviously, the goal in this circumstance would be for Bobby to
learn how to work in a
group. Not only that, but he will also need to learn how to not

get angry if he isn’t being listened
to at the moment. The end state that we desire is for Bobby to
not only learn the material and
accomplish the tasks, but also to be able to work in a group
without getting frustrated.
In forming possible strategies, I feel that it would be important
to speak with Bobby’s
parents to see if they know anything that could possibly help.
Also, if there is a school
psychologist, they would probably be a good starting point too.
There’s always the heuristic of
trial-by-fire. We can continue throwing him into group
activities, hoping that he will learn what
he needs to. Of course, we will probably need to provide
guidance and correction when needed
to keep him on track. Another, more reasonable, strategy would
be to reduce the number of
members in his group. Start him off in a group with one other
person. Once he is able to
complete his work and is acting in accordance with our
standards, then we can add another child
to his group.
The first strategy provided will likely not work out well. We
will continue throwing him

in the group setting in hopes that he learns from it. This hasn’t
been working, which has led to
this whole dilemma in the first place. Continuing down this
path will likely reinforce poor
behavior and Bobby’s education will suffer as a result. The
second strategy seems like the more
likely candidate. By starting him off in a group with one other
person, it will eliminate the total
amount of time that he is not listened to, which causes him to
grow angry and pout in the corner.
Once he is able to handle a group with one other child, then we
add another. We keep him in
IDEAL STRATEGY 4
this group until he is able to perform and not get angry if he
isn’t listened to. We will still need
to provide guidance and correction for behavior in this setting,
but it will not be nearly as drastic
as throwing him into a group of four or five other students all at
once.
Looking back and learning from this scenario will be pretty
vital, especially in the
inclusive environments that we are seeing more and more of in

today’s education. Bobby is just
one child, but there are likely dozens of children with similar
problems in each school district
around America. Bobby won’t be the last time we see this
exact, or pretty similar, issue.
I personally found this strategy to work pretty well for this
scenario. Especially if we are
able to involve the child’s parents or a school psychologist, we
will be able to better cater our
plan of action towards the needs of the individual child (Nunn
& McMahan, 2000). By doing
this, we aren’t just taking a canned remedy and applying it to
any child that exhibits similar
problems.
Classroom Implementation
While the IDEAL problem solving strategy can be used in
almost any circumstance, I
feel that it will be relied on heavily in science classes. In a
science lab, you can pretty much
tailor the entire lab to the IDEAL strategy. Typically, you’re
already going to identify what the
problem is, what outcome you’re looking for, identify ways that
you’ll conduct the experiment,

and form a hypothesis all before you even begin the experiment.
Afterwards, you’ll analyze and
compare your results and record what you’ve learned.
Aside from science labs, I feel that the IDEAL strategy will
facilitate just about any
lesson. You can apply these steps in determining how you will
present the material to a given
group of students. For example, you might have two classes
going over the exact same lesson.
However, due to certain personalities in each class, you decide
that you may have to present the
IDEAL STRATEGY 5
information in different manners. Using the IDEAL strategy,
you can determine how you will
present the information to each class. Afterwards, you’ll have
another useful tool in the toolbox
for future classes.
On the other hand, this might not work at all. By anticipating
outcomes, you leave it up
to chance. Granted, the chances are in your favor after
completing the first four steps, but there
is still a chance that you are selecting the wrong course of

action.
Conclusion
As we’ve discussed, the IDEAL strategy is fairly simple to
follow. By identifying the
problem and defining goals, you lay out what the problem is and
what you want the end state to
be. By exploring possible strategies, anticipating the outcome,
and acting, you analyze different
courses of action, pick the best one, and put it into action.
Afterwards, you look back and learn
from the whole experience. Whether good or bad, you will
learn and be able to deal with similar
situations in the future.
In Bobby’s case, we identified that he doesn’t work well in
groups, and that our goal is to
get him to accomplish his tasks in a group setting. We looked
at two courses of action after
(hopefully) speaking to his parents and a school psychologist.
One was obviously not going to
work, while the other was more likely to show success. We
chose a course of action in which
Bobby would be slowly introduced to a larger and larger group.
Finally, we looked at how easily the IDEAL strategy would be

applied in a science class,
or more specifically in a science lab. We also looked at how
the IDEAL strategy seems to be
useful in any class, given different requirements dictated by
personalities within the classes. We
ended the discussion by addressing that the IDEAL strategy has
a downside due to “guessing”
which course of action is the most appropriate for your
situation.
IDEAL STRATEGY 6
References
LeFrançois, G. (2011). Psychology for teaching (11th ed.). San
Diego, CA: Bridgepoint
Education, Inc.
Nunn, G. D., & McMahan, K. R. (2000). 'IDEAL' problem
solving using a collaborative effort
for special needs and at-risk students. Education, 121(2), 305.

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