Using the Inventory of Problems-29 (IOP-29) with the Inventory of Problems Memory (IOP-M) in Malingering-Related Assessments: a Study with a Slovenian Sample of Experimental Feigners

Abstract

A recently published article harshly criticized forensic practitioners operating in Slovenia for not including in their assessments any tests specifically designed to assess negative distortion (Areh, 2020). To promote better forensic assessment practice and stimulate future research on symptom and performance validity assessment in Slovenia, the current study translated the Inventory of Problems-29 (IOP-29; Viglione & Giromini, 2020) and its recently developed memory module (IOP-M; Giromini et al., 2020) into Slovene language and tested their validity and effectiveness by conducting a simulation/analogue study. Among 150 volunteers, 50 completed the IOP-29 and IOP-M under standard instructions; 50 were asked to respond as if they suffered from depression; and 50 were asked to respond pretending to suffer from schizophrenia. Statistical analyses showed that (1) the IOP-29 discriminated well between simulators and honest test-takers (d ≥ 3.56), demonstrating the same effectiveness when inspecting feigned depression (sensitivity = 88%) and feigned schizophrenia (sensitivity = 88%) at an almost perfect specificity (98%); (2) the IOP-M identified 50% of simulators of depression and 80% of simulators of schizophrenia at perfect specificity (100%); and (3) combining the results of the IOP-29 with those of the IOP-M notably improved classification accuracy so as to demonstrate incremental validity. Taken together, these findings provide initial support for using the IOP-29 and IOP-M in applied settings in Slovenia. Limitations related to the design of the study and recommendations for further research are provided.

Full text

Vol.:(0123456789)
1 3
Psychological Injury and Law
https://doi.org/10.1007/s12207-021-09412-2
Using theInventory ofProblems‑29 (IOP‑29) withtheInventory
ofProblems Memory (IOP‑M) inMalingering‑Related Assessments:
aStudy withaSlovenian Sample ofExperimental Feigners
MajaMašaŠömen1· StašaLesjak1· TejaMajaron1· LucaLavopa2· LucianoGiromini2· DonaldViglione3·
AnjaPodlesek1
Received: 1 February 2021 / Accepted: 6 May 2021
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
Abstract
A recently published article harshly criticized forensic practitioners operating in Slovenia for not including in their assess-
ments any tests specifically designed to assess negative distortion (Areh, 2020). To promote better forensic assessment prac-
tice and stimulate future research on symptom and performance validity assessment in Slovenia, the current study translated
the Inventory of Problems-29 (IOP-29; Viglione & Giromini, 2020) and its recently developed memory module (IOP-M;
Giromini etal., 2020) into Slovene language and tested their validity and effectiveness by conducting a simulation/analogue
study. Among 150 volunteers, 50 completed the IOP-29 and IOP-M under standard instructions; 50 were asked to respond as
if they suffered from depression; and 50 were asked to respond pretending to suffer from schizophrenia. Statistical analyses
showed that (1) the IOP-29 discriminated well between simulators and honest test-takers (d ≥ 3.56), demonstrating the same
effectiveness when inspecting feigned depression (sensitivity = 88%) and feigned schizophrenia (sensitivity = 88%) at an
almost perfect specificity (98%); (2) the IOP-M identified 50% of simulators of depression and 80% of simulators of schizo-
phrenia at perfect specificity (100%); and (3) combining the results of the IOP-29 with those of the IOP-M notably improved
classification accuracy so as to demonstrate incremental validity. Taken together, these findings provide initialsupport for
using the IOP-29 and IOP-M in applied settingsin Slovenia. Limitations related to the design of the study and recommenda-
tions for further research are provided.
Keywords Malingering· Psychological assessment· Symptom validity tests· Performance validity tests· Inventory of
Problems
Malingered mental illness appears to be as old as mental
illness itself (Resnick, 1984). According to the Diagnostic
and Statistical Manual of Mental Disorders (DSM-5; Ameri-
can Psychiatric Association, 2013), the term “malingering”
refers to “the intentional production of false or grossly exag-
gerated physical or psychological symptoms, motivated by
external incentives, such as avoiding military duty, avoiding
work, obtaining financial compensation, evading criminal
prosecution, or obtaining drugs” (p. 726). Resnick (1984)
also mentions purposes such as wanting to transfer out of
prison, avoid civil litigation, or achieve hospital admission,
which is most frequent among the homeless. Among pris-
oners specifically, relocation, medication, compensation,
attention, or amusement may all be reasons why inmates
may feign mental illness. However, it must be emphasized
that, while feigning symptomatology is present in both facti-
tious disorder and malingering, the DSM-5 considers facti-
tious disorder a genuine mental disorder as it is motivated
by internal incentives, whereas malingering is considered
deliberate behavior and as such not a form of psychopathol-
ogy (Rogers & Bender, 2018).
Three different models have been proposed (Rogers
& Bender, 2018) as explanations for malingering. The
MajaMaša Šömen, Staša Lesjak, and Teja Majaron contributed
equally to this paper.
* Anja Podlesek
anja.podlesek@ff.uni-lj.si
1 Department ofPsychology, Faculty ofArts, University
ofLjubljana, Ljubljana, Slovenia
2 Department ofPsychology, University ofTurin, Turin, Italy
3 California School ofProfessional Psychology, Alliant
International University, SanDiego, CA, USA

Psychological Injury and Law
1 3
adaptational model describes malingering as the result of
a cost-benefit analysis, where the malingerer predicts the
utility of malingering will be greater than any of alternative
solutions. The pathogenic model hypothesizes that, at first,
malingerers invent their symptoms because of an actual dis-
ability that they are experiencing and trying to control and
that, only later on, they lose the control over malingering.
The criminological model describes malingering as an anti-
social act which is more often committed by people with
antisocial traits. Regardless of which of these explanations
is more suitable, malingering should be recognized and pre-
vented in its early stages as it presents a tremendous cost for
society. Indeed, undetected malingering cases are provided
with compensations or unnecessary psychiatric treatment
creating enormous financial expenses (Chafetz & Underhill,
2013), and more broadly malingering compromises the
efficacy of the entire mental health system, as practitioners
waste medical resources and time that they should dedicate
to provide treatment to true patients (Viglione etal., 2017).
Malingering is not an uncommon condition. Mittenberg
etal. (2003) estimate that 29% of personal injury cases,
30% of disability cases, 19% of criminal cases, and 8% of
medical cases probably involve malingering or symptom
exaggeration. Larrabee etal. (2009) even suggested that the
base rate of malingering in psychological injury cases is
40%, although Young (2015, 2019) has convincingly char-
acterized this estimate as too high. Nevertheless, given that
malingering can cause mistaken, life-changing decisions in
high stake evaluations and the misuse of mental health and
financial resources, forensic and other high-stake evaluations
should always evaluate the credibility of symptom presenta-
tions and claims of impairment (Bush etal., 2014).
Symptom andPerformance Validity
Assessment
To evaluate the credibility of presented complaints, foren-
sic assessors rely on various techniques and tests. A widely
accepted tool, in this context, is the Structured Interview
of Reported Symptoms (SIRS; Rogers, Bagby, etal., 1992;
Rogers, Kropp, etal., 1992; for an updated version, see also
Rogers etal., 2010, and Rogers etal., 2020). It is a compre-
hensive, interview measure that is frequently administered
to evaluate response styles associated with intentional distor-
tion of self-reported psychiatric symptoms. Another inter-
view that is widely used in the field is the Miller Forensic
Assessment of Symptoms Test (M-FAST; Miller, 2001). In
contrast to the SIRS, the 25-item M-FAST is typically used
for screening purposes only.
In addition to structured interviews, practitioners usually
administer both self-report symptom validity tests (SVTs)
and performance validity tests (PVTs) too. An SVT is an
instrument designed to evaluate the extent to which the
test-takers complain about symptoms or problems that do
not really exist in the real clinical world or that occur very
rarely (sometimes called “pseudosymptoms”). An example
is the Structured Inventory of Malingered Symptomatol-
ogy (SIMS; Smith & Burger, 1997), a 75-item, true/false
questionnaire covering a broad spectrum of improbable
symptoms concerning conditions such as psychosis, neuro-
logical impairment, and affective disorders. Other examples
are the embedded validity scales in multiscale personality
inventories such as the Minnesota Multiphasic Personality
Inventory (MMPI-3; Ben-Porath & Tellegen, 2020a,b), Per-
sonality Assessment Inventory (PAI; Morey, 1991, 2007),
and Millon Clinical Multiaxial Inventory (MCMI-IV; Millon
etal., 2015).
PVTs, in contrast, are performance-based measures of
cognitive ability that are typically aimed at detecting poor
cooperation, motivation, or effort. Examples of PVTs are the
test of memory malingering (TOMM; Tombaugh, 1996), the
Victoria Symptom Validity Test (VSVT; Slick etal., 2005),
and the Word Memory Test (WMT; Green etal., 1996). The
main reason for their efficacy in discriminating valid versus
invalid cognitive symptom presentations is that most feign-
ers do not realize that even brain-injured patients typically
perform quite well on simple recognition tasks, and many
mistakenly believe that severe memory problems might
occur with a variety of different mental health disorders.
As such, they tend to exert inadequate or less than optimal
effort and often perform more poorly than bona fide patients.
During the past few years, research has shown that com-
bining multiple methods with different symptom validity
assessment approaches on a single case can yield substan-
tial incremental validity (Boone, 2013; Erdodi etal., 2017;
Giger etal., 2010; Giromini etal., 2019a, b, c; Larrabee,
2008). The underlying assumption is that different tools
may tap different feigning strategies, so that using multiple,
diverse tests might provide incremental validity compared to
using one test alone or two similar measures using the same
method or feigning strategies. Statistically, the lower the
correlation between any two tests, the greater the potential
for incremental validity and better prediction (Bush etal.,
2014). In addition, because of the large amount of variance
shared by measures using the same method, using tests that
differ in the method employed is preferable. Practitioners are
therefore encouraged to include multiple SVTs and PVTs in
their assessments, so as to provide incremental validity and
increased signal detection (Sherman etal., 2020).
The Inventory ofProblems‑29 andInventory
ofProblems—Memory
Because malingerers differ in the preferred strategies of defi-
ance and different situations induce different approaches to

Psychological Injury and Law
1 3
malingering, Viglione and Giromini developed two measures
that contain multiple detection strategies, namely, the Inven-
tory of Problems-29 (IOP-29; Viglione etal., 2017; Viglione
& Giromini, 2020) and the Inventory of Problems—Memory
(IOP-M; Giromini etal., 2020). The IOP-29 is typically con-
ceived of as an SVT, and the IOP-M is a forced-choice PVT;
each takes about 10min to be completed. When used together,
the IOP-29 and IOP-M might offer a quick and yet effective
and multimethod validity check (Giromini etal., 2020).
The SVT component of the “IOP combo” is the IOP-29, a
29-item, self-administered test focused on the credibility of
various symptom presentations (Viglione & Giromini, 2020).
Two of its items have an open-ended format, whereas all
other 27 offer three response options, i.e., “true,” “false,” and
“doesn’t make sense.” Differently from many other measures
used in the field, its chief feigning score—the False Disorder
probability Score (FDS)—does not compare the responses
of the test-taker against a single set of normative reference
values obtained from a large sample of non-clinical respond-
ers. Instead, it considers two different sets of reference val-
ues, one coming from bona fide patients and one coming
from experimental simulators. A low score suggests that
the IOP-29 under examination closely resembles the IOP-
29s included in the bona fide reference sample, and a high
score suggests that it closely resembles those included in the
simulators reference sample. Derived from logistic regres-
sion, the FDS thus is a probability score that ranges from
zero to one, with higher scores reflecting less credible symp-
tom presentations. According to the test manual (Viglione
& Giromini, 2020), a score of FDS ≥ 0.50 should offer sen-
sitivity and specificity values of about 80% across different
conditions. A higher cutoff, of FDS ≥ 0.65, would yield a
specificity of about 90%, and a lower cutoff, of FDS ≥ 0.30,
would yield a sensitivity of about 90%. Research, so far, has
largely supported these claims (e.g., Gegner etal., 2021;
Giromini etal., 2018; Giromini etal., 2019a, b, c; Ilgunaite
etal., 2020; Roma etal., 2019; Winters etal., 2020). IOP-
29 generates similar validity results to the MMPI and PAI
validity scales (Viglione etal., 2017), even outperforming
the SIMS (Giromini etal., 2018) and the Rey Fifteen Item
Test (Gegner etal., 2021), and providing incremental validity
when combined with the TOMM (Giromini etal., 2019a, b,
c) and the MMPI-2 (Giromini etal., 2019a, b, c). Thus, in
their introductory description and conceptualization of the
field of psychological injury and law, the Editor-in-Chief of
Psychological Injury and Law and his colleagues referred to
the IOP-29 as “a newer stand-alone SVT that has the required
psychometric properties for use in forensic disability and
related assessments. Its research profile is accumulating, a
hallmark for use in legal settings” (Young etal., 2020; p. 9).
The PVT component of the “IOP combo” is the IOP-M
(Giromini etal., 2020), a performance validity test mod-
ule designed to be used in combination with the otherwise
free-standing symptom validity test, IOP-29. Its main pur-
pose is to detect feigned memory deficits or, more broadly,
cognitive impairment. It is administered immediately after
completing the IOP-29. It contains 34 implicit recognition
two-alternative-forced-choice test items. The results of the
developmental study conducted by Giromini etal. (2020), in
which 192 participants were instructed to respond honestly
(honest controls) and 168 were instructed to feign mental
illness (experimental simulators), suggested that the IOP-M
has the potential to yield incremental validity and that it
might improve classification accuracy over using the IOP-
29 alone. In fact, only 6 of the 168 simulators (i.e., less
than 4%) passed both the IOP-29 and IOP-M, and only 3 of
the 192 honest responders (i.e., less than 2%) failed both.
However, differently from the IOP-29, the IOP-M has not
been thoroughly investigated. To our knowledge, only two
studies to date — one in Australia by Gegner etal. (2021)
focusing on feigned mild traumatic brain injury (mTBI) and
one in Brazil by de Francisco Carvalho etal. (2021) focusing
on post-traumatic stress disorder (PTSD) — have replicated
the initial findings of Giromini etal. (2020). As such, addi-
tional research on the effectiveness of the IOP-M would be
beneficial.
The Aim ofthePresent Study
A recent article by Areh (2020) has pointed out that forensic
assessors pay little or no attention to possible malingering in
Slovenia. In a quite provocative article (its title is Forensic
assessment may be based on common sense assumptions
rather than science), he summarized the psychological
tests that had been used more frequently in 166 forensic
personality assessments conducted in Slovenia in the period
2003–2018 and argued that “possible malingering of the per-
son being evaluated was not detected” (p. 1). In fact, out of
166 inspected evaluations, 42 on criminal cases and 124 on
civil cases, none included any stand-alone SVTs or PVTs,
and very few included any broadband personality inventories
that incorporate embedded measures of response style. For
instance, the MMPI was used in 3 evaluations only, repre-
senting less than 2% of the total. As such, he criticized Slo-
venian forensic practitioners for not including in their assess-
ments “specific psychological instruments used to detect
malingering” (p. 7). It should be noted, however, that a brief
literature search revealed that commonly used SVTs or PVTs
such as the SIMS or TOMM have not been researched or
validated in Slovenia. Thus, providing Slovenian practition-
ers with an empirically sound measure of negative response
bias in Slovene language would be beneficial.
To respond to this call, we developed a Slovene adaptation
of the IOP-29 and IOP-M and tested their joint validity. The
IOP-29 has already been adapted to numerous other languages

Psychological Injury and Law
1 3
— English, German, French, Dutch, Italian, Spanish, Brazil-
ian and European Portuguese, traditional and simplified Chi-
nese, and Lithuanian (www. iop- test. com). Published studies
have shown solid support in its initial English language and
promising adaptation to other languages (e.g., Ilgunaite etal.,
2020). However, the IOP-M has been cross-validated only by
Gegner etal. (2021), and no Slovene version of either IOP
instrument was available, when we designed our study. The
primary purpose of our research project was thus to determine
how a healthy Slovene-speaking population would respond to
both tests and how many simulators that present themselves
as psychologically injured would get detected by the IOP
instruments when both test components (i.e., the IOP-29 and
IOP-M) are administered. We expected results similar to those
with samples speaking other languages, that is that the IOP-29
and IOP-M would both individually discriminate simulators
from an honest non-patient sample, and that the IOP-M would
identify simulators who were not identified by the IOP-29.
Method
Participants
We decided to test whether the IOP-29 is able to effectively
discriminate simulators of depression and schizophre-
nia from honest responders. Based on previous research
(Giromini etal., 2020), no differences were expected
between simulators of depression and schizophrenia. Thus,
considering an alpha of 0.05, a power of 0.80, and an alloca-
tion ratio of 2 to 1 (two simulator groups, one control group),
it was determined that 144 participants would be needed (48
in one group and 96 in the other) to detect a Cohen’s d effect
size of 0.50. Accordingly, we aimed to recruit approximately
50 participants for the honest group and approximately 50
participants for each of the two simulator groups.
The overall sample included 150 Slovenian partici-
pants, aged 18 to 75years (M = 30.5, SD = 13.3), with 57
(38%) being men. To validate both measures, participants
were randomly assigned to three groups with one respond-
ing honestly and the other two attempting to convince the
examiner that they suffered depression or schizophrenia
following a work-related accident causing physical pain.
The three groups, each with 50 participants, did not differ
significantly with regard to gender, χ2(2) = 0.68, p = 0.71;
age, F(2, 147) = 1.24, p = 0.29; and education, χ2(2) = 5.03,
p = 0.08. In the “honest” group, there were 19 (38%) men.
This group had an average age of 28.2years (SD = 11.1),
and 27 (54%) participants had high school education or less,
and 23 (46%) participants had a bachelor’s degree or more.
Simulators of depression had an average age of 32.3years
(SD = 15.5), with 34 (68%) participants having a high school
education or less and 16 (32%) having bachelor’s degree or
more, and 17 (34%) of them were men. The third group,
which was simulating schizophrenia, had an average age of
27.5 (SD = 11.1) and included 21 (42%) men; 23 (46%) par-
ticipants had a high school education or less, and 27 (54%)
had a bachelor degree or more.
Measures
As with other linguistic adaptations of the IOP-29 and the
IOP-M, our Slovenian versions were developed by follow-
ing the classic translation-back translation procedure method
(Brislin, 1980; Geisinger, 2003; Van de Vijver & Hambleton,
1996). All participants were then administered both the IOP-
29 and the IOP-M in Slovene language.
Inventory of Problems-29 (Viglione & Giromini,2020).
The IOP-29 is a self-administered test designed to assist
practitioners to evaluate the credibility of symptom presen-
tations related to various psychiatric or cognitive disorders.
Its main purpose is to discriminate bona fide patients from
feigners. It is composed of 29 items and administered via
classic paper-and-pencil format or online, using a tablet or
a PC. Items address diverse mental health symptoms, atti-
tudes towards one’s own condition, test-related behaviors,
claims of impairment, and problem-solving abilities. As
noted above, the chief feigning measure of the IOP-29 is the
FDS, a probability value derived from logistic regression,
which compares the responses of the test-taker against those
provided by a group of bona fide patients and those provided
by a group of experimental feigners (Viglione & Giromini,
2020). The higher the score, the lower the credibility of the
Table 1 Means (and standard deviation in parentheses) of IOP-29
FDS and IOP-M scores in different groups
Simulator
Honest Depression Schizophrenia
IOP-29 0.16 (0.13) 0.75 (0.19) 0.78 (0.21)
IOP-M 33.5 (0.8) 28.6 (4.4) 23.1 (6.7)
Table 2 Classification accuracy of IOP-29 FDS and IOP-M
a Specificity
b Sensitivity
Simulator
Honest Depression Schizophrenia
IOP-29
FDS ≥ .50 49 (98%)a6 (12%) 6 (12%)
FDS < .50 1 (2%) 44 (88%)b44 (88%)b
IOP-M
# of correct ≥ 30 50 (100%)a25 (50%) 10 (20%)
# of correct < 30 0 (0%) 25 (50%)b40 (80%)b

Psychological Injury and Law
1 3
presentation. According to the test authors, the cutoff score
of FDS ≥ 0.50 ensures the best balance between sensitivity
and specificity (Giromini etal., 2018; Viglione & Giromini,
2020; Viglione etal., 2017).
Inventory of Problems–Memory (Giromini etal.,2020).
The IOP-M is administered immediately after completing the
IOP-29. It consists of 34 two-alternative-forced-choice items.
Each item presents two words or brief statements — one that
was part of the IOP-29-item content (target) and one that was
not (foil). To preserve the standard IOP-29 administration
procedure, incidental memory is tested: there is no mention
of a subsequent memory test or an expectation to remember
the IOP-29 items. Based on Giromini etal. (2020) findings, at
least 30 of the 34 IOP-M items should be answered correctly
by individuals who do not suffer from relatively severe cogni-
tive problems. As such, if the total number of IOP-M items
answered correctly is lower than 30, the performance is con-
sidered to be non-credible. Conversely, a total score of ≥ 30
is interpreted as a credible result.
Procedure
The study was approved by the Ethical Committee of the
Faculty of Arts, University of Ljubljana. Participants were
recruited from the general population via convenience
snowball sampling. That is, we first distributed flyers in
the faculty and invited our family members, friends, and
acquaintances to participate in the study. We also asked
our participants to help us spread the word and invite their
acquaintances to participate as well, if there was interest.
Although participation was completely voluntary, all partici-
pants were informed that, upon the completion of data analy-
sis, three of them would receive a 20€ Amazon voucher.
Individuals who have met the inclusion criteria (having
Slovenian nationality, not having any psychiatric or cogni-
tive disorders, no familiarity with the IOP-29) were then
asked to sign an informed consent form and were divided
into three groups of 50. The first group was asked to answer
as honestly as possible, the second group was instructed to
Fig. 1 Distribution of IOP-29
FDS scores by group
IOP-29 FDS
1.00
.90
.80
.70
.60
.50
.40
.30
.20
.10
.00
20151050 20151050
IOP-29 FDS
1.00
.90
.80
.70
.60
.50
.40
.30
.20
.10
.00
20151050
S
imulator of
SC
Z
S
imulator of DE
P
Ho
n
es
t
Honest Simulator of depression Simulator of schizophrenia
Fig. 2 Distribution of IOP-M
scores by group
IOP-M (# of correct)
35
30
25
20
15
10
5
3020100
3020100
IOP-M (# of correct)
35
30
25
20
15
10
5
3020100
Si
mu
l
ator of SCZ
Si
mu
l
ator of DEP
H
onest
Honest Simulator of depression Simulator of schizophrenia

Psychological Injury and Law
1 3
simulate schizophrenia, and the third group was instructed
to simulate depression. Specifically, participants assigned to
the schizophrenia and depression group were presented with
a short vignette on the situation in which being diagnosed
with mental illness would lead to an economic advantage
and were instructed to take the tests as if they wanted to con-
vince the examiner that they were experiencing symptoms
associated with schizophrenia or depression, respectively. A
list of symptoms of the disorder to be feigned was presented.
Additionally, both groups were cautioned not to overdo the
expression of the disorder in order to not be detected as
feigners. All participants were administered a short soci-
odemographic questionnaire in addition to the IOP-29 and
IOP-M. For each participant, FDS values were calculated
using the official IOP-29 scoring program, which can be
found at www. iop- test. com, and IOP-M errors were counted
using a scoring sheet created by the test authors (Giromini
etal., 2020).
Results
Table1 shows the scores obtained on the two instruments
in different groups of participants. As expected, the IOP-
29 FDS values statistically significantly differed among the
three groups, F(2, 147) = 193.52, p < 0.001. More specifi-
cally, Bonferroni corrected post hoc tests revealed that the
“honest” group scored notably lower than both simulators
Fig. 3 Scatterplot IOP-29
versus IOP-M scores within the
“honest” group
IOP-M (# of correct)
3530252015105
IOP-29 FDS
1.00
.90
.80
.70
.60
.50
.40
.30
.20
.10
.00
IOP-M (# of correct)
3530252015105
IOP-29 FDS
1.00
.90
.80
.70
.60
.50
.40
.30
.20
.10
.00
Fig. 4 Scatterplot IOP-29 versus IOP-M scores within the simulators of depression

Psychological Injury and Law
1 3
of depression (d = 3.69, p < 0.001) and simulators of schiz-
ophrenia (d = 3.56, p < 0.001), whereas the two simulator
groups did not statistically significantly differ from each
other (d = 0.14, p ≈ 1.00). The IOP-M yielded statistically
significant group differences as well, F(2, 147) = 62.93,
p < 0.001. In this case, however, all pairwise comparisons
were statistically significant: the “honest” group had a nota-
bly higher IOP-M score than both the simulators of depres-
sion (d = 1.55, p < 0.001) and the simulators of schizophre-
nia (d = 2.18, p < 0.001), and the simulators of depression
scored higher than the simulators of schizophrenia (d = 0.97,
p < 0.001).
In terms of classification accuracy, the standard IOP-29
cutoff score of FDS ≥ 0.50 yielded a specificity of 0.98 and
a sensitivity of 0.88 (Table2). Noteworthy, the same exact
sensitivity results emerged when inspecting feigned depres-
sion and feigned schizophrenia. The IOP-M showed a perfect
specificity, but its sensitivity was notably higher in the schiz-
ophrenia simulators’ group (0.80) than it was for the simula-
tors of depression (0.50). To offer a better appreciation of
the performance of both the IOP-29 and IOP-M, Figs.1 and
2 show full frequency distributions of FDS scores across
the three groups.
To test the incremental validity, three scatterplots were
examined. As shown in Fig.3, the only false-positive gener-
ated by the IOP-29 FDS was correctly classified as a (true)
negative outcome by the IOP-M. Figure4 shows that, when
inspecting the simulator depression group, four of the six
false-negative classifications generated by the IOP-29 FDS
were correctly classified as (true) positive outcomes by the
IOP-M. Likewise, Fig.5 shows that, when inspecting the
simulator schizophrenia group, four of the six false-negative
classifications generated by the IOP-29 FDS were correctly
classified as (true) positive outcomes by the IOP-M. Also
noteworthy, in the “honest” group, no one failed both the
IOP-29 and IOP-M, and in each of the simulator subgroups,
only two cases out of 50 passed both tests. The overall fre-
quency with which both the IOP-29 and IOP-M misclassified
the same case was 4 out of 150, i.e., 2.7%.
Discussion
The aim of our study was to test the validity of our Slovenian
adaptation of the Inventory of Problems-29 (IOP-29; Viglione
& Giromini, 2020) and Inventory of Problems–Memory (IOP-
M; Giromini etal., 2020). Our statistical analyses showed
that, when comparing the mean values of the IOP-29 FDS
in the honest versus the two simulating groups, the IOP-29
discriminated significantly between the groups. However,
no differences between the two simulating groups emerged.
The average IOP-29 FDS values found in the two simulat-
ing groups (0.75 for the depression simulants and 0.78 for
the schizophrenia simulants) are similar to those observed in
experimental simulator samples in other studies (e.g., 0.77
in Ilgunaite etal., 2020; 0.82 in Giromini etal., 2019a, c).
Honest versus both simulator groups also differed for the IOP-
M, but the pairwise comparison between the two simulating
groups was significant as well. More importantly, combining
the results of the IOP-29 with those of the IOP-M remark-
ably increased classification accuracy, both when inspecting
feigned depression and when inspecting feigned schizophre-
nia. All in all, thus, our study provides additional support for
the growing research base for using the IOP-29 and IOP-M
in applied settings. Besides, this article fills an important gap
within the Slovenian forensic context (Areh, 2020), given
that (to our knowledge) no stand-alone SVTs or PVTs with
research support were available to Slovenian practitioners,
prior to this publication.
The effect sizes generated by the IOP-29 when comparing
the honest group against the two simulator groups were very
Fig. 5 Scatterplot IOP-29
versus IOP-M scores within the
simulators of schizophrenia
IOP-M (# of correct)
3530252015105
IOP-29 FDS
1.00
.90
.80
.70
.60
.50
.40
.30
.20
.10
.00

Psychological Injury and Law
1 3
large, d ≥ 3.56 (for characterization of d values in malinger-
ing research, please see Rogers etal., 2003). Besides, the
Slovenian IOP-29 yielded excellent classification accuracy
both in terms of specificity (98%) and sensitivity (88% in
both simulating groups). Given that, the Slovenian IOP-29
proved to be very accurate in our study. Also, noteworthy,
there were no significant differences between simulators who
faked depression versus schizophrenia. This finding is con-
sistent with a previous study conducted by Giromini etal.
(2019c), in which IOP-29 scores produced by feigners of
depression, schizophrenia, mTBI, and PTSD did not signifi-
cantly differ from each other. As such, our study seems to
confirm Viglione and Giromini’s (2020) claim that the IOP-
29 likely performs similarly well when used in remarkably
different contexts and with different symptom presentations.
Such generalizability of a single cutoff score across different
disorders, cultures, and languages has rarely if ever demon-
strated for other SVTs.
Another fact that deserves mentioning is that, in our inves-
tigation, the IOP-29 performed similarly well as it previously
did in other simulation studies conducted in Italy (Giromini
etal., 2019b), Lithuania (Ilgunaite etal., 2020), Portugal
(Giromini etal., 2019a), UK (Winters etal., 2020), and Aus-
tralia (Gegner etal., 2021). To some extent, thus, our inves-
tigation also contributes to the growing empirical research
suggesting that the IOP-29 can be applied cross-culturally
with no need to make any significant adjustments to its FDS
formula and cutoffs.
When compared to the IOP-29, the IOP-M showed
higher specificity (100%), but lower sensitivity (≈ 90% for
the IOP-29; ≤ 80% for the IOP-M). Furthermore, the sensi-
tivity of the IOP-M was notably higher when considering
simulators of schizophrenia (80%) rather than when consid-
ering simulators of depression (50%). This finding could be
possibly attributed to the nature of the IOP-M and the dif-
ference between the two conditions. More specifically, one
might speculate that, while people simulating schizophrenia
likely linked symptoms of abnormal reality interpretation
with memory deficits, depression simulators perhaps did not
recognize memory deficits as the most common symptom of
depression — and this may be the reason why the difference
between the two simulating groups was found on IOP-M.
Nevertheless, the examination of scatterplots revealed that
the combination of both test components (IOP-29 and IOP-
M) yielded promising results regarding the classification of
the participants both when testing feigned depression and
when testing feigned schizophrenia. Indeed, the informa-
tion that, with only two exceptions, at least one of the test
components was able to identify the feigners’ testing results
as invalid is very encouraging. Similarly, importantly, the
only one false-positive result generated by the IOP-29 was
correctly classified as a credible performance by the IOP-
M. Thus, it does seem that adding the IOP-M contributes
to both the sensitivity and specificity of the original IOP-
29, consistent with Giromini etal. (2020) and Gegner etal.
(2021).
Several limitations, however, should be underscored.
First, since we did not include in our study any other SVTs
or PVTs, comparative validity could not be investigated.
On the other hand, the lack of such instruments in Slovene
language is exactly one of the primary reasons why this
study was initiated. Second, our findings are limited by the
fact that we did not have access to any clinical samples,
so that our study essentially is a sensitivity study. Actual
overall classification accuracy is likely to be lower because
of reduced specificity if clinical samples were employed.
Thus, research with genuinely impaired individuals and
feigners is needed to better appreciate the specificity of the
Slovenian IOP-29 and IOP-M. Third, this study only inves-
tigated feigned depression and feigned schizophrenia, so
that additional research is needed to appreciate the extent
to which the Slovenian IOP-29 and IOP-M could be used in
applied settings in which other problems (e.g., pain, mTBI
symptoms, etc.) may be feigned. Fourth, as is the case for
all simulation/analogue studies, the ecological validity of
our investigation may be questioned, as there is no way to
assess whether real-life malingerers would adopt the same
strategies utilized by our experimental simulators, when pre-
tending to be mentally ill. Additionally, group assignment
was a quasi-independent variable, and we did not manipulate
the valid versus invalid response condition but randomly
assigned participants to the given instruction. The internal
validity of such a research paradigm depends on the fidelity
with which participants perform the given instructions (Rai
etal., 2019). In a study using the experimental malinger-
ing paradigm, An etal. (2019) found that the group that
feigned cognitive decline performed well despite being
asked to try to feign cognitive deficits, possibly because
they made an effort to achieve credible feigning as required
by the instructions given, and that some participants in the
control group performed worse than expected according to
their abilities, possibly due to lack of interest and low effort,
leading to an underestimation of the difference between the
control and simulating groups. Unfortunately, we could not
rely on established SVTs or PVTs as criteria for monitor-
ing participants’ compliance with the given instructions, as
such instruments do not exist in Slovene. In the absence
of a gold standard, we could recommend using tests such
as the TOMM or the Rey Fifteen Item Test, which is not
language-based, to determine the extent to which simula-
tors follow the feigning instructions. Another option would
be to include bilingual participants who speak both Slovene
and English (or some other languages, e.g., Italian) and give
them the IOP in Slovene and another consolidated SVT (e.g.,
the MMPI, SIMS, etc.) in another language to check their
compliance with the feigning instructions.

Psychological Injury and Law
1 3
Nevertheless, this study is the first to independently rep-
licate Giromini etal. (2020) encouraging findings concern-
ing the potential utility of the IOP-M when investigating
feigned depression and feigned schizophrenia, and the first
to contribute to the study of the IOP-29 and IOP-M within a
Slovenian sample. Given the encouraging results, we invite
Slovenian researchers and practitioners to contact the cor-
responding author, in case they were interested in using or
further researching the IOP instruments.
Funding The authors acknowledge the financial support from the Slo-
venian Research Agency (research core funding No. P5-0110).
Data Availability For test security reasons, our data will not be placed
in an open access repository. However, we will be willing to share it
with interested readers upon reasonable request.
Declarations
Ethics Approval All procedures performed in studies involving human
participants were in accordance with the ethical standards of the insti-
tutional research committee and with the 1964 Helsinki declaration and
its later amendments or comparable ethical standards. The study was
approved by the Ethical Committee of Faculty of Arts, University of
Ljubljana, Approval No. 172-2019.
Informed Consent Informed consent was obtained from all individual
participants included in the study.
Conflict of Interest The fifth and sixth authors declare that they own a
share in the corporate (LLC) that possesses the rights to Inventory of
Problems. The other five authors declare that they have no conflict of
interest to report.
References
American Psychiatric Association. (2013). Diagnostic and statisti-
cal manual of mental disorders. (5th ed.). American Psychiatric
Association.
An, K. Y., Charles, J., Ali, S., Enache, A., Dhuga, J., & Erdodi, L.
A. (2019). Reexamining performance validity cutoffs within the
Complex Ideational Material and the Boston Naming Test-Short
Form using an experimental malingering paradigm. Journal
of Clinical and Experimental Neuropsychology, 41(1), 15–25.
https:// doi. org/ 10. 1080/ 13803 395. 2018. 14834 88
Areh, I. (2020). Forensic assessment may be based on common sense
assumptions rather than science. International Journal of Law and
Psychiatry, 71, 101607. https:// doi. org/ 10. 1016/j. ijlp. 2020. 101607
Ben-Porath, Y. S., & Tellegen, A. (2020a). MMPI-3 Manual for admin-
istration, scoring, and interpretation. University of Minnesota
Press.
Ben-Porath, Y. S., & Tellegen, A. (2020b). MMPI-3 Technical manual.
University of Minnesota Press.
Boone, K. B. (2013). Clinical practice of forensic neuropsychology.
New York, NY: Guilford.
Brislin, R. W. (1980). Translation and content analysis of oral and writ-
ten material. In H. C. Triandis & J. W. Berry (Eds.), Handbook
of cross-cultural psychology (Vol.1., pp. 389–444). Boston, MA:
Allyn & Bacon.
Bush, S. S., Heilbronner, R. L., & Ruff, R. M. (2014). Psychologi-
cal assessment of symptom and performance validity, response
bias, and malingering: Official position of the Association for
Scientific Advancement in Psychological Injury and Law. Psycho-
logical Injury and Law, 7(3), 197–205. https:// doi. org/ 10. 1007/
s12207- 014- 9198-7
de Francisco Carvalho, L., Reis, A., Colombarolli, M. S., Pasian, S.
R., Miguel, F. K., Erdodi, L. A., Viglione, D. J., & Giromini, L.
(2021). Discriminating feigned from credible PTSD symptoms: A
validation of a Brazilian version of the Inventory of Problems-29
(IOP-29). Advanced online publication. https:// doi. org/ 10. 1007/
s12207- 021- 09403-3
Chafetz, M., & Underhill, J. (2013). Estimated costs of malingered
disability. Archives of Clinical Neuropsychology, 28(7), 633–639.
https:// doi. org/ 10. 1093/ arclin/ act038
Erdodi, L. A., Abeare, C. A., Lichtenstein, J. D., Tyson, B., & T.,
Kucharski, B., Zuccato, B. G., & Roth, R. M. . (2017). Wechsler
Adult Intelligence Scale-Fourth Edition (WAIS-IV) processing
speed scores as measures of non-credible responding – The third
generation of embedded performance validity indicators. Psy-
chological Assessment, 29(2), 148–157. https:// doi. org/ 10. 1037/
pas00 00319
Gegner, J., Erdodi, L. A., Giromini, L., Viglione, D. J., Bosi, J., &
Brusadelli, E. (2021). An Australian study on feigned mTBI
using the Inventory of Problems–29 (IOP-29), its Memory
Module (IOP-M), and the Rey Fifteen Item Test (FIT). Applied
Neuropsychology: Adult. Advance online publication. https:// doi.
org/ 10. 1080/ 23279 095. 2020. 18643 75
Geisinger, K. F. (2003). Testing and assessment in cross-cultural psy-
chology. In J. R. Graham, J. A. Naglieri, & I. B. Weiner (Eds.),
Handbook of psychology (Vol. 10). Assessment Psychology
(pp. 95–118). New Jersey, NJ: John Wiley & Sons. https://doi.
org/https:// doi. org/ 10. 1002/ 04712 64385. wei10 05
Giger, P., Merten, T., Merckelbach, H., & Oswald, M. (2010). Detec-
tion of feigned crime-related amnesia: A multi-method approach.
Journal of Forensic Psychology Practice, 10, 440–463. https:// doi.
org/ 10. 1080/ 15228 932. 2010. 489875
Giromini, L., Barbosa, F., Coga, G., Azeredo, A., Viglione, D. J., &
Zennaro, A. (2019a). Using the inventory of problems-29 (IOP-
29) with the Test of Memory Malingering (TOMM) in symptom
validity assessment: A study with a Portuguese sample of experi-
mental feigners. Applied Neuropsychology: Adult, 27(6), 504–516.
https:// doi. org/ 10. 1080/ 23279 095. 2019. 15709 29
Giromini, L., Carfora Lettieri, S., Zizolfi, S., Zizolfi, D., Viglione, D.,
Brusadelli, E., Perfetti, B., Angiola di Carlo, D., & Zennaro, A.
(2019b). Beyond rare-symptoms endorsement: A clinical com-
parison simulation study using the Minnesota Multiphasic Per-
sonality Inventory-2 (MMPI-2) with the Inventory of Problems-29
(IOP-29). Psychological Injury and Law, 12, 212–224. https:// doi.
org/ 10. 1007/ s12207- 019- 09357-7
Giromini, L., Viglione, D., Pignolo, C., & Zennaro, A. (2018). A clini-
cal comparison, simulation study testing the validity of SIMS and
IOP-29 with an Italian sample. Psychological Injury and Law, 11,
340–350. https:// doi. org/ 10. 1007/ s12207- 018- 9314-1
Giromini, L., Viglione, D. J., Pignolo, C., & Zennaro, A. (2019c).
An Inventory of Problems–29 sensitivity study investigating
feigning of four different symptom presentations via malingering
experimental paradigm. Journal of Personality Assessment, 102,
563–572. https:// doi. org/ 10. 1080/ 00223 891. 2019. 15669 14.
Giromini, L., Viglione, D., Zennaro, A., Maffei, A., & Erdodi, L.
A. (2020). SVT meets PVT: Development and initial valida-
tion of the Inventory of Problems-Memory (IOP-M). Psycho-
logical Injury and Law, 13, 261–274. https:// doi. org/ 10. 1007/
s12207- 020- 09385-8

Psychological Injury and Law
1 3
Green, P., Allen, L. M., & Astner, K. (1996). The Word Memory Test:
A user’s guide to the oral and computer administered forms. Cog-
niSyst Inc.
Ilgunaite, G., Giromini, L., Bosi, J., Viglione, D. J., & Zennaro, A.
(2020). A clinical comparison simulation study using the Inven-
tory of Problems-29 (IOP-29) with the Center for Epidemiologic
Studies Depression Scale (CES-D) in Lithuania. Applied Neu-
ropsychology: Adult. Advance online publication. https://doi.
org/https:// doi. org/ 10. 1080/ 23279 095. 2020. 17255 18
Larrabee, G. J. (2008). Aggregation across multiple indicators improves
the detection of malingering: Relationship to likelihood ratios. The
Clinical Neuropsychologist, 22, 666–679. https:// doi. org/ 10. 1080/
13854 04070 14949 87
Larrabee, G. J., Millis, S. R., & Meyers, J. E. (2009). 40 plus or minus 10,
a new magical number: Reply to Russell. The Clinical Neuropsy-
chologist, 23, 841–849. https:// doi. org/ 10. 1080/ 13854 04090 27967 35
Miller, H. A. (2001). M-FAST: Miller forensic assessment of symptoms
test professional manual. Psychological Assessment Resources
Inc.
Millon, T., Grossman, S., & Millon, C. (2015). Millon Clinical Multi-
axial Inventory–IV (MCMI-IV) manual. Bloomington, MN: NCS
Pearson.
Mittenberg, W., Patton, C., Morgan, E., & Condit, D. (2003). Base rates
of malingering and symptom exaggeration. Journal of Clinical
and Experimental Neuropsychology, 24, 1094–1102. https:// doi.
org/ 10. 1076/ jcen. 24.8. 1094. 8379
Morey, L. C. (1991). Personality assessment inventory–professional
manual. Odessa, FL: Psychological Assessment Resources.
Morey, L. C. (2007). Personality Assessment Inventory (PAI). Profes-
sional manual. (2nd ed.). Psychological Assessment Resources.
Rai, J. K., An, K. Y., Charles, J., Ali, S., & Erdodi, L. A. (2019).
Introducing a forced choice recognition trial to the Rey Complex
Figure Test. Psychology & Neuroscience, 12(4), 451–472. https://
doi. org/ 10. 1037/ pne00 00175
Resnick, P. J. (1984). The detection of malingered mental illness.
Behavioral Sciences & the Law, 2(1), 21–38. https:// doi. org/ 10.
1002/ bsl. 23700 20104
Rogers, R., Bagby, R. M., & Dickens, S. E. (1992). Structured Inter-
view of Reported Symptoms (SIRS) and professional manual.
Odessa, FL: Psychological Assessment Resources.
Rogers, R., & Bender, D. (2018). Clinical assessment of malingering
and deception. (3rd ed.). Guilford Press.
Rogers, R., Kropp, P., Bagby, M., & Dickens, S. (1992). Faking specific
disorders: A study of the structured interview of reported symp-
toms (SIRS). Journal of Clinical Psychology, 48(5), 643–648.
https:// doi. org/ 10. 1002/ 1097- 4679(199209) 48:5% 3c643:: AID-
JCLP2 27048 0511% 3e3.0. CO;2-2
Rogers, R., Sewell, K. W., & Gillard, N. D. (2010). Structured inter-
view of reported symptoms, second edition: professional test
manual. (2nd ed.). Psychological Assessment Resources.
Rogers, R., Sewell, K. W., Martin, M. A., & Vitacco, M. J. (2003).
Detection of feigned mental disorders: A meta-analysis of the
MMPI-2 and malingering. Assessment, 10(2), 160–177. https://
doi. org/ 10. 1177/ 10731 91103 01000 2007
Rogers, R., Velsor, S. F., & Williams, M. M. (2020). A brief commen-
tary on SIRS versus SIRS-2 critiques. Advance online publication.
https:// doi. org/ 10. 1007/ s12207- 020- 09379-6
Roma, P., Giromini, L., Burla, F., Ferracuti, S., Viglione, D. J.,
& Mazza, C. (2019). Ecological validity of the inventory of
problems-29 (IOP-29): An Italian study of court-ordered, psy-
chological injury evaluations using the Structured Inventory
of Malingered Symptomatology (SIMS) as criterion variable.
Psychological Injury and Law, 13, 57–65. https:// doi. org/ 10. 1007/
s12207- 019- 09368-4
Sherman, E. M. S., Slick, D. J., & Iverson, G. L. (2020). Multidimen-
sional malingering criteria for neuropsychological assessment: A
20-year update of the malingered neuropsychological dysfunc-
tion criteria. Archives of Clinical Neuropsychology, 35, 735–764.
https:// doi. org/ 10. 1093/ arclin/ acaa0 19
Slick, D., Hopp, G., Strauss, E., & Thompson, G. B. (2005). VSVT
Victoria Symptom Validity Test. Odessa, FL: Psychological
Assessment Resources.
Smith, G. P., & Burger, G. K. (1997). Detection of malingering: Valida-
tion of the Structured Inventory of Malingered Symptomatology
(SIMS). Journal of the American Academy on Psychiatry and
Law, 25, 180–183.
Tombaugh, T. N. (1996). Test of memory malingering (TOMM). New
York, USA: Multi Health Systems.
Van de Vijver, F., & Hambleton, R. K. (1996). Translating tests. Euro-
pean Psychologist, 1(2), 89–99. https:// doi. org/ 10. 1027/ 1016-
9040.1. 2. 89
Viglione, D. J., Giromini, L., & Landis, P. (2017). The development of
the Inventory of Problems–29: A brief self-administered measure
for discriminating bona fide from feigned psychiatric and cogni-
tive complaints. Journal of Personality Assessment, 99(5), 534–
544. https:// doi. org/ 10. 1080/ 00223 891. 2016. 12338 82
Viglione, D. J., & Giromini, L. (2020). Inventory of Problems–29:
Professional manual. Columbus, OH: IOP-Test, LLC.
Winters, C. L., Giromini, L., Crawford, T. J., Ales, F., Viglione, D. J.,
& Warmelink, L. (2020). An Inventory of Problems–29 (IOP–29)
study investigating feigned schizophrenia and random responding
in a British community sample. Psychiatry, Psychology and Law.
Advance online publication. https:// doi. org/ 10. 1080/ 13218 719.
2020. 17677 20.
Young, G. (2015). Malingering in forensic disability-related assess-
ments: Prevalence 15±15%. Psychological Injury and Law, 8(3),
188–199. https:// doi. org/ 10. 1007/ s12207- 015- 9232-4
Young, G. (2019). The cry for help in psychological injury and law:
Concepts and review. Psychological Injury and Law, 12(3–4),
225–237. https:// doi. org/ 10. 1007/ s12207- 019- 09360-y
Young, G., Foote, W. E., Kerig, P. K., Mailis, A., Brovko, J., Kohutis,
E. A., McCall, S., Hapidou, E. G., Fokas, K. F., & Goodman-
Delahunty, J. (2020). Introducing psychological injury and law.
Psychological Injury and Law, 13, 452–463. https:// doi. org/ 10.
1007/ s12207- 020- 09396-5
Publisher’s Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.