Disintegration as an Additional Trait in the Psychobiological Model of Personality - Assessing Discriminant Validity via Meta-Analysis

Abstract

This meta-analytic study investigates the relations between Disintegration-like phenomena (i.e., various aspects of symptomatology with the prefix “schizo-”, both at the clinical and the sub-clinical level) and the traits of the Psychobiological Model of Personality (PBMP). The empirically based benchmark for assuming the distinctness of the trait Disintegration was .30. The sample included 26 manuscripts with 30 studies and 424 effect sizes. By computing inverse sampling variance weighted mean correlation coefficients under a random-effects assumption, the following associations were found between Disintegration and Harm Avoidance, Novelty Seeking, Reward Dependence, Persistence, Self-Directedness, Cooperativeness, and Self-Transcendence: .23, .04, -.15, -.02, -.23, -.16, and .17, respectively. Two variables were found to moderate the Disintegration - Self-Transcendence correlation. Despite the theoretical expectation and some empirical evidence that Self-Transcendence (and other character traits) should capture variations in Disintegration-like phenomena, our results suggest that schizo-type phenomena are not adequately covered by the PBMP.

Full text

1
Disintegration as an Additional Trait in the Psychobiological Model of Personality
- Assessing Discriminant Validity via Meta-Analysis
Ljiljana B. Lazarević Institute of Psychology, University of Belgrade
Michael Bosnjak GESIS - Leibniz Institute for the Social Sciences and University of Mannheim
Goran Knežević Department of Psychology, University of Belgrade
Boban Petrović Institute for Criminological and Sociological Research
Danka Purić Department of Psychology, University of Belgrade
Predrag Teovanović Faculty for Special Education and Rehabilitation, University of Belgrade
Goran Opačić Department of Psychology, University of Belgrade
Bojana Bodroža Department of Psychology, University of Novi Sad
Corresponding author:
Ljiljana B. Lazarevic, ljiljana.lazarevic@f.bg.ac.rs
Čika Ljubina 18-20, 11000 Belgrade, Serbia
Office phone: +381112639724
Mobile phone: +381641287614
To appear in Zeitschrift für Psychologie – Hotspots in Psychology, January 2017,
DOI: 10.1027/2151-2604/a000254
Cite at your own risk

2
Disintegration as an Additional Trait in the Psychobiological Model of Personality
- Assessing Discriminant Validity via Meta-Analysis
Abstract
This meta-analytic study investigates the relations between Disintegration-like
phenomena (i.e., various aspects of symptomatology with the prefix “schizo-”, both at the
clinical and the sub-clinical level) and the traits of the Psychobiological Model of Personality
(PBMP). The empirically based benchmark for assuming the distinctness of the trait
Disintegration was .30. The sample included 26 manuscripts with 30 studies and 424 effect
sizes. By computing inverse sampling variance weighted mean correlation coefficients under
a random-effects assumption, the following associations were found between Disintegration
and Harm Avoidance, Novelty Seeking, Reward Dependence, Persistence, Self-Directedness,
Cooperativeness, and Self-Transcendence: .23, .04, -.15, -.02, -.23, -.16, and .17,
respectively. Two variables were found to moderate the Disintegration - Self-Transcendence
correlation. Despite the theoretical expectation and some empirical evidence that Self-
Transcendence (and other character traits) should capture variations in Disintegration-like
phenomena, our results suggest that schizo-type phenomena are not adequately covered by
the PBMP.
Key words: Disintegration; Schizo phenomena; Psychobiological model of
personality (PBMP); Temperament and Character Inventory (TCI) and Tridimensional
Personality Questionnaire (TPQ); meta-analysis

3
Disintegration as an Additional Trait in the Psychobiological Model of Personality
- Assessing Discriminant Validity via Meta-Analysis
1. Introduction
Substantial empirical evidence supports the assumption that psychotic-like
phenomena form a continuum ranging from various sub-clinical forms to schizophrenia (e.g.,
Hanssen, Krabbendam, Vollema, Delespaul, & van Os, 2006). Several attempts have been
made to conceptualize the dispositional roots of psychotic-like phenomena as a trait within
personality models; the best known is Eysenck’s Psychoticism (Eysenck & Eysenck,
1976). However, empirical evidence demonstrated that this is not a valid measure of
psychotic-like behaviour since it shares substantial variance with Agreeableness and
Conscientiousness (Costa & McCrae, 1992; Zuckerman, 1989). Alternative personality
models, based on the lexical approach, did not include psychotic-like phenomena into the
taxonomy of basic personality traits. Two such, most popular models are the Big Five model
proposing five basic personality traits (Costa & McCrae, 1992) and the HEXACO model
assuming the existence of six traits (basically, a variations of Big Five model +
Honesty/Humility trait, Ashton & Lee, 2007).
Recently, a conceptualization of psychotic-like phenomena as indicators of a
personality trait distinct from the Big Five has been proposed by Knežević, Savić, Kutlešić
and Opačić (2016b). The authors argue that psychosis proneness, termed Disintegration, can
be conceptualized as a broad, hierarchically organized, multidimensional behavioural
disposition rooted in the information processing systems responsible for reality testing, and
normally distributed in the general population. According to Knežević et al. (2016b), the
Disintegration factor comprises nine converging facets (General Executive Impairment,
Perceptual Distortions, Enhanced Awareness, Depression, Paranoia, Mania, Flattened Affect,

4
Somatic Dysregulations and Magical Thinking). It was found to be independent from the Big
Five, and its structure was replicated across informants (self-, mother’s and father’s report),
samples (undergraduate students and general population) and units of analyses (facets and
items). The basic theoretical understanding of Disintegration is somewhat similar to the
articulations of Oddity (Watson, Clark & Chmielewski, 2008) and Schizotypy/Dissociation
(Ashton & Lee, 2012), but it has a much broader scope and thus differs in operationalization.
One of the frequently used personality models attempting to conceptualize
psychotic-like experiences within the normal personality variations is the Psychobiological
Model of Personality (PBMP) (Cloninger, Przybeck & Svrakic, 1991). In comparison to Big
Five or HEXACO, which were derived from lexical studies, PBMP was derived from a
clinical perspective, and is based on biological evidence and evidence from studies focusing
on psychopathology. Furthermore, PBMP was developed with an explicit goal to encompass
both normal and psychopathological aspects of personality in a unified framework. Therefore,
it would be particularly useful to explore if, and to what extent, PBMP addresses psychotic-
like phenomena (De Fruyt, Van se Wiele & Van Heeringen, 2000; Markon, Krueger &
Watson, 2005).
The PBMP proposes four temperament and three character dimensions. The
temperament factors, i.e., Harm Avoidance (HA), Novelty Seeking (NS), Reward
Dependence (RD), and Persistence (P) are postulated as biologically based and heritable
dimensions of individual differences (Cloninger et al., 1991). The three character dimensions,
i.e., Self-Directedness (SD), Cooperativeness (C), and Self-Transcendence (ST) are presumed
to mature as a consequence of life experiences (Svrakic, Draganic, Hill, Bayon, Przybeck &
Cloninger, 2002). According to Cloninger, Svrakic and Przybeck (1993), the inclusion of
character dimensions in the model enables distinguishing clinical from non-clinical
populations. Those advocating the use of Cloninger’s model state that it has higher validity in

5
capturing aspects of personality in psychopathology, in comparison to, for example, the Big
Five dimensions. Such traits are, in their opinion, diagnostically unspecific, i.e., they poorly
differentiate between clinical diagnoses (Cloninger et al., 1993; Svrakic, Whitehead,
Przybeck & Cloninger, 1993).
Factorial studies on the PBMP support the personality structure proposed by
Cloninger (e.g., Bagby, Marshall & Georgiades, 2005; Cloninger, 2000; Daneluzzo, Stratta &
Rossi, 2005; Hori, Teraishi, Sasayama, Matsuo, Kawamoto, Kinoshita, & Kunugi, 2012), and
its predictive validity has been corroborated (e.g., Borg, Peters, Schultz & de Jong, 2012;
Cloninger et al.,1993; Fossati, Cloninger, Villa, Borroni, Grazioli, Giarolli, et al., 2007;
Karwautz, Troop, Rabe-Hesketh, Collier & Treasure, 2003). Apart from the applicability of
PBMP in diagnosing Axis I disorders, there is evidence arguing its validity in prediction of
various personality disorders (PD). For instance, high Novelty Seeking, low Reward
Dependence and low Harm Avoidance were found to characterize antisocial PD, whereas low
Novelty Seeking, high Reward Dependence, and high Harm Avoidance were typical for
avoidant PD (Svrakic et al., 1993). Furthermore, significant negative correlations occurred
between Cooperativeness and most PDs (de la Rie, Duijsens & Cloninger, 1998). It was also
found that low scores of Self-Directedness and Cooperativeness define the core features of
PDs, regardless of their cluster (Bayon, Hill, Svrakic, Przybeck, & Cloninger, 1996; Svrakic
et al., 1993). Namely, it is argued that the combination of high Self-Transcendence with high
Self-Directedness and Cooperativeness leads to mature creativity. However, in less mature
(less Self-Directed and Cooperative) individuals, high Self-Transcendence can lead to
unusual, schizotypy-associated behaviour, making these individuals prone to psychosis
(Bayon et al., 1996; Laidlaw, Dwivedi, Naito & Gruzelier, 2005).
Cloninger (2000) claims that the PBMP advantage over the Big Five are its two traits,
i.e., Self-Transcendence and Persistence, which have important clinical implications.

6
Specifically, the inclusion of Self-Transcendence enables precise mapping of schizotypal
tendencies in personality and “differentiating schizoid from schizotypal patients” (Cloninger
et al, 1993, p. 982).
Empirical findings mainly support the hypothesis that Self-Transcendence correlates
positively with schizotypal PD (e.g., Bora & Veznedaroglu, 2007; Bagby et al., 2005; Ha,
Kim, Abbey & Kim, 2007), but this is not always obtained (Bayon et al., 1996; Ball, Tennen,
Polling, Kranzler & Rounsaville, 1997; Bejerot, Schlette, Ekselius, Adolfsson & von
Knorring, 1998). The relation between Self-Transcendence and schizoid PD is not
straightforward either, as some studies show positive correlations (e.g., Bagby et al., 2005; Ha
et al., 2007), while others demonstrate lack of relations (e.g., Ball et al., 1997; Bayon et al.,
1996), or even negative correlations (Bejerot et al., 1998). It seems that, in spite of the
theoretical articulations and expectations, the Self-Transcendence scale fails to adequately
capture psychotic-like phenomena.
In this study, the concept of Disintegration will serve as a working definition of the
psychotic-like domain, and a basis for establishing the eligibility criteria and search terms for
the studies to be included in this meta-analysis. The main advantage of the Disintegration
construct, supported by empirical evidence on the broadness of the domain, is that it
subsumes the most important models of schizotypy proposed up to date (Knežević et al.,
2016b). Moreover, the Disintegration model clearly distinguishes between the two aspects of
what is usually regarded as negative schizotypy, i.e., social anhedonia and blunted affect.
Namely, it was shown that although social anhedonia and blunted affect co-vary, only the
latter is influenced by Disintegration - the former is the primary indicator of low
Extraversion. This feature of the model might help explaining the correlations between the
Extraversion-like constructs and Disintegration (if obtained) as at least partially influenced by
predictor-criterion contamination. Finally, Disintegration represents a continuum of normally

7
distributed variations of psychotic like-phenomena from widely present subclinical forms to
fully-developed schizophrenia, i.e., personality trait. The consequence of choosing such a
conceptualization of the domain is that the search will encompass a broader range of trait-like
conceptualizations of schizotypy/schizophrenia/psychosis and will not be limited only to
narrow conceptualizations (e.g., focusing exclusively on schizotypal personality disorder).
Therefore, concepts including phenomena such as depression or mania, even though usually
not a part of the most famous models of schizotypy, will also be regarded as relevant, thus
increasing the chances of finding substantive correlations with PBMP personality traits.
1.1. Relevance of Disintegration in explaining various behaviours
The importance of psychosis-proneness in explaining and predicting both psychotic
disorders and non-psychotic psychopathology has already been documented (e.g., Rössler,
Hengartner, Ajdacic-Gross, Haker, Gamma & Angst, 2011). The relevance of Disintegration
disposition has been evidenced in various behaviours, neurocognitive functions and social
behavioural problems (Barrantes-Vidal, Fañanás, Rosa, Caparrós, Riba & Obiols, 2003),
motor coordination and sensory integration (Kaczorowski, Barrantes-Vidal & Kwapil, 2009),
emotional processing (Kerns, 2006), spiritual experiences (Jackson,1997), paranormal beliefs
(Goulding, 2005), early adolescent cannabis misuse (Stefanis, Delespaul, Henquet, Bakoula,
Stefanis & Van Os, 2004), militant extremism (Stankov, Saucier & Knežević, 2010), criminal
behaviour (Knežević, 2003), quality of intimate relationships (Kwapil, 1998), and elevated
social Internet use (Mittal, Tessner & Walker, 2007). Considerable data demonstrates the role
of psychotic-like behaviour in creative production (Brod, 1997; Eysenck, 1995), although the
interpretation of this finding is still controversial (Simonton, 2014). The rich nomological
network of Disintegration and its potential role in explaining various aspects of behaviour

8
raises the question whether it is adequately captured by any of the existing personality models
in general, and PBMP specifically.
2. Why should Disintegration be considered an additional trait to the PBMP
dimensions?
In spite of the Cloninger et al. (1993) claim that the addition of character dimensions,
especially Self-Transcendence, adds significantly to the explanatory value of PBMP in
schizotypal PD, there are at least three reasons to believe that Disintegration-like phenomena
are not adequately covered by the PBMP, which we will sketch in the subsections to follow.
2.1. Marginal conceptual overlap
In view of the Knežević et al. (2016b) conceptualization of Disintegration, there
seems to be an overlap of Self-Transcendence with certain aspects of the Disintegration
spectrum (namely with Magical Thinking and Enhanced Awareness facets), but not with
others (e.g., Perceptual Distortions, General Executive Impairment, Flattened Affect, etc.). In
other words, the Disintegration spectrum cannot be adequately represented by Magical
Thinking and Enhanced Awareness alone. It should thus be expected that the Self-
Transcendence - Disintegration correlation would depend on the type of Disintegration-like
measure used in the particular study as well as its sample characteristic.
2.2. Correlational studies
The available empirical evidence suggests that measures of Disintegration are non-
substantially correlated with either of the PBMP dimension. For instance, Aukst-Margetic,
Jakovljevic, Ivanec and Margetic (2011) reported the following correlations between
Disintegration-like phenomena and Novelty Seeking (-.04), Harm Avoidance (.24), Reward

9
Dependence (-.19), Persistence (-.34), Self-Directedness (-.31), Cooperativeness (-.26), and
Self-Transcendence (.10). This evidence suggests that Disintegration-like phenomena tend to
form a distinct personality factor, not substantially related to PBMP constructs. However, a
systematic review and meta-analytic synthesis of all available studies would be instrumental
to substantiate this assumption. To the best of our knowledge, only one meta-analytic study
was aimed to determine the associations between PBMP traits and schizophrenia (Ohi,
Hashimoto, Yasuda, Fukumoto, Yamamori, Iwase et al., 2012) but in all analysed studies the
focus was on personality profiles after the onset of the disease. Therefore, a meta-analytic
study investigating relations between PBMP traits and the whole spectrum of Disintegration
phenomena (not only schizophrenia) would inform us whether the Disintegration continuum
is (not) adequately captured by the PBMP traits.
2.3. Factor-analytic evidence (construct validity)
A significant body of empirical evidence speaks in favour of the distinctness of
Disintegration-like phenomena from other basic personality traits. The majority of these
studies are focused on Big Five factors, and they demonstrate that Disintegration phenomena
tend to separate from the Big Five (e.g., De Fruyt, De Clercq, Bolle, Wille, Markon &
Krueger, 2013; Watson et al., 2008). Furthermore, the Schizotypy/Dissociation factor was
also found to be separate from the six-factor HEXACO personality model (which, to
simplify, can be reduced to Big Five, + Honesty/Humility factor, Ashton & Lee, 2012;
Ashton, Lee, de Vries, Hendrickse, & Born, 2012).
The evidence regarding joint factor analysis of PBMP and Disintegration-like traits is
scarce. However, available factor-analytical studies using PBMP and Disintegration-like
phenomena show that all traits load on corresponding higher order factors, except for the
Self-Transcendence which loads on the psychosis/schizotypy factor along with other

10
schizotypy measures (Giakoumaki, Roussos, Tsapakis, Koiliari, Pasparakis, Zouraraki &
Bitsios, 2013; Giakoumaki, Roussos, Zouraraki, Spanoudakis, Mavrikaki, Tsapakis &
Bitsios, 2013). These studies favour the interpretation of Self-Transcendence as a disposition
lying at the same continuum with schizotypy/schizophrenia. Since these findings contradict
some of the aforementioned studies (e.g., Ball et al., 1993; Bejerot et al., 1998) these
discrepancies are worth investigating meta-analytically.
3. Criteria for accepting discriminant validity of Disintegration
By which empirical criterion can one judge whether a trait is distinct from the PBMP
traits or not? As a guidance, the correlations among the PBMP traits can be used. So, if the
correlation between psychosis-proneness and PBMP traits does not exceed the highest
correlation found within the PBMP model, it can be taken as an indication for the
discriminative validity of Disintegration from the PBMP traits. As already stated, there has
been no meta-analytic study investigating the interrelations of all seven PBMP traits. The
available empirical findings, however, indicate that correlations among the PBMP character
and temperament traits amount to .57; for instance, Reward Dependence - Cooperativeness
.54 and Self–Directedness - Cooperativeness .57 (Cloninger et al., 1993). Meta-analytic
studies performed for other personality models, i.e., Big Five, show that - no matter whether
the correlations are corrected or not - some of them always exceed the level of .30 (most of
them are in the .20 to .40 range in absolute values, Mount, Barrick, Scullen & Rounds, 2005;
Rushton & Irwing, 2008; van der Linden, Nijenhuis & Bakker, 2010). Therefore, setting a
strict benchmark at .30 - which is the level always exceeded by at least some of the
correlations obtained between the Big Five traits in each of the aforementioned meta-analyses
- would demonstrate that Disintegration-like phenomena are distinct from any of the PBMP
traits.

11
4. Research question and hypotheses
The overall aim of this meta-analytic study is to explore the discriminant validity of
Disintegration in relation to each of the personality traits defined by the Psychobiological
Model of Personality (Cloninger et al., 1991; Cloninger et al., 1993). Furthermore, we will
analyse if, and to what extent, the correlations between Disintegration and the PBMP traits
are being moderated by the following variables: (1) sub-dimension of Disintegration -
positive, negative, other; (2) mean age of the sample; (3) clinical versus non-clinical sample;
(4) student versus non-student sample; (5) self- versus other reports; (6) continent of sample
(America, Europe, other); (7) language within which the study was conducted (English versus
non-English); (8) year of the publication.
We assume indicators of Disintegration are non-substantially correlated, i.e., less than
.30 in magnitude, with any of the personality traits defined by the Psychobiological Model of
Personality. We do, however, expect the correlation of Disintegration with Self-
Transcendence to differ depending on the operationalization of Disintegration used and the
characteristics of the sample.
5. Method
5.1. Inclusion and exclusion criteria
In order to be included in the meta-analysis, studies had to meet five criteria. First, in
order to be considered, each study needed to include a measure of at least one dimension of
PBMP, as assessed by the Temperament and Character Inventory (TCI, Cloninger et al.,
1993) or Tridimensional Personality Questionnaire, (TPQ, Cloninger et al., 1991). Second,
the studies needed to include instruments assessing any symptom-cluster postulated to be a
part of a Disintegration model with perceptual/cognitive distortions as its core content. The
full list of instruments used can be found in Table 1. In accordance with the concept of

12
Disintegration we included phenomena regardless of the segment of the continuum to which
they belong (e.g., sub-clinical or clinical forms), regardless of the clinical picture within
which they were presented in clinical samples (e.g., schizophrenia or schizotypal personality
disorder), and regardless of whether they were confined only to the core symptoms of
perceptual/cognitive distortions or captured items/symptoms of almost all personality
disorders, given that the core symptoms were present. This means that the measures of, for
example, pure Depression or Mania were not included in the meta-analysis unless they were a
part of a model including the core symptoms of Disintegration, i.e., perceptual/cognitive
distortions. The concept of Disintegration is best captured by a spectrum of phenomena listed
under the models labelled by words with prefix ‘schizo-’. The third inclusion criteria required
that all studies needed to report zero-order correlations of PBMP dimensions with
disintegration. Fourth, we have limited our search to adult samples. Finally, all studies
published in peer-reviewed journals before June 2014 were included in the sample. No
language, geographical or cultural restrictions were imposed.
5.2. Literature search strategy and study selection
The literature search was conducted within the following bibliographic databases:
EBSCO, PsycNET, Science Direct, SpringerLink, Oxford Journals, Wiley Online Library,
Cambridge Journals, HighWire, Free Medical Journals, JSTOR, OvidSP, Open Access
Archives and SAGE Journals. In order to ensure an exhaustive search for the studies of
interest, “schizo*” was searched in the title, abstract, and/or the keywords of the paper, while
“personality trait” was searched throughout the whole text of the paper.
This initial search procedure yielded 9510 records (titles and abstracts) which were
then individually screened for relevance according to the eligibility criteria specified above.
Figure 1 describes all stages of the selection process. As a first step of determining if the

13
inclusion criteria were met, co-authors carefully read abstracts of each and every study.
Based on this abstract examination procedure, 9289 manuscripts were judged as non-relevant
according to our eligibility criteria, while 221 manuscripts were deemed relevant and
retrieved electronically for further examination.
Figure 1. Selection process of the studies included in meta-analysis
The next step of manuscript examination was to select publications reporting effect
sizes of interest, i.e., correlations between the PBMP dimensions and disintegration measures.
In this screening phase, a total of 195 manuscripts were excluded, 157 of which did not use
the PBMP model and two of which were not possible to obtain. Another 38 manuscripts
reported irrelevant effect size measures (group differences, beta coefficients, partial
correlations, factor loadings), but for a number of studies zero-order correlations could have
been extracted from the data set. We contacted the authors of 10 articles via e-mail; two of
them provided usable data and were included in the final sample. Details about these studies
are provided in the online Supplementary materials, Appendix A. The final set of manuscripts
considered for this meta-analysis consisted of 26 manuscripts reporting 424 effect sizes from

14
30 studies. Studies included in the meta-analysis and their sample characteristics are
displayed in Table 1. Complete datasets are provided as online supplements
1
.
1
(DOI URL will be provided upon acceptance of the manuscript)

15
Table 1
Characteristics of studies included in the meta-analysis, by sample type, personality measure and schizo- measure(s)
Study
N
Sample type
Personality
measure
Schizo measure
Albayrak, Y., Ekinci, O., & Çayköylü, A. (2012).
94
Consecutive outpatients with a diagnosis of
schizophrenia
TCI
SANS, and SAPS
Altınyazar, V., & Günderici, A. (2013).
51
Schizophrenic patients
TCI
OCTRIP
Bagby, R. M., Marshall, M. B., & Georgiades, S. (2005).
121
Community sample
TCI
PDQ-IV+
Ball, S. A., Tennen, H., Poling, J. C., Kranzler, H. R., & Rounsaville, B. J. (1997).
370
Patients in treatment for substance dependence
TCI
SCID
Bayon, C., Hill, K., Svrakic, D. M., Przybeck, T. R., & Cloninger, C. R. (1996).
103
Psychiatric consecutive non-schizophrenic out-
patients
TCI
MCMI-II
Bejerot, S., Schlette, P., Ekselius, L., Adolfsson, R., & Knorring, L. V. (1998).
36
Patients obsessive-compulsive disorder)
TCI
SCID
Bora, E., & Veznedaroglu, B. (2007).
52 + 75
Two samples: patients with schizophrenia (52)
and general population (75)
TCI
SPQ-B
Casey, J. E., & Joyce, P. R. (1999)
91
Patients without an organic mental disorder
TCI
SCID-PQ
Cortés, M. J., Valero, J., Gutiérrez-Zotes, J. A., Hernández, A., Moreno, L., Jariod,
M., ... & Labad, A. (2009).
29
Patients with schizophrenic disorder
TCI-R
PANSS
de la Rie, S. M., Duijsens, I. J., & Cloninger, C. R. (1998).
154
General population
TCI
VKP
Guillem, F., Bicu, M., Semkovska, M., & Debruille, J. B. (2002).
52
Patients meeting the DSM-IV diagnostic criteria
TCI
SAPS and SANS
Gutiérrez, F., Navinés, R., Navarro, P., García-Esteve, L., Subirá, S., Torrens, M., &
Martín-Santos, R. (2008).
224
Psychiatric out-patients
TCI
SCID-I and
SCID-II
Ha, J. H., Kim, E. J., Abbey, S. E., & KIM, T. S. (2007).
585
Community sample
TCI
PDQ-IV+
Hori, H., Noguchi, H., Hashimoto, R., Nakabayashi, T., Saitoh, O., Murray, R. M., ...
& Kunugi, H. (2008).
86
Patients with chronic schizophrenia
TCI
PANSS

16
Hori, H., Teraishi, T., Sasayama, D., Matsuo, J., Kawamoto, Y., Kinoshita, Y., &
Kunugi, H. (2012).
451
Community sample
TCI
SPQ
Laidlaw, T. M., Dwivedi, P., Naito, A., & Gruzelier, J. H. (2005).
80
Students
TCI
PSQ
Margetić, B. A., Jakovljević, M., Ivanec, D., & Margetić, B. (2011).
120
Outpatients with diagnosis of schizophrenia
TCI
PANSS
Margetić, B., Aukst Margetić, B., & Ivanec, D. (2013).
56
Patients with diagnosis of schizophrenia or
schizoaffective disorder
TCI
PANSS
Mulder, R. T., Joyce, P. R., Sullivan, P. F., Bulik, C. M., & Carter, F. A. (1999).
256
Patients (bulimia nervosa and major depression)
TCI
SCID-II
Nagoshi, C. T., Walter, D., Muntaner, C., & Haertzen, C. A. (1992).
117
Community sample
TPQ
PDQ-R
Nitzburg, G. C., Malhotra, A. K., & DeRosse, P. (2014).
415
Healthy volunteers
TCI
CAPE
Poustka, L., Murray, G. K., Jääskeläinen, E., Veijola, J., Jones, P., Isohanni, M., &
Miettunen, J. (2010).
41
Individuals with psychosis
TCI
PANSS
Ritsner, M., & Susser, E. (2004).
90
Consecutively recruited schizophrenia patients
TPQ
PANSS
Smith, M. J., Cloninger, C. R., Harms, M. P., & Csernansky, J. G. (2008).
35 + 34 +
63 + 56
Four samples: individuals with schizophrenia
(35), their non-psychotic siblings (34), controls
(63), and their siblings (56)
TCI
SANS, SAPS,
SIPS, and CPPS
Svrakic, D. M., Draganic, S., Hill, K., Bayon, C., Przybeck, T. R., & Cloninger, C. R.
(2002).
109
Consecutive psychiatric out-patients
TCI
PDQ-R
Svrakic, M. D., Whitehead, C., Przybeck, R.T., & Cloninger, C.R. (1993).
136
Psychiatric inpatients
TCI
SIDP-R
Note: SANS = Scale for the Assessment of the Negative Symptoms; SAPS = Scale for the Assessment of the Positive Symptoms; OCTRIP = Operational Criteria Checklist
for Psychotic Illness; PDQ-IV+ = Personality Disorder Questionnaire-IV+; SCID = Structured Clinical Interview for DSM-III-R; MCMI-II = The Millon Clinical Multiaxial
Inventory; SPQ-B= Schizotypal Personality Questionnaire Brief Form (SPQ-B); SCID-PQ = Structured Clinical Interview for DSM-III-R personality questionnaire; PANSS
= Positive and Negative Symptom Scale; VKP = Vragenlijst voor Kenmerken van de Persoonlijkheid; SCID-I = Structural Clinical Interview for DSM-IV Axis I Disorders;
SCID-II = Structured Clinical Interview for DSM-IV Axis II Disorders; SPQ = Schizotypal Personality Questionnaire; PSQ = Personality Syndrome Questionnaire; PDQ-R
Personality Diagnostic Questionnaire-Revised; CAPE = Community Assessment of Psychotic Experiences; SIPS = Structured Interview for Prodormal Symptoms; CPPS =
Chapman Psychosis Proneness Scales; SIDP-R = Structured Interview for DSM-H1-R Personality-Revised

17
5.3. Coding procedure and moderators
Studies were coded by all authors of this report. All coders possess a high level of
expertise in the field of personality psychology. Each report was coded by one person.
However, for a small number of studies the coding was not entirely straightforward, e.g. the
underlying personality model was not explicated, or the number of participants the relevant
correlations were obtained for was unclear. In these cases, at least three coders examined the
manuscript in detail until absolute agreement was reached. For example, 12 effect sizes from
de la Rie et al. (1998) study were reported as “below .20” (see Table 4 on p. 368). Here, the
most lenient values (.19) were used as the estimated scores, most likely inflating the average
effect sizes.
In addition to effect sizes (zero-order correlations between Disintegration-type
variables and each of the PBMP dimensions), we extracted information about potential
moderators namely manuscript-level, sample-level and effect-size-level variables.
Manuscript-level variables encompass the names of the authors, the journal name, the year of
publication, language of the study, state of the first author. Sample-level variables refer to
characteristics inherent to the sample used for computing correlation estimates, i.e. the mean
age of the sample, continent of sample (America, Europe, other), clinical versus non-clinical
sample, student versus non-student sample, and language within which the study had been
conducted (English versus non-English). Effect-size-level variables refer to characteristics of
the scale used to assess PBMP personality traits, the sub-dimension of Disintegration
assessed (positive, negative, other), and whether the data were obtained from self- versus
expert ratings.
5.4. Meta-analysis procedure

18
To compute an overall mean correlation for each bivariate relationship of interest
(Disintegration and each of the PBMP dimensions), extracted zero-order correlations were
synthesized using a Hedges/Olkin-type random effects model (e.g., Hedges and Olkin, 1985
and Raudenbush, 2009). In Hedges/Olkin-type meta-analyses, observed effect sizes are
synthesized using a weighted mean procedure, with the inverse sampling variances of each
correlation coefficient serving as weights. This procedure ensures that more precise
correlations, that is, those being associated with a smaller sampling variances, are being
assigned a larger weight when computing the overall mean correlation across all studies
considered. In addition, the estimated amount of ‘true’ variability (T-square) around the
estimated mean correlation coefficient is being computed. As a next step, the homogeneity of
the overall weighted mean is estimated, answering the question if, and to what extent, the
variability between observed correlations can be explained by sampling error only, and/or by
systematic differences among effect sizes. Three heterogeneity estimators are typically being
reported: (1) the Q statistic indicating heterogeneity if significant, (2) the I2 statistic estimates
(in percent) how much of the total variability in the correlations can be attributed to
heterogeneity among the true correlations, and (3) the H2 statistic, a ratio of the total amount
of variability in the observed correlations to the amount of sampling variability. In case of
heterogeneity, moderator analyses are being performed aimed at explaining the variability
among correlations. For an in-depth treatment of meta-analytic procedures, we recommend
Bornstein, Hedges, Higgins, and Rothstein (2009), and Card (2011).
The rma-function with zero-order correlations along with the corresponding sample
sizes as input, implemented in the R package metafor, Version 1.9.5 (Viechtbauer, 2010),
was used. The rma function provides a general framework for fitting various meta-analytic
models that are typically used in practice. Moderator analyses were performed with the aid of

19
mixed-effects meta-regressions with Knapp and Hartung (2003) adjustments implemented in
metafor. The R script is available in the online supplementary material
2
.
6. Results
6.1. Main results
The meta-analytically computed mean correlations between Disintegration and each
PBMP dimension separately indicate non-substantial relationships ranging from r= -.23 for
the correlation between Disintegration and Self-Directedness, to r= .23 for the correlation
between Disintegration and Harm Avoidance. The results are presented in Table 2; the
original dataset and complete R output is provided as an online supplement
3
. These results
are below the empirically set criterion of .30, and clearly support our main hypothesis
considering Disintegration distinct from any of the PBMP traits.
2
(DOI URL will be provided upon acceptance of the manuscript)
3
(DOI URL will be provided upon acceptance of the manuscript)

20
Table 2
Summary of meta-analytic findings of correlations between Disintegration and the Psychobiological Model of Personality
Disintegration and:
Meta-analytic summary statistics
(random effects models)
Heterogeneity estimators
Summary of mixed-effects meta-regressions aimed at explaining heterogeneity
using conceptual and study descriptors as moderators
N
k
Mean r
(95% CI)
T2
(95% CI)
Qtotal
(df, p)
I2%
(95% CI)
H2
(95% CI)
Model fit:
R2%
Residual
heterogeneity:
Qe(df, p)
Statistically highly significant moderators (p < .01)
Novelty Seeking
3932
62
.04
(.00, .08)
.02
(.01, .03)
176.78
(61, < .01)
67.94
(53.00, 78.96)
3.12
(2.13, 4.75)
3.16%
144.82
(53, < .01)
None
Harm Avoidance
3920
66
.23
(.18, .27)
.03
(.02, .05)
280.32
(65, < .01)
79.06
(70.52, 86.53)
4.78
(3.39,7.43)
20.47%**
213.60
(57, <.01)
None
Reward
Dependence
3920
63
- .15
(-.20, -.10)
.03
(.02, .05)
419.08
(62, < .01)
82.12
(74.22, 88.32)
5.59
(3.88, 8.56)
25.71%**
194.97
(54, < .01)
None
Persistence
3754
57
-.02
(-.06, .03)
.02
(.01, .04)
170.60
(56, < .01)
71.28
(58.11, 82.45)
3.48
(2.39, 5.70)
1.14%
134.61
(48, < .01)
None
Self-Directedness
4009
59
-.23
(-.28, -.17)
.04
(.03, .06)
501.23
(58, < .01)
87.10
(80.93, 91.32)
7.75
(5.24, 11.52)
27.62%**
233.79
(49, < .01)
None
Cooperativeness
3643
55
-.16
(-.21,.-.10)
.03
(.02, .05)
346.25
(54, < .01)
82.58
(74.14, 88.89)
5.74
(3.87, 9.00)
19.61%**
169.14
(46, < .01)
None
Self-
Transcendence
3832
61
.17
(.11, .22)
.04
(.02, .06)
407.48
(60, < .01)
85.07
(78.36, 90.05)
7.00
(4.62, 10.05)
55.91%
144.20
(51, < .01)
Dimension of Disintegration:
Positive (.21) > Negative (.06)
Sample:
Clinical (.08) < Nonclinical (.29)
Note: ** All moderators generating this fit fall below the .01 significance threshold and are therefore not considered further.

21
6.2. Moderator analyses
Moderator analyses, i.e., meta-regressions, have been conducted for each set of
Disintegration - PBMP dimension correlations. Meta-regressions were performed including
all moderators in order to simultaneously predict the variability of effect sizes. Heterogeneity
is substantial for all seven estimated mean correlations, as indicated by both the I2 statistic
(i.e., percentage of the overall variance due to between-studies heterogeneity) and the Q and
H2 heterogeneity estimators, suggesting a difference in true correlations between the studies.
Mixed-effects meta-regressions aimed to explain heterogeneity using conceptual (e.g.,
positive and negative symptoms) and study descriptors (e.g., age of participants) as
moderators showed that, in case of Self-Transcendence, the chosen descriptors explain
55.91% of heterogeneity among correlations. Namely, mean correlations for studies using
positive symptoms were higher than those using negative symptoms as markers of
Disintegration (.21 and .06 respectively). Also, mean Disintegration - Self-Transcendence
correlations are higher in non-clinical samples (.29) than in studies where subjects suffered
from mental health problems (.08).
The mean age of the participants, country of the respondents, language of the study
and type of the sample (student vs. non-student) were not found to moderate any of the
Disintegration - PBMP correlations. Overall, a substantial amount of heterogeneity remains
unexplained even after introducing the proposed moderators, which is indicated by the high
residual heterogeneity (Qe) in Disintegration – PBMP correlations. However, since the focus
of our study was the relationship between PBMP traits and Disintegration, and not why
estimations vary between studies, unexplained heterogeneity is not undermining our main
conclusion. Future studies might attempt to uncover which variables do moderate the
relationships between Disintegration and PBPM traits.

22
7. Discussion
The main finding of this meta-analysis is that mean correlations between
Disintegration and each of the PBMP traits are well below the benchmark value for
considering Disintegration a distinct trait (.30). These findings are clearly in favour of our
main hypothesis that Disintegration is not adequately covered by the PBMP, even though this
model was designed to encompass both normal and pathological aspects of personality.
Our results have shown that the average correlation between Disintegration and Self-
Transcendence is low, i.e., .17. The correlation of Self-Transcendence with positive
symptoms of Disintegration is expectedly higher than with negative symptoms, but still
below the criterion of .30. Although this trait is meant to be particularly useful in
differentiating individuals with schizotypal personality disorder from healthy controls a
substantial correlation with Disintegration is absent. The content of Self-Transcendence (self-
reported experiences of extrasensory perception and other aspects of Self-Transcendence, like
absorption, intense concentration and fascination with engaging stimuli, Cloninger et al.,
1993) seems to entail Openness-like phenomena rather than Disintegration, as evidenced by
the Self-Transcendence - Openness correlation of .41 (De Fruyt, et al. 2000).
Interestingly, moderator analyses also revealed more Disintegration - Self-
Transcendence commonality in non-clinical than in clinical samples (still below the
benchmark value). This can be ascribed to the tendency of high Self-Transcendence subjects
in non-clinical samples to endorse Disintegration items, especially those entailing both
phenomena to some extent (in line with the evidence that phantasy prone subjects show a
tendency for endorsing Disintegration items, Sanchez-Bernardos & Avia, 2006). Subjects
with high Disintegration scores (i.e., those with mental health problems), on the other hand,
are probably more likely to feel that Self-Transcendence items do not reflect their mostly
disturbing inner states directly and adequately. This moderating effect signals the fact that at

23
least some phenomena bordering the domains of Openness and Disintegration can have a
different meaning for clinical and non-clinical samples. Having in mind the evidence on the
equal factorial structure and equal external correlations of the Disintegration symptoms in
clinical and nonclinical populations (e.g. Hanssen et al., 2006), further exploration of the
extent of this tendency is needed.
Relations between openness and Disintegration symptoms have been addressed in a
recent attempt to conceptualize PDs as extreme, maladaptive variants of the five basic
personality traits, rather than discrete categories. Studies show a significant overlap of four
basic personality domains, i.e., Neuroticism, Extraversion, Agreeableness, and
Conscientiousness with four major domains from the Personality Inventory for DSM5 (PID5)
(Suzuki, Samuel, Pahlen & Krueger, 2015). However, attempts of the Big Five model
proponents to conceptualize psychotic-like phenomena as the extreme level of Openness
(DeYoung, Grazioplene, & Peterson, 2012; Dilchert, Ones, & Krueger, 2015) are far from
being substantiated (DeYoung, Carey, Krueger, & Ross, 2016; Knežević, Lazarević, Bošnjak,
Petrović, Purić, Teovanović et al., 2016a; Knežević et al., 2016b; Watson et al., 2008),
leading to the formulation of “a perpetually problematic fifth domain” (Suzuki et al., 2015, p.
351). Although some evidence indicate that Alternative DSM-5 model includes schizo-
phenomena, due to its recent development, thorough empirical examination should
corroborate the claim that it is comprehensive enough to include both Psychoticism and other
basic traits.
The highest positive correlation with Disintegration was obtained for Harm
Avoidance (r = .23). This correlation is in line with the meta-analytical correlation between
Neuroticism and Disintegration (Knežević et al., 2016a), and slightly lower than meta-
analytically derived Neuroticism - Schizotypal PD correlations (Samuel & Widiger, 2008;
Saulsman & Page, 2004). Although this correlation indicates some commonality between the

24
dimensions, its low value testifies again about different dispositional roots of anxiety-related
phenomena and Disintegration. The highest negative correlation (r = -.23) was with Self-
Directedness. Having in mind the theoretically expected sensitivity of Self-Directedness to
various types of maladaptive behaviour this result is not surprising. However, as Self-
Directedness tends to correlate more strongly with Harm Avoidance than Disintegration (r = -
.47, Cloninger, 1993), it is obvious that it entails neurotic-like maladaptations to a much
greater extent than those related to shizotypy/disintegration.
8. Conclusion and Implications
In accordance with our main hypothesis, there are no substantial correlations between
Disintegration and either of the PBMP traits. Although claiming to be a model more
important in explaining clinically-relevant phenomena, the PBMP did not show higher
correlations with Disintegration than the Big Five model (Knežević et al., 2016a). This
finding supports the notion that Disintegration-like phenomena and their behavioural
consequences are not adequately represented by the PBMP, in spite of the fact that it is
designed to encompass the whole spectrum of personality variations - from normal to
pathological, including schizotypal/disintegrative phenomena explicitly. Extending the
PBMP by a Disintegration factors matches a parallel recent development, namely the
emergence of the DSM-5 model of personality (Suzuki et al., 2015), for which the empirical
basis is currently in an early phase.

25
References
References marked with an asterisk indicate studies included in the meta-analysis.
* Albayrak, Y., Ekinci, O., & Çayköylü, A. (2012). Temperament and character personality
profile in relation to suicide attempts in patients with schizophrenia. Comprehensive
psychiatry, 53, 1130-1136. doi: 10.1016/j.comppsych.2012.04.007
* Altınyazar, V., & Günderici, A. (2013). Personality traits of schizophrenic patients in
remission and their first-degree relatives: a dopaminergic and glutamatergic gene
polymorphism study. Bulletin of Clinical Psychopharmacology, 23, 138-48.
doi: 10.5455/bcp.20130308015536
Ashton, M. C., & Lee, K. (2007). Empirical, theoretical, and practical advantages of the
HEXACO model of personality structure. Personality and Social Psychology Review,
11(2), 150–66. doi:10.1177/1088868306294907
Ashton, M. C., & Lee, K. (2012). Oddity, schizotypy/dissociation, and personality. Journal of
Personality, 80, 113–134. doi:10.1111/j.1467-6494.2011.00735.x
Ashton, M. C., Lee, K., de Vries, R. E., Hendrickse, J., & Born, M. P. (2012). The maladaptive
personality traits of the Personality Inventory for DSM-5 (PID-5) in relation to the
HEXACO personality factors and schizotypy/dissociation. Journal of Personality
Disorders, 26, 641–659. doi: 10.1521/pedi.2012.26.5.641
Aukst-Margetić, B., Jakovljević, M., Ivanec, D., Margetić, B. (2011). Temperament, character,
and quality of life in patients with schizophrenia and their first-degree relatives.
Comprehensive Psychiatry, 52, 425–430.
doi: 10.1016/j.comppsych.2010.08.007.
* Bagby, R. M., Marshall, M. B., & Georgiades, S. (2005). Dimensional personality traits and
the prediction of DSM-IV personality disorder symptom counts in a nonclinical sample.
Journal of Personality Disorders, 19, 53-67. doi: 10.1521/pedi.19.1.53.62180

26
* Ball, S. A., Tennen, H., Poling, J. C., Kranzler, H. R., & Rounsaville, B. J. (1997).
Personality, temperament, and character dimensions and the DSM-IV personality
disorders in substance abusers. Journal of abnormal psychology, 106, 545–553. doi:
10.1037/0021-843X.106.4.545
Barrantes-Vidal, N., Fañanás, L., Rosa, A., Caparrós, B., Riba, M.D., & Obiols, J.E. (2003).
Neurocognitive, behavioural and neurodevelopmental correlates of schizotypy clusters
in adolescents from the general population. Schizophrenia research, 61, 293-302. doi:
10.1016/S0920-9964(02)00321-3
* Bayon, C., Hill, K., Svrakic, D. M., Przybeck, T. R., & Cloninger, C. R. (1996). Dimensional
assessment of personality in an out-patient sample: relations of the systems of Millon
and Cloninger. Journal of psychiatric research, 30, 341-352. doi: 10.1016/0022-
3956(96)00024-6
* Bejerot, S., Schlette, P., Ekselius, L., Adolfsson, R., & Knorring, L. V. (1998). Personality
disorders and relationship to personality dimensions measured by the Temperament and
Character Inventory in patients with obsessive-compulsive disorder. Acta Psychiatrica
Scandinavica, 98, 243-249. doi: 10.1111/j.1600-0447.1998.tb10075.x
* Bora, E., & Veznedaroglu, B. (2007). Temperament and character dimensions of the relatives
of schizophrenia patients and controls: the relationship between schizotypal features and
personality. European Psychiatry, 22, 27-31. doi:10.1016/j.eurpsy.2006.07.002
Borg, C., Peters, M. L., Schultz, W. W., & de Jong, P. J. (2012). Vaginismus: Heightened Harm
Avoidance and Pain Catastrophizing Cognitions. Journal of Sexual Medicine, 9, 558-
567. doi:10.1111/j.1743-6109.2011.02535.x
Bornstein, M., Hedges, L. V., Higgins, J. P. T. & Rothstein, H. R. (2009). Introduction to Meta-
analysis. West Sussex: John Wiley & Sons, Ltd.

27
Brod, J. H. (1997). Creativity and schizotypy. In G. Claridge (Ed.), Schizotypy: Implications
for illness and health (pp. 274-298). New York: Oxford University Press.
Card, N.A. (2011). Applied meta-analysis for the social sciences. New York: Guilford Press.
* Casey, J. E., & Joyce, P. R. (1999). Personality disorder and the Temperament and Character
Inventory in the elderly. Acta Psychiatrica Scandinavica, 100, 302-308.
doi: 10.1111/j.1600-0447.1999.tb10865.x
Cloninger, C. R. (2000). Biology of personality dimensions. Current Opinion in Psychiatry,
13, 611-616. doi: 10.1097/00001504-200011000-00024
Cloninger, C. R., Przybeck, T. R., & Svrakic, D. M. (1991). The tridimensional personality
questionnaire: US normative data. Psychological reports, 69, 1047-1057.
doi: 10.2466/pr0.1991.69.3.1047
Cloninger, C. R., Svrakic, D. M., & Przybeck, T. R., (1993). A psychobiological model of
temperament and character. Archives of General Psychiatry 50, 975–990. doi:
10.1001/archpsyc.1993.01820240059008
* Cortés, M. J., Valero, J., Gutiérrez-Zotes, J. A., Hernández, A., Moreno, L., Jariod, M., ... &
Labad, A. (2009). Psychopathology and personality traits in psychotic patients and their
first-degree relatives. European Psychiatry, 24, 476-482.
doi: 10.1016/j.eurpsy.2009.06.002
Costa, P. T., & McCrae, R. R. (1992). "Four ways five factors are basic". Personality and
Individual Differences, 13, 653-665. doi: 10.1016/0191-8869(92)90236-I
Daneluzzo, E., Stratta, P., & Rossi, A. (2005). The contribution of temperament and character
to schizotypy multidimensionality. Comprehensive psychiatry, 46, 50-55.
doi: 10.1016/j.comppsych.2004.07.010

28
De Fruyt, F., De Clercq, B., Bolle, M. D., Wille, B., Markon, K., & Krueger, R. F. (2013).
General and maladaptive traits in a Five-Factor framework for DSM-5 in a university
student sample. Assessment, 20, 295–307. doi:10.1177/1073191113475808
De Fruyt, F., Van De Wiele, L., & Van Heeringen, C. (2000). Cloninger's psychobiological
model of temperament and character and the five-factor model of personality.
Personality and individual differences, 29, 441-452.
doi: 10.1016/S0191-8869(99)00204-4
* de la Rie, S. M., Duijsens, I. J., & Cloninger, C. R. (1998). Temperament, character, and
personality disorders. Journal of Personality Disorders, 12, 362-372.
doi: 10.1521/pedi.1998.12.4.362
Dilchert, S., Ones, D. S., & Krueger, R. F. (2015). Maladaptive Personality Constructs,
Measures, and Work Behaviors. Industrial and Organizational Psychology, 7, 98-110.
doi:10.1111/iops.12115
DeYoung, C. G., Grazioplene, R. G., & Peterson, J. B. (2012). From madness to genius: The
Openness/Intellect trait domain as a paradoxical simplex. Journal of Research in
Personality, 46, 63–78. doi:10.1016/j.jrp.2011.12.003
DeYoung, C. G., Carey, B. E., Krueger, R. F. & Ross, S. R. (2016). Ten Aspects of the Big
Five in the Personality Inventory for DSM–5. Personality Disorders: Theory, Research,
and Treatment, 7, 113-123. http://dx.doi.org/10.1037/per0000170
Eysenck, H. J. (1995). Genius: The natural history of creativity. Cambridge, UK: Cambridge
University Press.
Eysenck, H. J., & Eysenck, S. B. G. (1976). Psychoticism as a dimension of personality. New
York: Crane, Russak & Co.
Fossati, A., Cloninger, C. R., Villa, D., Borroni, S., Grazioli, F., Giarolli, L., Battaglia, M. &
Maffei, C. (2007). Reliability and validity of the Italian version of the Temperament

29
and Character Inventory-Revised in an outpatient sample. Comprehensive Psychiatry,
48, 380-387. doi: 10.1016/j.comppsych.2007.02.003
Giakoumaki, S. G., Roussos, P., Tsapakis, E. M., Koiliari, E., Pasparakis, E., Zouraraki, C., &
Bitsios, P. (2013). Cognitive and personality analysis of startle reactivity in a large
cohort of healthy males. Biological psychology, 94, 582-591.
doi: 10.1016/j.biopsycho.2013.09.005
Giakoumaki, S. G., Roussos, P., Zouraraki, C., Spanoudakis, E., Mavrikaki, M., Tsapakis, E.
M., & Bitsios, P. (2013). Sub-optimal parenting is associated with schizotypic and
anxiety personality traits in adulthood. European Psychiatry, 28, 254-260. doi:
10.1016/j.eurpsy.2012.07.002
Goulding, A. (2005). Healthy schizotypy in a population of paranormal believers and
experients. Personality and Individual Differences, 38, 1069-1073.
doi:10.1016/j.paid.2004.07.006
* Guillem, F., Bicu, M., Semkovska, M., & Debruille, J. B. (2002). The dimensional symptom
structure of schizophrenia and its association with temperament and character.
Schizophrenia Research, 56, 137-147. doi: 10.1016/S0920-9964(01)00257-2
*Gutiérrez, F., Navinés, R., Navarro, P., García-Esteve, L., Subirá, S., Torrens, M., & Martín-
Santos, R. (2008). What do all personality disorders have in common? Ineffectiveness
and uncooperativeness. Comprehensive psychiatry, 49, 570-578.
doi: 10.1016/j.comppsych.2008.04.007
* Ha, J. H., Kim, E. J., Abbey, S. E., & KIM, T. S. (2007). Relationship between personality
disorder symptoms and temperament in the young male general population of South
Korea. Psychiatry and clinical neurosciences, 61, 59-66.
doi: 10.1111/j.1440-1819.2007.01611.x

30
Hanssen, M., Krabbendam, L., Vollema, M., Delespaul, P., & Van Os, J. (2006). Evidence for
instrument and family-specific variation of subclinical psychosis dimensions in the
general population. Journal of Abnormal Psychology, 115, 5-14. doi: 10.1037/0021-
843X.115.1.5
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. San Diego, CA:
Academic Press.
* Hori, H., Noguchi, H., Hashimoto, R., Nakabayashi, T., Saitoh, O., Murray, R. M., ... &
Kunugi, H. (2008). Personality in schizophrenia assessed with the Temperament and
Character Inventory (TCI). Psychiatry research, 160, 175-183.
doi:10.1016/j.psychres.2007.05.015
* Hori, H., Teraishi, T., Sasayama, D., Matsuo, J., Kawamoto, Y., Kinoshita, Y., & Kunugi, H.
(2012). Relationships between season of birth, schizotypy, temperament, character and
neurocognition in a non-clinical population. Psychiatry research, 195, 69-75.
doi:10.1016/j.psychres.2011.07.028
Jackson, M. C. (1997). Benign schizotypy? The case of spiritual experience. In G. S. Claridge
(Ed.), Schizotypy: Relations to illness and health (pp. 227-250). New York: Oxford
University Press
Kaczorowski, J. A., Barrantes-Vidal, N., & Kwapil, T. R. (2009). Neurological soft signs in
psychometrically identified schizotypy. Schizophrenia research, 115, 293-302.
doi:10.1016/j.schres.2009.06.018
Karwautz, A., Troop, N. A., Rabe-Hesketh, S., Collier, D. A., & Treasure, J. L. (2003).
Personality disorders and personality dimensions in anorexia nervosa. Journal of
Personality Disorders, 17, 73-85. doi: 10.1521/pedi.17.1.73.24057
Kerns, J. G. (2006). Schizotypy facets, cognitive control, and emotion. Journal of Abnormal
Psychology, 115, 418-427. doi: 10.1037/0021-843X.115.3.418

31
Knapp, G., & Hartung, J. (2003). Improved tests for a random effects meta-regression with a
single covariate. Statistics in Medicine, 22, 2693–2710. doi: 10.1002/sim.1482
Knežević, G. (2003). Koreni amoralnosti [Roots of amorality]. Beograd, Društvo psihologa
Srbije
Knežević, G., Lazarević, Lj. B., Bošnjak, M., Purić, D., Petrović, B., Teovanović, P., Opačić,
G. & Bodroža, B. (2016a). Psychosis-proneness and Big Five traits: Meta-analysis.
Personality and Individual Differences, 95, 214-222.
http://dx.doi.org/10.1037/per0000170
Knežević, G., Savić, D., Kutlešić, V. & Opačić, G. (2016b). A Reconceptualization of
Psychosis Proneness as a Personality Trait Named Disintegration: Cross-Validation
and Relations with the Five-Factor Model. Manuscript submitted for publication.
Kwapil, T. R. (1998). Social anhedonia as a predictor of the development of schizophrenia-
spectrum disorders. Journal of abnormal psychology, 107, 558-565.
doi: 10.1037/0021-843X.107.4.558
*Laidlaw, T. M., Dwivedi, P., Naito, A., & Gruzelier, J. H. (2005). Low self-directedness
(TCI), mood, schizotypy and hypnotic susceptibility. Personality and Individual
Differences, 39, 469-480. doi:10.1016/j.paid.2005.01.025
* Margetić, B. A., Jakovljević, M., Ivanec, D., & Margetić, B. (2011). Temperament, character,
and quality of life in patients with schizophrenia and their first-degree relatives.
Comprehensive psychiatry, 52, 425-430.
doi:10.1016/j.comppsych.2010.08.007
* Margetić, B., Aukst Margetić, B., & Ivanec, D. (2013). Temperament and character in
patients with schizophrenia with a history of restraint. The Journal of Forensic
Psychiatry & Psychology, 24, 621-633. doi: 10.1080/14789949.2013.830317

32
Markon, K. E., Krueger, R. F., & Watson, D. (2005). Delineating the structure of normal and
abnormal personality: an integrative hierarchical approach. Journal of personality and
social psychology, 88, 139-157. doi: 10.1037/0022-3514.88.1.139
Mittal, V. A., Tessner, K. D., & Walker, E. F. (2007). Elevated social Internet use and
schizotypal personality disorder in adolescents. Schizophrenia research, 94, 50-57.
doi:10.1016/j.schres.2007.04.009
Mount, M. K., Barrick, M. R., Scullen, S. M., & Rounds, J. (2005). Higher-order dimensions
of the Big Five personality traits and the big six vocational interest types. Personnel
Psychology, 58, 447–478. doi: 10.1111/j.1744-6570.2005.00468.x
* Mulder, R. T., Joyce, P. R., Sullivan, P. F., Bulik, C. M., & Carter, F. A. (1999). The
relationship among three models of personality psychopathology: DSM-III-R
personality disorder, TCI scores and DSQ defences. Psychological Medicine, 29, 943-
951. doi: 10.1017/S0033291799008533
* Nagoshi, C. T., Walter, D., Muntaner, C., & Haertzen, C. A. (1992). Validation of the
Tridimensional Personality Questionnaire in a sample of male drug users. Personality
and Individual Differences, 13, 401-409. doi:10.1016/0191-8869(92)90067-Y
* Nitzburg, G. C., Malhotra, A. K., & DeRosse, P. (2014). The relationship between
temperament and character and subclinical psychotic-like experiences in healthy adults.
European Psychiatry, 29, 352-357. doi:10.1016/j.eurpsy.2013.11.006
Ohi, K., Hashimoto, R., Yasuda, Y., Fukumoto, M., Yamamori, H., Iwase, M., ... & Takeda,
M. (2012). Personality traits and schizophrenia: evidence from a case–control study and
meta-analysis. Psychiatry research, 198, 7-11. doi:10.1016/j.psychres.2011.12.018
* Poustka, L., Murray, G. K., Jääskeläinen, E., Veijola, J., Jones, P., Isohanni, M., & Miettunen,
J. (2010). The influence of temperament on symptoms and functional outcome in people

33
with psychosis in the Northern Finland 1966 Birth Cohort. European Psychiatry, 25,
26-32. doi:10.1016/j.eurpsy.2009.09.006
Raudenbush, S. W. (2009). Analyzing effect sizes: Random effects models. In H. Cooper, L.
V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-
analysis (2nd ed., pp. 295–315). New York: Russell Sage Foundation.
* Ritsner, M., & Susser, E. (2004). Temperament types are associated with weak self-construct,
elevated distress and emotion-oriented coping in schizophrenia: evidence for a complex
vulnerability marker?. Psychiatry research, 128, 219-228.
doi: 10.1016/j.psychres.2004.06.007
Rössler, W., Hengartner, M. P., Ajdacic-Gross, V., Haker, H., Gamma, A., & Angst, J. (2011).
Subclinical psychosis symptoms in young adults are risk factors for subsequent
common mental disorders. Schizophrenia Research, 131, 18-23.
doi:10.1016/j.schres.2011.06.019
Rushton, J. P., & Irwing, P. (2008). A general factor of personality from two meta-analyses of
the Big Five: Digman (1997) and Mount, Barrick, Scullen, and Rounds (2005).
Personality and Individual Differences, 45, 679–683. doi: 10.1016/j.paid.2008.07.015
Sanchez-Bernardos, M.L., & Avia, M. D. (2006). The relationship between fantasy proneness
and schizotypy in adolescents. Journal of Nervous and Mental Diseases, 194, 411-414.
Samuel, D. B., & Widiger, T. A. (2008). A meta-analytic review of the relationships between
the five-factor model and DSM-IV-TR personality disorders: A facet level analysis.
Clinical Psychology Review, 28, 1326–1342. doi:10.1016/j.cpr.2008.07.002
Saulsman, L. M., & Page, A. C. (2004). The five-factor model and personality disorder
empirical literature: A meta-analytic review. Clinical Psychology Review, 23, 1055–
1085. doi:10.1016/j.cpr.2002.09.001

34
Simonton, D. K. (2014). Can creative productivity be both positively and negatively correlated
with psychopathology? Yes! Front in Psychology, 5, 455.
doi:10.3389/fpsyg.2014.00455
*Smith, M. J., Cloninger, C. R., Harms, M. P., & Csernansky, J. G. (2008). Temperament and
character as schizophrenia-related endophenotypes in non-psychotic siblings.
Schizophrenia Research, 104, 198-205. doi:10.1016/j.schres.2008.06.025
Stankov, L., Saucier, G., & Knežević, G. (2010). Militant extremist mind-set: Proviolence, Vile
World, and Divine Power. Psychological assessment, 22, 70-86. doi:10.1037/a0016925
Stefanis, N. C., Delespaul, P., Henquet, C., Bakoula, C., Stefanis, C. N., & Van Os, J. (2004).
Early adolescent cannabis exposure and positive and negative dimensions of psychosis.
Addiction, 99, 1333-1341.doi:10.1111/j.1360-0443.2004.00806.x
Suzuki, T., Samuel, D. B., Pahlen, S. & Krueger, R. F. (2015). DSM-5 Alternative Personality
Disorder Model Traits as Maladaptive Extreme Variants of the Five-Factor Model: An
Item-Response Theory Analysis. Journal of Abnormal Psychology, 124, 343-354.
http://dx.doi.org/10.1037/abn0000035
*Svrakic, D. M., Whitehead, C., Przybeck, T. R., & Cloninger, C. R. (1993). Differential
diagnosis of personality disorders by the seven-factor model of temperament and
character. Archives of General Psychiatry, 50, 991-999.
doi: 10.1001/archpsyc.1993.01820240075009
* Svrakic, D. M., Draganic, S., Hill, K., Bayon, C., Przybeck, T. R., & Cloninger, C. R. (2002).
Temperament, character, and personality disorders: etiologic, diagnostic, treatment
issues. Acta Psychiatrica Scandinavica, 106, 189-195. doi: 10.1034/j.1600-
0447.2002.02196.x

35
van der Linden, Nijenhuis & Bakker (2010). The General Factor of Personality: A meta-
analysis of Big Five intercorrelations and a criterion-related validity study. Journal of
Research in Personality, 44, 315–327. doi:10.1016/j.jrp.2010.03.003
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of
Statistical Software, 36, 1-48.
Watson, D., Clark, L. A., & Chmielewski, M. (2008). Structures of personality and their
relevance to psychopathology: II. Further articulation of a comprehensive unified trait
structure. Journal of Personality, 76, 1545-1585. doi: 10.1111/j.1467-
6494.2008.00531.x
Zuckerman, M. (1989). Personality in the third dimension: A psychobiological approach.
Personality and Individual Differences, 10, 391-418.
doi: 10.1016/0191-8869(89)90004-4