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Topic; Dissociative Symptom disorder

the guideline and two scholarly article to use it uploaded below. APA  format 7th edition. NO plagiarism

brain
sciences

Communication

Hopelessness, Dissociative Symptoms, and Suicide
Risk in Major Depressive Disorder: Clinical and
Biological Correlates

Mauro Pettorruso 1 , Giacomo d’Andrea 1,* , Giovanni Martinotti 1,2, Fabrizio Cocciolillo 3,4,
Andrea Miuli 1 , Ilenia Di Muzio 1 , Rebecca Collevecchio 1 , Valeria Verrastro 5,
Fabio De-Giorgio 6 , Luigi Janiri 7,8, Massimo di Giannantonio 1, Daniela Di Giuda 3,4,† and
Giovanni Camardese 7,8,†

1 Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University, Via dei Vestini 33,
66013 Chieti, Italy; [email protected] (M.P.); [email protected] (G.M.);
[email protected] (A.M.); [email protected] (I.D.M.); [email protected] (R.C.);
[email protected] (M.d.G.)

2 Department of Pharmacy, Pharmacology, Clinical Science, University of Hertfordshire, Herts AL109AB, UK
3 Unità Operativa Complessa di Medicina Nucleare, Fondazione Policlinico Universitario A. Gemelli IRCCS,

00168 Roma, Italia; [email protected] (F.C.); [email protected] (D.D.G.)
4 Istituto di Medicina Nucleare, Università Cattolica del Sacro Cuore, 00168 Roma, Italia
5 Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro,

88100 Catanzaro, Italy; [email protected]
6 Section of Legal Medicine, Institute of Public Health, Università Cattolica del Sacro Cuore, 00168 Rome, Italy;

[email protected]
7 Department of Psychiatry, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, 00168 Rome, Italy;

[email protected] (L.J.); [email protected] (G.C.)
8 Institute of Psychiatry, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
* Correspondence: [email protected]
† Equally contributed as last authors.

Received: 20 June 2020; Accepted: 4 August 2020; Published: 5 August 2020
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Abstract: Background: Major depressive disorder (MDD) has different clinical presentations and is
associated with neurobiological alterations. Hopelessness, anhedonia, and dissociation represent some
of the most pervasive psychopathological symptoms that often lead to suicidal thoughts, attempts, and
actions. To further research on the concept of depression endophenotypes, this study aimed to assess
the possible relationships between hopelessness and other clinical and biological correlates (i.e., striatal
dopaminergic dysfunction) in depressed patients. Methods: We recruited 51 subjects with MDD. All
subjects underwent 123I-FP-CIT SPECT to assess striatal dopamine transporter (DAT) availability and
a psychometric evaluation using the psychometric scale to assess depressive, anxious, dissociative,
and hopelessness symptoms aside from suicidal ideation. Result: An inverse correlation between the
hopelessness score and dopamine transporter availability in all basal ganglia was bilaterally found.
(Right Putamen, r = −0.445, p < 0.01; Left Putamen, r = −0.454, p < 0.01; Right Caudate, r = −0.398,
p < 0.01; Left Caudate, r = −0.467, p < 0.01) Moreover, a positive correlation was also found between
hopelessness and dissociative symptoms. Conclusions: These results provide important evidence on
the neurobiological and clinical correlates of different psychopathological symptoms of depression
with potential implications in terms of devising more effective treatment programs.

Keywords: dopamine transporter; suicidality; mood disorders; basal ganglia; DaTSCAN; dissociation

Brain Sci. 2020, 10, 519; doi:10.3390/brainsci10080519 www.mdpi.com/journal/brainsci

Brain Sci. 2020, 10, 519 2 of 11

1. Introduction

Major depressive disorder (MDD) is a high-burden disease characterized by several psychopathological
dimensions, including mood deflection, suicidality, psychomotor retardation or agitation, loss of motivation,
hopelessness and anhedonia [1]. In recent decades, hopelessness has emerged as one of the core features of
MDD [2]. It could be defined as a dimension characterized by negative expectancies for the future, lack of
general motivation, and the attribution of wrong meanings to personal experiences [3]. From a clinical
point of view, the experience of a lack of positive expectations for the future combined with the distress
and mental pain that often occurs in depressed patients leads to an increased risk of suicide, as it appears
the only way to escape from their inner “unsolvable problems.” In fact, hopelessness seems to be strictly
related to suicidal ideation and this relationship is stronger than the one between suicidality and depression
severity [4], as reported by a recent systematic review on this argument [2]. In addition, hopelessness could
be considered a clinical predictor for any suicide attempts [5] (with a 90–94.2% accuracy [6,7]) even when
depressive symptoms are contained [8].

In addition to the dimensions classically related to MDD and suicide, (i.e., impulsivity, helplessness,
mental pain, rumination) dissociative symptoms seem to play a leading role in the psychopathological
processes of depression [9,10]. In this clinical context, dissociative symptoms seem to be attempts
to isolate particular mental processes, such as thoughts, feelings, or states of mind that could be too
distressing or painful to be mentalized from consciousness [11]. This seems to be particularly true for
patients who suffer hopelessness, who find a way to deal with the lack of positive future prospects
through dissociation [12].

In recent years, studies have attempted to explain the psychopathological aspects of MDD through
investigating its neurobiological underpinnings to identify dimension-targeted pharmacological
treatments. Based on the historical monoamine hypothesis of depression [13], the leading roles of
serotonin (5-HT), norepinephrine (NE), and dopamine (DA) in the pathophysiology of MDD are
well-known. Nowadays, there is an increasing interest in the role of the dopaminergic synapses in
MDD, as confirmed by the numerous preclinical, neuroimaging, and pharmacological studies on this
subject [14]. The dopamine transporter (DAT) represents an important element of the synaptic cleft
and regulates DA activities through the presynaptic reuptake of the neurotransmitter in the striatum
and midbrain. It is often used as a target for the evaluation of dopaminergic circuit efficiency [15].
Using peculiar radiotracers for DAT, single-photon emission computerized tomography (SPECT) has
been extensively used in MDD patients and has shown an important reduction in DAT availability
in subcortical regions as result of a striatal dopaminergic dysfunction [16–18]. In particular, several
studies have focused on the roles of this dysfunction in anhedonic patients with MDD by following the
hypothesis of a cortico-striatal-limbic dopaminergic dysfunction, involving selected areas of ventral
(nucleus accumbens) and dorsal (putamen, caudate) striatum, in which the reward system seems to
play a crucial role [19,20]. One of the clinical correlates of reward system disfunction appears to be the
lack of motivation, a core element of both anhedonia and hopelessness.

Concerning suicidality, the roles of dopaminergic dysregulations are still relatively unknown [21]
since the literature has reported contrasting results in both in vivo and post-mortem analysis. On one
hand, some studies showed diminished striatal dopaminergic signaling in depressed patients attempting
suicide [22,23]. On the other hand, several studies failed to find a correlation between suicidality and
striatal dopaminergic dysfunctions [24–26].

Considering the common psychopathological aspects shared by anhedonia and hopelessness,
such as the loss of motivation and negative beliefs, which seem to involve the dopaminergic reward
system, the main aim of this study was to assess whether hopelessness is related to a peculiar striatal
dopaminergic dysfunction in a sample of depressed patients; in addition, we assess suicidality through
the use of a single item of Hamilton Depression Rating Scale, in order to evaluate a possible correlation
between suicide risk and DAT availability. Secondarily, we investigated possible relationships
between hopelessness and other psychopathological dimensions of MDD to assess their clinical impact
on suicidality.

Brain Sci. 2020, 10, 519 3 of 11

2. Materials and Methods

2.1. Subjects

Patients enrolled at the “A. Gemelli” Hospital of the Catholic University of the Sacred Heart
in Rome, Italy were considered for this study. All subjects underwent 123I-FP-CIT SPECT to assess
striatal DAT availability, which was performed at the Nuclear Medicine Unit of the Catholic University
of the Sacred Heart. Only patients with a current major depressive episode (MDE) in the context
of MDD following the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria were
extracted retrospectively from a previously collected dataset. We included in the study subjects not
reporting SPECT alteration according to BASAL GANGLIA software [27] and without any neurological
diagnosis in the subsequent three years of clinical follow-up. An accurate neurological examination
was performed to rule out idiopathic Parkinson’s disease. Exclusion criteria included the diagnosis of
Parkinson’s disease or Atypical Parkinsonism, past or current abuse or substance/alcohol use disorders,
bipolar or psychotic disorders, and the current use of psychoactive medication with action towards the
dopaminergic system.

The sample size was established on the basis of a power analysis with a minimum Rho correlation
set to 0.4, power value was 0.80 with a type one error rate (alpha) set to 0.05 in the current sample.

Fifty-one depressed patients were enrolled.
Before the diagnostic exams, all patients were evaluated through a clinical interview conducted

by trained medical staff. During this interview, some psychometric scales largely and widely approved
by the literature were used; these scales included the 21-item Hamilton Depression Rating Scale
(HDRS-21) (Cronbach alpha value = 0.7) [28] to assess depression severity, the Beck Hopelessness
Scale (BHS) to evaluate hopelessness (Cronbach alpha value = 0.87) [29], the Hamilton Anxiety Rating
Scale (HARS) to assess anxiety symptoms (Cronbach alpha value = 0.89) [30] and the Dissociative
Experiences Scale (DES) to screen dissociative symptoms (Cronbach alpha value = 0.96) [31]. In order
to evaluate suicidality, we used the third item of the HDRS-21, which investigates the intensity of
suicidal thoughts (with a range from 0 to 4).

The study was approved by the ethical committee of the “Università Cattolica del Sacro Cuore”
(Protocol Number: 16113/13, date: 17 July 2013), all patient data were treated confidentially and
anonymously, and the interviews were conducted in line with the Helsinki Declaration (2013) [32].

2.2. SPECT Procedure

SPECT acquisition and processing were performed as previously published [16,33].
All subjects had been free from psychotropic drugs for 4 weeks before the SPECT study to adhere

to the current neuroimaging guidelines. [34] Thirty minutes after the thyroid blockade, which was
administered using 400 mg of oral potassium perchlorate, an intravenous injection of 185 MBq of
123I-FP-CIT was given (DaTSCAN, GE Healthcare).

SPECT was carried out using a dual-head gamma camera system (E.CAM, Siemens Medical
System) equipped with high resolution, low-energy, parallel-hole collimators.

Acquisition started between 180 and 240 min after injection and lasted 45 min.
We applied a “step-and-shoot” protocol with a radius of rotation ≤15 cm and the following

parameters: 120 projection angles over 360◦ (angular step of 3◦), 128 × 128 matrix, 1.23 zoom
factor, 3.90 × 3.90 mm pixel size, and 45 s per view. Data were reconstructed using filtered back
projection using a Butterworth filter (cut-off frequency: 0.45 cycle/cm, order: 8). Chang’s first-order
attenuation correction was also applied (attenuation coefficient: 0.11 cm−1). Reconstructed transaxial,
sagittal, and coronal slices (slice thickness: 3.9 mm) were reoriented according to the canthomeatal
plane. Data were collected and analyzed by the same observer, who was blind to all clinical
information and psychometric measures. After preliminary qualitative (visual) assessments, region
of interest (ROI) analyses were performed to quantify the striatal 123I-FP-CIT binding ratios. Five
adjacent transaxial slices representing the most intense striatal uptake were summed up in a single

Brain Sci. 2020, 10, 519 4 of 11

19.5-mm-thick reference section. A set of two-dimensional ROIs was manually drawn with the help of
an anatomical brain atlas [35] and saved as a template. The following ROIs were positioned on the
reference section: two symmetrical irregular ROIs over the right and left striata (as radiotracer-specific
binding), two symmetrical circular ROIs over the right and left caudates and putamen, respectively
(as radiotracer-specific binding), and one irregular ROI over the occipital cortex (as radiotracer
non-specific binding).

All ROIs were positioned by the same highly experienced observer. The mean counts per pixel in
each region were used for semi-quantitative analysis. Specific and non-specific 123I-FP-CIT binding
ratios were calculated bilaterally for the striatum, putamen, and caudate nucleus using the following
formula: ((mean counts in striatal ROI)-(mean counts in occipital ROI))/(mean counts in occipital ROI).

2.3. Statistical Analysis

Statistical analysis was performed using SPSS for MAC 26.0 (SPSS inc. Chicago, Illinois) software.
Continuous variables were expressed as a mean ± standard deviation (SD), while categorical variables
are reported as average number and percentage. Pearson’s correlation analysis was used to assess the
relationship between SPECT data and psychometric measures. A Multiple linear regression has been
conducted to investigate the potential impact of confounding variables (i.e., sex, age) on changes in
striatal DAT availability.

Two groups (high suicide risk vs. low suicide risk) were created retrospectively based on the
results obtained at the 3rd item of the HDRS-21 on suicide. The two groups were compared through
the ANOVA analysis.

All tests were two-sided with a level of significance set at p < 0.05.

3. Results

3.1. Sociodemographic and Clinical Assessment

The total number of subjects enrolled in this study was 51 (22 males; 43.1%), with a mean age
of 65.82 ± 12.42. All sociodemographic and psychometric data are reported in Table 1. Striatal DAT
availability is reported in Table 2.

Table 1. Descriptive for the variables of the study (n = 51).

Variable
Number

(Percentage)
Mean SD Range Median

Age 65.82 12.42 30–82 69
Education years 10.6 5.10 5–18 10.5

Sex
Male

Female
22 (43.1%)
29 (56.1%)

HDRS-21 21.67 3.51 18–31 21
Suicidality

(HDRS-21 ITEM 3 > 0)
20 (39.2%)

BHS 11.57 3.1 6–19 12
HAM-A 15.35 3.19 10–23 15

DES 7.42 6.06 1.07–38.93 6.07

Note. SD: standard deviation. HDRS-21: 21-item Hamilton Depression Rating Scale; BHS: Back Hopelessness
Scale; SHAPS: Snaith Hamilton Pleasure Scale; HAM-A: Hamilton Anxiety Rating Scale; DES: Dissociative
Experiences Scale.

Brain Sci. 2020, 10, 519 5 of 11

Table 2. DAT striatal availability.

Striatal 123I-FP-CIT Binding Ratios Mean SD Range Median

Right Putamen 2.56 0.33 1.68–3.29 2.60
Left Putamen 2.46 0.37 1.54–3 2.52
Right Caudate 3.35 0.45 2.07–4.3 3.27
Left Caudate 3.29 0.40 2.39–4.1 3.30

Right Striatum 2.68 0.43 1.65–3.61 2.69
Left Striatum 2.63 0.43 1.72–3.56 2.59

Note. SD: standard deviation.

3.2. Correlations between Psychometric Scales and Striatal DAT Availability

All variables were normally distributed according to the Shapiro–Wilk test.
Pearson correlation analyses were conducted to investigate possible correlations between the

specific dimensions evaluated through psychometric assessments and the DAT availability in the
basal ganglia. According to our analysis, depression severity showed an inverse correlation with DAT
availability in right Caudate (R = −0.388, p = 0.005) and Left Putamen (R = −0.291, p = 0.038).

In addition, an inverse correlation was found between hopelessness and DAT availability in
all basal ganglia areas bilaterally, showing that as the hopelessness intensity in depressed patients
increased, DAT levels in the basal ganglia reduced progressively, as shown in Figure 1 (all correlation
coefficients and confidence intervals are available in Supplementary Materials).

Brain Sci. 2020, 10, x FOR PEER REVIEW 5 of 11

Table 2. DAT striatal availability.

Striatal 123I-FP-CIT Binding Ratios Mean SD Range Median
Right Putamen 2.56 0.33 1.68–3.29 2.60
Left Putamen 2.46 0.37 1.54–3 2.52
Right Caudate 3.35 0.45 2.07–4.3 3.27
Left Caudate 3.29 0.40 2.39–4.1 3.30

Right Striatum 2.68 0.43 1.65–3.61 2.69
Left Striatum 2.63 0.43 1.72–3.56 2.59

Note. SD: standard deviation.

3.2. Correlations between Psychometric Scales and Striatal DAT Availability

All variables were normally distributed according to the Shapiro–Wilk test.
Pearson correlation analyses were conducted to investigate possible correlations between the

specific dimensions evaluated through psychometric assessments and the DAT availability in the
basal ganglia. According to our analysis, depression severity showed an inverse correlation with
DAT availability in right Caudate (R = −0.388, p = 0.005) and Left Putamen (R = −0.291, p = 0.038).

In addition, an inverse correlation was found between hopelessness and DAT availability in all
basal ganglia areas bilaterally, showing that as the hopelessness intensity in depressed patients
increased, DAT levels in the basal ganglia reduced progressively, as shown in Figure 1 (all correlation
coefficients and confidence intervals are available in Supplementary Materials).

Figure 1. Correlations between hopelessness and dopamine transporter. (a): Correlation between
hopelessness and right putamen. (b): Correlation between hopelessness and right caudate. (c): Correlation
between hopelessness and right striatum. (d): Correlation between hopelessness and left putamen. (e):
correlation between hopelessness and left caudate. (f): Correlation between hopelessness and left striatum.
The correlation coefficients and p-values are reported for each plot.

A multiple linear regression has been conducted to investigate the potential impact of
confounding variables (i.e., sex, age) on the association between hopelessness and striatal DAT
availability in our sample.

Figure 1. Correlations between hopelessness and dopamine transporter. (a): Correlation between hopelessness
and right putamen. (b): Correlation between hopelessness and right caudate. (c): Correlation between
hopelessness and right striatum. (d): Correlation between hopelessness and left putamen. (e): correlation
between hopelessness and left caudate. (f): Correlation between hopelessness and left striatum. The correlation
coefficients and p-values are reported for each plot.

A multiple linear regression has been conducted to investigate the potential impact of confounding
variables (i.e., sex, age) on the association between hopelessness and striatal DAT availability in
our sample.

Brain Sci. 2020, 10, 519 6 of 11

Hopelessness was the only factor associated to striatal DAT modifications in bilateral putamen and
left caudate (right putamen: BHS beta = −0.457, p = 0.001; Sex. Beta = 0.001, p = 0.994; Age beta = 0.114,
p = 0.403; left putamen BHS beta = −0.462, p = 0.001; Sex. Beta = 0.057, p = 0.673; Age beta = 0.077,
p = 0.569; left caudate BHS beta = −0.489, p < 0.001; Sex. Beta = 0.130, p = 0.317; Age beta = 0.228,
p = 0.085; left striatum BHS beta = −0.327, p = 0.021; Sex. Beta = −0.094, p = 0.509; Age beta = 0.99,
p = 0.489; right striatum BHS beta = −0.290, p = 0.043; Sex. Beta = −0.068, p = 0.640; Age beta = 0.088,
p = 0.544), while a simultaneous role of age was detected in right caudate region (right caudate BHS
beta = −0.425, p = 0.002; Sex. Beta = 0.238, p = 0.074; Age beta = 0.277, p = 0.040).

No other significant correlations between psychometric scores and DAT availability were found
(all correlation coefficients and confidence intervals are available in Supplementary Materials).

3.3. Suicide Risk and Striatal DAT Availability

High suicide risk group showed lower DAT availability in Left Putamen and Right Caudate,
compaired to low suicide risk group, as reported in Table 3.

Table 3. DAT striatal availability in High suicide Risk (n = 20) vs. Low suicide Risk subjects (n = 31)
(ANOVA).

Striatal 123I-FP-CIT Binding Ratios Mean SD Range F-value p Value

Right Putamen
High Suicide Risk 2.48 0.36 1.68–3.29

1.598 0.212
Low Suicide Risk 2.60 0.30 2.00–3.29

Left Putamen
High Suicide Risk 2.31 0.45 1.54–3.00

5.677 0.021 *
Low Suicide Risk 2.56 0.27 1.82–3.00

Right Caudate
High Suicide Risk 3.19 0.50 2.07–4.30

4.412 0.041 *
Low Suicide Risk 3.45 0.39 2.95–4.28

Left Caudate
High Suicide Risk 3.18 0.43 2.39–3.90

2.918 0.094
Low Suicide Risk 3.37 0.36 2.70–4.10

Right Striatum
High Suicide Risk 2.58 0.43 1.65–3.40

1.633 0.207
Low Suicide Risk 2.74 0.42 1.81–3.61

Left Striatum
High Suicide Risk 2.52 0.44 1.76–3.56

2.150 0.149
Low Suicide Risk 2.70 0.41 1.72–3.50

Note. SD: standard deviation. *: p value < 0.05.

3.4. Correlations between Psychometric Scales

We found a significant positive correlation between hopelessness and dissociation (Pearson’s
correlation analysis: r = 0.320, p = 0.05; Figure 2), reflecting an increase in dissociative symptoms in
depressed patients with higher hopelessness, as shown in Figure 2.

Brain Sci. 2020, 10, x FOR PEER REVIEW 7 of 11

Figure 2. Correlations between hopelessness and dissociation.

4. Discussion

Our results show the existence of an inverse correlation between hopelessness and DAT
availability, which appears to have widely decreased in all basal ganglia. To the best of our
knowledge, this is the first study to show a relationship between hopelessness in MDD and striatal
dopaminergic dysfunction.

The existence of a striatal DA dysfunction has been highlighted in several preclinical and clinical
studies on MDD [14]. These findings seem to be particularly consistent for depressed patients with
specific psychopathological characteristics, such as anhedonia, deeply related to the dopaminergic
reward system [20,36]. Previous studies, in fact, have found a dopaminergic striatal dysfunction in
anhedonic patients, involving the reward system and basal ganglia, in particular ventral striatum
(nucleus accumbens) [17,19,20]. On the other hand, no consideration regarding the potential
relationship between hopelessness and dopaminergic dysfunction has been reported in previous
research [21–26].

Considering the common psychopathological aspects shared by anhedonia and hopelessness,
such as the loss of motivation and negative beliefs, which seems to involve the dopaminergic reward
system, we hypothesized that hopelessness would be correlated to a striatal dopaminergic
disfunction, as previously reported for anhedonia.

The inverse correlation between hopelessness intensity and DAT availability involving all the
basal ganglia is an interesting element emerged in our study, since previous evidence on anhedonia
showed that dopaminergic dysfunction appeared to be particularly focused in ventral and only in
some specific areas of dorsal striatum (particularly caudate). From a clinical point of view, this is
consistent with the substantial differences characterizing anhedonia and hopelessness.

The former represents the inability to experience pleasure or interest in almost all activities of
daily life and seems to be a transdiagnostic dimension which is not only interesting for studies on
MDD [37]. The latter consists of negative expectations about the future, which could involve the self
and others, where subjects find it impossible to solve their problems, so that they never reach their
life goals [3]. This lack of hope could lead to suicidal ideation as suicide becomes perceived as the
only way to escape from a presumed tragic and incomplete future.

In our opinion, these findings could be explained by considering the different dopaminergic
circuits involved; while anhedonia seems to be principally related to a dysfunction of the ventral
striatum (considered the main core of dopaminergic reward pathways), hopelessness seems to
involve different and more complexly subcortical DA pathways. In particular, a dysfunction of the
Default Mode Network (DMN) [38] that regulates mind wandering [39] and the ability to reflect on
their own events [40] could lead to hyper-reflexivity and rumination [41] on a present that, for a

Figure 2. Correlations between hopelessness and dissociation.

Brain Sci. 2020, 10, 519 7 of 11

In addition, depressive symptomatology intensity evaluated through the HDRS-21 was
significantly correlated to dissociation (Pearson’s correlation analysis: r = 0.386; p = 0.01) and
hopelessness (Pearson’s correlation analysis: r = 0.371, p = 0.01). All other correlation analyses between
psychometric scales are reported in the Supplementary Materials.

4. Discussion

Our results show the existence of an inverse correlation between hopelessness and DAT availability,
which appears to have widely decreased in all basal ganglia. To the best of our knowledge, this is the
first study to show a relationship between hopelessness in MDD and striatal dopaminergic dysfunction.

The existence of a striatal DA dysfunction has been highlighted in several preclinical and clinical
studies on MDD [14]. These findings seem to be particularly consistent for depressed patients with
specific psychopathological characteristics, such as anhedonia, deeply related to the dopaminergic
reward system [20,36]. Previous studies, in fact, have found a dopaminergic striatal dysfunction in
anhedonic patients, involving the reward system and basal ganglia, in particular ventral striatum
(nucleus accumbens) [17,19,20]. On the other hand, no consideration regarding the potential relationship
between hopelessness and dopaminergic dysfunction has been reported in previous research [21–26].

Considering the common psychopathological aspects shared by anhedonia and hopelessness,
such as the loss of motivation and negative beliefs, which seems to involve the dopaminergic reward
system, we hypothesized that hopelessness would be correlated to a striatal dopaminergic disfunction,
as previously reported for anhedonia.

The inverse correlation between hopelessness intensity and DAT availability involving all the
basal ganglia is an interesting element emerged in our study, since previous evidence on anhedonia
showed that dopaminergic dysfunction appeared to be particularly focused in ventral and only in
some specific areas of dorsal striatum (particularly caudate). From a clinical point of view, this is
consistent with the substantial differences characterizing anhedonia and hopelessness.

The former represents the inability to experience pleasure or interest in almost all activities of
daily life and seems to be a transdiagnostic dimension which is not only interesting for studies on
MDD [37]. The latter consists of negative expectations about the future, which could involve the self
and others, where subjects find it impossible to solve their problems, so that they never reach their life
goals [3]. This lack of hope could lead to suicidal ideation as suicide becomes perceived as the only
way to escape from a presumed tragic and incomplete future.

In our opinion, these findings could be explained by considering the different dopaminergic
circuits involved; while anhedonia seems to be principally related to a dysfunction of the ventral
striatum (considered the main core of dopaminergic reward pathways), hopelessness seems to involve
different and more complexly subcortical DA pathways. In particular, a dysfunction of the Default
Mode Network (DMN) [38] that regulates mind wandering [39] and the ability to reflect on their own
events [40] could lead to hyper-reflexivity and rumination [41] on a present that, for a depressed
patient, appears impossible to live and endure [42]. In this context, hopelessness appears as an
element generated by wider and deeper alterations of the dopaminergic pathways, generating clinical
manifestations different from anhedonia.

Another important finding of our investigation was the positive correlation between dissociative
symptoms and hopelessness: depressed patients with high hopelessness experience severe dissociative
symptoms. From a clinical point of view, this finding could be explained when considering dissociation
as a way to coexist with hopelessness: dissociative symptoms seem to be a manner to deal with stressful
mental processes and tolerate the lack of positive future prospects and the emotional pain and distress
experienced by these patients [12].

Concerning suicidality, our preliminary analysis shows differences between high suicide risk and
low suicide risk MDD patients in DAT availability: patients with high suicidality showed lower DAT
levels in right caudate and left putamen. These findings are particularly interesting considering that
the role of dopaminergic dysregulations in suicidality is still relative uncertain [21–26].

Brain Sci. 2020, 10, 519 8 of 11

Our results, therefore, highlighting a dopaminergic dysfunction of basal ganglia both in
hopelessness and in suicidality separately, reinforce the psychopathological correlation of the two
aforementioned clinical dimensions already described in previous studies [43].

Taken together, the finding of low levels of DAT in subcortical areas in subjects with severe
hopelessness and high suicidality suggests the possible use of dopaminergic system modulators as
strategies to contain suicidal risk in these patients. Analyzing patient responses to pharmacological
agents modulating the dopaminergic system could improve the clinical outcomes and deserve to
be specifically tested. These treatments are potentially effective in the context of integrated clinical
approaches that include adequate psychotherapeutic management. Furthermore, considering our
preliminary results, we can speculate that the treatment of high hopelessness of MDD patients through
dopaminergic modulators could help physicians to contain dissociative symptoms, considering the
frequent cooccurrence of hopelessness and dissociation in these patients.

5. Limitations

Our results should be interpreted cautiously due to several limitations: firstly, the small sample
size could be an important limitation to our speculations. Secondly, 123I-FP-CIT is a non-specific
radiotracer for DAT because of its capacity to bind the serotonin transporter (SERT), although only
low-SERT density has been reported in the basal ganglia [44,45]. Thirdly, our study does not include a
detailed assessment of suicidality through the use of a specific scale, since BHS gives only an indirect
indication of patients’ suicidal risk and the 3rd item of HDRS-21 is not a validated scale for the
assessment of suicidal risk. In addition, possible confounding factors (i.e., marital status, traumatic
experiences, number of MDE, time from the first MDE) should be taken into account in future research,
since they could affect DAT levels in basal ganglia.

6. Conclusions

Our results support the hypothesis of specific pathophysiological alterations underpinning
different MDD endophenotypes. In particular, the significant correlation between hopelessness and
striatal dopaminergic dysfunction represents new and important evidence on this topic. Furthermore,
the correlation between suicidality and striatal dopaminergic dysfunction is particularly intriguing,
although our results should be confirmed with validated assessment scales for suicidality. Further
studies on both hopelessness and suicidality are necessary to confirm our results and to test potential
interventions to reverse the functional consequences caused by these leading clinical features of
MDD. If confirmed, these results could help physicians treat patients by considering their peculiar
clinical features and possibly provide dopaminergic treatments specific for hopelessness and prevent
suicidal ideation.

Supplementary Materials: The following are available online at http://www.mdpi.com/2076-3425/10/8/519/s1,
Table S1: correlation between hopelessness and DAT levels in basal ganglia, Table S2: correlations between
psychometric scales, Table S3: correlation between psychometric scales and DAT levels in basal ganglia.

Author Contributions: M.P., G.d., G.C. and D.D.G. contributed to the development of the study concept and
design. M.P., G.d., F.C., G.C., D.D.G. collected clinical and imaging data. G.d. and M.P. performed the statistical
analysis. M.P., G.d., G.M., A.M., G.C., D.D.G. carried out the data interpretation. G.d., R.C., I.D.M. and A.M.
wrote the first draft of the manuscript. M.d.G., G.M., V.V., F.D.-G. and L.J. revised the manuscript and provided
substantial comments. All authors have read and agreed to the published version of the manuscript.

Funding: This research received no external funding.

Acknowledgments: This work was supported by the “Departments of Excellence 2018–2022” initiative of the
Italian Ministry of Education, University and Research for the Department of Neuroscience, Imaging and Clinical
Sciences (DNISC) of the University of Chieti-Pescara. We thank Riccardo Della Monica for the precious help for
the elaboration of the graphs.

Conflicts of Interest: The authors declare no conflict of interest to disclose.

Brain Sci. 2020, 10, 519 9 of 11

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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

  • Introduction
  • Materials and Methods
    • Subjects
    • SPECT Procedure
    • Statistical Analysis
  • Results
    • Sociodemographic and Clinical Assessment
    • Correlations between Psychometric Scales and Striatal DAT Availability
    • Suicide Risk and Striatal DAT Availability
    • Correlations between Psychometric Scales
  • Discussion
  • Limitations
  • Conclusions
  • References

Dissociation in Psychiatric Disorders: A Meta-Analysis
of Studies Using the Dissociative Experiences Scale
Lisa Lyssenko, Dipl.-Psych., Christian Schmahl, Dr.med., Laura Bockhacker, Dr.med., Ruben Vonderlin, M.Sc.,
Martin Bohus, Dr.med., Nikolaus Kleindienst, Dr.rer.hum.biol.

Objective: Dissociation is a complex, ubiquitous construct in
psychopathology. Symptoms of dissociation are present in a
variety of mental disorders and have been connected to
higher burden of illness and poorer treatment response, and
not only in disorders with high levels of dissociation. This
meta-analysis offers a systematic and evidence-based study
of the prevalence and distribution of dissociation, as assessed
by the Dissociative Experiences Scale, within different cat-
egories of mental disorders, and it updates an earlier meta-
analysis.

Method: More than 1,900 original publications were
screened, and 216 were included in the meta-analysis,
comprising 15,219 individuals in 19 diagnostic cate-
gories.

Results: The largest mean dissociation scores were found in
dissociative disorders (mean scores .35), followed by post-
traumatic stress disorder, borderline personality disorder, and
conversion disorder (mean scores .25). Somatic symptom
disorder, substance-related and addictive disorders, feeding
and eating disorders, schizophrenia, anxiety disorder, OCD,
and most affective disorders also showed mean dissociation
scores .15. Bipolar disorders yielded the lowest dissociation
scores (mean score, 14.8).

Conclusions: The findings underline the importance of
careful psychopathological assessment of dissociative symp-
toms in the entire range of mental disorders.

Am J Psychiatry 2018; 175:37–46; doi: 10.1176/appi.ajp.2017.17010025

Dissociation is a ubiquitous construct in modern psychopa-
thology. DSM-5 defines dissociation as “disruption of and/or
discontinuity in the normal integration of consciousness,
memory, identity, emotion, perception, body representation,
motor control, and behavior” (1). The corresponding phe-
nomena cover a range from relatively common experiences,
suchasbeingcompletelyabsorbedbyabookormovie,tosevere
states, such as not recognizing oneself in the mirror (2). More
common experiences have often been linked to mild forms of
absorption, that is, focusing on one aspect of experiences and
blocking others (3). More severe dissociative experiences are
reflected in the DSM-5 subtypes of dissociative disorders:
dissociative amnesia describes the inability to recall autobio-
graphical information; depersonalization/derealization disor-
derscompriseexperiencesoffeelingdisconnectedorestranged
from one’s body, thoughts,oremotionsand/or perceiving one’s
surroundings as foggy, surreal, or visually distorted (1).

Beyond the disorders primarily characterized by disso-
ciation, “transient, stress-related severe dissociative symp-
toms” serve as a criterion for borderline personality disorder
(1),andadissociativesubtypeofposttraumaticstressdisorder
(PTSD) was introduced in DSM-5 (4). Less noted but equally
important research has shown that dissociative features also

seem to play a role in the pathology of many other mental
disorders, such as schizophrenia (5), eating disorders (6),
panic disorders (7), affective disorders (8, 9), and obsessive-
compulsive disorder (OCD) (10).

Dissociative symptoms in mental disorders are of high
clinical relevance. They have been linked to maladaptive
functioning and symptom severity in some disorders, such as
executive functioning in borderline personality disorder (11),
neuropsychological performance in depression (9), number
of binge episodes in eating disorders (6), alexithymia in panic
disorders (12), and anxiety and depression in OCD (13). Apart
from a higher burden of illness, patients may also benefit less
from psychotherapeutic interventions. Several studies have
indicated that dissociative symptoms can serve as a predictor
for nonresponse in psychotherapeutic treatments of PTSD
(14–16), OCD (17–19), and panic disorders (20).

Transdiagnostically, the experience of dissociative symp-
toms has been linked to acute or chronic stress (21). Neuro-
biological findings suggest that dissociative phenomena are
likelytodisruptinformationprocessing,learning,andmemory
on various levels (22). Dissociation has been further linked
to physiological processes such as sleep (23) and fluid intake
(24), as well as to personality variables, such as fantasy

See related features: Editorial by Dr. Spiegel (p. 4) and Clinical Guidance (Table of Contents)

Am J Psychiatry 175:1, January 2018 ajp.psychiatryonline.org 37

ARTICLES

proneness and suggestibility (25). On a cognitive-emotional
level, dissociation may be a learned automatic response to re-
duce or avoid aversive emotional states (26, 27). As a secondary
process, the experience of dissociation can induce stress itself
because it not only disrupts neurocognitive functioning, but can
also be perceivedas losing control (28). Recurrent dissociation
may therefore reduce the individual’s confidence in reality
monitoring ability, perceivedcontrol,and sense of self (29, 30),
which in turn may result in a higher burden of disease.

The transdiagnostic evaluation of those mechanisms is im-
peded by the fact that neurobiological studies have been mostly
conducted in populations of patients who had experienced
various traumas, often chronically and/or early in life (e.g., 31).
Althoughthestatisticalassociationwasfoundtoberathersmallin
some studies (27), several studies have pointed to a strong asso-
ciation between trauma and dissociation (32–36). Thus, the ex-
perience of trauma does not seem to be a conditio sine qua non
for pathological dissociation. Studies covering a broader range of
mental disorders could shed light on common mechanisms and
enhance the development of transdiagnostic treatment modules
to deal with dissociative symptoms. The meta-analysis we present
hereaimstostimulatethislineofresearchbyprovidinganoverview
oftheoccurrenceofdissociativesymptomsacrossmentaldisorders.

By far, the most commonly
used psychometric instrument
for the assessment of dissocia-
tive experience is the Dissocia-
tive Experiences Scale (DES)
(2). The DES is a self-rating
instrument comprising 28 items
that build on the assumption
of a “dissociative continuum”
ranging from mild normative
to severe pathological disso-
ciation. Subjects are asked
to make slashes on 100-mm
lines to indicate where they fall
onacontinuum for questions
on experiences of amnesia,
absorption, depersonalization,
andderealization—forexample,
“Some people have the experi-
ence of driving a car and sud-
denly realizing that they don’t
remember what has happened
during all or part of the trip.
Mark the line to show what
percentageoftimethishappens
toyou”(2,p.733).Asthescoring
procedure of the continuous
scale was time consuming, a
revised version of the scale,
the Dissociative Experiences
Scale–II (DES-II) (37) uses an
11-point Likert scale ranging
from 0 to 100.

Studies on the psychometric properties of the scale have
shown high validity and reliability for both versions, both in
clinicalandnonclinicalpopulations(38–42).Thefirst,andsofar
the only, comprehensive meta-analysis on the DES, by van
IjzendoornandSchüngel(43),conductedin1996,showsamean
Cronbach’s alpha of 0.93 in 16 studies, a high predictive validity
concerning dissociative disorders and PTSD, as well as a high
convergent validity with alternative measures of dissociation
(mean Cohen’s d=1.82; N=5,916). While initial studies (e.g., 44)
found a three-factor structure with the factors amnesia, ab-
sorption, and depersonalization/derealization, the factorial
structure of the DES remains controversial (41, 42, 45, 46).

Considering the high number of original publications on
theDES(N.2,000),fewmeta-analyseshavebeenconducted.
One meta-analysis on schizophrenia showed a large effect
size comparing dissociation scores of patients (N=293) and
healthy subjects (N=474) (g=20.86, 95% CI=21.13, 20.60),
with trauma history being a potential mediator (5). Scalabrini
et al. (47) compared the dissociation scores in borderline
personality disorder with those in other mental disordersand
found significantly elevated dissociative symptoms in patients
withborderlinepersonalitydisordercomparedwithpatientswith
all other disorders (N=2,035; d=0.54, p,0.01) but lower levels of

FIGURE 1. PRISMA Flow Diagram for a Meta-Analysis of Dissociation in Psychiatric Disorders
Id

e
n

ti
fi

c
a

ti
o

n
E

li
g

ib
il

it
y

S
c

re
e

n
in

g
In

c
lu

d
e

d

Records identifi ed through
database searching (PubMed,

PsycINFO, Web of Science,
Academic Search Premier)

(N=3,492)

Excluded duplicates
(N=1,585)

Full-text articles assessed for
eligibility (N=1,247)

Articles eligible for review
(N=221)

Excluded because <4 articles
per diagnosis (N=5)

Records screened
(N=1,907)

Records excluded at title or
abstract screening (N=660)

Studies included
(N=216)

Full-text articles excluded (N=1,026)
– Healthy sample (N=296)

– No distinguishable diagnostic groups (N=149)

– No analysable DES score (N=142)

– Unpublished dissertations (N=109)

– No DES score (N=103)

– No DSM diagnosis (N=108)

– Other DES versions (N=27)

– Conference papers (N=23)

– Other reasons (N=69)

38 ajp.psychiatryonline.org Am J Psychiatry 175:1, January 2018

DISSOCIATION IN PSYCHIATRIC DISORDERS

dissociation than in patients
withPTSD(d=20.50,p,0.01)
and dissociative disorders (d=
20.35, p,0.05). As noted,
theonlycomprehensivemeta-
analysis, by van Ijzendoorn
and Schüngel (43), was pub-
lished about 20 years ago and
included 85 individual studies
with about 6,000 patients.
As expected, the highest scores
for dissociation were found for
dissociative disorders (mean=
35.3), followed by PTSD
(mean=32.6), affective disor-
ders (mean=19.4), schizophre-
nia (mean=19.1), personality
disorders (mean=16.6), eating
disorders (mean=14.5), and
anxiety disorders (mean=10.2).
Comparison scores were cal-
culated for healthy samples
(mean=11.57) and students
(mean=14.27). The authors
conclude that “against the background of potential comor-
bidity and undiscovered dissociation, the means for normals
and nondissociative patients were remarkably similar” (43,
p. 372).

Since the meta-analysis by van Ijzendoorn and Schüngel
(43), dissociation has been studied in a range of mental
disorders that had not been included, such as OCD (10) and
substance abuse (48). Other research has shown that dis-
sociation plays a role in diseases like panic disorders (7, 31),
which showed surprisingly low mean dissociation scores
in that first analysis. The goal of our meta-analysis is thus to
provide an evidence base for the prevalence and distribution
of dissociation in adults suffering from mental disorders.

METHOD

Study Selection
We searched the following databases for primary stud-
ies through November 2016: PubMed, PsycINFO, Web
of Science, and Academic Search Premier. Our search
strategy aimed at articles using the DES or the German
version of the scale (FDS) (49, 50) in adults with mental
disorders. Although there are formal differences between
versions I and II of the DES (visual analogue scale versus
Likert-type scale, both ranging from 0 to 100), differences
in the results for the two versions have been shown to be
negligible (51). Therefore, we decided not to differentiate
between the versions of the scale. We developed the search
strategy for PsycINFO (“dissoc* exper* scale” OR “FDS”)
and adapted it for the other databases. We reviewed relevant
review articles and related systematic reviews to identify

studies that were missed in the database searches. If full text
was not retrievable from online databases or university li-
braries, we contacted the corresponding authors. There
were no language or publication date restrictions.

Two trained investigators independently screened titles
and abstracts for relevance. In the full-text screening, the
following inclusion criteria were imposed: 1) studying a
population with mental disorders diagnosed according to
ICD (52) or DSM; 2) reporting the sample size and the mean
score and standard deviation on the DES, or sufficient in-
formation to calculate them; and 3) specification of psy-
chometric properties fortranslationsofnon-English versions
of the DES. Data were extracted by two independent raters
using a standard form and systematically screened for full
agreement between raters. Every disagreement was resolved
by discussion within the review team. The protocol for this
meta-analysis is available in PROSPERO (the “International
prospective register of systematic reviews”) and can be
accessed at http://www.crd.york.ac.uk/prospero/display_
record.asp?ID=CRD42015020731.

Data Synthesis
Diagnostic group, mean and standard deviation of the dis-
sociation score, and number of participants were extracted
from the primary studies. For each diagnostic group, the
random-effects model described in DerSimonian and Laird
(53) was used to calculate a group-specific mean and the 95%
confidence interval. This approach allows for the integration
of data from intrinsically heterogeneous populations that
result, for example, from the use of different diagnostic
systems. To quantify heterogeneity of the dissociation scores

TABLE 1. Overview of the Results of a Meta-Analysis of Dissociation in Psychiatric Disordersa

Diagnostic Group k N
Mean

DES Score 95% CI I2 (%)

Dissociative identity disorder 29 1,313 48.7 46.4, 50.9 77.9
Dissociative disordersb 70 3,073 38.9 36.1, 41.6 95.3
Posttraumatic stress disorder 33 2,106 28.6 25.6, 31.5 96.9
Borderline personality disorder 27 1,705 27.9 25.3, 30.6 89.2
Conversion disorder 20 857 25.6 21.5, 29.7 93.4
Depersonalization/derealizationdisorder 16 759 25.1 22.7, 27.4 80.2
Anorexia nervosa 6 253 24.1 16.3, 31.9 92.9
Bulimia nervosa 8 353 22.0 16.9, 27.0 90.5
Gambling disorder 4 187 19.9 7.9, 31.8 98.5
Alcohol use disorder 12 1,467 19.7 16.5, 23.0 97.5
Somatic symptom disorder 4 132 18.8 16.4, 21.2 16.1
Feeding and eating disordersb 24 1,401 18.6 16.0, 21.2 91.6
Schizophrenia 17 594 17.8 15.6, 20.2 80.5
Other substance-related disorders 14 1,107 17.7 14.7, 20.7 91.9
Panic disorder 11 319 15.6 10.8, 20.4 94.9
Obsessive-compulsive disorder 14 858 15.3 13.2, 17.4 80.3
Depressive disordersb 12 833 15.3 11.2, 19.4 98.1
Anxiety disordersb 19 615 15.2 12.4, 18.0 93.1
Bipolar and related disordersb 7 208 14.8 8.8, 20.8 97.3
Total 216 15,219

a Articles that reported on more than one diagnostic group were included in every category the authors reported
dissociation scores on. Diagnostic groups are sorted in descending order of Dissociative Experiences Scale (DES) mean
score. k=number of included studies; N=number of patients included in diagnostic group; I2= heterogeneity statistic.

b DSM-5 main category.

Am J Psychiatry 175:1, January 2018 ajp.psychiatryonline.org 39

LYSSENKO ET AL.

between studies, we used I2 (54)—an index, based on chi-
square statistics and degrees of freedom, that was recom-
mended for Cochrane Reviews (55). Because only descriptive
data on dissociation scores were included in the analysis,
the risk of bias in the primary studies was assumed to be
unlikely and therefore was not assessed. Data synthesis
was conducted with R, version 3.2.4 (56), using the metafor
package (57).

RESULTS

The search in the electronic databases yielded 1,907 different
articles (Figure 1). After exclusion of 660 articles during title
or abstract screening, 1,247 articles were retrieved for full-
text screening, of which 1,026 were subsequently excluded;
reasons for exclusion are listed in Figure 1. Across all di-
agnostic groups, weincluded 216 articles with a total of 15,219
individuals.

To calculate meta-analytic statistics, the original studies
were grouped according to the DSM diagnosis described in
the articles. For some diagnoses, this procedure revealed
specific subcategories of DSM chapters (e.g., gambling dis-
orders). For some categories, only articles reporting on
broader categories or entire DSM chapters (e.g., bipolar
disorders) werefound. To avoid the confounding influence of
diagnostic specification, we included articles reporting on
subcategories in both the relevant subcategory as well as the
corresponding broader category. Articles that reported on
more than one diagnostic group were included in every
category the authors reported dissociation scores on. In cases
ofco-occurringdisorders,weincludedtheindividualsinboth
categories. We included all subcategories in which at least
four studies reported data, regardless of whether this sub-
category of disorders is still included in DSM-5. In the final

step, we excluded five studies because there were not enough
studies for each diagnosis: one study each on kleptomania
(58) and pathological Internet use (59) and three studies on
mixed personality disorders (60).

Diagnostic categories, number of individual studies, and
number of individual patients as well as statistics are listed in
Table 1. A graphical illustration of the results is presented in
Figure2.Forestplotsofeachdiagnostic categoryareincluded
in the datasupplement that accompanies theonline edition of
this article.

The highest dissociation scores were found for dissocia-
tive identity disorders, with a mean score of 48.7 (95%
CI=46.4, 50.9), based on 29 publications with 1,313 patients
(Figure 3; the full reference list of included studies can be
found in the online data supplement).

Scores for posttraumatic stress disorder were the second
highest, with a mean score of 28.6 (95% CI=25.6, 31.5), based
on 33 publications with 2,106 patients (Figure 4).

Scores for borderline personality disorder were third
largest, with a mean score of 27.9 (95% CI=25.3, 30.6), based
on 27 publications and 1,705 individual patients (Figure 5).
Scores for other mental disorders were distributed among (in
descending order) conversion disorder (mean=25.6), somatic
symptoms disorder (mean=18.8), substance-related and ad-
dictive disorders (gambling disorder, mean=19.9; alcohol
use disorder, mean=19.7; other substance-related disorders,
mean=17.7), feeding and eating disorders (mean=18.6),
schizophrenia (mean=17.8), OCD (mean=15.3), depressive
disorders (mean=15.3), anxiety disorders (mean=15.2), and
bipolar and related disorders (mean=14.8).

Only three categories yielded enough studies to analyze
dissociation subfactors: borderline personality disorder,
dissociative disorders, and schizophrenia. Patients suffering
from borderline personality disorder and schizophrenia

FIGURE 2. Mean Dissociative Experiences Scale Score for Each Diagnostic Group in a Meta-Analysis of Dissociation in
Psychiatric Disordersa

0

10

20

30

40

50

60

A
nx

ie
ty

d
is
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a Error bars indicate 95% confidence interval.

40 ajp.psychiatryonline.org Am J Psychiatry 175:1, January 2018

DISSOCIATION IN PSYCHIATRIC DISORDERS

had the highest scores for absorption, and patients with dis-
sociativedisordershadthehighestscoresfordepersonalization/
derealization (see Table S1 in the online data supplement for
details).

Heterogeneity, as assessed by I2, was .70% in all anal-
yses, except for somatic symptom disorders (I2=16.1%); the
highest heterogeneity was observed in gambling disorders
(I2=98.5%) (see Table 1).

DISCUSSION

This is the second meta-analysis of dissociation scores in a
broad variety of psychiatric disorders. While the first meta-
analysis was published more than 20 years ago (43) and
comprised85individualstudies,ourmeta-analysis reportson
216 individual studies with more than 15,000 individuals with
mental disorders. The largest dissociation scores were found
for dissociative disorders, followed by PTSD, borderline
personality disorder, and conversion disorder, and the lower
range of scores included substance-related and addictive
disorders, feeding and eating disorders, schizophrenia,
anxiety disorder, OCD, and affective disorders.

Our data confirm some but not all of the results reported in
the earlier meta-analysis. Confirming results were found
regarding dissociative disorders showing the highest overall

dissociation scores. In their analysis, van Ijzendoorn and
Schüngel (43) reported mean dissociation scores of 45.6
for multiple personality disorder (now called dissociative
identity disorder), 41.1 for unspecified dissociative disorders,
and 35.3 for the category of dissociative disorder not other-
wise specified. In our study we differentiated between dis-
sociative identity disorder and depersonalization/derealization
disorder, as listed in DSM-5 (1). Although the existence of
dissociativeidentitydisorderhasbeendiscussedcontroversially
(e.g., 61), our result of a mean dissociation score of 48.7 in a
total of 1,313 individuals with this diagnosis indicates very
high levels of dissociative experience in this diagnostic group.
Interestingly, depersonalization/derealization disorder yielded
numerically lower DES scores than PTSD and border-
line personality disorder. This may be due to the fact that
depersonalization/derealization disorder does not cover the
entire spectrum of dissociative symptoms, therefore leading
to lower overall dissociation scores.

Dissociation scores in PTSD and schizophrenia in our
analysis were close to those reported by van Ijzendoorn and
Schüngel (43), although their study included only one study
onschizophrenia(comparedwith17here)andfourstudieson
PTSD (compared with 33 here). Scores in PTSD were the
second highest in our analysis, reflecting the importance of
dissociation in relation to PTSD (62), for which a dissociative

FIGURE 3. Forest Plot of Dissociative Experiences Scale Scores in Dissociative Identity Disordera

0.00 20.00 40.00 60.00 80.00

Mean

First Author and Year

Berger 1994 (13)

Boon 1993 (18)

Carlson 1993 (28)

Choe 1995 (34)

Dell 2002 (40)

Dorahy 2005 (45)

Draijer 1993 (46)

Ellason 2003 (49)

Frischholz 1990 (70)

Gleaves 1995a (75)

Latz 1995 (99)

Lauer 1993 (100)

Martínez−Taboas 1995 (109)

Nijenhuis 1997 (127)

Nijenhuis 1999 (128)

Pokrajac 1994 (140)

Putnam 1996 (148)

Rodewald 2006 (153)

Ross 1988 (158)

Ross 1989 (157)

Ross 1995 (156)

Sar 1996 (166)

Sar 2007b (165)

Scroppo 1998 (173)

Shearer 1994 (177)

Tutkun 1995 (202)

Wassink 1996 (207)

Welburn 2003 (209)

Yargic 1998 (211)

Random-effects model

DES Score (95% CI)

26.80 (13.80, 39.80)

49.40 (45.49, 53.31)

42.80 (40.31, 45.29)

59.54 (54.09, 64.99)

46.15 (39.01, 53.29)

55.10 (44.29, 65.91)

56.80 (50.93, 62.67)

47.80 (41.87, 53.73)

55.00 (48.45, 61.55)

59.85 (51.83, 67.87)

59.50 (51.12, 67.88)

46.60 (36.59, 56.61)

60.30 (53.64, 66.96)

38.60 (32.27, 44.93)

54.20 (48.02, 60.38)

54.21 (44.00, 64.42)

44.60 (42.04, 47.16)

45.37 (41.73, 49.01)

37.20 (27.07, 47.33)

38.30 (29.14, 47.46)

44.60 (42.33, 46.87)

49.10 (43.40, 54.80)

51.10 (44.39, 57.81)

45.97 (38.16, 53.78)

48.50 (34.23, 62.77)

47.20 (39.29, 55.11)

48.86 (41.92, 55.80)

44.52 (36.23, 52.81)

46.10 (38.26, 53.94)

48.66 (46.38, 50.93)

a Reference numbers refer to the list of analyzed studies included in the online data supplement. DES=Dissociative Experiences Scale.

Am J Psychiatry 175:1, January 2018 ajp.psychiatryonline.org 41

LYSSENKO ET AL.

subtype was introduced in DSM-5. Although dissociative
symptoms are less pronounced in schizophrenia (mean
score, 17.8), they have been studied intensively in this disorder
because of similarities in the description of dissociative phe-
nomena and psychotic symptoms (63). Empirical studies have
yielded varying correlations between schizophrenia and
different aspects of dissociation, with depersonalization/
derealization showing the strongest relation (5). Several
authors have emphasized the relevance of depersonalization
as a mediator between childhood trauma and hallucinatory
experiences, thus acting as a risk factor for schizophrenia (e.g.,
64). It is hypothesized that depersonalization may facilitate a
person’s attribution of their own thoughts to external sources
(65), and a trauma-dissociation subgroup within schizophrenia
has been proposed (66).

Our data differ from the earlier meta-analysis (43) with
respect to eating disorders, anxiety disorders, and affective
disorders. While eating disorders and anxiety disorders show
considerably higher mean dissociation scores in our analysis
than in the earlier one (18.6 compared with 14.5 for eating
disorders; 15.2 compared with 10.2 for anxiety disorders), we

found lower scores for affective disorders (15.3 for depressive
disorders and 14.8 for bipolar disorders compared with 19.4
for affective disorders in the earlier analysis). Recent re-
search points to differential relations between dissociation
and symptoms of these disorders. In anorexia nervosa, where
thehighestmeandissociationscoreswerefound(meanscore,
24.1), symptoms of depersonalization in the form of body
schema distortions have been investigated (67). In bulimia
nervosa, dissociative qualities of amnesia, timelessness, and
involuntariness seem to play a role in bingeing behavior
and severity (6, 68). In anxiety disorders, experiences of
depersonalization/derealization have often been described
in relationship with panic attacks, although the sequence
of incidence is not clear: dissociation might trigger panic
attacks—for example, via the fear of losing control—but
concomitantsymptomsofpanicattacks,suchashyperarousal
or hyperarousal, might also produce dissociation (29). In
depressive disorders, the research on mechanisms of disso-
ciation is impeded by a strong overlap between depressive
symptoms such as emotional numbing, feelings of de-
tachment, and restricted emotional responsiveness (69), as

FIGURE 4. Forest Plot of Dissociative Experiences Scale Scores in Posttraumatic Stress Disordera

0.00 20.00 40.00 60.00 80.00

Mean

First Author and Year

Abramowitz 2010 (1)

Akyüz 2007 (4)

Amdur 1996 (6)

Aydin 2012 (8)

Bokhan 2012 (16)

Bolu 2014 (17)

Branscomb 1991 (22)

Bremner 1992 (23)

Callegari 2007 (26)

Chard 2005 (33)

Crowson 1998 (37)

Dasse 2015 (39)

El-Hage 2003 (48)

Espirito-Santo 2008 (51)

Evren 2011 (60)

Favaro 2000 (64)

Favaro 2006 (65)

Frewen 2014 (69)

Frueh 1994 (71)

Geraerts 2007 (73)

Karatzias 2010 (92)

Landre 2012 (96)

Matlack 2010 (110)

Mickleborough 2011 (118)

Najavits 2012 (124)

Nardo 2013 (125)

Nejad 2007 (126)

Öezdemir 2015 (132)

Prasko 2016a (141)

Putnam 1996 (148)

Tapia 2007 (199)

Tapia 2012 (198)

Zucker 2006 (214)

Random-effects model

DES Score (95% CI)

47.30 (40.80, 53.80)

18.70 (14.37, 23.03)

30.43 (27.33, 33.53)

27.93 (17.71, 38.15)

19.20 (18.67, 19.73)

50.24 (43.80, 56.68)

41.11 (36.07, 46.15)

27.00 (22.15, 31.85)

28.75 (23.36, 34.14)

19.48 (15.54, 23.42)

54.16 (48.94, 59.38)

29.80 (23.57, 36.03)

23.03 (19.41, 26.65)

35.00 (31.26, 38.74)

26.34 (22.30, 30.38)

19.10 (11.18, 27.02)

20.00 (13.42, 26.58)

33.17 (30.27, 36.07)

40.10 (33.45, 46.75)

34.50 (30.62, 38.38)

29.80 (26.33, 33.27)

26.80 (20.67, 32.93)

23.87 (21.16, 26.58)

9.30 (5.50, 13.10)

19.44 (15.14, 23.74)

14.60 (10.20, 19.00)

26.01 (23.89, 28.13)

44.40 (40.14, 48.66)

21.56 (15.45, 27.67)

31.50 (28.17, 34.83)

36.87 (28.81, 44.93)

22.80 (14.55, 31.05)

15.10 (13.86, 16.34)

28.57 (25.61, 31.54)

a Reference numbers refer to the list of analyzed studies included in the online data supplement. DES=Dissociative Experiences Scale.

42 ajp.psychiatryonline.org Am J Psychiatry 175:1, January 2018

DISSOCIATION IN PSYCHIATRIC DISORDERS

well as by shared covariates, such as sleep quality and dis-
tortions in autobiographic memory (23, 70).

Our analysis is the first to report systematically retrieved
mean dissociation scores for borderline personality disorder,
somatic symptom disorder, conversion disorder, substance-
related and addictive disorders, and OCD. Borderline per-
sonality disorder showed dissociation scores similar to those
of PTSD in 27 studies (mean score, 27.9). Furthermore, our
study confirmed the significance of dissociative symptoms in
borderline personality disorder, which has been acknowl-
edged by adding dissociative experiences as part of one of the
nine criteria for borderline personality disorder in DSM-IV
(71). Although classified as a personality disorder, borderline
personality disorder is closely associated with traumatic
stress. Rates of adverse childhood experiences have been
consistently demonstrated to be higher than 50% (72). In-
dependent of trauma experience and comorbid diagnoses,
almost all patients with borderline personality disorder re-
port identity confusion, unexplained mood changes, and
depersonalization (73).

“Somatic symptom and related disorders” is a new cate-
gory in DSM-5 (1) and comprises a broad spectrum of
disorders, including somatic symptom disorder (formerly
known as somatoform disorders), illness anxiety disorders,
conversion disorder (functional neurological symptom dis-
order), and factitious disorder. Notably, conversion disorder

is part of the dissociative spectrum in ICD-10 (52), and
dissociation scores were in a range similar to those of other
dissociative and trauma-related disorders in our meta-
analysis.

The high mean dissociation scores for addictive disorders—
19.9 for gambling disorder, 19.7 for alcohol use disorder, and
17.7 for other substance-related disorders—may be partly
related to comorbidities with PTSD, borderline personal-
ity disorder, and dissociative disorders (74–76). General
findings regarding the link between dissociation and sub-
stance abuse have been inconsistent but suggest lower
scores in samples without comorbid disorders (77–79). The
mean dissociation score of 15.3 for OCD falls within the
lower range of dissociative symptoms. Nevertheless, dis-
sociation has gained increasing attention in this area of
research. On a symptomatic level, dissociative amnesia has
been related to checking compulsion (80). This effect does
not seem to be linked to poorer memory or reality moni-
toring performance but rather to a reduced confidence in
these abilities (81).

Recent population-based studies show mean dissociation
scores in the general population of 8 in a Finnish sample
(N=2,001)(82)and10inaPortuguesesample(N=224)(83).In
their meta-analysis, van Ijzendoorn and Schüngel (43) report
a mean score of 11.6 for healthy subjects. Those numbers
appear to be considerably lower than all mean dissociation

FIGURE 5. Forest Plot of Dissociative Experiences Scale Scores in Borderline Personality Disordera

0.00 20.00 40.00 60.00 80.00

Mean

First Author and Year

Barnow 2011 (10)

Berger 1994 (13)

Brodsky 1995 (24)

Frewen 2014 (69)

Grambal 2016 (77)

Kanter 2001 (91)

Kleindienst 2011 (93)

Korzekwa 2009 (94)

Krause-Utz 2014 (95)

Lauer 1993 (100)

Löffler-Stastka 2009 (106)

Macchi 1998 (107)

Mazzotti 2016 (111)

Pokrajac 1994 (140)

Putnam 1996 (148)

Ross 2007 (155)

Russ 1996 (160)

Sar 2003 (163)

Semiz 2005 (176)

Semiz 2008 (175)

Shearer 1994 (177)

Simeon 2003c (187)

Turner 1998 (201)

Vuchelen 1996 (203)

Zanarini 2000 (213)

Zweig-Frank 1994a (215)

Zweig-Frank 1994b (216)

Random-effects model

DES Score (95% CI)

21.04 (16.49, 25.59)

24.40 (13.37, 35.43)

19.58 (15.44, 23.72)

30.22 (28.29, 32.15)

19.06 (15.95, 22.17)

40.17 (32.45, 47.89)

25.80 (21.46, 30.14)

26.90 (18.39, 35.41)

32.25 (25.33, 39.17)

17.70 (9.65, 25.75)

19.10 (14.48, 23.72)

30.59 (25.15, 36.03)

29.60 (26.61, 32.59)

39.31 (32.11, 46.51)

21.60 (14.85, 28.35)

22.70 (19.06, 26.34)

32.87 (25.87, 39.87)

44.41 (35.56, 53.26)

41.96 (35.59, 48.33)

41.33 (37.77, 44.89)

25.02 (19.75, 30.29)

25.80 (18.63, 32.97)

30.85 (25.05, 36.65)

30.65 (24.61, 36.69)

21.80 (19.66, 23.94)

22.36 (18.07, 26.65)

24.80 (21.43, 28.17)

27.95 (25.32, 30.57)

a Reference numbers refer to the list of analyzed studies included in the online data supplement. DES=Dissociative Experiences Scale.

Am J Psychiatry 175:1, January 2018 ajp.psychiatryonline.org 43

LYSSENKO ET AL.

scores calculated for mental disorders in our analysis. Van
Ijzendoorn and Schüngel’s conclusion that “the means for
normals and nondissociative patients were remarkably
similar” (43, p. 372) does not seem to be supported by our
results. The variety of mental disorders ranging between
15 and 25 in dissociation scores clearly speaks for dissociative
experience as an unspecific and ubiquitous psychopatho-
logical phenomenon. From a clinical perspective, this finding
underlines the importance of careful evaluation of disso-
ciativesymptoms,andnotonlyinpatientswithdissociativeor
trauma-related disorders.

Our study has several limitations. Although the overall
number of included studies was quite large, the number of
studies and subjects per diagnostic category varied sub-
stantially. We only included categories with at least four
individual studies, but categories varied between four and
66 studies andbetween187and 2,860 subjects. Aswehad no a
priori hypothesis to explain heterogeneity, we did not carry
out subgroup analysis. Heterogeneity may be rooted in dif-
ferent factors, including heterogeneity of the diagnostic
entity, diagnostic shifts over time, and differences between
individual studies, for example, with respect to diagnostic
procedures, gender distribution, and the countries of origin.
Most likely, comorbidity and trauma experiences also in-
fluence dissociation scores and should be systematically
considered in future studies. Finally, we note that the DES is
a self-rating instrument and that certain dissociative fea-
tures may be over- or underrepresented in comparison to
observer-based ratings (84).

In summary, our meta-analysis confirms the prevalence of
dissociative symptoms not only in dissociative disorders,
posttraumatic stress disorder, and borderline personality
disorder, but in nearly all mental disorders. Research on the
distinct diagnostic categories suggests a variety of mecha-
nisms linking dissociative experiences to a higher burden of
illness and detrimental effects on treatment. An evaluation
of dissociation should therefore be part of every careful
psychopathological assessment, and future studies should
engage a transdiagnostic perspective to enhance the devel-
opment of treatment modules to deal with dissociative
symptoms.

AUTHOR AND ARTICLE INFORMATION

From the Institute for Psychiatric and Psychosomatic Psychotherapy,
Central Institute of Mental Health, Mannheim, Germany; the Depart-
ment of Psychosomatic Medicine and Psychotherapy, Medical Faculty
Mannheim, Heidelberg University, Mannheim, Germany; the Depart-
ment of Psychiatry, Schulich School of Medicine and Dentistry, Western
University, London, Ontario; and the Department of Health, Antwerp
University, Antwerp, Belgium.

The first two authors contributed equally.

Address correspondence to Ms. Lyssenko ([email protected]).

Dr. Schmahl has received advisory panel payments from Boehringer
Ingelheim. The other authors report no financial relationships with
commercial interests.

Received Jan. 6, 2017; revisions received April 22, June 1, and June 19,
2017; accepted June 26, 2017; published online September 26, 2017.

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46 ajp.psychiatryonline.org Am J Psychiatry 175:1, January 2018

DISSOCIATION IN PSYCHIATRIC DISORDERS

(
NR326

Mental

Health

Nursing
RUA:

Scholarly

Article

Review

Guidelines
)

Purpose

The student will review, summarize, and critique a scholarly article related to a mental health topic.

Course outcomes: This assignment enables the student to meet the following course outcomes.

(CO 4) Utilize critical thinking skills in clinical decision-making and implementation of the nursing process for psychiatric/mental health clients. (PO 4)

(CO 5) Utilize available resources to meet self-identified goals for personal, professional, and educational development appropriate to the mental health setting. (PO 5)

(CO 7) Examine moral, ethical, legal, and professional standards and principles as a basis for clinical decision-making. (PO 6)

(CO 9) Utilize research findings as a basis for the development of a group leadership experience. (PO 8)

Due date: Your faculty member will inform you when this assignment is due. The Late Assignment Policy applies to this assignment.

Total points possible: 100 points


Preparing the assignment

1) Follow these guidelines when completing this assignment. Speak with your faculty member if you have questions.

a. Select a scholarly nursing or research article, published within the last five years, related to mental health nursing. The content of the article must relate to evidence-based practice.

· You may need to evaluate several articles to find one that is appropriate.

b. Ensure that no other member of your clinical group chooses the same article, then submit your choice for faculty approval.

c. The submitted assignment should be 2-3 pages in length, excluding the title and reference pages.

2) Include the following sections (detailed criteria listed below and in the Grading Rubric must match exactly).

a. Introduction (10 points/10%)

· Establishes purpose of the paper

· Captures attention of the reader

b. Article Summary (30 points/30%)

· Statistics to support significance of the topic to mental health care

· Key points of the article

· Key evidence presented

· Examples of how the evidence can be incorporated into your nursing practice

c. Article Critique (30 points/30%)

· Present strengths of the article

· Present weaknesses of the article

· Discuss if you would/would not recommend this article to a colleague

d. Conclusion (15 points/15%)

· Provides analysis or synthesis of information within the body of the text

· Supported by ides presented in the body of the paper

· Is clearly written

e. Article Selection and Approval (5 points/5%)

· Current (published in last 5 years)

· Relevant to mental health care

· Not used by another student within the clinical group

· Submitted and approved as directed by instructor

f. APA format and Writing Mechanics (10 points/10%)

NR326 Mental Health Nursing

RUA: Scholarly Article Review Guidelines

NR326 Mental Health Nursing

RUA: Scholarly Article Review Guidelines

NR326_RUA_Scholarly_Article_Review_V4b_FINAL_MAY21 1

· Correct use of standard English grammar and sentence structure

· No spelling or typographical errors

· Document includes title and reference pages

· Citations in the text and reference page

For writing assistance (APA, formatting, or grammar) visit the APA Citation and Writing page in the online library.

Please note that your instructor may provide you with additional assessments in any form to determine that you fully understand the concepts learned in the review module.



Grading Rubric Criteria are met when the student’s application of knowledge demonstrates achievement of the outcomes for this assignment.

Assignment Section and Required Criteria

(Points possible/% of total points available)

Highest Level of Performance

High Level of Performance

Satisfactory Level of Performance

Unsatisfactory Level of Performance

Section not present in paper

Introduction

(10 points/10%)

10 points

8 points

0 points

Required criteria

1. Establishes purpose of the paper

2. Captures attention of the reader

Includes 2 requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Article Summary

(30 points/30%)

30 points

25 points

24 points

11 points

0 points

Required criteria

1. Statistics to support significance of the topic to mental health care

2. Key points of the article

3. Key evidence presented

4. Examples of how the evidence can be incorporated into your nursing practice

Includes 4 requirements for section.

Includes 3 requirements for section.

Includes 2 requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Article Critique

(30 points/30%)

30 points

25 points

11 points

0 points

Required criteria

1. Present strengths of the article

2. Present weaknesses of the article

3. Discuss if you would/would not recommend this article to a colleague

Includes 3 requirements for section.

Includes 2 requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Conclusion

(15 points/15%)

15 points

11 points

6 points

0 points

1. Provides analysis or synthesis of information within the body of the text

2. Supported by ides presented in the body of the paper

3. Is clearly written

Includes 3 requirements for section.

Includes 2 requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Article Selection and Approval

(5 points/5%)

5 points

4 points

3 points

2 points

0 points

1. Current (published in last 5 years)

2. Relevant to mental health care

Includes 4

Includes 3

Includes 2

Includes 1

No requirements for

(
NR326

Mental

Health

Nursing
RUA:

Scholarly

Article

Review

Guidelines
)

NR326_RUA_Scholarly_Article_Review_V4b_FINAL_MAY21 1

3. Not used by another student within the clinical group

4. Submitted and approved as directed by instructor

requirements for section.

requirements for section.

requirements for section.

requirement for section.

this section presented.

APA Format and Writing Mechanics

(10 points/10%)

10 points

8 points

7 points

4 points

0 points

1. Correct use of standard English grammar and sentence structure

2. No spelling or typographical errors

3. Document includes title and reference pages

4. Citations in the text and reference page

Includes 4 requirements for section.

Includes 3 requirements for section.

Includes 2 requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Total Points Possible = 100 points

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