European Journal of Trauma & Dissociation 8 (2024) 100384

Contents lists available at ScienceDirect

European Journal of Trauma & Dissociation
journal homepage: www.elsevier.com/locate/ejtdResearch Paper

Validation of the Global Psychotrauma Screen for adolescents in Greece
Ioanna Koutsopoulou a, Emma Grace b, *, Evgenia Gkintoni c, Miranda Olff d, eaDepartment of Psychology, General Hospital “Agios Andreas,” Patras, Greece
International Psychology Program, College of Graduate and Professional Studies, The Chicago School, United Statesc
Department of Psychology, University General Hospital of Patras & University of Ioannina, GreecedDepartment of Psychiatry, Amsterdam Neuroscience & Public Health, Amsterdam UMC, Amsterdam, The Netherlandse
ARQ National Psychotrauma Centre, Diemen, The Netherlandsb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Global Psychotrauma Screen
Adolescents
Screening
TraumaDissociation

Introduction: Adolescents are vulnerable to traumatic exposure. However, there is a lack of developmentally
appropriate, freely accessible, transdiagnostic screening instruments for trauma in adolescents. The purpose ofthis study was to examine the psychometric potential of the Global Psychotrauma Screen Teen version (GPS-T)
for the assessment of traumatic, dissociative, and other transdiagnostic symptoms among adolescents in Greece.
Method: This observational study was conducted with adolescents in Greece (N = 122) who completed a 55-item
questionnaire.
Results: The results supported satisfactory internal consistency reliability, convergent validity, and divergent
validity of the GPS-T. The construct validity findings suggested a three-factor structure of the GPS-T symptoms.
The GPS-T domains had acceptable sensitivity and specificity with the cut-off scores of 3 for PTSD and 2 for the
dissociation, anxiety, and depression domains respectively. The GPS-T symptoms differed on four levels of
severity.
Conclusion: The findings suggest that the GPS-T is appropriate for screening of traumatic, dissociative, and othertransdiagnostic symptoms among adolescents in Greece. Future research should conduct a replication with larger
samples and a test-retest phase.

1. Introduction
1.1. Trauma in adolescents
Exposure to potentially traumatic events (PTEs) is common in ado­lescents (Connell et al., 2018; Darnell et al., 2019), often resulting intrauma-related disorders during this developmental stage that canpersist into adulthood (Copeland et al., 2018; Frewen et al., 2024;
Kessler et al., 2017; King et al., 2020; McKay et al., 2021). Over 60% ofyouth are exposed to at least one PTE and between 8%-25% of themdevelop PTSD before they reach the age of 18 years (Darnell et al., 2019;
McLaughlin, 2023). In Greece, the United Nations Children’s Fund
(UNICEF, 2020) reported that 70% of adolescents were exposed to
psychological violence, 47.7% to physical violence, and 9.8% to sexual
violence. However, PTSD is underdiagnosed among adolescents in
Greece (Belivanaki et al., 2017). Symptoms of PTSD in youth can becomorbid with dissociation (Anderson et al., 2023; Choi et al., 2019;
Choi et al., 2017; Howard et al., 2021), depression, anxiety (Cao et al.,2021; Darnell et al., 2019), and sleep disorders (Armour et al., 2014).
Such comorbidities require a transdiagnostic assessment using adimensional approach (Frewen et al., 2021; Olff et al., 2021; Williamson
et al., 2021).
1.2. Screening of trauma in adolescents
Several measures for screening of trauma have been developed andvalidated for adolescents using a discrete-disorder approach; however,they do not account for the transdiagnostic nature of trauma-related
symptoms and do not differentiate between the child and adolescentage groups (Grace et al., 2021). The Global Psychotrauma Screen (GPS)was developed by an international group of trauma experts with the
Global Collaboration on Traumatic Stress (GCTS) to address the need for

Abbreviations: GPS, Global Psychotrauma Screen; CRIES, Children’s Revised Impact of Event Scale; DES-B, Brief Dissociative Experiences Scale; GAD, Generalized
Anxiety Disorder; PHQ, Patient Health Questionnaire.
* Corresponding author.
E-mail address: egrace@thechicagoschool.edu (E. Grace).
https://doi.org/10.1016/j.ejtd.2024.100384
Received 12 November 2023; Received in revised form 15 January 2024; Accepted 15 January 2024
Available online 19 January 2024
2468-7499/© 2024 Elsevier Masson SAS. All rights reserved.

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European Journal of Trauma & Dissociation 8 (2024) 100384

7. Four levels of the GPS-T Symptoms severity (low, mild, moderate,and extreme) will be statistically different. The more severe cate­gories of the GPS-T Symptoms will predict lower scores on the GPS-T
Functioning.

a free and easily accessible transdiagnostic screening tool for health careproviders worldwide (Olff, 2022; Olff et al., 2020). The GPS wasdeveloped using the transdiagnostic theoretical framework which posits
that the symptoms of trauma are not limited to PTSD and may include avariety of interrelated symptoms of common mental disorders associ­ated with trauma such as depression, anxiety, dissociation, and others(Frewen et al., 2024; Frewen et al., 2021; Havermans et al., 2023; Olffet al., 2020; Olff et al., 2021; Williamson et al., 2021). These interrelated
symptoms are influenced by risk factors and have an impact on func­
tioning in major areas of life. Consequently, the GPS is comprised ofthree parts: (1) GPS Symptoms; (2) GPS Risk Factors; and (3) GPS
Functioning. Detailed report on the GPS development provided by Fre­wen et al. (2021) and Olff et al. (2020); while we summarize the GPS
structure and items below.
The GPS Symptoms consists of nine conceptual dimensions or do­mains that were identified using an expert consensus approach. Eachdomain was operationalized into empirical dimensions selected frompreviously validated measures: (1) the PTSD domain consists of five coretraumatic symptoms: intrusion, avoidance, hypervigilance, detachment,
and blame; (2) the Disturbances in Self-Organization (DSO) domain
measures two symptoms of Complex PTSD: worthlessness and anger; (3)the anxiety domain is comprised of the symptoms of anxiety and worry;(4) the depression domain includes depressed mood and anhedonia; (5)the sleep problems domain screens for insomnia; (6) the self-harmdomain assesses for the attempts of intentional self-harm; (7) the
dissociation domain measures the symptoms of derealization anddepersonalization; (8) the other problems domain screens for nonspecific physical, emotional, or social problems; and (9) the substanceabuse domain screens for the use of psychoactive substances (Frewen
et al., 2021; Olff, 2022; Olff et al., 2020).
The GPS Risk Factors includes five empirical dimensions such asother stressful events, childhood trauma, history of mental illness, thelack of social support, and the lack of psychological resilience (Frewen
et al., 2024). The GPS Functioning was operationalized into one
empirical item that screens for possible functional impairment in major
areas of life (Olff, 2022). The GPS Teen version (GPS-T) was semanti­cally adapted from the original GPS for screening of adolescents aged 11
to 17 years, while retaining the same conceptual and empirical structure(GCTS, 2021; Grace et al., 2021).

Detailed statistical hypotheses are reported in Supplementary
Material.
2. Method
2.1. Ethical considerations
Upon obtaining an approval of the Committee of Research, Morale,and Ethics at the General Hospital “Agios Andreas” in Patras, Greece(AΔA: 63HΛ46906Λ-64Y), Ioanna Koutsopoulou collected data using
convenience sampling in Greece between May 2022–May 2023 (seeTable 1). Parental written informed consent and adolescent’s assent
were obtained prior to data collection. Adolescents were screened for
eligibility to participate in the study using two inclusion criteria: 11 to
17 years old and residing in Greece. No monetary or other compensation
was provided for participation in this study.
2.2. Measures
The study questionnaire consisted of six research instruments with a
total of 55 items. The questionnaire began with demographic items,
including age, gender, education, and family status, followed by ques­
tions about COVID-19 and other stressors (see Supplementary Material).
The validation instrument was GPS-T consisting of 22 dichotomous (yesno) items for trauma-related symptoms and risk factors, and one func­
tioning item measured on a continuous scale from 1 to 10 (Olff, 2022).
The GPS-T was translated into Greek, backtranslated, and develop­
mentally and culturally adapted by a team of three bilingual psycholo­
gists, two teachers of English, and a speech therapist, following theprocedures from Sousa and Rojjanasrirat (2011) and is available at
Global Collaboration on Traumatic Stress (2023). In the present sample,
Cronbach’s alpha for the GPS-T total symptom score was .88, indicating
very good internal consistency.
The reference measures were selected based on their theoreticalrelevance and validation in previous studies. A reference standard for
PTSD was the Children’s Revised Impact of Event Scale – 8 (CRIES-8),
which has been validated and used internationally, including in Greece

1.3. Research aims
The purpose of this observational study was to assess reliability,
convergent validity, divergent validity, construct validity, screening
accuracy, and severity levels of the GPS-T among adolescents in Greece.

Table 1
Demographic characteristics (N = 122).

1.4. Hypotheses
Based on the previous validation studies of the GPS (Frewen et al.,2024; Frewen et al., 2021; Grace et al., 2023; Oe et al., 2020; Olff et al.,2021; Rossi et al., 2021; Salimi et al., 2023), we hypothesized that:
1. The GPS-T will have moderate-to-high levels of internal consistencyof the total symptoms and domains.
2. The GPS-T will have moderate-to-high levels of convergent validity
with CRIES-8, DES-B (items on depersonalization and derealization),
GAD-7, PHQ-9, and GAD-F and PHQ-F (functioning items).
3. The GPS-T will have moderate-to-high levels of divergent validity inrelation to the DES-B total score.
4. There will be three latent factors underlying the GPS-T manifest
variables.
5. The sensitivity and specificity of the GPS-T for probable PTSD,
dissociation, depression, and anxiety will be moderate-to-high.
6. The GPS-T Risk Factors will predict higher levels of the GPS-T
Symptoms while controlling for demographic and COVID-19
variables.

Characteristics

Participants n (%)

Age
GenderFemaleMale
Prefer not to answer
Education
Primary school
High school
Senior high school
University*
Family Status
Parent(s)Sibling(s)Grandparent(s)Other relative(s)Location
PatrasOther cities/villages

14.8 (Median 15; Min 11; Max 17)
70 (57.4)
46 (37.7)
6 (4.9)17 (13.9)
39 (32)59 (48.4)
7 (5.7)122 (100)
72 (59)15 (12.3)
3 (2.5)115 (94.3)
7 (5.7)

Note:*
These seven participants started school before the age of 6 years (age 5 and ahalf years), thus, graduated from high school earlier, and entered university at
the age of 17 years and before they reached 18 years.
2I. Koutsopoulou et al.

European Journal of Trauma & Dissociation 8 (2024) 100384

EFA for the data. Tetrachoric EFA was conducted because of the GPS-T’s
dichotomous item structure. The principal axis factoring with the obli­
que Promax rotation was applied to identify latent constructs. The
sensitivity and specificity analyses were conducted to assess thescreening accuracy of GPS-T for detecting transdiagnostic symptoms of
trauma, dissociation, depression, and anxiety. The Receiver Operating
Characteristic (ROC) analysis was conducted to calculate the Area Under
the Curve (AUC), sensitivity, specificity, positive predictive value (PPV),
negative predictive value (NPV) and the Likelihood Ratios (LR) of the
GPS-T domain scores.
The relationship between the GPS-T Symptoms and Risk Factors wasassessed using a hierarchical multiple regression model that included
three blocks: (1) four demographic variables; (2) COVID-19 items; (3)GPS-T Risk Factors. For severity analysis, we created the GPS-T Symp­
toms’ severity groups based on the percentile cut-off points as follows:
low ≤30th percentile, mild 31–74th percentile, moderate 75–94th
percentile, and severe ≥95th percentile (Fissette et al., 2014). The Welch
ANOVA, followed by the Games-Howell post-hoc test for pairwise
comparisons, was utilized to compare the GPS-T Symptoms’ severity
groups. The one-way ANOVA with the Scheffé post-hoc test was con­ducted to compare the GPS-T Functioning scores among the severity
groups.

(Children and War Foundation, 1998; Dow et al., 2012; Dyregrov et al.,
1996; Lianos et al., 2023; Perrin et al., 2005; Verlinden et al., 2014). In
the current sample, Cronbach’s alpha for CRIES-8 was .93, indicating
excellent internal consistency. A cut-off score of ≥ 17 on CRIES-8 isrecommended for PTSD (Perrin et al., 2005).
We used the Brief Dissociative Experiences Scale (DES-B, Dalenberg& Carlson, 2010) as a reference standard, given its brevity and common
utilization for screening of dissociative symptoms. DES-B has beenvalidated for use with adults in Greece (Tzikos et al. 2021) and withadolescents outside of Greece (Howard et al., 2021). In the present
sample, Cronbach’s alpha for DEB-B was .79, showing good internalconsistency. A cut-off score of >16 on DES-B indicates the probability ofclinical dissociation (Pietkiewicz et al., 2019). We used the DES-B items
on depersonalization and derealization for measuring convergent val­
idity of the corresponding GPS-T Dissociation domain score, and the
DES-B total score to assess divergent validity.
The reference measures for anxiety and depression were GAD-7(Spitzer et al., 2006) and the Patient Health Questionnaire – 9(PHQ-9; Kroenke et al., 2001) because they have well-established psy­chometric properties within the adolescent population (Mossman et al.,2017) and are available in Greek. A cut-off score of >10 on each GAD-7
and PHQ-9 confirm generalized anxiety disorder and major depressive
disorder (Kroenke et al., 2001; Spitzer et al., 2006). In the current
sample, Cronbach’s alpha for GAD-7 was .91 and for PHQ-9 was .82,
confirming very good internal consistency. Additionally, we used thePHQ-9 and GAD-7 items on sleep-related symptoms to assess convergent
validity of the GPS-T Insomnia item. To assess convergent validity of the
GPS-T Functioning, we used the PHQ-F and GAD-F items.

3. Results
3.1. Sample characteristics
A total of 122 participants completed the questionnaire. De­
mographic information is reported in Table 1. Exposure characteristics
including the COVID-19-related stressors and other PTEs are presented
in Table 2. Some participants reported clinically established diagnoses(see Table 3). Additionally, two participants had behavioral issues, one
participant reported a circumstantial substance use, and one participant
had issues related to their gender identity.

2.3. Statistical analyses
The statistical procedures were performed using STATA.17 (Stata­Corp, 2021) and SPSS.26 (IBM Corp., 2019). The convergent validityand divergent validity of GPS-T were assessed using the Spearman’s
correlation coefficient. For Exploratory Factor Analysis (EFA), theassumption of homogeneity on key variables (Kyriazos, 2018) was
checked by randomly splitting the sample into two halves andcomparing them on key variables. The data suitability for factor analysis
was checked using the Kaiser–Meyer–Olkin (KMO) test for sampling
adequacy and the Bartlett’s test of sphericity for the appropriateness of

3.2. GPS-T symptom and risk factor endorsement
The most frequently reported GPS-T symptom was anxiety, whilesubstance use was the least frequent (see Fig. 1). The mean scores on
GPS-T and other measures are reported in Table 4. The GPS-T Symp­
toms’ sum scores were higher in the participants who endorsed the GPST Risk Factors such as Childhood Trauma, History of Mental Illness, andOther Events (see Table 5). There was a weak positive correlation of age
with the GPS-T Symptoms (rho = 0.216; p = 0.017) and Risk Factors(rho = 0.320; p < 0.001). Females had higher sum scores on the GPS-T
Symptoms: t(111) = 3.6, p < 0.001, r = 0.33; and the GPS-T Risk Factorst(112) = 4.8, p < 0.001, r = 0.41.

Table 2
Exposure characteristics (N = 122).
Characteristics
COVID-19 (in descending order)
Lockdown in the area
Change or disruption in education
Limited play or sports
Limited meetings with peers and others
Home quarantine
Impact (had COVID-19)
Illness
Death in family
Other issues
Hospitalization
Other Events or Stressors (in descending order)
Grandparent’s death (not related to COVID-19)
Unspecified1
Exams
Bullying incidents
Conflicts with parents
Emotional abuse
Parent’s death (not related to COVID-19)
Two events (grandparent’s death and bullying)
Family’s financial problems
False accusation of sexual abuse

Participants n (%)
118 (96.7)
117 (95.9)
102 (83.6)
94 (77)78 (63.9)
57 (46.7)
39 (32)14 (11.5)
9 (7.4)1 (0.8)

Table 3
Formally diagnosed mental disorders (N = 122).

11 (9)
8 (6.6)8 (6.6)6 (4.9)3 (2.5)2 (1.6)
1 (0.8)1 (0.8)1 (0.8)1 (0.8)Diagnosis

Participants n (%)

Eating disorders1
Unspecified2
Depressive disorders3
Autism spectrum disorder
Obsessive-compulsive and depressive disorders
Attention deficit and hyperactivity disorder
Dyslexia
Dysgraphia
Total

4 (3.3)3 (2.5)2 (1.6)2 (1.6)
1 (0.8)1 (0.8)1 (0.8)1 (0.8)15 (12.3)

Notes:
1
One of the participants also had suicidal thoughts.
2
These participants did not wish to disclose their diagnoses.
3
One of the participants also reported a past suicidal attempt.

Note:1Participants did not wish to disclose the events.
3

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European Journal of Trauma & Dissociation 8 (2024) 100384

Fig. 1. Frequency distribution of the GPS-T Symptoms (%; N = 122).
Fig. 1 Alt text: A bar chart plotting the frequency distribution in percentage for the GPS-T Symptoms based on the responses of one hundred twenty-two participants.

3.3. Reliability of GPS-T

Depression (rho = 0.15 p < 0.01) domain scores with the DES-B sum
score indicated satisfactory divergent validity. The divergent validity of
the GPS-T Insomnia was supported by the lower reference scores on thesleep-related items of PHQ-9 and GAD-7 in the participants who
endorsed the item: t(120) = -3.1, p = 0.002, r = 0.27.

The results presented in Table 6 show acceptable internal consis­
tency reliability of the GPS-T items and domains.
3.4. Convergent validity of the GPS-T
The GPS-T Symptoms and the PTSD, Dissociation, Depression, andAnxiety domain scores had positive correlations with the reference
measures, indicating acceptable convergent validity, except for the GPST Functioning item which was below the hypothesized (see Table 7).
Convergent validity of the GPS-T Insomnia was evident through thehigher reference scores in participants endorsing the item: t(120) = -4.9,
p < 0.001, r = 0.41.

Table 5Comparison of the GPS-T symptoms by the GPS-T risk factor items (N = 122).
GPS Risk Factors

Responses

n (%)

χ2

p

φ

Other events (#17)

Yes
No
Yes
No
Yes
No
Yes
No
Yes
No

38 (31.1)
84 (68.9)
31 (25.4)
91 (74.6)
35 (28.7)
87 (71.3)
33 (27)89 (73)49 (40.2)
73 (59.8)

45.81

.001

.613

16.59

.413

.369

37.25

.002

.553

26.32

.05

.464

22.06

.141

.425

Lack of social support (#19)

3.5. Divergent validity of the GPS-T

Childhood trauma (#20)

The low correlations of the GPS-T Symptoms (rho = 0.36, p < 0.01),
PTSD (rho = 0.27, p < 0.01), Anxiety (rho = 0.24, p < 0.01), andHistory of mental illness (#21)
Resilience (#22)

Table 4
Mean and standard deviation scores on the study measures (N = 122).
Variables

M

SD

GPS Symptoms
GPS PTSDGPS CPTSD
GPS Anxiety
GPS Depression
GPS Dissociation
GPS Functioning
CRIES-8
GAD-7
PHQ-9
DES-B

6.93
1.98
3.02
1.2
1.2
0.39
7.02
13.98
9.36
8.84
7.34

4.43
1.81
2.23
0.8
0.82
0.68
2.28
12.33
6.57
6.41
6.52

Table 6
Internal consistency of GPS-T (N = 122).
GPS

α/ρ

Total (α)
Symptoms (α)
PTSD (α)
CPTSD (α)
DSO (ρ)Anxiety (ρ)
Depression (ρ)
Dissociation (ρ)

0.88
0.87
0.79
0.78
0.48
0.55
0.57
0.60

Note: α - Cronbach’s alpha coefficient; ρ Spearman-Brown’s coefficient

Note: M – mean; SD – standard deviation.
4

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European Journal of Trauma & Dissociation 8 (2024) 100384

3.6. Construct validity of the GPS-T

had a lower score on the GPS-T Functioning, F(3) = 8.25, p = 0.001, thanthe other three severity groups, which did not differ from each other.

The assumption of homogeneity between the randomly split two
halves of the sample on key variables was met based on the t-test or χ 2
results, thus allowing to proceed with EFA. The KMO of 0.82 indicatedhigh sampling adequacy. The Bartlett’s test of sphericity confirmed theappropriateness of EFA based on large correlations between items,χ 2(136) = 720.456, p < 0.001.
The initial analysis identified Factors 1, 2, 3, and 4 with Eigenvalues>1, which explained 57% of the total variance (see Table 8). The rotatedfactor loadings in the initial EFA model showed that Factor 1 was rep­resented by the PTSD, anxiety, and depression symptoms along withother physical, social, or emotional problems. However, some items did
not meet the expected thresholds for factor loadings and uniqueness (seeTable 9). Factor 2 included the dissociation items of depersonalizationand derealization, although the latter did not meet the thresholds forfactor loadings and uniqueness. Factor 3 was represented by the items of
insomnia, self-harm, and substance use, although substance use excee­
ded the threshold for uniqueness. Factor 4 was comprised of the two
DSO items; however, both items exceeded the uniqueness threshold.
Considering the issues with the four-factor model, an additional EFA
model was created to test the three-factor structure. The three-factor
model improved the factor loadings and uniqueness and explained
51% of the total variance. Factor 1 remained the same as in the initialmodel, except for the intrusion item. Factor 2 combined the two disso­
ciation items with insomnia, substance use, self-harm, and intrusion.
Factor 3 consisted of the two DSO items that were initially in Factor 4.
The internal consistency reliability based on the Cronbach’s Alpha re­sults was very good in Factor 1, good in Factor 2, and low-to-moderate inFactor 3. (see Table 10).

3.9. Analysis of the GPS-T risk factors
In line with the previous psychometric studies on the GPS in adults(Frewen et al., 2024; Frewen et al., 2021; Grace et al., 2023; Havermans
et al., 2023; Oe et al., 2020; Olff et al., 2021; Rossi et al., 2021; Salimi
et al., 2023), we tested if the GPS-T Risk Factors would predict the GPS-T
Symptoms, while controlling for demographic variables. Because thedata were collected during the COVID-19 pandemic, a global emergency
that had exacerbated mental health responses (Ollf et al., 2021; Mag­klara et al., 2022), it was important to investigate the GPS-T’s ability todifferentiate this transitory PTE from more stable risk factors that exis­ted before the pandemic and would likely continue after it. The
pandemic-related variables included in this study, such as exposure to
COVID-19, death in family, quarantine, hospitalization, disruptions in
education and social activities, were identified as stressors earlier in the
pandemic (Gassman-Pines et al., 2020; Fitzpatrick et al., 2021).
As hypothesized, the results of the hierarchical multiple regression
showed that the GPS-T Risk Factors explained most of the variance in the
GPS-T Symptoms (see Table 14). Out of the nine COVID-19-related
variables, only being quarantined at home due to the COVID-19 expo­
sure in the family was associated with more GPS-T Symptoms. Amongthe demographic variables, female gender predicted higher GPS-T
Symptoms in Block 1; however, this change was minimal and became
insignificant when accounting for the COVID-19 variables in Block 2 andthe GPS-T Risk Factors in Block 3.
4. Discussion

3.7. Sensitivity and specificity of the GPS-T

4.1. Interpretation of results

The results of the ROC analysis showed high AOC values for the GPST PTSD, Anxiety, Depression, and Dissociation domains (see Table 11).
For the GPS-T PTSD domain, a cutoff score 3 showed the higher per­centage of correctly classified cases while maintaining an optimal bal­ance of sensitivity relative to specificity. The GPS-T Dissociation,
Depression, and Anxiety domains achieved optimal sensitivity relative
to specificity with a score of 2. See Table 12 for detailed results.

The results of this study supported our hypotheses in that the GPS-T
items and domains demonstrated acceptable internal consistency, thus
supporting the earlier studies on the psychometric properties of the GPS
adult version (Frewen et al., 2024; Frewen et al., 2021; Grace et al.,2023; Havermans et al., 2023; Oe et al., 2020; Olff et al., 2021; Rossi
et al., 2021; Salimi et al., 2023). Similarly, the GPS-T Symptoms, PTSD,
Anxiety, and Depression domains showed satisfactory convergent val­
idity and divergent validity.
The GPS-T Dissociation domain had satisfactory convergent validity
in relation to the corresponding DES-B items for depersonalization andderealization. Dissociative symptoms, as indicated by the DES-B total
score, were higher in adolescents with more severe levels of the GPS-T
Symptoms and those experiencing sleep problems, consistent with

3.8. Severity analysis of the GPS-T symptoms
The distribution of the GPS-T Symptoms’ severity levels showed thatmost participants had a mild level of severity, followed by low, mod­erate, and high levels (see Table 13). All four severity groups differedfrom one another on the GPS-T Symptoms: F(3, 35.46) = 920.79, p =0.001, η2 = 0.883. The GPS-T Functioning score differentiated the low
and extreme severity groups from all other groups of the GPS-T Symp­
toms, but the mild and moderate groups did not differ from each other: F(3, 57.21) = 14.76, p = 0.001, η2 = 0.273. When controlling for de­
mographics, only the group with low severity of the GPS-T Symptoms

Table 8The EFA total variance (N = 122).

Table 7
Convergent validity of the GPS-T (N = 122).
GPS-T Variables

Criterion Variables

Spearman’s rho or t-test

Symptoms
PTSD
Anxiety
Depression
Dissociation

CRIES-8 total
CRIES-8 total
GAD-7 total
PHQ-9 total
DES-B sum of items 2 & 5
DES-B total
GAD item 4 & PHQ item 3
GAD-F & PHQ-F

rho = 0.758**
rho = 0.664**
rho = 0.579**
rho = 0.651**
rho = 0.637**
rho = 0.423**
t(120) = -4.9**
rho = 0.41**

Sleep problems
Functioning

Notes:**
p < 0.001
5

Factor

Eigenvalues total

Variance %Cumulative %Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Factor 6
Factor 7
Factor 8
Factor 9
Factor 10
Factor 11
Factor 12
Factor 13
Factor 14
Factor 15
Factor 16
Factor 17

5.539
1.933
1.264
1.067
.969
.944
.779
.767
.633
.573
.498
.454
.411
.360
.310
.255
.244

32.58111.372
7.437
6.274
5.700
5.554
4.581
4.510
3.721
3.370
2.929
2.673
2.419
2.117
1.826
1.500
1.438

32.58143.95351.38957.66363.36368.91873.49978.00981.72985.09988.02890.701
93.12095.23797.06398.562100.000

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European Journal of Trauma & Dissociation 8 (2024) 100384

Table 9Four-factor EFA model with rotated factor loadings and unique variances (N = 122).
Variable

Label

Factor 1

GPS 4
Numbness
GPS 5
Self-blame
GPS 16
Other problems
GPS 2
Avoidance
GPS 3
Hyperarousal
GPS 10Depressed mood
GPS 9
Worry
GPS 8
Anxiety
GPS 11Anhedonia
GPS 1
Intrusion
GPS 14
Derealization
GPS 15Depersonalization
GPS 12
Insomnia
GPS 18Substance use
GPS 13Self-harm
GPS 7
Anger
GPS 6
Worthlessness
Cronbach’s Alpha
Average Inter-Item Covariance

Factor 2

.756
.702
.677
.672
.646
.602
.495
.464
.338
.334

Factor 3

.859
.385

0.857
0.096

Factor 4

.915
.442
.418

0.603
0.069

Uniqueness
.384
.470
.463
.506
.571
.443
.398
.702
.798
.637
.237
.737
.261
.683
.526
.670
.640

.539
.413
0.477
0.074

0.645
0.060

Notes: Oblique Promax rotation was used. The rotated factor loadings show which variables represent each factor. Kaiser normalization was on in this model. The factor
loadings of > 0.4 and uniqueness of < 0.6 are acceptable (Stevens, 2009).

DES-B and the GPS-T Dissociation domain both measured only thepsychoform symptoms of dissociation.
Based on the construct validity results, the three-factor structure of
the GPS-T appeared theoretically and developmentally more adequate
for adolescents. The earlier evidence on the GPS adult version alsosuggested the three-factor structure (Grace et al., 2023; Rossi et al.,2021; Salimi et al., 2023). In this study, the symptoms of PTSD, anxiety,and depression represented one factor, highlighting the emotionality of
trauma-related responses in adolescents associated with internalizing
trauma (Darnell et al., 2019). The second factor grouped together thesymptoms involving altered states of consciousness such as dissociative
symptoms of depersonalization and derealization, insomnia, substanceuse, and self-harm. The co-occurrence of these symptoms with intrusion

Table 10Three-factor EFA model with rotated factor loadings and unique variances (N =122).
Variable

Label

GPS 4
Numbness
GPS 5
Self-blame
GPS 2
Avoidance
GPS 16
Other problems
GPS 3
Hyperarousal
GPS 10Depressed mood
GPS 9
Worry
GPS 8
Anxiety
GPS 11Anhedonia
GPS 13Self-harm
GPS 12
Insomnia
GPS 18Substance use
GPS 14
Derealization
GPS 15Depersonalization
GPS 1
Intrusion
GPS 7
Anger
GPS 6
Worthlessness
Cronbach’s Alpha
Average Inter-Item Covariance

Factor 1
.761
.707
.677
.669
.650
.602
.499
.479
.333

0.857
0.096

Factor 2

.713
.551
.530
.456
.439
.373
0.720
0.052

Factor 3

.548
.430
0.477
0.074

Uniqueness
.407
.474
.519
.463
.571
.464
.461
.695
.807
.461
.691
.682
.607
.749
.633
.670
.633

Table 12Sensitivity and specificity of the GPS-T domain scores (N = 122).

Notes: Oblique Promax rotation was used. The rotated factor loadings show
which variables represent each factor. Kaiser normalization was on in thismodel. The factor loadings of > 0.4 and uniqueness of < 0.6 are acceptable.

previous studies that found similar associations (Armour et al., 2014;
Choi et al., 2019; Choi et al., 2017; Howard et al., 2021; Hyland et al.,2023). However, it is important to note that dissociative symptoms are
not often detected in adolescents after trauma (Anderson et al., 2023;
Wamser-Nanney & Cherry, 2018). This could be due to the assessment
instruments measuring either the psychoform or somatoform symptoms
of dissociation (Pietkiewicz et al., 2019) but not both. In this study,

GPS Cut Points ≥Sensitivity %

PTSD
1
2
3
4
5
Anxiety1
2
Depression
1
2
Dissociation
1
2

CRIES-8
91.1
82.2
68.9
57.8
28.9
GAD-7
90.9
69.1
PHQ-9
93.8
79.2
DES-B
91.6
58.3

Specificity %Accuracy %

LR+

LR-

44.2
67.5
80.5
88.3
98.7

61.5
73
76.2
77.1
73

1.63
2.53
3.53
4.94
2.25

0.02
0.26
0.39
0.48
0.73

35.8
76.1

60.7
72.3

1.42
2.89

0.25
0.41

37.8
75.7

59.8
77.1

1.51
3.25

0.17
0.28

78.2
94.5

79.5
91

3.84
9.78

0.2
0.49

Note: LR – Likelihood Ratio.

Table 11
ROC analysis of the GPS-T (N = 122).
Reference Standards

GPS

AOC

CRIES-8
GAD-7
PHQ-9
DES-B

PTSD
Anxiety
Depression
Dissociation

0.819
0.747
0.79
0.888

95% CIPPVNPVPrevalence

LL

UL

%

%

%

0.74
0.66
0.72
0.79

0.89
0.83
0.87
0.99

50
92
70
80

65.4
70.6
50
82.7

36.7
47.1
53
20.2

Note: AOC – area under the curve; PPV – positive predictive value; NPV – negative predictive value; LL – lover limit; UL – upper limit.
6I. Koutsopoulou et al.

European Journal of Trauma & Dissociation 8 (2024) 100384

Table 13Differences in GPS-T Symptoms and GPS-T Functioning by severity levels.
Severity Levels
Low
Mild
Moderate
Extreme
Total

n (%)
37 (30.3)
55 (45.1)
23 (18.9)
7 (5.7)122 (100)

GPS-T Symptoms

GPS-T Functioning

M

SD

M

SD

1.84
7.07
12.17
15.43
6.93

1.09
1.97
1.03
0.53
4.43

8.32
6.91
6.35
3.29
7.02

1.78
1.9
2.21
2.63
2.28

Table 14
Hierarchical multiple regression on the GPS-T Symptoms and GPS-T Risk Factors(N = 122).

suggests that re-experiencing trauma alters consciousness and exter­
nalizes into self-destructive behaviors. According to the ICD-11, thesymptoms of depersonalization and derealization typically occur in
mid-adolescence, and sleep deprivation or substance use can exacerbate
their intensity (WHO, 2018). Self-harm was also noted within thepattern of dissociative symptoms (Tzikos et al., 2021). The DSO symp­
toms representing a separate factor from PTSD was in line with the
ICD-11 conceptualization of CPTSD (Kazlauskas et al., 2023; WHO,2018). Adolescents are more vulnerable to CPTSD than adults (WHO,2018), because their self-concept and affect regulation are still devel­
oping and can be damaged by prolonged or frequent traumas.
This study affirmed the screening accuracy of the GPS-T PTSD
domain using a cut-off score of 3 for adolescents, consistent with thepsychometric studies on the GPS for adults. A cut-off score of 2
demonstrated accuracy of the GPS-T Dissociation, Anxiety, andDepression domains for adolescents; although, a cut-off score of 1 isrecommended for screening of adults using the respective GPS domains(Olff, 2022; Grace et al., 2023).
All four severity levels of the GPS-T Symptoms differed from eachother, thereby supporting our hypothesis. However, only the low andextreme levels of severity of the GPS-T Symptoms had differing effects
on the GPS-T Functioning score, suggesting that the symptoms had to be
extremely severe to detect functional impairment in adolescents. This
could be attributed to the convergent validity of the GPS-T Functioning
item being lower than hypothesized. Changing the item’s response
format from continuous (1-10) to dichotomous (yes-no), similar to other
GPT-T items, could help adolescents to respond more definitively by
distinguishing only between low and severe functional impairment.
The GPS-T Risk Factors had the predicted impact on the GPS-T
Symptoms. The demographic and COVID-19 variables did not makesignificant changes in the GPS-T Symptoms score, except in the case ofhome quarantine during the COVID-19 pandemic. This finding supports
earlier research in Greece, which reported the adverse effects of socialand physical isolation on youth during the COVID-19 lockdown (Mag­klara et al., 2022).

Block 1: Demographics

N=
122

F(4, 117) =
3.14

p=
0.017

Predictor
Variables

Coefficient

Std.
error

t

p

95% CI

Age
Gender0.503-1.441

0.35
0.69

1.44
-2.1

Education
Family Size
cons

0.022
0.207
1.292

0.69
1.23
4.12

0.03
0.17
0.31

0.153
0.038
*
0.975
0.866
0.754

Block 2: COVID-19

4.2. Limitations and future directions
There are several limitations to the findings of this study. This study
could not assess the test-retest reliability of the GPS-T and did notinclude reference standards for DSO, self-harm, and substance use, toavoid overburdening and emotional risks for the participants. The
findings on the construct validity of the GPS-T need replication with alarger sample size. Future studies on the psychometric properties of the
GPS-T should aim to address these limitations to enhance psychometricproperties of the GPS-T.

R2 =
0.1

LB

UB

-0.19
-2.8

1.19
-0.08

-1.35
-2.23
-6.87

1.4
2.64
9.45

N=
122

F(13, 108) =
1.54

p=
0.154
95% CI

R2 =0.16

Predictor Variables

Coefficient

Std.
error

t

p

LB

UB

Age
Gender
Education
Family size
COVID illness
COVID
hospitalization
COVID quarantine

0.586-1.301-0.0430.437-0.64-1.592

0.37
0.7
0.73
1.3
1.04
4.43

1.56
-1.85
-0.06
0.34
-0.62
-0.36

0.121
0.067
0.953
0.738
0.539
0.720

-0.16
-2.69
-1.49
-2.15
-2.7
-10.38

1.33
0.09
1.40
3.02
1.42
7.19

2.139

0.95

2.25

0.25

4.03

COVID death infamilyCOVID lockdown
COVID disruption
in education
COVID lack of play,sportsCOVID lack ofmeetings withfriends
COVID other issues
cons

1.292

1.3

0.99

0.027
*
0.324

-1.29

3.88

0.58
0.113

2.95
2.78

0.20
0.04

0.845
0.968

-5.28
-5.4

6.44
5.62

-0.261

1.7

-0.15

0.878

-3.63

3.11

-0.103

1.51

-0.07

0.946

-3.09

2.88

0.072
-1.875

1.64
5.01

0.04
-0.37

0.965
0.709

-3.19
-11.81

3.33
8.06

Block 3: GPS-T Risk Factors

N=
122

F(14, 107) =
6.15

p=
0.001

R2 =
0.45

Predictor
Variables

Coefficient

Std.
error

t

p

95% CILBUBAgeGender
Education
Family size
COVID illness
COVID
hospitalization
COVID quarantine
COVID death infamilyCOVID lockdown
COVID disruption
in education
COVID lack ofplay, sports
COVID lack ofmeetings withfriends
COVID other issues
GPS Risk Factors
cons

0.171
-0.4530.047
1.087-1.457-1.662

0.31
0.58
0.59
1.07
0.85
3.61

0.55
-0.78
0.08
1.02
-1.71
-0.46

0.584
0.439
0.936
0.31
0.09
0.646

-0.45
-1.61
-1.12
-1.03
-3.14
-8.81

0.78
0.7
1.22
3.2
0.23
5.49

2.426
1.047

0.78
1.06

3.13
0.99

0.002**
0.326

0.89
-1.06

3.96
3.15

1.802
-1.218

2.41
2.27

0.75
-0.54

0.457
0.593

-3
-5.72

6.58
3.29

0.153

1.38

-0.11

0.912

-2.9

2.91

0.47

1.23

0.38

0.704

-1.97

2.91

1.334
1.978
-1.444

1.35
0.27
4.08

0.99
7.48
-0.35

0.325
0.001**
0.724

-1.34
1.45
-9.53

4.01
2.5
6.64

Notes:*
p < 0.05;**
p < 0.01.

4.3. Conclusion
This study provides novel evidence on the psychometric potential of
GPS-T in Greece as a valid tool for rapid screening of transdiagnostic
symptoms of trauma, dissociation, depression, anxiety, and others thatadolescents may experience following PTEs. Screening is important toprevent long-term negative mental health outcomes or to detect symp­
tomatic adolescents and open the way to health care (Olff et al., 2020;

Verhagen et al., 2022). The present study contributes new findings inadolescents, adding to the international studies on psychometric prop­
erties of the GPS in adults, thereby offering health care providers, re­searchers, and policymakers an opportunity to compare the7European Journal of Trauma & Dissociation 8 (2024) 100384

I. Koutsopoulou et al.

trauma-related symptoms in adolescents longitudinally, as they growup, and cross-sectionally with their parents.

the COVID-19 pandemic and lockdown. Journal of Affective Disorders, 296, 126–129.
https://doi.org/10.1016/j.jad.2021.09.052
Children and War Foundation (1998). Children’s Revised Impact Of Event Scale - 8(CRIES-8). [Measurement instrument]. https://www.corc.uk.net/outcome-experience-measures/child-revised-impact-of-events-scale/.
Choi, K. R., Ford, J. D., Briggs, E. C., Munro-Kramer, M. L., Graham-Bermann, S. A., &Seng, J. S. (2019). Relationships between maltreatment, posttraumatic
symptomatology, and the dissociative subtype of PTSD among adolescents. Journalof Trauma & Dissociation, 20(2), 212–227. https://doi.org/10.1080/
15299732.2019.1572043
Choi, K. R., Seng, J. S., Briggs, E. C., Munro-Kramer, M. L., Graham-Bermann, S. A.,
Lee, R. C., & Ford, J. D. (2017). The dissociative subtype of posttraumatic stressdisorder (PTSD) among adolescents: Co-occurring PTSD, depersonalization/
derealization, and other dissociation symptoms. Journal of the American Academy ofChild & Adolescent Psychiatry, 56(12), 1062–1072. https://doi.org/10.1016/j.
jaac.2017.09.425
Connell, C. M., Pittenger, S. L., & Lang, J. M. (2018). Patterns of trauma exposure inchildhood and adolescence and their associations with behavioral well-being.
Journal of Traumatic Stress, 31(4), 518–528. https://doi.org/10.1002/jts.22315
Copeland, W. E., Shanahan, L., Hinesley, J., Chan, R. F., Aberg, K. A., Fairbank, J. A., vanden Oord, E. J. C. G., & Costello, E. J. (2018). Association of childhood trauma
exposure with adult psychiatric disorders and functional outcomes. JAMA Network
Open, 1(7), Article e184493. https://doi.org/10.1001/jamanetworkopen.2018.4493
Dalenberg, C. & Carlson E. (2010). Brief Dissociative Experiences Scale (DES-B) modified
for DSM-5 [Measurement instrument]. https://www.psychiatry.org/File%20Li
brary/Psychiatrists/Practice/DSM/APA_DSM5_Severity-of-Dissociative-SymptomsChild-Age-11-to-17.pdf.
Darnell, D., Flaster, A., Hendricks, K., Kerbrat, A., & Comtois, K. A. (2019). Adolescentclinical populations and associations between trauma and behavioral and emotional
problems. Psychological Trauma: Theory, Research, Practice and Policy, 11(3),266–273. https://doi.org/10.1037/tra0000371
Dow, B. L., Kenardy, J. A., Le Brocque, R. M., & Long, D. A. (2012). The utility of theChildren’s Revised Impact of Event Scale in screening for concurrent PTSD following
admission to intensive care. Journal of Traumatic Stress, 25(5), 602–605. https://doi.
org/10.1002/jts.21742
Dyregrov, A., Kuterovac, G., & Barath, A. (1996). Factor analysis of the Impact of Event
Scale with children in war. Scandinavian Journal of Psychology, 36, 339–350. cxcj8d.
Fissette, C. L., Snyder, D. K., Balderrama-Durbin, C., Balsis, S., Cigrang, J., Talcott, G. W.,
Tatum, J., Baker, M., Cassidy, D., Sonnek, S., Heyman, R. E., & Smith Slep, A. M.
(2014). Assessing posttraumatic stress in military service members: Improving
efficiency and accuracy. Psychological Assessment, 26(1), 1–7. https://doi.org/
10.1037/a0034315
Fitzpatrick, O., Carson, A., & Weisz, J. R. (2021). Using mixed methods to identify the
primary mental health problems and needs of children, adolescents, and theircaregivers during the Coronavirus (COVID-19) Pandemic. Child Psychiatry and
Human Development, 52(6), 1082–1093. https://doi.org/10.1007/s10578-02001089-z
Frewen, P., Vincent, A., & Olff, M. (2024). Childhood trauma histories in men andwomen assessed by the Childhood Attachment and Relational Trauma Screen(CARTS) and the Global Psychotrauma Screen (GPS): Results from the Global
Collaboration on Traumatic Stress (GC-TS). Child Abuse and Neglect, 149(106610),
1–12. https://doi.org/10.1016/j.chiabu.2023.106610
Frewen, P., McPhail, I., Schnyder, U., Oe, M., & Olff, M. (2021). Global Psychotrauma
Screen (GPS): Psychometric properties in two internet-based studies. European
Journal of Psychotraumatology, 12(1), 1–13. https://doi.org/10.1080/
20008198.2021.1881725
Gassman-Pines, A., Ananat, E. O., & Fitz-Henley, J., II (2020). COVID-19 and parent-childpsychological well-being. Pediatrics, 146(4), Article e2020007294. https://doi.org/
10.1542/peds.2020-007294
Global Collaboration on Traumatic Stress (2021). Global Psychotrauma Screen teen
version user guide. https://www.global-psychotrauma.net/_files/ugd/893421_27d
9d8d6dc5f4a84a679d79eb3a4933c.pdf.
Global Collaboration on Traumatic Stress. (2023). Global Psychotrauma Screen Teen
Version, Greek translation. https://www.global-psychotrauma.net/_files/ugd/8934
21_a02c62dd4b52466db438d3b6df432592.pdf.
Grace, E., Rogers, R., Usher, R., Rivera, I., Elbakry, H., Sotilleo, Sh., Doe, R., Toribio, M.,
Coreas, N., & Olff, M. (2023). Psychometric properties of the Global Psychotrauma
Screen in the United States. Health Psychology and Behavioral Medicine, 11(1), Article
2266215. https://doi.org/10.1080/21642850.2023.2266215, 1-20.
Grace, E., Sotilleo, Sh., Rogers, R., Doe, R., & Olff, M. (2021). Semantic adaptation of the
Global Psychotrauma Screen for children and adolescents in the United States.
European Journal of Psychotraumatology, 12(1), Article 1911080. https://doi.org/
10.1080/20008198.2021.1911080, 1-12.
Havermans, D., Hoeboer, C., Sobczak, S., Primasari, I., Coimbra, B., Hovnanyan, A., Zrnic
Novakovic, I., Langevin, R., Aakvaag, H., Grace, E., Dragan, M., Lueger-Schuster, B.,
El-Hage, W., & Olff, M (2023). The mental health impact of COVID-19 pandemic andexposure to other potentially traumatic events up to old age. Journal of TraumaticStress, 36(3). https://doi.org/10.1002/jts.22937
Howard, A., Gonzálvez, C., & Kearney, C. A. (2021). Unique factor structures of theadolescent Dissociative Experiences Scale and Posttraumatic Cognitions Inventory
and their relation to PTSD symptom clusters in maltreated youth. Journal of
Aggression, Maltreatment & Trauma. https://doi.org/10.1080/
10926771.2021.1894290
Hyland, P., Hamer, R., Fox, R., Vallières, F., Karatzias, T., Shevlin, M., & Cloitre, M.
(2023). Is dissociation a fundamental component of ICD-11 Complex Posttraumatic

Ethics compliance
The study was conducted in accordance with the Declaration of
Helsinki and received an approval by the Committee of Research,
Morale, and Ethics at the General Hospital “Agios Andreas” in Patras,
Greece (AΔA: 63HΛ46906Λ-64Y). See details under Method.
Informed consent
Informed consent was obtained from the participants’ legal guard­
ians and informed assent was obtained from the participants.
Funding
This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.
Data availability
The data from this study cannot be made publicly available to protect
confidentiality of minor participants.
CRediT authorship contribution statement
Ioanna Koutsopoulou: Conceptualization, Data curation, Investi­
gation, Project administration, Writing – review & editing. Emma
Grace: Conceptualization, Formal analysis, Methodology, Writing –original draft, Writing – review & editing. Evgenia Gkintoni: Concep­
tualization, Investigation, Writing – review & editing. Miranda Olff:
Conceptualization, Methodology, Supervision, Writing – review &editing.
Declaration of competing interest
No potential conflicts of interest were reported by the authors.
Acknowledgements
We thank Beatrice Leupin, Eleni Koutsopoulou, Alex Bistas, andMaria Korina Stefopoulou in Greece for their contribution to the trans­
lation and adaptation of the GPS-T Greek version. Special thanks toSouleyman Akhmedov in France for translating the title, abstract, andkeywords from English into French.
Supplementary materials
Supplementary material associated with this article can be found, inthe online version, at doi:10.1016/j.ejtd.2024.100384.
References
Anderson, K., Hillman, S., Zhong, W., & Cross, R. (2023). Exploring looked-afteradolescents’ reports of their dissociative experiences. European Journal of Trauma
and Dissociation, 7(100344). https://doi.org/10.1016/j.ejtd.2023.100334
Armour, C., Elklit, A., Lauterbach, D., & Elhai, J. D. (2014). The DSM-5 dissociative-PTSD
subtype: Can levels of depression, anxiety, hostility, and sleeping difficulties
differentiate between dissociative-PTSD and PTSD in rape and sexual assault
victims? Journal of Anxiety Disorders, 28(4), 418–426. https://doi.org/10.1016/j.
janxdis.2013.12.008
Belivanaki, M., Ropi, S., Kanari, N., Tsiantis, J., & Kolaitis, G. (2017). Trauma and posttraumatic stress disorder among psychiatric inpatient children and adolescents.
European Journal of Psychotraumatology, 8(sup4), Article 1351161. https://doi.org/
10.1080/20008198.2017.1351161
Cao, C., Wang, L., Fang, R., Liu, P., Bi, Y., Luo, S., Grace, E., & Olff, M. (2021). Anxiety,depression, and PTSD symptoms among high school students in China in response to8

I. Koutsopoulou et al.

European Journal of Trauma & Dissociation 8 (2024) 100384
global collaboration on traumatic stress. European Journal of Psychotraumatology, 11(1), Article 1752504. https://doi.org/10.1080/20008198.2020.1752504
Perrin, S., Meiser-Stedman, R., & Smith, P (2005). The Children’s Revised Impact ofEvent Scale (CRIES): Validity as a screening instrument for PTSD. Behavioural andCognitive Psychotherapy, 33(4), 487–498. https://doi.org/10.1017/
s1352465805002419
Pietkiewicz, I. J., Hełka, A. M., & Tomalski, R. (2019). Validity and reliability of therevised Polish online and pen-and-paper versions of the Dissociative Experiences
Scale (DESR-PL). European Journal of Trauma and Dissociation, 3, 235–243. https://doi.org/10.1016/j.ejtd.2019.02.003
Rossi, R., Socci, V., Talevi, D., Cinzia Niolu, C., Pacitti, F., Di Marco, A., Rossi, A.,
Siracusano, A., Di Lorenzo, G., & Olff, M. (2021). Trauma-spectrum symptoms
among the Italian general population in the time of the COVID-19 outbreak.
European Journal of Psychotraumatology, 12(1). https://doi.org/10.1080/
20008198.2020.1855888
Salimi, Y., Hoeboer, C., Motevalli Haghi, S. A., Williamson, R. E., Rahimi, M. D., RajabiGilan, N., Almasi, A., & Olff, M. (2023). Trauma and its consequences in Iran: Crosscultural adaption and validation of the Global Psychotrauma Screen in a
representative sample. BMC Psychiatry, 23(1), 65. https://doi.org/10.1186/s12888023-04564-8
Sousa, V. D., & Rojjanasrirat, W. (2011). Translation, adaptation and validation of
instruments or scales for use in cross-cultural health care research: A clear and userfriendly guideline. Journal of Evaluation in Clinical Practice, 17, 268–274. https://doi.
org/10.1111/j.1365-2753.2010.01434.x
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure forassessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092
StataCorp. (2021). Stata statistical software: Release 17. College Station, TX: StataCorp
LLC.
Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed., pp.
52–53). Routledge/Taylor & Francis Group.
Tzikos, A., Arvaniti, A., Kalamara, E., Vorvolakos, T., Kafalis, G., Samakouri, M., &Livaditis, M. (2021). Validating Dissociative Experience Scale (DES) in a Greek
sample. Journal of Trauma & Dissociation: The Official Journal of the International
Society for the Study of Dissociation (ISSD), 22(5), 522–539. https://doi.org/10.1080/
15299732.2020.1869648
United Nations Children’s Fund. (2020). A situation Analysis of Children and Youth.
Greece 2020. https://www.unicef.org/greece/media/2041/file/Full%20Report:%
20The%20Analysis%20of%20the%20Situation%20of%20Children%20and%20
Youth%20in%20Greece%202021.pdf.
Verhagen, I., Noom, M., Lindauer, R., Daams, J., & Hein, I. (2022). Mental healthscreening and assessment tools for forcibly displaced children: A systematic review.
European Journal of Psychotraumatology, 13(2). https://doi.org/10.1080/
20008066.2022.2126468
Verlinden, E., van Meijel, E. P., Opmeer, B. C., Beer, R., de Roos, C., Bicanic, I. A.,
Lamers-Winkelman, F., Olff, M., Boer, F., & Lindauer, R. J. (2014). Characteristics of
the Children’s Revised Impact of Event Scale in a clinically referred Dutch sample.
Journal of Traumatic Stress, 27(3), 338–344. https://doi.org/10.1002/jts.21910
Wamser-Nanney, R., & Cherry, K. E. (2018). Children’s trauma-related symptoms
following complex trauma exposure: Evidence of gender differences. Child Abuse &Neglect, 77, 188–197. https://doi.org/10.1016/j.chiabu.2018.01.009
Williamson, R., Hoeboer, Ch. M., Primasari, I., Qing, Y., Coimbra, B. M., Hovnanyan, A.,
Grace, E., & Olff, M. (2021). Symptom networks of COVID-19-related versus otherpotentially traumatic events in a global sample. Journal of Anxiety Disorders, 84,
Article 102476. https://doi.org/10.1016/j.janxdis.2021.102476
World Health Organization. (2018). International classification of diseases for mortality andmorbidity statistics(11th revision). https://icd.who.int/browse11/l-m/en#/http%3a%2f%2fid.who.int%2ficd%2fentity%2f334423054.

Stress Disorder? Journal of Trauma & Dissociation, 1–17. https://doi.org/10.1080/
15299732.2023.2231928
IBM Corp. (2019). IBM SPSS statistics for windows, version 26.0. Armonk, NY: IBM Corp.
Kazlauskas, E., Kairyte, A., & Zelviene, P. (2023). Complex posttraumatic stress disorderin adolescence: A two-year follow-up study. Clinical Child Psychology and Psychiatry,
1–13. https://doi.org/10.1177/13591045231187975
Kessler, R. C., Aguilar-Gaxiola, S., Alonso, J., Benjet, C., Bromet, E. J., Cardoso, G.,
Degenhardt, L., de Girolamo, G., Dinolova, R. V., Ferry, F., Florescu, S., Gureje, O.,
Haro, J. M., Huang, Y., Karam, E. G., Kawakami, N., Lee, S., Lepine, J. P.,
Levinson, D., Navarro-Mateu, F., … Koenen, K. C. (2017). Trauma and PTSD in the
WHO World Mental Health Surveys. European Journal of Psychotraumatology, 8(sup5), Article 1353383. https://doi.org/10.1080/20008198.2017.1353383
King, C. D., Hill, S. B., Wolff, J. D., Bigony, C. E., Winternitz, S., Ressler, K. J.,
Kaufman, M. L., & Lebois, L. A. M. (2020). Childhood maltreatment type and severity
predict depersonalization and derealization in treatment-seeking women withposttraumatic stress disorder. Psychiatry Research, 292, Article 113301. https://doi.
org/10.1016/j.psychres.2020.113301
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief
depression severity measure. Journal of General Internal Medicine, 16(9), 606–613.
https://doi.org/10.1046/j.1525-1497.2001.016009606.x
Kyriazos, T. (2018). Applied psychometrics: Sample size and sample power
considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9,2207–2230. https://doi.org/10.4236/psych.2018.98126
Lianos, P., Velissaropoulos, C., Desylla, T., Sofianou, A.-P., Nikolopoulou, M. L., &Athanasiou, V. (2023). Prosocial skills and adolescents’ response to trauma: the roleof social support and parental behavior from a psychoanalytic perspective.
International Journal of Psychoanalysis and Education: Subject, Action & Society, 3(1).
https://doi.org/10.32111/SAS.2023.3.1.1
Magklara, K., Lazaratou, H., Barbouni, A., Poulas, K., & Farsalinos, K. (2022). The impact
of COVID-19 lockdown on children’s and adolescents’ mental health in Greece.
Children & Society. https://doi.org/10.1111/chso.12605, 10.1111/
chso.12605Advance online publication.
McLaughlin, K. (2023). Posttraumatic stress disorder in children and adolescents:
Epidemiology, pathogenesis, clinical manifestations, course, assessment, anddiagnosis. In D. Brent, & M. Friedman (Eds.), UpToDate. Waltham, MA: UpToDate
Inc. https://www.uptodate.com/contents/posttraumatic-stress-disorder-in-children-and-adolescents-epidemiology-pathogenesis-clinical-manifestations-c
ourse-assessment-and-diagnosis.
McKay, M. T., Cannon, M., Chambers, D., Conroy, R. M., Coughlan, H., Dodd, P.,
Healy, C., O’Donnell, L., & Clarke, M. C. (2021). Childhood trauma and adult mental
disorder: A systematic review and meta-analysis of longitudinal cohort studies. Acta
Psychiatrica Scandinavica, 143(3), 189–205. https://doi.org/10.1111/acps.13268
Mossman, S. A., Luft, M. J., Schroeder, H. K., Varney, S. T., Fleck, D. E., Barzman, D. H.,
Gilman, R., DelBello, M. P., & Strawn, J. R. (2017). The generalized anxiety disorder
7-item scale in adolescents with generalized anxiety disorder: Signal detection andvalidation. Annals of Clinical psychiatry: Official Journal of the American Academy ofClinical Psychiatrists, 29(4), 227–234A.
Oe, M., Kobayashi, Y., Ishida, T., Chiba, H., Matsuoka, M., Kakuma, T., Frewen, P., &Olff, M. (2020). Screening for psychotrauma related symptoms: Japanese translationand pilot testing of the Global Psychotrauma Screen. European Journal of
Psychotraumatology, (1), 11. https://doi.org/10.1080/20008198.2020.1810893
Olff, M. (2022). Global Psychotrauma Screen (GPS) user guide. Global Psychotrauma
Screen user guide. https://www.global-psychotrauma.net/_files/ugd/8934
21_537cebfa2bfe4a77bdc6f2a9366291ea.pdf.
Olff, M., Primasari, I., Qing, Y., Coimbra, B. M., Hovnanyan, A., Grace, E.,
Williamson, R., Hoeboer, Ch. M., & the GPS-CCC Consortium. (2021). Mental healthresponses to COVID-19 around the world. European Journal of Psychotraumatology, 12(1), Article 1929754. https://doi.org/10.1080/20008198.2021.1929754
Olff, M., Bakker, A., Frewen, P., Aakvaag, H., Ajdukovic, D., Brewer, D., …
Borbon, Elmore (2020). Screening for consequences of trauma – An update on the9