Content uploaded by Dana Churbaji
Author content
All content in this area was uploaded by Dana Churbaji on Sep 19, 2024
Content may be subject to copyright.
1
ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Original research
ADULT MENTAL HEALTH
Emotion regulation profiles in Syrian refugees and
migrants in Germany: self- efficacy, resilience and
well- beingcomparisons
Dana Churbaji ,1 Pascal Schlechter,1 Angela Nickerson,2 Nexhmedin Morina1
To cite: ChurbajiD,
SchlechterP, NickersonA,
etal. BMJ Ment Health
2024;27:1–7.
►Additional supplemental
material is published online
only. To view, please visit the
journal online (https:// doi.
org/ 10. 1136/ bmjment- 2024-
301099).
1University of Münster, Munster,
Germany
2UNSW, Sydney, New South
Wales, Australia
Correspondence to
Dana Churbaji, University of
Münster, Munster, Nordrhein-
Westfalen, Germany; churbaji@
uni- muenster. de
Received 29 March 2024
Accepted 30 August 2024
© Author(s) (or their
employer(s)) 2024. Re- use
permitted under CC BY- NC.
Published by BMJ.
Open access
ABSTRACT
Background Emotion regulation (ER) plays a central
role in psychopathology. Understanding person- centred
patterns of ER strategies is crucial for prevention and
intervention strategies. However, there is a paucity of
research on ER profiles and their psychological correlates
in forcibly displaced people (FDP).
Objective This study aimed to identify habitual ER
profiles and to examine the predictive role of different
psychological variables on these profiles in Syrian FDP in
Germany.
Method In a sample of 991 individuals, we
conducted a latent profile analysis (LPA) to assess
habitual reappraisal and suppression of emotion as ER
strategies, as well as self- efficacy, resilience, well-
being comparisons, trauma exposure and International
Classification of Diseases 11th Revision post- traumatic
stress disorder (PTSD) symptoms as potential predictors
of ER profile membership.
Results LPA identified four distinct ER profiles: high
regulators (12.8%), low regulators (20.6%), reappraisal
regulators (25.1%) and suppressive regulators (41.5%).
In multinomial regression analysis, self- efficacy,
resilience, appetitive well- being comparisons and
trauma exposure were significantly associated with
profile membership, while PTSD and aversive well- being
comparisons showed no significant association. High
regulators exhibited the highest levels of self- efficacy,
resilience and appetitive well- being comparisons,
followed by reappraisal, suppressive and low regulators.
Additionally, high regulators reported the highest
number of traumatic events, followed by suppressive and
low regulators.
Conclusions Our results indicate a higher adaptiveness
in high regulation ER profiles as opposed to low
regulation ER profiles.
Clinical implications Given that most FDP in our
sample relied predominantly on one ER strategy,
developing interventions that focus on cultivating a
broad repertoire of ER strategies may be beneficial.
BACKGROUND
Increasing forced migration, driven by armed
conflict and extreme climates, requires a deeper
understanding of mental health challenges faced
by affected populations.1 Post- traumatic stress
disorder (PTSD) and depression have been identi-
fied as the most prevalent mental disorders in forc-
ibly displaced people (FDP) resettled in Western
countries.1 Yet the heterogeneity of mental health
outcomes among FDP remains poorly understood.2
Furthermore, mental health interventions for refu-
gees still fail to adequately support a significant
proportion of individuals.3 This highlights the need
to better understand the mechanisms of psycho-
pathology in FDP. Previous studies have mainly
focused on identifying predictors of adverse mental
health outcomes. Numerous studies have found a
dose- response relationship between exposure to
potentially traumatic events (PTE), postmigration
stressors and psychopathology in forced migra-
tion contexts.4 The present study aimed to identify
distinct profiles of emotion regulation (ER) and
their psychological correlates in FDP including
WHAT IS ALREADY KNOWN ON THIS TOPIC
⇒Emotion regulation (ER) is an important
transdiagnostic factor in the context of mental
health in forced migration.
⇒Previous latent profile analysis revealed distinct
profiles of ER contributing to our understanding
of ER in forcibly displaced people (FDP);
however, sample sizes were relatively small and
ER profiles have not been linked to important
psychological variables including self- efficacy,
resilience, well- being comparisons, International
Classification of Diseases 11th Revision post-
traumatic stress disorder symptoms and trauma
exposure.
WHAT THIS STUDY ADDS
⇒In 991 Syrian FDP residing in Germany,
we found 4 distinct ER profiles labelled as
high regulators, low regulators, reappraisal
regulators and suppressive regulators.
⇒Linking the ER profiles to different levels of self-
efficacy, resilience and appetitive well- being
comparisons provides nuanced insights into ER
among Syrian FDP.
HOW MIGHT THIS STUDY AFFECT RESEARCH,
PRACTICES OR POLICY
⇒By elucidating distinct ER profiles in a
vulnerable population, this study provides
important knowledge for future intervention
research, ultimately helping to address mental
health needs of FDP.
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
2ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
PTSD, exposure to PTE, self- efficacy, resilience and well- being
comparisons.
ER has emerged as a key transdiagnostic factor across various
mental disorders.5 Although there is no universally accepted
definition of ER, the definition by Gross6 suggests that individ-
uals differ in their habitual use of strategies to modify emotions,
either before they are generated (cognitive reappraisal) or after
they have occurred (expressive suppression), referred to as
antecedent- focused and response- focused ER strategies, respec-
tively. In contrast to emotion suppression, cognitive reappraisal
is categorised as an adaptive ER strategy. Individuals with
PTSD exhibit a reduced ER ability.5 In fact, emotion suppres-
sion reflects a core avoidance symptom in PTSD. A recent study
with veterans with and without PTSD suggested that expressive
suppression but not cognitive reappraisal is related to PTSD.7
In the context of forced migration, both premigration and post-
migration difficulties are associated with ER difficulties.8 Nick-
erson et al9 reported that reappraisal (vs suppression) reduced
negative affect after exposure to trauma- related visual stimuli in
a sample of traumatised treatment- seeking refugees in Australia.
However, linking specific ER strategies directly to psycho-
logical outcomes oversimplifies complex, habitual ER patterns,
as individuals often rely on multiple ER strategies.10 Recent
studies have implemented latent profile analysis (LPA) as a
person- centred approaches to investigate different ER patterns
in psychopathology.10–12 LPA groups individuals into homo-
geneous subgroups based on their common patterns across
multiple ER strategies. Dixon- Gordon et al11 identified four
ER classes in achievement- related stressors among US students:
high regulators (high reappraisal and suppression), low regula-
tors (low reappraisal and suppression), ‘maladaptive’ regulators
(high suppression, low reappraisal) and ‘adaptive’ regulators
(high reappraisal, low suppression). They observed that high
and ‘maladaptive’ regulators exhibited lower mental health
compared with low and ‘adaptive’ regulators. In contrast, the
results by Lougheed and Hollenstein12 suggested higher psycho-
pathology rates in ‘maladaptive’ and low regulators, as opposed
to high and ‘adaptive’ regulators among Canadian adolescents.
However, in a smaller sample of 93 FDP Specker and Nick-
erson13 identified three habitual ER classes—‘high’, ‘adaptive’
and ‘maladaptive’. Their findings showed that ‘maladaptive’
regulators exhibited more PTSD symptoms, while high regu-
lators experienced a broader range of PTE. Notably, they did
not find a low regulators class, arguably due to higher emotion
suppression linked to prevalent PTEs. Relatedly, an experimental
study by Specker and Nickerson14 with 82 refugees revealed that
low variability in ER was linked to higher psychopathology,
unlike high ER variability profiles. In summary, despite incon-
sistencies regarding the adaptiveness of high regulation profiles,
current findings suggest that a high regulator profile in FDP is
beneficial, emphasising the importance of diverse ER strategies10
in reducing psychopathology in FDP.
Nevertheless, categorising profiles as ‘adaptive’ versus
‘maladaptive’ may not be useful in cross- cultural settings, as
evidence both supports15 16 and opposes9 a different function
of suppression in individuals with non- Western socialisation.
Hence, the terms reappraisal profile (high reappraisal, low
suppression) and suppressive profile (low reappraisal, high
suppression) may be more useful. In this context, it is crucial to
examine how different ER profiles manifest and correlate with
various psychological factors such as resilience, self- efficacy and
well- being comparisons, as well as mental health complaints
such as PTSD. Resilience, defined as the capacity to recover from
adversity, has been associated with life- satisfaction among Syrian
refugees.17 Similarly, self- efficacy, the belief in one’s ability to
control and manage life events has been associated with better
mental health outcomes in FDP.18 Both constructs are theoreti-
cally assumed to be protective and associated with ER profiles
with high adaptiveness.
However, research on comparative thinking concerning one’s
well- being in forced migration is scarce. Well- being compari-
sons are important to consider, as judgements of well- being are
based on ordinal standards. Empirically, they comprise several
comparison types—including social, temporal, criteria- based,
dimensional and counterfactual. According to theoretical models
and factor analysis, they can be divided into aversive (ie, threat-
ening the comparer’s motives, eg, “I’m doing worse now than
last year”) and appetitive (ie, consonant with or challenging
the comparer’s motives, eg, “I’m doing better than most refu-
gees”) comparisons.19 A recent study on Arabic- speaking FDP in
Germany revealed high prevalence of well- being comparisons,
with aversive well- being comparisons associated with lower
levels of subjective well- being.20 In fact, evidence suggests that
especially aversive well- being comparisons are associated with
psychopathology including PTSD.19 Well- being comparisons are
further significantly correlated with ER,21 yet this still needs to
be investigated in FDP. Accordingly, it is assumed that appetitive
well- being comparisons will be associated with ER profiles with
high adaptiveness in contrast to aversive well- being comparisons.
The primary aim of our study was to examine the different
habitual ER profiles among 991 Arabic- speaking Syrian FDP in
Germany using LPA. In line with the study by Dixon- Gordon et
al,11 we hypothesised finding profiles of high regulators (high
in reappraisal and suppression), low regulators (low in both
ER strategies), reappraisal regulators (high reappraisal, low
suppression) and suppressive regulators (high suppression, low
reappraisal). Theoretically, we expected that suppressive and
low regulators would show higher PTE, PTSD symptoms13 14
and aversive well- being comparison frequency, but lower self-
efficacy, resilience and appetitive well- being comparisons rela-
tive to high and reappraisal regulators.
METHODS
Design, procedures and ethics
The present study is part of a larger project assessing putative
psychological mechanisms underlying mental health outcomes
in Arabic- speaking refugees and migrants in Germany, marking
the first publication concerning well- being comparisons in FDP.20
The present study addresses a unique research question and uses
most of the data for the first time. Inclusion criteria were being
over 18 years of age, native Arabic speaker and forced migration
to Germany. Exclusion criteria were psychotic disorders, current
suicide risk or lacking informed consent. The link to the survey
was posted on Facebook groups like ‘Syrian refugees in Germany’
(see Churbaji and Morina20 for further details). Written consent
was collected at the survey’s start. If participants failed to meet
the inclusion criteria or withheld consent, the survey concluded
automatically, providing contact details of the Arabic- speaking
principal investigator. Skipping questions or navigating back in
the survey was not possible. Demographic variables were assessed
via single- choice items listed in table 1, including an ‘other’ option
for open- ended responses, which were then classified accordingly.
We followed the Strengthening the Reporting of Observational
Studies in Epidemiology guidelines for observational studies.
Sample
Between May and June 2021, 4765 individuals followed the link
posted in various Facebook groups. Of these, 1752 (36.8%) met
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
3
ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
the inclusion criteria, and 1070 (22.5%) completed the entire
survey and were included in the study. The current study is based
on participants who indicated Syria as their country of origin
(92.6%; n=991). Most participants were young- aged, female,
with at least a high school degree and applied for asylum after
fleeing to Germany (table 1). With an average of 5.49 years
(SD=2.01) since living in Germany, 87.1% arrived in Germany
between 2014 and 2019.
Instruments
The Arabic version of the Emotion Regulation Questionnaire
(ERQ22) is a 10- item self- report questionnaire assessing habitual
use of cognitive reappraisal (6 items) and expressive suppres-
sion (4 items) on a 7- point Likert scale (1—strongly disagree to
7—strongly agree). It was validated based on a sample of 811
Arabic- speaking individuals in Lebanon, reporting a Cronbach’s
α of 0.76 for the reappraisal subscale and 0.66 for the suppres-
sion subscale. Similarly, the scale yielded an internal consistency
of α=0.80 for reappraisal and α=0.67 for suppression in the
current sample.
PTSD symptoms were assessed using the Arabic version of
the International Trauma Questionnaire (ITQ23), a self- report
measure based on the diagnostic criteria of the International
Classification of Diseases 11th Revision (ICD- 11) for PTSD.
While the ITQ measures both symptoms of PTSD according to
the ICD- 11 and disturbances of self- organisation, we were only
interested in PTSD symptoms for the sake of brevity. That is,
we assessed six items focusing on re- experience, avoidance and
sense of current threat. Respondents rate their level of distress
for each symptom over the past month on a 5- point Likert scale
(0—not at all to 4—extremely). In the current sample, α was
0.84.
Self- efficacy was assessed using the General Self- Efficacy
scale (GSE24). The scale consists of 10 items using a 4- point
Likert scale (1—not at all true to 4—exactly true). The scale
has been cross- culturally adapted and translated in 25 coun-
tries. The Arabic version was validated based on 264 subjects
from Syria reporting an α value of 0.79. In the current sample,
α was 0.89.
The Arabic version of the Brief Resilience Scale (BRS17) assesses
an individual’s capacity to bounce back from stressful events.
The scale consists of six items rated on a 5- point Likert scale
(1—strongly disagree to 5—strongly agree) with items 2, 4 and
6 reverse- coded. The BRS revealed good internal consistency in
a sample of Syrian refugees in Iraq. In the current study, α was
0.79.
The Comparison Standard Scale- Well- being (CSS- W25) was
applied to assess the frequency of comparisons related to one’s
own well- being. The original CSS- W comprises 14 frequency
items divided into appetitive and aversive comparison subscales
using a 6- point Likert scale (0—not at all to 5—often). The
aversive comparison subscale includes upward social compari-
sons, upward retrospective and downward prospective temporal
comparisons, upward counterfactual comparisons and upward
criteria- based comparisons. The appetitive comparison subscale
comprises downward social comparisons, downward retro-
spective and upward prospective temporal comparisons, down-
ward counterfactual comparisons and downward criteria- based
comparisons. In the current study, two items assessing war- related
counterfactual comparison (eg, thought you would be doing
better now if war- related circumstances had been different) were
added summing up to 16 items. The CSS- W Arabic was trans-
lated and validated based on a sample of Arabic- speaking FDP
in Germany showing good internal consistency.20 In the current
sample, the α values were 0.72 for the aversive subscale and 0.65
for the appetitive subscale.
The Refugee Trauma History Checklist (RTHC26) assessed
trauma exposure. It includes eight yes/no items evaluating expo-
sure to war, forced separation from loved ones, loss of family
members, witnessing violence, personal physical violence,
torture, sexual violence and other life- threatening situations
before and after leaving the home country.
Table 1 Sociodemographic variables and outcome variables
Variable N (%) M (SD)
Observed
range
Gender
Female 61.5
Age in years 30.25 (8.49) 18–67
Current state of residence
Refugee residence permit 67.4
Permanent residency status 16.1
Naturalisation 5.7
Student residency permit 2.2
Other 8.6
Household
Family or partner 70.9
Shared apartment 7.9
Single 19
Other 2.2
Education
Elementary school (6 years) 0.7
Secondary school (9 years) 9.2
High school diploma (12 years) 33.8
Undergraduate and postgraduate
studies (>12 years)
56.3
Occupation
Full time 18.3
Part time 7.7
Student or vocational training 44.9
Unemployed 28.9
Retired 0.3
Years since living in Germany 5.49 (2.01) 0–22
Migration
Asylum 55.1
Family reunification process 25.7
Visa application 13.2
UNHCR resettlement programme 0.8
Other 5.2
Outcome variables
ITQ 9.02 (5.45) 0–24
ERQ suppression 15.62 (5.25) 4–28
ERQ reappraisal 27.86 (6.10) 6–42
GSE 27.10 (5.29) 10–40
BRS 18.43 (4.45) 6–30
CSS- W aversive 18.61 (8.42) 0–40
CSS- W appetitive 16.10 (7.36) 0–40
BRS, Brief Resilience Scale; CSS- W, Comparison Standard Scale- Well- being;
ERQ, Emotion Regulation Questionnaire; GSE, General Self- Efficacy scale; ITQ,
International Trauma Questionnaire; UNHCR, United Nations High Commissioner for
Refugees .
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
4ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
Analysis
The LPA was conducted using ‘TidyLPA’27 package in R for
MAC. The logistic multinominal regression was performed
with Latent Gold software for Windows.28 All remaining
descriptive analyses were conducted using IBM SPSS Statis-
tics (V.27) for MAC. First, we conducted LPA to identify
latent subgroups based on the observed ER variables. We
aimed to categorise individuals into distinct profiles with
similar ER response patterns. The default LPA model from
TidyLPA, assuming equal variances and zero covariances
across profiles, was used. To determine the optimal number
of latent profiles, we started with a one- profile solution and
successively increased the number of profiles. The successive
models were compared using the goodness- of- fit indices: log
likelihood, Akaike Information Criterion and sample- size-
adjusted Bayesian Information Criterion, with lower abso-
lute values indicating a better fit. The bootstrap likelihood
ratio test (BLRT) was also used; a significant value (p<0.05)
suggests the model with ‘k’ classes outperforms the previous
one with ‘k−1’ classes. Finally, higher entropy values were
considered to indicate a greater distinction between profiles.
We ran a logistic multinomial regression to examine how
our predictor variables are related to membership in the
identified latent profiles. In the bias- adjusted three- step
approach27 after estimating the latent profile model (step
1), subjects are classified to profiles based on their posterior
profile membership probabilities (step 2). In step 3, profile
memberships are regressed on sum scores on GSE, RTHC,
ITQ, BRS and CSS- W (aversive and appetitive subscale). In
this step, the underestimation bias of the regression param-
eter’s estimates due to membership classification errors is
corrected using the maximum likelihood method. Multicol-
linearity was assessed using Pearson’s correlation coefficient
with a cut- off value of 0.80 (online supplemental appendix,
table A1). The largest profile served as the reference category
for the logistic multinomial regression output. Additionally,
direct comparisons between the profiles are provided to
highlight variable differences.
RESULTS
Descriptive statistics
Exposure to at least one PTE was reported by 98.2% of partic-
ipants. The majority experienced war at close quarters (90%),
followed by forced separation from family and friends (53.5%),
and loss or disappearance of loved ones (42.4%) as shown in
online supplemental appendix, table A2. Table 1 shows the mean
values of outcome variables.
Latent profile analysis
Online supplemental appendix, table A3 shows model fit statis-
tics for the LPA. We chose the 4- profile model as the most suit-
able among the tested solutions due to the substantial reduction
of at least 173 points in all ICs compared with the 3- profile
model, along with a significant BLRT value (p<0.05). Although
the BLRT was also significant in the 5- profile solution, the
model was associated with relatively small reduction in ICs of
maximum 38 points. The observed 4- profile model aligns with
our theoretical framework proposing four ER profiles with an
entropy value of 0.78. Figure 1 illustrates the standardised esti-
mated means and 95% CIs of the items for each profile.
The four profiles reflect our hypotheses. Profile 1 is char-
acterised by lower scores on all items, indicating a low regula-
tors profile with 12.8% of participants. Profile 2, representing
20.6% of participants is characterised by higher scores on all
items, aligning with high regulators. Profile 3 accounts for 25.1%
of participants, with higher scores in reappraisal and lower in
suppression, suggesting a profile of reappraisal regulators.
Finally, the largest group, profile 4, includes 41.5% of partic-
ipants, and is characterised by higher suppression and lower
reappraisal scores, pointing to suppressive regulators. While
reappraisal items effectively differentiate between the profiles,
Figure 1 Estimated standardised suppression and reappraisal item means and 95% CIs across the four profiles. Reap 1 to Reap 6 denotes to the six
items measuring reappraisal in the Emotion Regulation Questionnaire. Supp 1 to Supp 4 denotes the four items measuring suppression in the same
questionnaire.
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
5
ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
suppression items do not significantly distinguish between low
and reappraisal regulators, a pattern that is similarly observed
between high and suppressive regulators (figure 1).
Table 2 presents mean values of outcome variables across
profiles. On protective variables comprising self- efficacy, resil-
ience and appetitive well- being, high regulators showed the
highest values followed closely by reappraisal regulators. In
contrast, low regulators exhibited the lowest values on these
variables. For PTE exposure, high regulators had the highest
values followed by suppressive and low regulators with similar
values, and reappraisal regulators showing the lowest values. For
aversive well- being comparisons, both reappraisal and high regu-
lators showed similarly low values in contrast to suppressive and
low regulators showing similarly high values. For PTSD, reap-
praisal regulators demonstrated the lowest values, with all other
profiles displaying similarly high values.
Multinomial regression analysis
Table 3 shows the log ORs for belonging to each profile relative
to suppressive regulators. Appetitive well- being comparisons,
self- efficacy, resilience and PTE exposure were significantly
associated with profile membership, while aversive well- being
comparisons and PTSD symptoms were not. The covariates
explain 7.4% of the variance in the data. Reflecting on the
pattern observed in table 2, higher PTE exposure decreased the
probability of being among reappraisal regulators compared
with suppressive regulators and significantly differentiated reap-
praisal against suppressive and high regulators. Appetitive well-
being comparisons distinguished all profiles except low against
suppressive regulators and reappraisal against high regulators,
with higher values linked to high or reappraisal regulators rela-
tive to suppressive regulators. Self- efficacy distinguished all
profiles except between reappraisal and suppressive regula-
tors, with higher self- efficacy linked to high regulators relative
to suppressive regulators. Resilience distinguished all profiles
except between reappraisal and high regulators and between low
and suppressive regulators, with higher resilience associated with
high or reappraisal regulators relative to suppressive regulators.
DISCUSSION
We assessed ER profiles of Syrian FDP in Germany. In line with
theoretical expectations, we identified four distinct ER profiles:
suppressive regulators, which constituted the largest profile,
followed by reappraisal regulators, high regulators and low regu-
lators. From the predictors assessed, PTE exposure, self- efficacy,
resilience and appetitive well- being comparisons were signifi-
cantly associated with profile membership, while PTSD and
aversive well- being comparisons were not. As hypothesised, high
and reappraisal regulators reported higher values in self- efficacy,
resilience and appetitive well- being comparisons, reflecting
higher adaptiveness relative to low and suppressive regulators.
In line with Lougheed and Hollenstein,12 our findings
revealed a high regulators profile comprising individuals who
habitually employ both reappraisal and suppression strategies to
regulate their emotions. Our findings suggest that despite high
rates of PTE exposure in this profile, individuals with a high
regulation ER profile reported higher rates of protective psycho-
logical factors comprising self- efficacy, resilience and appetitive
well- being comparisons, suggesting a form of adaptation and
psychological resilience. While Specker and Nickerson13 did
not identify a low regulators profile, their experimental study14
showed that low regulation was associated with higher levels
of psychopathology. Corroborating this, profiles of low regu-
lators were significantly associated with lower mean values in
self- efficacy, resilience and appetitive well- being comparisons
compared with high and reappraisal regulators.
Our data further reveal that while suppressive regulators
displayed lower levels of protective factors than reappraisal
and high regulators, they still have higher mean scores on
these protective factors than low regulators. This observation
may support the argument that suppression, often classified
as a ‘maladaptive’ ER strategy,5 should be considered within a
cross- cultural context. A recent meta- analysis reported greater
use of emotion suppression in individuals with non- Western
socialisation.16 Still, the association between suppression and
higher psychopathology is well- documented.5 9 Taking into
account (1) the debate on oversimplifying cultures intro ‘west-
east’ dichotomy with little consideration of variations within
cultures,29 (2) the specific context of the present sample in which
FDP navigate between the heritage and the host culture30 and (3)
the high rates of PTE exposure in our sample (98%), attributing
an adaptive or maladaptive function to suppression based on our
assessment should be handled carefully. Nevertheless, navigating
between the heritage and the host culture may necessitate the use
of both suppression and reappraisal ER strategies.30 This may
also account for the notably high adaptiveness of the high regu-
lation profile in our sample, surpassing the protective factors
observed in individuals with a reappraisal profile who habitually
favour reappraisal over suppression.
Although the association between PTSD and ER is well-
documented5 and PTSD scores were high, PTSD was not signifi-
cantly associated with ER profiles after accounting for PTE
exposure, self- efficacy, resilience and well- being comparisons. In
the present sample, this could be attributed to PTSD playing a
minor role in ER profile membership after accounting for these
factors given (1) the high educational background (90.1% have
≥12 years of education) and (2) the long years since living in
Germany leading to relatively low levels of PTSD symptoms.
Table 2 Means of outcome variables across profiles
Low regulators
M (SD)
High regulators
M (SD)
Reappraisal regulators
M (SD)
Suppressive regulators
M (SD)
CSS- W appetitive 14.28 (7.03) 18.22 (8.45) 16.72 (7.04) 15.23 (6.78)
CSS- W aversive 19.63 (8.53) 17.76 (7.81) 17.51 (8.34) 19.35 (8.62)
GSE 23.82 (5.82) 29.24 (5.03) 28.00 (4.58) 26.44 (5.04)
BRS 16.57 (4.68) 19.95 (4.22) 19.29 (4.48) 17.74 (4.14)
ITQ 9.27 (6.15) 9.27 (5.30) 8.20 (5.18) 9.32 (5.43)
RTHC 4.15 (2.12) 4.49 (2.33) 3.77 (1.9) 4.32 (2.07)
BRS, Brief Resilience Scale; CSS- W, Comparison Standard Scale- Well- being; GSE, General Self- Efficacy scale; ITQ, International Trauma Questionnaire; RTHC, Refugee Trauma
History Checklist.
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
6ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
This could suggest that the association between ER strategies
and PTSD is impacted by factors like self- efficacy, resilience and
well- being comparisons. However, more nuanced research is
warranted to understand this outcome. Furthermore, the unex-
pected lack of significance of aversive well- being comparisons as
a predictor of ER strategies might be a result of aversive compar-
isons leading to negative affect, which is managed to a similar
extent by either cognitive reappraisal or suppression, with no
difference between the profiles. Alternatively, suppressive regu-
lators may be less accurate in noticing and remembering (and
hence reporting) aversive comparisons as they are more likely
to avoid a comparison process before completion. Overall, the
disparity between aversive and appetitive well- being compari-
sons highlights the importance of differentiating between the
two subscales of the CSS- W20 and warrants further investigation.
Despite the large sample size, our study has several limitations.
The low and high regulator profiles might represent extreme
response styles due to the self- report nature of the instruments,
although scoring trends in the CSS- W aversive subscale counter
this argument. The cross- sectional design omits causal infer-
ences, and future research should investigate these associations
in experimental or longitudinal settings and include more ER
strategies beyond suppression and reappraisal such as acceptance
and experiential avoidance. While our study focused on PTSD
symptoms, future research should include symptoms of other
disorders like depression or anxiety that are prevalent in FDP.
Furthermore, our recruitment via social media limits generalis-
ability, as our sample consisted of mainly young and educated
adults and it could not be verified that all participants were refu-
gees from Syria. The high PTE exposure (98%) in our sample
additionally limits generalisability to high adversity populations.
Additionally, internal consistencies of some subscales such as
reappraisal in ERQ and appetitive comparison in the CSS- W were
rather low. Yet, these values are similar to those reported in the
original validation studies and may be attributable to the breath
of these constructs.22 25 Additionally, omitting the assessment
of functional impairment and self- organisation disturbances in
the ITQ hindered the examination of PTSD and complex PTSD
prevalence. Finally, limiting the assessment of PTE exposure to
war- related experiences inhibits the ability to draw conclusion
on other interpersonal traumatic experiences.
Clinical implications
Our study has important clinical implications, indicating a high
adaptability among individuals relying on both suppression
and reappraisal as habitual ER strategies in FDP. Given that the
majority of our sample relied on either suppression or reap-
praisal ER strategies, interventions designed to broaden the ER
strategies in FDP may prove useful. Future studies should inves-
tigate the efficacy of psychoeducational approaches to promote
diverse ER repertoire, potentially paving the way for effective
and cost- effective, large- scale interventions for FDP in need of
mental healthcare.
In conclusion, our study identified four distinct ER profiles
among Syrian Arabic- speaking FDP in Germany. High regulators
showed the highest values in protective mechanisms followed
by reappraisal regulators, suppressive regulators and low regu-
lators. Our findings extend the current literature by elucidating
the association between these profiles and various psycholog-
ical factors. Future research should further investigate the inter-
action between habitual ER profiles, additional psychological
mechanisms and psychopathology in individuals with a history
of forced migration. This exploration may provide valuable
Table 3 Output of the bias- adjusted three- step multinominal regression analysis including log ORs and paired comparison of the profiles
Profiles
Low
regulators SE High regulators SE
Reappraisal
regulators SE
Suppressive
regulators Wald test P value
Comparison between profiles, p value
Low versus
suppressive
regulators
High versus
suppressive
regulators
Reappraisal
versus
suppressive
regulators
Reappraisal versus
high regulators
Low versus high
regulators
Low versus
reappraisal
regulators
Intercept 2.68 1.01 −6.63 0.96 −2.67 0.86 0 64.09 <0.00 <0.00 <0.00 <0.00 <0.00 <0.00 <0.00
Covariates
CSS- W appetitive −0.03 0.02 0.07 0.02 0.06 0.02 0 32.48 <0.00 0.15 <0.00 <0.00 0.52 <0.00 <0.00
CSS- W aversive −0.02 0.02 −0.02 0.01 −0.02 0.02 0 2.92 0.4 0.36 0.25 0.14 0.73 0.94 0.14
GSE −0.09 0.03 0.11 0.03 0.04 0.02 0 34.30 <0.00 <0.00 <0.00 0.10 <0.05 <0.00 <0.00
BRS −0.04 0.04 0.09 0.03 0.07 0.03 0 17.63 <0.00 0.32 <0.00 <0.05 0.49 <0.00 <0.05
ITQ −0.01 0.03 0.02 0.02 −0.01 0.02 0 2.73 0.43 0.61 0.31 0.48 0.13 0.26 1
RTHC −0.02 0.06 −0.01 0.05 −0.15 0.05 0 8.98 0.03 0.69 0.92 <0.01 <0.05 0.79 0.07
The profile suppressive regulators is set as the reference group.
BRS, Brief Resilience Scale; CSS- W, Comparison Standard Scale- Well- being; GSE, General Self- Efficacy scale; ITQ, International Trauma Questionnaire; RTHC, Refugee Trauma History Checklist.
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
7
ChurbajiD, etal. BMJ Ment Health 2024;27:1–7. doi:10.1136/bmjment-2024-301099
Open access
insights for the development of more effective psychological
interventions.
Contributors DC and NM designed the study. DC conducted the study and the
statistical analyses and wrote a first draft of the manuscript. DC is the guarantor
for the study. All authors have contributed to and approved the final version of the
manuscript.
Funding The authors have not declared a specific grant for this research from any
funding agency in the public, commercial or not- for- profit sectors.
Competing interests None declared.
Patient consent for publication Consent obtained directly from patient(s).
Ethics approval The University of Münster’s local ethics committee granted ethical
approval for the study (reference 2021- 37- DCh). Participants gave informed consent
to participate in the study before taking part.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available on reasonable request. Data are
available on request on the Open Science Framework (https://doi.org/10.17605/OSF.
IO/PA5HB).
Supplemental material This content has been supplied by the author(s). It
has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have
been peer- reviewed. Any opinions or recommendations discussed are solely those
of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and
responsibility arising from any reliance placed on the content. Where the content
includes any translated material, BMJ does not warrant the accuracy and reliability
of the translations (including but not limited to local regulations, clinical guidelines,
terminology, drug names and drug dosages), and is not responsible for any error
and/or omissions arising from translation and adaptation or otherwise.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non- commercially,
and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non- commercial. See:http://creativecommons.org/licenses/by-nc/4.0/.
ORCID iD
DanaChurbaji http://orcid.org/0000-0001-9939-3905
REFERENCES
1 Blackmore R, Boyle JA, Fazel M, etal. The prevalence of mental illness in
refugees and asylum seekers: A systematic review and meta- analysis. PLoS Med
2020;17:e1003337.
2 Minihan S, Liddell BJ, Byrow Y, etal. Patterns and predictors of posttraumatic stress
disorder in refugees: A latent class analysis. J Affect Disord 2018;232:252–9.
3 Kip A, Priebe S, Holling H, etal. Psychological interventions for posttraumatic stress
disorder and depression in refugees: A meta-analysis of randomized controlled trials.
Clin Psychol Psychoth 2020;27:489–503.
4 Nguyen TP, Guajardo MGU, Sahle BW, etal. Prevalence of common mental disorders
in adult Syrian refugees resettled in high income Western countries: a systematic
review and meta- analysis. BMC Psychiatry 2022;22:15.
5 Carmassi C, Conti L, Gravina D, etal. Emotional dysregulation as trans- nosographic
psychopathological dimension in adulthood: A systematic review. Front Psychiatry
2022;13:900277.
6 Gross JJ. The Emerging Field of Emotion Regulation: An Integrative Review. Rev Gen
Psychol 1998;2:271–99.
7 Khan AJ, Maguen S, Straus LD, etal. Expressive suppression and cognitive reappraisal
in veterans with PTSD: Results from the mind your heart study. J Affect Disord
2021;283:278–84.
8 Nickerson A, Bryant RA, Schnyder U, etal. Emotion dysregulation mediates the
relationship between trauma exposure, post- migration living difficulties and
psychological outcomes in traumatized refugees. J Affect Disord 2015;173:185–92.
9 Nickerson A, Garber B, Liddell BJ, etal. Impact of Cognitive Reappraisal on Negative
Affect, Heart Rate, and Intrusive Memories in Traumatized Refugees. Clin Psychol Sci
2017;5:497–512.
10 Ford BQ, Gross JJ, Gruber J. Broadening Our Field of View: The Role of Emotion
Polyregulation. Emot Rev 2019;11:197–208.
11 Dixon- Gordon KL, Aldao A, De Los Reyes A. Repertoires of emotion regulation: A
person- centered approach to assessing emotion regulation strategies and links to
psychopathology. Cogn Emot 2015;29:1314–25.
12 Lougheed JP, Hollenstein T. A Limited Repertoire of Emotion Regulation Strategies is
Associated with Internalizing Problems in Adolescence. Soc Dev 2012;21:704–21.
13 Specker P, Nickerson A. Investigating the relationship between distinctive patterns of
emotion regulation, trauma exposure and psychopathology among refugees resettled
in Australia: a latent class analysis. Eur J Psychotraumatol 2019;10:1661814.
14 Specker P, Nickerson A. An experimental investigation of spontaneous emotion
regulation variability, negative affect, and posttraumatic stress disorder among
traumatized refugees. Psychol Trauma 2023;15:219–26.
15 Butler EA, Lee TL, Gross JJ. Does Expressing Your Emotions Raise or Lower Your
Blood Pressure? The Answer Depends on Cultural Context. J Cross Cult Psychol
2009;40:510–7.
16 Weiss NH, Thomas ED, Schick MR, etal. Racial and ethnic differences in emotion
regulation: A systematic review. J Clin Psychol 2022;78:785–808.
17 Yıldırım M, Aziz IA, Vostanis P, etal. Associations among resilience, hope, social
support, feeling belongingness, satisfaction with life, and flourishing among Syrian
minority refugees. J Ethn Subst Abuse 2024;23:166–81.
18 Nickerson A, Byrow Y, O’Donnell M, etal. Cognitive mechanisms underlying the
association between trauma exposure, mental health and social engagement in
refugees: A longitudinal investigation. J Affect Disord 2022;307:20–8.
19 Morina N. Comparisons Inform Me Who I Am: A General Comparative- Processing
Model of Self- Perception. Perspect Psychol Sci 2021;16:1281–99.
20 Churbaji D, Morina N. Cognitive factors underlying the impact of postmigration
stressors on subjective well-being: Well-being comparisons and self-efficacy. Clin
Psychol Psychoth 2024;31:e2928.
21 Schlechter P, Morina N. The associations among well- being comparisons and
affective styles in depression, anxiety, and mental health quality of life. J Clin Psychol
2024;80:355–69.
22 Kahwagi R- M, Zeidan RK, Haddad C, etal. Emotion regulation among Lebanese
adults: Validation of the Emotion Regulation Questionnaire and association with
attachment styles. Perspect Psychiatr Care 2021;57:809–20.
23 Vallières F, Ceannt R, Daccache F, etal. ICD- 11 PTSD and complex PTSD amongst
Syrian refugees in Lebanon: the factor structure and the clinical utility of the
International Trauma Questionnaire. Acta Psychiatr Scand 2018;138:547–57.
24 Scholz U, Doña BG, Sud S, etal. Is general self- efficacy a universal construct?
Psychometric findings from 25 countries. Eur J Psychol Assess 2002;18:242–51.
25 Morina N, Schlechter P. Habitual aversive and appetitive well- being comparisons in
dysphoria: Introducing the Comparison Standards Scale for well- being. J Affect Disord
2023;322:132–40.
26 Sigvardsdotter E, Nilsson H, Malm A, etal. Development and Preliminary Validation
of Refugee Trauma History Checklist (RTHC)- A Brief Checklist for Survey Studies. Int J
Environ Res Public Health 2017;14:1175.
27 Rosenberg J, Beymer P, Anderson D, etal. tidyLPA: An R Package to Easily Carry
Out Latent Profile Analysis (LPA) Using Open- Source or Commercial Software. JOSS
2019;3:978.
28 Bakk Z, Tekle FB, Vermunt JK. Estimating the Association between Latent Class
Membership and External Variables Using Bias- adjusted Three- step Approaches. Sociol
Methodol 2013;43:272–311.
29 Vignoles VL, Owe E, Becker M, etal. Beyond the “east- west” dichotomy: Global
variation in cultural models of selfhood. J Exp Psychol Gen 2016;145:966–1000.
30 Eng T, Kuiken D, Temme K, etal. Navigating the Emotional Complexities of Two
Cultures: Bicultural Competence, Feeling Expression, and Feeling Change in Dreams. J
Cult Evol Psychol 2005;3:267–85.
copyright. on September 19, 2024 by guest. Protected byhttp://mentalhealth.bmj.com/BMJ Ment Health: first published as 10.1136/bmjment-2024-301099 on 18 September 2024. Downloaded from
