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Background: Violent loss (i.e. loss through homicide, suicide, or accident) is associated with high levels of prolonged grief disorder (PGD). Objective: The current meta-analysis aims at identifying correlates of PGD in adults exposed to violent loss. Method: We conducted a systematic literature search in PsycINFO, PsycARTICLES, PubMed, Web of Science, and Scopus. We used the Pearson correlation coefficient r as an effect size measure and a random effects model was applied to calculate effect sizes. Results: Thirty-seven eligible studies published between 2003 and 2017 (N = 5911) revealed 29 potential correlates. Most studies used a cross-sectional design. Analyses revealed large significant effect sizes for comorbid psychopathology (r = .50–.59), suicidality (r = .41, 95% confidence interval [CI] [.30; .52]), and rumination (r = .42, 95% CI [.31; .52]), while medium effect sizes were found for exposure to traumatic events and factors concerning the relationship to the deceased. Small effect sizes emerged for sociodemographic characteristics, multiple loss, physical symptoms, and religious beliefs. Ten variables did not show a significant association with PGD. Heterogeneity and a small number of studies assessing certain correlates were observed. Conclusions: The associations with psychological disorders may indicate shared mechanisms of psychopathology. Moreover, we recommend that clinicians carefully assess suicidal ideation among individuals with PGD who have been exposed to violent loss. Further research is warranted using longitudinal study designs with large sample sizes to understand the relevance of these factors for the development of PGD.
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European Journal of Psychotraumatology
ISSN: 2000-8198 (Print) 2000-8066 (Online) Journal homepage:
A systematic review and meta-analysis of
correlates of prolonged grief disorder in adults
exposed to violent loss
Carina Heeke, Christina Kampisiou, Helen Niemeyer & Christine
To cite this article: Carina Heeke, Christina Kampisiou, Helen Niemeyer & Christine Knaevelsrud
(2019) A systematic review and meta-analysis of correlates of prolonged grief disorder in
adults exposed to violent loss, European Journal of Psychotraumatology, 10:1, 1583524, DOI:
To link to this article:
© 2019 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Published online: 27 Mar 2019.
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A systematic review and meta-analysis of correlates of prolonged grief
disorder in adults exposed to violent loss
Carina Heeke
, Christina Kampisiou
, Helen Niemeyer
and Christine Knaevelsrud
Department of Clinical-Psychological Intervention, Freie Universität Berlin, Berlin, Germany;
Research Department, Center Überleben
gGmbH, Berlin, Germany
Background: Violent loss (i.e. loss through homicide, suicide, or accident) is associated with
high levels of prolonged grief disorder (PGD).
Objective: The current meta-analysis aims at identifying correlates of PGD in adults exposed
to violent loss.
Method: We conducted a systematic literature search in PsycINFO, PsycARTICLES, PubMed,
Web of Science, and Scopus. We used the Pearson correlation coefficient ras an effect size
measure and a random effects model was applied to calculate effect sizes.
Results: Thirty-seven eligible studies published between 2003 and 2017 (N= 5911) revealed
29 potential correlates. Most studies used a cross-sectional design. Analyses revealed large
significant effect sizes for comorbid psychopathology (r= .50.59), suicidality (r= .41, 95%
confidence interval [CI] [.30; .52]), and rumination (r= .42, 95% CI [.31; .52]), while medium
effect sizes were found for exposure to traumatic events and factors concerning the
relationship to the deceased. Small effect sizes emerged for sociodemographic character-
istics, multiple loss, physical symptoms, and religious beliefs. Ten variables did not show a
significant association with PGD. Heterogeneity and a small number of studies assessing
certain correlates were observed.
Conclusions: The associations with psychological disorders may indicate shared mechan-
isms of psychopathology. Moreover, we recommend that clinicians carefully assess suicidal
ideation among individuals with PGD who have been exposed to violent loss. Further
research is warranted using longitudinal study designs with large sample sizes to under-
stand the relevance of these factors for the development of PGD.
Una revisión sistemática y metanálisis de los correlatos de duelo
prolongado en adultos expuestos a pérdidas violentas
Antecedentes y objetivos: La pérdida violenta (ej. pérdida por homicidio, suicidio, acci-
dente) está asociada con niveles elevados de trastorno por duelo prolongado (PGD, por sus
siglas en inglés). El objetivo del metanálisis actual es identificar los correlatos del PGD en
adultos expuestos a pérdidas violentas.
Método: Condujimos una búsqueda sistemática de literatura en PsycINFO, PsycARTICLES,
PubMed, Web of Science y Scopus. Usamos el coeficiente rde correlación de Pearson como
medición del tamaño del efecto de la muestra y se aplicó el modelo de efectos aleatorios
(REM) para calcular los tamaños del efecto.
Resultados: Treinta y siete estudios elegibles publicados entre el año 2003 y 2017 (N=5911)
revelaron 29 correlatos potenciales. La mayoría de los estudios usaron un diseño transversal.
Los análisis revelaron tamaños del efecto significativamente grandes para comorbilidad
psicopatológica (r= .50-.59), suicidalidad (r=. 41, 95% IC[.30; .52]) y rumiación (r=.42, [.31;
.52]), mientras que los tamaños del efecto medianos fueron encontrados para exposición a
eventos traumáticos y factores concernientes a la relación del deceso. Los tamaños del
efecto pequeños emergieron en las características sociodemográficas, pérdidas múltiples,
síntomas físicos y creencias religiosas. Díez variables no mostraron una asociación significa-
tiva con PGD. Se observó heterogeneidad y un número pequeño de estudios que evalúan
ciertos correlatos.
Conclusiones: Las asociaciones con trastornos psicológicos podrían indicar mecanismos
compartidos de psicopatología. Además, recomendamos que los clínicos evalúen cuidado-
samente la ideación suicida entre los individuos con PGD que han estado expuestos a
pérdidas violentas. Son necesarias investigaciones futuras usando diseños de estudio long-
itudinales con muestras de tamaño grandes para comprender la relevancia de estos factores
para el desarrollo del PGD.
Received 30 August 2018
Revised 24 January 2019
Accepted 6 February 2019
Prolonged grief disorder;
correlates; persistent
complex bereavement
disorder; meta-analysis;
violent loss; bereavement
trastorno de duelo
prolongado; correlatos;
trastorno de duelo complejo
persistente; metanálisis;
pérdida violenta; duelo
The first systematic review
of correlates of PGD in
survivors of violent loss.
The systematic literature
search identified 37 studies
and revealed 29 correlates.
Large effect sizes were
found for comorbid
psychopathology, suicidality
and rumination.
Results are relevant in the
light of the inclusion of PGD
in the forthcoming ICD-11.
CONTACT Carina Heeke Department of Clinical-Psychological Intervention, Freie Universität Berlin, Habelschwerdter
Allee 45, Berlin 14195, Germany
2019, VOL. 10, 1583524
© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (,
which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
PsycINFOPsycARTICLESPubMedWeb of ScienceScopus
2003201737N= 591129
大多使设计r = .50 - .59),r
= .41,95CI [.30; .52]r = .42[.31; .52]
1. Introduction
Violent loss has been defined as the loss of a sig-
nificant other through homicide, suicide, or acci-
dent, and also includes deaths due to natural
disasters, terrorism, or warfare (Rynearson, 2006).
Violent death is often perceived as preventable, and
may impede the survivorssearch for reasons and
meaning, or induce them to assign blame to others
or themselves (Rynearson, 2006). Individuals
exposed to violent loss often perceive lack of recog-
nition or stigmatizing social attitudes, which may
aggravate the process of adjustment (Feigelman,
Gorman, & Jordan, 2009). Grieving a violent
death may therefore be different from grieving a
non-violent death, and evidence indicates that los-
ing someone by violent means is associated with a
greater risk of developing adverse mental health
outcomes, in particular prolonged grief disorder
(PGD) (Burke & Neimeyer, 2013;Schaal,Jacob,
Dusingizemungu, & Elbert, 2010).
PGD has been defined as a maladaptive reaction to
the loss of a significant other. It is marked by persis-
tent separation distress and is combined with cogni-
tive, emotional and behavioural symptoms (e.g.
difficulty accepting death, sadness, guilt) resulting in
functional impairment for at least 6 months following
loss (Prigerson et al., 2009; WHO, 2018). PGD was
not included as distinct clinical entity in the
Diagnostic and Statistical Manual of Mental
Disorders, Fifth Edition (DSM-5). Instead, it was
included as persistent complex bereavement disor-
der, as a condition for further study (American
Psychiatric Association, 2013). The International
Classification of Diseases, 11th revision (ICD-11),
on the other hand, included PGD as clinical disorder
in June 2018 (Maercker et al., 2013; WHO, 2018). A
recent meta-analysis including 14 population-based
studies found a PGD prevalence rate of 9.8% among
adults exposed to non-violent bereavement
(Lundorff, Holmgren, Zachariae, Farver-Vestergaard,
&OConnor, 2017). Evidence suggests higher PGD
prevalence rates among those exposed to violent loss
compared to those exposed to non-violent loss
(Currier, Holland, Coleman, & Neimeyer, 2008;
Schaal et al., 2010), yet no meta-analysis exists that
measures this rate.
Two previous non-systematic literature reviews
provide an overview of potentially relevant factors
associated with PGD among adults exposed to violent
loss (Hibberd, Elwood, & Galovski, 2010; Kristensen,
Weisaeth, & Heir, 2012). The authors identified
female gender, a close relationship to the deceased,
multiple loss, self-blame, social support, and waiting
for death confirmation as risk factors and correlates
for PGD.
1.1. Previous research on risk factors and
correlates of PGD
Based on the literature among survivors of violent
loss, we will give an overview of potentially relevant
risk factors and correlates for PGD. Findings on the
association of gender with PGD have been mixed:
while some studies found women to be at higher
risk of PGD (Morina, Rudari, Bleichhardt, &
Prigerson, 2010; Neria et al., 2007), others did not
find an association when other trauma- and loss-
related variables were statistically controlled for
(Schaal et al., 2010; Stammel et al., 2013). Some
studies showed that a higher educational level was
associated with lower PGD severity (Dyregrov,
Nordanger, & Dyregrov, 2003; Neria et al., 2007).
Several studies in survivors of violent loss indicate
that grief symptoms decrease as time goes by (Heeke,
Stammel, & Knaevelsrud, 2015; Schaal et al., 2010).
Loss of a closely related family member was asso-
ciated with more severe grief reactions than the loss
of a distantly related family member, indicating that
the emergence of PGD is associated with the relation-
ship to the person lost (Neria et al., 2007; Stammel et
al., 2013). Multiple loss is frequent in contexts of war,
terrorism, or accidents, and has been linked to more
severe grief in some studies (Mercer & Evans, 2006;
Stammel et al., 2013).
Violent death may evoke visual images of the
deceaseds final minutes, and cognitions about what
he or she must have gone through (Baddeley et al.,
2015; Smid et al., 2015). Survivors may subsequently
engage in avoidance of these intrusive images. Several
authors report high comorbidities with post-trau-
matic stress disorder (PTSD) (Morina, von Lersner,
& Prigerson, 2011; Schaal, Dusingizemungu, Jacob,
Neuner, & Elbert, 2012). Depression and anxiety
have likewise been considered as comorbid with
PGD (Morina, 2011; Neria et al., 2007).
In line with cognitive theories of grief, several
studies investigated the impact of cognitive inter-
pretations of the loss on PGD outcomes and found
global negative beliefs and negative assumptive
worldviews to be associated with PGD (Boelen,
de Keijser, & Smid, 2015; Mancini, Prati, &
Black, 2011). This suggests that the subjective
interpretation of the loss may play a role in the
development of PGD. Rumination has been
defined as repetitive thinking about negative emo-
tions and a focus on their causes, meanings, and
consequences (Nolen-Hoeksema, 1991). Anecdotal
evidence from grief-related case studies indicates
that survivors of violent loss may be more likely to
engage in ruminative thoughts about the decea-
seds death or what the survivor could have done
to prevent this from happening (Higson-Smith,
2014;Smidetal.,2015; Wagner, Knaevelsrud, &
Maercker, 2005). Morina (2011) furthermore
reported an association between rumination
and PGD.
Research suggests that a greater extent of social
support may function as a protective factor against
the development of PGD (Burke, Neimeyer, &
McDevitt-Murphy, 2010; Hibberd et al., 2010).
However, survivors also report stigma and insensitive
reactions pointing to a potentially harmful social
environment (Feigelman et al., 2009; Peters,
Cunningham, Murphy, & Jackson, 2016).
1.2. Objectives
To date, researchers and clinicians have relied on
individual study findings to describe the association
of a variable with PGD. To obtain an overview of the
diverse studies published in the field, a synthesis of
the evidence has an advantage over interpreting sin-
gle-study results owing to increased statistical power
and precision (Borenstein, Hedges, Higgins, &
Rothstein, 2009). Meta-analyses have been referred
to as the gold standardfor synthesizing and sum-
marizing individual study results (Head, Holman,
Lanfear, Kahn, & Jennions, 2015).
The primary aim of the present study is to identify
potential correlates for PGD after violent loss through
a systematic review. Secondly, we aim to quantify the
magnitude of the relationship between potential cor-
relates and PGD through a meta-analysis. Thirdly, we
evaluate the quality of included studies.
2. Method
The systematic review and meta-analysis were con-
ducted in accordance with recommendations from
the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) statement
(Moher, Liberati, Tetzlaff, Altman, & The Prisma
Group, 2009). The protocol was pre-registered in
PROSPERO in November 2016 (registration no.
2.1. Inclusion criteria
We included quantitative studies that investigate cor-
relates for PGD in adults (18 years) who had lost a
significant other to violent death. From studies that
included both violent and non-violent loss, only those
in which at least 70% of the participants had lost a
significant other to violent loss were included.
Correlates were defined as any variable that contrib-
uted to variability in prolonged grief in terms of
symptom severity or diagnostic status. We focused
our analysis on validated instruments that specifically
assessed complicated or prolonged grief reactions,
rather than general extent of grief (Tomita &
Kitamura, 2002). We provide a list of included and
excluded PGD instruments in Appendix A. Except
for standard sociodemographic data, we excluded
those factors from our analysis that were only
assessed with qualitative interviews, non-validated
questionnaires, or single-item questions. We
excluded articles if they met any of the following
studies focusing on conditions other than PGD
[e.g. bereavement-related depression, major
depressive disorder (MDD), PTSD]
single-case and intervention studies
studies with professionals (e.g. nurses, firemen)
or patient samples
studies that recruited participants on the basis of
a specific comorbid psychiatric disorder (e.g.
MDD, PTSD) or physical condition (e.g. HIV/
AIDS, Alzheimers disease)
studies that included non-adult participants
(< 18 years) or unfitting types of loss (job loss,
pet loss) in the same comparison group as adults
who experienced violent loss
studies that did not provide sufficient data to
calculate effect sizes.
Since PGD instruments apply diverse time criteria
(e.g. 2, 6, and 14 months) (Bui et al., 2015; Horowitz
et al., 1997; Prigerson et al., 2009,1999), we did not
specify exclusion criteria for time since loss.
However, owing to the importance of the 6 month
time criterion for the PGD conceptualization in ICD-
11, we carried out sensitivity analyses which included
only those studies that apply the 6 month criterion to
measure the robustness of the effect sizes. Results can
be accessed in Appendix B.
2.2. Identification and selection of studies
Journal articles, books, book chapters, and dissertations,
published and unpublished, in the English or German
language between 1980 and 31 December 2017 were
considered for inclusion. We originally searched data-
bases until August 2016, but repeated the search in
December 2017 to look for new articles that had been
published in the meantime. The following databases
were searched: PsycINFO, PsycARTICLES, PubMed,
Web of Science, and Scopus. Search terms for the data-
bases were: prolonged grief,traumatic grief,complicated
grief,pathological grief,persistent complex bereavement
disorder OR (grief AND (risk OR predict*ORpredis-
position)). In addition, a snowball search system was
employed to identify relevant studies by manually
searching reference lists of initially included articles
(Lipsey & Wilson, 2001). Our search strategy resembles
the PICOS (population, intervention/exposure, com-
parator, outcome, study design) approach (World
Health Organization, 2014) and is therefore presented
in Appendix C in terms of the PICOS system as well.
2.3. Screening procedure
Two authors (CH, CKa) decided on the inclusion or
exclusion of each study. In case of disagreement,
consensus was reached by discussion. We screened
25% of the full texts independently, chosen based on
computerized randomization. Interrater reliability
was calculated using Cohens kappa for categorical
variables (Orwin, 1994).
2.4. Coding and data extraction
Manuscripts reporting analyses from the same data
set were included if they reported effect size estimates
for different correlates. If a correlate was repeatedly
reported in different studies on the basis of the same
or an overlapping data set, we used the article with
the largest sample size or the most comprehensive
article (Borenstein et al., 2009). If estimates of sub-
scales and the whole scale were reported, only the
association of the overall score with PGD was used.
Meta-analyses were conducted for those correlates
that were measured in at least two studies. Where a
study reported both continuous (symptom severity)
and categorical (diagnosis) estimates of a correlate,
we used the effect size for PGD symptom severity
because of the statistical advantages of continuously
measured variables (Borenstein et al., 2009). In case
of longitudinal data, we used the data that were
closest to the 6 month criterion for PGD.
2.5. Effect size calculation
Pearsonscorrelation coefficient rwas used as a mea-
sure of effect size (Borenstein et al., 2009). Effect sizes
of .1 r< .25 are considered as small, .25 r<.4as
medium, and r.4 as large (Cohen, 1988).
2.6. Meta-analytical procedure
A random effects model (REM) was used to calculate
effect sizes. The assumption for the REM is that the
true effects differ between sample groups in different
studies, and differences in effect size may not only be
attributed to random error inherent in each study
(Borenstein et al., 2009). To identify and quantify
this heterogeneity, we used the Q-statistic and the I
index (Borenstein et al., 2009; Crombie and Davies,
2009). Qdetermines the conformity to the normal
distribution of effect sizes. A significant value
(p< .05) indicates heterogeneity. I
is an estimate of
the ratio of true heterogeneity in the observed varia-
tion, with a score 25 indicating low heterogeneity,
50 moderate heterogeneity, and 75 high heteroge-
neity (Borenstein et al., 2009; Higgins & Thompson,
2002). Moderate to high levels of heterogeneity may
lead to difficulties in the interpretation of the mean
effect size, and possible moderators contributing to
the heterogeneity should be examined (Borenstein et
al., 2009; Higgins & Green, 2011). In cases of hetero-
geneity, subgroup analyses were performed. At least
10 studies should be available for each subgroup
analysis (Higgins & Green, 2011). All subgroup ana-
lyses were conducted using mixed effects analysis.
Subgroups were based on the quality of the study,
the type of loss studied, and the means of data assess-
ment (interview or questionnaire).
2.7. Quality assessment/risk of bias
Quality assessment was performed using an adjusted
list based on Standards for Reporting of Diagnostic
Accuracy Studies (STARD) (Bossuyt et al., 2015). To
increase the applicability of the tool to all types of
studies, items on the STARD list were selected on the
basis of recommendations from a review on tools for
quality assessment (Shamliyan, Kane, & Dickinson,
2010). Items were rated as high risk of bias
(score = 0), low risk of bias(score = 2), or unclear
(score = 1) (Higgins et al. (2011). An overall score of
< 10 indicated low quality, a score of 10 and < 13
indicated medium quality, and a score of 13 indi-
cated high quality. The individual item-based ratings
can be found in Appendix D. Two authors (CH, CKa)
independently rated the studies. In case of disagree-
ment, consensus was reached by discussion. The
interrater reliability was calculated using Cohens
kappa for categorical variables (Orwin, 1994).
2.8. Publication bias
Publication bias is defined as the selective publication
of studies with significant or positive results (Rothstein,
Sutton, & Borenstein, 2005).Itcanleadtoanover-
estimation of effects, because non-significant findings
are less likely to be published. The presence of publica-
tion bias was measured using Eggersregressiontest
(Egger, Smith, Schneider, & Minder, 1997). A signifi-
cant finding would indicate publication bias. Duval and
Tweedies(2000) trim-and-fill procedure computes the
number of presumably missing studies and produces
an effect size estimate that is corrected for bias. At least
six studies per correlate and a homogeneous data set
are required to measure publication bias (Sterne &
Egger, 2005). The difference between original and cor-
rected effect size was tested for significance by examin-
ing whether the original fell within the confidence
limits of the bias-corrected effect size estimate
(Niemeyer, Musch, & Pietrowsky, 2013).
All analyses were performed using the
Comprehensive Meta-Analysis software (Biostat, 2011).
3. Results
3.1. Description of the studies
Figure 1 displays the selection process and reasons for
study exclusion. Interrater reliability for the full-text
screening was substantial (κ= .76) (Landis & Koch,
1977). Thirty-seven studies fulfilled the inclusion cri-
teria. Twelve publications were based on overlapping
data sets associated with five individual studies. The
systematic review therefore comprised 30 original
studies. The 12 publications based on overlapping
data sets were still included because they reported
effect size estimates for different correlates. The 30
original data sets comprise a total sample size of
N= 5911 people (excluding control groups).
From the 30 original studies, n= 13 studies
(43.3%; n= 2245, 38.0% of total study participants)
referred to an individual homicide, suicide, or acci-
dent, whereas 17 studies (56.7%; n= 3666, 62% of
total study participants) were conducted with partici-
pants who had lost a significant other mainly due to
collective violence (war, terrorism, natural disaster,
collective accidents). Two studies only provided esti-
mates for correlates, which were not examined in any
other study (Kristensen, Tonnessen, Weisaeth, &
Heir, 2012; Neimeyer & Burke, 2011); hence, these
studies were not included in the quantitative synth-
esis. Characteristics of the studies included in the
meta-analysis are displayed in Table 1.
3.2. Quality assessment
Out of 37 studies, nine studies (24.3%) showed low
quality, 15 (40.5%) showed medium quality, and 13
(35.1%) showed high quality (Table 1). The majority
of all studies stated research questions, eligibility cri-
teria, source of the recruited sample, basic sociode-
mographic/clinical characteristics, and study
limitations. However, several of the low- and med-
ium-quality studies did not clearly state the setting of
data assessment, did not specify how missing data
were handled, or did not perform a power calcula-
tion. Only seven studies used random sampling or
approached the entire population. The individual
item-based ratings are presented in Appendix D.
The interrater reliability was high (κ= .84) (Landis
and Koch (1977).
3.3. Correlate effect size estimates
The main results of the meta-analyses for each corre-
late are displayed in Table 2. Twenty-nine correlates
were examined by at least two studies across the 37
studies published between 2003 and 2017. Only five
correlates (17.2%) were examined in more than 10
studies, demonstrating that only a limited number of
variables is routinely assessed. Altogether, 19 correlates
showed significant associations with PGD. Four socio-
demographic variables showed a small association with
PGD (gender, education, employment, having another
child born after a loss, or having remaining children).
Four sociodemographic variables did not show an
association with PGD (marital status, ethnicity, age,
and income). Heterogeneity was a minor problem
among sociodemographic characteristics and age was
the only correlate to display significant heterogeneity.
Among factors associated with the death and the
deceased, only the relationship to the deceased showed
a significant association with PGD (r= .38; 95% con-
fidence interval [CI] [.23; .53]): having lost a closely
related person (partner, parent, child, or sibling) was
associated with more severe PGD compared to having
lost a distantly related person. For time since loss, the
combined effect size of seven studies did not reach
significance (r=.15; 95% CI [.30; .01]). The studies
showed considerable heterogeneity. However, the
small number of studies did not allow for subgroup
All health-related characteristics were significantly
associated with PGD. Physical/somatic symptoms
showed a medium-sized association with PGD
(r= .23, 95% CI [.12; .34]) based on three studies. All
other health-related characteristics (e.g. depression or
PTSD) showed high associations with PGD (r> .40).
Three factors concerning how bereaved individuals
relate to others were identified in the included stu-
dies: attachment anxiety, attachment avoidance, and
social support. Only attachment anxiety was signifi-
cantly related to PGD (r= .33, 95% CI [.15; .50]).
Regarding cognitive characteristics, only rumination
was measured more than once across the included
studies, and showed a large association with PGD
(r= .42, 95% CI [.31; .52]).
Multiple loss and the presence of religious beliefs
showed small positive associations with PGD (r= .11,
95% CI [.04; .18]; r= .12, 95% CI [.01; .23], respec-
tively). Based on five studies, the exposure to
Figure 1. Flowchart of study identification and selection. [PRISMA 2009 flow diagram (Moher et al., 2009).]
Table 1. Characteristics of studies included in the systematic review.
Location of data
assessment Loss type Sample type NPG measure
Age (years), mean
or range
Time since loss (years or months),
mean or range
Anderson (2010) USA Suicide Individual 201 ICG 48.89 90.5 5.51 (6484 m) H
Aronson et al. (2017) USA Suicide 24.3%; accidents 27.1%; combat 48.6% Individual 70 ICG-R 52.90 100.0 4.00 y M
Burke et al. (2010)
USA Homicide Individual 54 ICG-R 48.61 88.9 1.75 y M
Capitano (2013) USA Suicide Individual 219 ICG 3140 y: 3.7%;
4150 y: 32.4%;
5160 y: 44.7%;
6170 y: 12.8%;
71 y: 5.9%
91.3 612 m: 6.4%;
1336 m: 34.7%;
3760 m: 20.1%;
61120 m or longer: 8.7%;
missing: 30.1%
Craig et al. (2008) USA (with Bosnian
Primarily war-related atrocities; some by natural
War-related loss/collective 126 ICG 42.00 56.0 Data collection 10 y post-war M
Currier et al. (2015) USA Accidents 58.9%; homicide 18.8%; suicide 22.3% Individual 195 ICG-R 21.00 80.0 Max. 2 y post-loss L
Dyregrov et al. (2015)
Norway Utøya terror attack Terrorism/collective 67 ICG 3978 55.0 1.5 y M
Dyregrov et al. (2003)
Norway Suicide 65.3%; accident 34.7% Individual 196 ICG NR 59.9 623 m M
Feigelman et al. (2008) USA Suicide 86%; accidents 8%; natural death 4%;
homicide 0.8%; other 0.9%
Individual 540 CG-Assessment NR 85.0 NR L
Field et al. (2014)
Cambodia 50% died in stampede Collective accident/
159 PG-13 49.29 100.0 6 m (for stampede group) M
Harris (2016) USA Suicide Individual 94 ICG 49.97 100.0 NR H
Heeke et al. (2015) Colombia Survivors of armed conflict War-related loss/collective 222 PG-13 48.70 59.0 12.12 y M
Hu et al. (2015) China Wenchuan earthquake Natural disaster/collective 271 ICG 44.87 54.6 Data collection 18 m after
Huh et al. (2017) South Korea Sewol ferry accident Collective accident/
84 ICG 47.40 57.0 1.5 y M
Kristensen et al. (2010)
Norway Tsunami in Southeast Asia Natural disaster/collective 130 ICG 45.70 51.5 2.2 y H
Kristensen et al. (2012)
Norway Tsunami in Southeast Asia Natural disaster/collective 130 ICG 45.70 51.5 2.2 y H
McDevitt-Murphy et al.
USA Homicide Individual 54 ICG-R 48.61 88.9 1.74 (29 days 58.30 m) M
Mitchell et al. (2017)
USA Suicide Individual 60 ICG 43.30 72.0 1 m L
Mitchell et al. (2004)
USA Suicide Individual 60 ICG 43.30 72.0 1 m L
Moore (2013) USA Suicide Individual 154 PG-13 NR 90.1 Max. 2 y H
Morina (2011) Kosovo War-related killings War-related loss/collective 100 Prolonged Grief
Disorder interview
50.10 100.0 Data collection 10 y post-war M
Morina et al. (2010) Kosovo War-related killings War-related loss/collective 60 ICG-R 40.60 33.3 78y L
Morina et al. (2011) Kosovo War-related killings War-related loss/collective 179 PG-13 20.30 58.1 Data collection 10 y post-war H
Mutabaruka et al.
Rwanda War-related killings War-related loss/collective 102 Inventory of Traumatic
45.00 68.6 Data collection 13 y post-
Neimeyer and Burke
USA Homicide Civilian/individual 46 ICG-R 50.23 89.1 1.63 y (1.158.3 (m) L
Neria et al. (2007) USA 9/11 terror attacks Terrorism/collective 704 CG-Assessment 45.13 79.0 2.53.5 y M
Rheingold and Williams
USA Homicide Individual 47 ICG 50.84 78.7 2.08 y M
Schaal et al. (2012)
Rwanda Genocide 62%; illness 27.5%; accident 3%;
other (mainly poisoning) 7.5%
War-related loss/collective 400 PG-13 37.18 87.7 11.50 y (138 y) H
Schaal et al. (2009) Rwanda War-related killings War-related loss/collective 40 PG-13 49.93 100.0 Data collection 13 y post-
Schaal et al. (2010)
Rwanda Genocide 62%; illness 27.5%; accident 3%; other
(mainly poisoning) 7.5%
War-related loss/collective 400 PG-13 37.18 87.7 11.50 y (138 y) H
(Continued )
traumatic events had a medium-sized association
with PGD (r= .27, 95% CI [.06; .45]).
Significant heterogeneity was observed in 12 corre-
lates (age, traumatic events, relationship to the
deceased, time since loss, depression, PTSD, anxiety,
global psychopathology, avoidance, social support,
attachment avoidance, and counselling experience).
Thus, at least some of the variance was due to true
differences between the study effects (Bienvenu et al.,
2004; Costa, Terracciano, & McCrae, 2001; Craske,
2003). To determine potential moderators of heteroge-
neity, we subsequently performed subgroup analyses.
3.4. Subgroup analyses
Subgroups were based on quality of study, type of loss
(individual or collective incident), and, if available,
means of data assessment (interview or question-
naire). Subgroup analyses were performed for the
three correlates that were examined by at least 10
studies and which had a heterogeneous data set
(age, depression, and PTSD).
Subgroup analyses for age revealed that among
people who had lost a significant other to an indi-
vidual incident (homicide, suicide, or accident), age
emerged as a significant correlate, with younger age
being associated with less PGD (r=.28, 95% CI
[43; .11]). By contrast, age was not a significant
correlate among people bereaved by collective vio-
lence (r=.02, 95% CI [.07; .11]). In both sub-
groups, heterogeneity was high. For the remaining
correlates, PTSD and depression, the interview mea-
sure, the type of loss, and the quality of the studies
did not have an impact on effect sizes or heteroge-
neity. Results of the subgroup analyses are displayed
in Table 3.
3.5. Publication bias
Publication bias analyses were applicable for four
correlates (gender, education, employment, and mar-
ital status) (Table 2). Eggers regression test was not
significant for any of the data sets and did therefore
not indicate publication bias. The trim-and-fill pro-
cedure imputed one study each into the subgroups
according to gender and education, but corrected
effect sizes did not significantly differ from original
effect sizes (Table 2).
4. Discussion
This study aimed at identifying correlates for PGD
among adults who had experienced violent loss. We
furthermore aimed to quantify the magnitude of the
relationship between correlates and PGD in a meta-
analysis. Sociodemographic characteristics (female
gender, low educational level, no employment, and
Table 1. (Continued).
Location of data
assessment Loss type Sample type NPG measure
Age (years), mean
or range
Time since loss (years or months),
mean or range
Stammel et al. (2013) Cambodia War-related killings War-related loss/collective 775 CG-Assessment 56.70 64.3 Data collection 30 y post-
Tolstikova et al. (2005) Canada/USA Motor vehicle accident 86% Individual 84 ICG 49.70 86.0 6.20 y (6 m 38 y) L
van Denderen et al.
Netherlands Homicide Individual 331 ICG 52.60 65.9 6.90 y H
Wagø et al. (2017)
Norway Utøya terror attack Terrorism/collective 67 ICG 3978 55.0 1.5 y H
Weder et al. (2010) Palestine (West
War-related killings War-related loss/collective 21 PG-13 44.87 52.4 15.00 y L
Williams et al. (2012)
USA Homicide Individual 47 ICG-R 49.66 89.4 1.74 y M
Xu et al. (2014) China Sichuan earthquake Natural disaster/collective 226 ICG 2745 100.0 2.412.83 y H
The sudden infant death syndromegroup in this study was excluded from this meta-analysis.
Repeated communication with study authors could not unequivocally clarify whether participants in the control group were bereaved by
violent loss, but all had experienced the Khmer Rouge regime (19751979). Sensitivity analysis without this study can be accessed in Appendix E.
Personal communication with author.
Data stem from the same study,
respectively, but provided different risk factor estimates. Overall study quality rating: L, low quality; M, medium quality; H, high quality.
PG, prolonged grief; ICG, Inventory of Complicated Grief; ICG-R, Inventory of Complicated Grief Revised; CG, complicated grief; y, years; m, months; NR, not reported.
having no other child after the loss of a child) showed
small associations with PGD, while large associations
were found for comorbid psychopathology and
rumination. We found small associations for multiple
loss, religious beliefs, and somatic/physical symp-
toms. Three correlates (traumatic events, attachment
Table 2. Meta-analyses of individual correlates.
95% CI of r
kN r
limit p-value r
[95% CI] Q
Sociodemographic characteristics
Female gender 14 2885 .20 .14 .25 < .001 .18 [.12; .23] 16.66 .06 40.61
Age 14 2971 .10 .20 .01 .07 85.44 < .001 84.79
Education 12 2769 .10 .14 .06 < .001 .11 [.15; .07] 8.47 .67 0.00
Employment: being employed 7 1127 .14 .21 .08 < .001 .14 [.21; .08] 4.68 .70 0.00
Marital status: being in a relationship or married 7 1479 .05 .11 .01 .09 .05 [.11; .01] 6.72 .35 10.69
Income 4 821 .09 .21 .03 .15 4.87 .18 38.36
Race/ethnicity: being white 2 740 .05 .13 .03 .24 0.001 .97 0.00
Having another child/other children left 5 602 .23 .36 .10 < .001 8.50 .08 52.96
Characteristics associated with death and the deceased
Relationship to the deceased: closely related (vs
distantly related)
4 1701 .39 .23 .53 < .001 33.00 < .001 90.91
Time since loss 7 913 .15 .30 .01 .07 29.52 < .001 79.68
Mode of death: suicide (vs accident) 3 716 .00 .10 .09 .94 2.64 .27 24.36
Age of deceased person 3 .10 .24 .04 .17 3.75 .15 46.71
Health-related characteristics
Depression 15 3139 .59 .52 .65 < .001 83.33 < .001 83.20
Post-traumatic stress disorder 13 3259 .59 .50 .67 < .001 113.02 < .001 89.38
Anxiety 8 2457 .52 .44 .59 < .001 29.27 < .001 76.08
Health conditions (physical/somatic symptoms) 3 496 .23 .12 .34 < .001 3.02 .22 33.77
Global psychopathology 3 327 .50 .28 .67 < .001 8.25 < .01 76.62
Suicidality 3 923 .41 .30 .52 < .001 2.50 .27 24.27
Avoidance 2 137 .54 .24 .74 < .001 4.46 < .05 77.57
Intrusion 2 137 .62 .43 .76 < .001 2.68 .10 62.66
Anger 2 278 .47 .36 .58 < .001 1.29 .26 22.53
Interpersonal characteristics
Social support 5 495 .02 .38 .34 .92 60.93 < .001 93.44
Personality characteristics
Attachment avoidance 2 396 .08 .09 .24 .38 2.86 .09 65.08
Attachment anxiety 2 396 .33 .15 .50 .001 4.01 < .05 75.09
Cognitive characteristics
Rumination 2 252 .42 .31 .52 < .001 0.64 .43 0.00
Multiple loss 5 1440 .11 .04 .18 < .01 6.00 .20 33.32
Traumatic events 5 1327 .27 .06 .45 .01 43.56 < .001 90.82
Counselling experience 2 975 .00 .27 .27 .99 14.01 < .001 92.86
Religiosity: having religious beliefs 2 292 .12 .01 .23 < .05 0.29 .59 0.00
k,number of studies; N, sample size per risk factor estimate; r, Pearsonsr;r
, Pearsonsrcorrected for publication bias; Q,Q-statistic for heterogeneity;
, ratio of true heterogeneity in the observed variation; CI, confidence interval.
Table 3. Subgroup analyses based on assessment type, type of loss and study quality.
Correlate Subgroup kr[95% CI]
Q, significance of Q,I
Comparison (p-value)
Depression Assessment Questionnaire 12 .60 [.52; .66]*** Q= 59.18, p< .001, I
= 81.41 p= .99
Interview 3 .59 [.19; .82]*** Q= 21.20, p< .001, I
= 90.57
Type of loss Individual 4 .69 [.53; .81]*** Q= 12.75, p< .001, I
= 76.46 p= .12
Collective 11 .55 [.49; .62]*** Q= 53.50, p< .01, I
= 81.31
Quality Low 3 .50 [.15; .74]*** Q= 16.92, p< .001, I
= 88.18 p= .74
Medium 8 .60 [.51; .68]*** Q= 26.27, p< .001, I
= 73.36
High 4 .62 [.47; .73]*** Q= 34.59, p< .001, I
= 91.33
PTSD Assessment Questionnaire 12 .62 [.54; .68]*** Q= 81.50, p< .001, I
= 86.50 NA
Interview 1 .24 [.07; .39]** NA
Type of loss Individual 3 .64 [.44; .78]*** Q= 9.66, p< .01, I
= 79.29 p= .52
Collective 10 .58 [.47; .66]*** Q= 95.53, p< .001, I
= 90.58
Quality Low 2 .42 [.04; .74] Q= 8.00, p< .001, I
= 87.50 p= .59
Medium 7 .62 [.50; .72]*** Q= 44.40, p< .001, I
= 86.49
High 4 .59 [.43; .72]*** Q= 55.20, p< .001, I
= 94.57
Age Type of loss Individual 6 .28 [.43; .11]** Q= 21.16, p< .01, I
= 76.36 p< .01
Collective 8 .02 [.07; .11] Q= 28.49, p< .001, I
= 75.43
Quality Low 1 .00 [.25; .25] NA p= .42
Medium 9 .04 [.15; .07] Q= 34.23, p< .001, I
= 76.63
High 4 .19 [.50; .17] Q= 48.86, p< .001, I
= 93.86
Analyses based on random effects model.
Analyses based on mixed effects analyses. **p< .01, ***p< .001.
k, number of studies; r, Pearsonsr;Q,Q-statistic for heterogeneity; I
, ratio of true heterogeneity in the observed variation; PTSD, post-traumatic stress
disorder; NA, not applicable.
anxiety, and relationship to the deceased) showed
medium-sized associations. Twelve correlates dis-
played significant heterogeneity, which limits the
interpretability of mean effect sizes. It was not possi-
ble to identify moderators that may have caused
heterogeneity. The analysis did not indicate publica-
tion bias.
We evaluated the study quality. Fifteen studies
were classified as being of medium quality, while
nine studies were of low quality and 13 showed
high quality. The most common flaws were non-
randomized selection of participants and imprecise
reporting of data analyses.
4.1. Sociodemographic characteristics
The meta-analysis showed a small positive association
of female gender with PGD. A number of factors may
account for this finding. Women score higher than
men on personality traits (e.g. neuroticism, openness
to feelings) associated with the development of
adverse mental health outcomes. They are more likely
to respond to stressful life events with anxiety and
avoidant behaviour (Bienvenu et al., 2004; Costa et
al., 2001; Craske, 2003). As such, women are at
greater risk than men of developing mental health
problems (Olff, Langeland, Draijer, & Gersons, 2007;
Tolin & Foa, 2006). However, the proportion of
females in the included studies was high. This may
lead to an overrepresentation of symptoms that are
more likely to be endorsed by women. Moreover,
female participants already far outnumbered males
in the development of the assessment instruments
(Bui et al., 2015; Prigerson et al., 1995,2009), which
may have led to a greater attribution of relevance to
symptoms occurring in women in the scale develop-
ment. As social norms of masculinity discourage
emotional expression in men, they may grieve differ-
ently from women (Creighton, Oliffe, Butterwick, &
Saewyc, 2013), and this aspect clearly needs further
research. The overrepresentation of women in the
included studies and during the scale development
may have the consequence that the identified corre-
lates and respective associations with PGD are more
likely to be representative of women.
The meta-analysis further showed that age was largely
unrelated to PGD. However, the subgroup analyses
revealed that in studies conducted with people exposed
to an individual death (homicide, suicide, or accident),
age was significantly negatively related to PGD, whereas
it was not among those who had lost a significant other to
collective violence. This is somewhat in contrast to pre-
vious studies of non-violent loss that reported a positive
association of age and PGD (Kersting, Braehler,
Glaesmer, & Wagner, 2011;Lundorffetal.,2017). This
issue warrants further research taking into account the
specific role of the type of loss (individual vs collective).
The small effect of education and PGD is in line with
previous research, which demonstrated that a higher
educational level is associated with lower levels of psy-
chopathology (Ross & Mirowsky, 2006). Education facil-
itates reappraisal strategies and the pursuit of
fundamental goals, including emotional well-being
(Ross & Mirowsky, 2006). Education has an impact on
multiple outcomes, such as social status, employment,
and health behaviour. Hence, the small effect of employ-
ment on levels of PGD was unsurprising. We assume that
having regular tasks in life and a daily structure helps in
dealing with bereavement. Qualitative evidence suggests
that parenting may offer a distraction from grief and
provide a sense of meaning and purpose in life
(Chidley, Khademi, Meany, & Doucett, 2014), which
supports that having another child was negatively asso-
ciated with PGD.
4.2. Characteristics associated with the death
and the deceased
Time since loss was not significantly associated with
PGD. Grief may not decrease in cases of violent loss
as feelings of guilt, visual images of the death, or
difficulties in finding meaning may contribute to
persistent grief among survivors (Rynearson, 2006).
However, some included studies reported data on the
association of time since loss with PGD a few months
after loss, while others reported data on this associa-
tion several decades after loss. This may have con-
tributed to the observed heterogeneity. High levels of
heterogeneity may lead to difficulties in interpreting
the mean effect size. Once more studies have
addressed time since loss, future meta-analyses
should clarify the role of this variable for the devel-
opment of PGD.
In line with the idea that PGD is a disorder that is
associated with the relationship to the lost person, a
close relationship emerged as a significant correlate of
PGD. This indicates that losing a member of the
nuclear family is associated with higher PGD severity
than losing a distantly related family member or
friend. The observed heterogeneity was largely
accounted for by one study (Mitchell, Kim,
Prigerson, & Mortimer-Stephens, 2004), which may
have overestimated the effect.
4.3. Health-related characteristics
The largest effect sizes were found for health indica-
tors, in particular comorbid psychopathology. In line
with previous results, the largest associations were
found for depression and PTSD. Because other
health-related factors were similarly related to PGD,
we suspect a shared mechanism of psychopathology,
which may be triggered by a certain risk (e.g. the loss
of a significant other). The disorders share multiple
risk factors (e.g. female gender, educational level,
exposure to traumatic events) as well as certain symp-
toms (feelings of hopelessness, intrusions), which
increase the occurrence of comorbidities (Cole &
Dendukuri, 2003; Xue et al., 2015). Heterogeneity
was particularly present among health-related indica-
tors, indicating a large between-study variance of the
effect sizes. The heterogeneity could not be explained
by moderating variables.
The high association of intrusion with PGD may
be largely accounted for by the fact that intrusions are
part of the PGD criteria set in the form of separation
distress(Horowitz et al., 1997; Prigerson et al., 2009).
However, it also seems possible that a high associa-
tion of intrusion with PGD is specific to violent loss
survivors. Visual intrusions may be particularly dis-
ruptive in the case of violent losses, where mourners
are likely to imagine the deceaseds last minutes as
painful. Future research should investigate whether
the violent nature of someones death is more likely
to evoke intrusions.
PGD was highly associated with suicidality. This
bears important clinical implications. Clinicians
should therefore carefully assess suicidal ideation
among their bereaved patients.
4.4. Cognitive characteristics
Rumination was the only cognitive factor that had
been assessed more than once among the included
studies. Some bereaved individuals may engage in
continuous rumination about the deceaseds death
or about their own reactions to the death, thereby
increasing the attention to a negative emotional state
and inhibiting actions that might distract the indivi-
dual (Nolen-Hoeksema, 1991).
4.5. Interpersonal characteristics
Despite the social environmentsimportance for psy-
chopathology (Brewin, Andrews, & Valentine, 2000),
only a few studies have investigated social support.
The non-significant association between social sup-
port and PGD was mainly due to one study, which
found a positive correlation (Anderson, 2010), while
the other studies consistently found negative correla-
tions (Burke et al., 2010; Kristensen, Lars, & Heir,
2010; Rheingold & Williams, 2015; Wagø, Byrkjedal,
Sinnes, Hystad, & Dyregrov, 2017). It was not possi-
ble to conduct subgroup analyses, and it remains for
future research to investigate the link between social
support and PGD further.
4.6. Personality characteristics
Two studies analysed the relation between attachment
styles and PGD. Two dimensions of attachment are
proposed: attachment-related anxiety (predisposition
towards anxiety and vigilance concerning rejection and
abandonment) and attachment-related avoidance (dis-
comfort with closeness and dependency or a reluctance
to be intimate with others) (Sibley, Fischer, & Liu, 2005).
We found attachment-related avoidance to be unrelated
to PGD and attachment-related anxiety to be positively
associated with PGD. This is in line with prior theoretical
conceptualizations (Fraley & Bonanno, 2004).
4.7. Other factors
Traumatic events may heighten the vulnerability
not only to depression and PTSD (Steel et al.,
ium-sized association. Moreover, we found a small
effect for multiple loss, indicating that having lost
more than one significant other was associated with
higher PGD severity.
Religious beliefs showed a small positive associa-
tion with PGD, suggesting that the presence of reli-
gious beliefs was associated with higher PGD
severity. Schaal et al. (2010) found the opposite
effect but did not report bivariate associations.
Their effect size was therefore not included in the
meta-analysis. Neimeyer and Burke (2011)exam-
ined the association between religious coping and
PGD among survivors of violent loss and reported a
significant positive association between negative
religious coping (punishing God reappraisals) and
PGD severity, but found no effect for positive reli-
gious coping (a secure relationship with God).
Further analyses are needed to understand the role
of religiosity and religious coping for PGD.
4.8. Limitations
Despite the various strengths of the meta-analysis,
several limitations should be considered when inter-
preting the results. The included studies were mainly
based on non-randomly selected samples; most data
relied on self-report measures. These studies are
prone to sampling bias. Our stringent inclusion cri-
teria may have resulted in the exclusion of some
relevant articles. This strategy, however, increased
the comparability between included studies. The
agreement during the full-text screening was only
substantial. The cross-sectional design of most studies
does not allow us to draw conclusions about causal
relationships. Some of the examined risk factors are
invariant factors (gender, age of deceased and
bereaved person, ethnicity, mode of death, relation-
ship to the deceased, and time since loss) and causal
relations can be assumed. For the remaining vari-
ables, it remains unclear whether the factors identi-
fied as correlates are a cause or an effect of low or
high prolonged grief symptom severity. Meta-
analyses based on longitudinal studies would there-
fore be a desirable approach for future research to
clarify the relationship between these variables and
PGD. Our meta-analysis was limited by the hetero-
geneity of examined correlates. It was not possible to
identify moderators that caused heterogeneity.
Several variables included in this meta-analysis were
only measured twice, which significantly limits con-
clusions that can be drawn about these correlates.
Finally, in six of the studies, the majority of the
sample experienced violent loss, but not all. We
decided to include these studies if more than 70% of
the sample experienced violent loss, but we are aware
that the studies including mixed natures of death do
not capture as precisely the specific nature of violent
loss as studies including participants with violent loss
5. Conclusions
This is the first systematic review and meta-analysis
to report on correlates for PGD among adults
exposed to the violent loss of a significant other. As
a result of the systematic literature research based on
precise inclusion criteria and the respective effect
calculations, the meta-analysis extends the knowledge
beyond conclusions from narrative reviews.
Altogether, 19 correlates showed significant associa-
tions with PGD. Sociodemographic characteristics
showed small associations with PGD, while comorbid
psychopathology and rumination showed large asso-
ciations. Some of the sociodemographic and health-
related characteristics were investigated in several
studies and these effect calculations therefore have a
valid empirical basis.
The results demonstrate that the relevant corre-
lates stemmed from a wide range of domains, includ-
ing factors a person is equipped with (gender, age),
biographical factors (multiple loss, traumatic events),
intrapsychological factors (rumination, attachment
style), and factors concerning the relationship to the
person lost, to name a few. This points to a complex
interplay of factors that potentially contribute to the
development of the disorder. It seems likely that
comparable to established vulnerabilitystress models
for other disorders a set of diverse factors facilitates
the development of PGD (Ingram & Luxton, 2005;
Maccallum & Bryant, 2013). Some of these factors
may uniquely contribute to PGD (e.g. relationship
to the person lost), while others (e.g. gender, educa-
tion) may be shared contributors to general psycho-
pathology (Brewin et al., 2000; Cole & Dendukuri,
2003). Further research using longitudinal study
designs is required to establish the causal link
between these factors and PGD.
Furthermore, there is cumulative evidence that
several of the identified correlates are important not
only among violent loss survivors but also among
people exposed to non-violent loss. Future meta-ana-
lyses focusing on correlates and risk factors among
non-violently bereaved individuals may clarify the
specificity of certain variables according to the type
of loss. Future research could also focus on examin-
ing whether it is the kinship relationship with the
deceased, or rather the interpersonal quality of the
relationship (emotional closeness, depth, conflict),
which influences grief reactions. The present meta-
analysis highlights the need for further investigation
of specific grief-related risk factors. Some correlates
with preliminary evidence may turn out to be impor-
tant in the future.
In the light of the inclusion of PGD in the ICD-11,
it is important for clinicians to identify bereaved
adults at risk for PGD, particularly in subgroups of
survivors of violent loss, which have been shown to
be more likely to be affected by PGD. Suicidality may
be prevalent among individuals with PGD and clin-
icians should therefore carefully assess suicidal ten-
dencies among their bereaved patients.
Disclosure statement
No potential conflict of interest was reported by the
Carina Heeke
Christine Knaevelsrud
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Appendix A. Identified and selected grief assessment instruments.
Instrument Authors Year Subscales
items Focus
Bereavement Experience Questionnaire
Guarnaccia & Hayslip 1998 3: Existential loss/emotional needs; guilt/
blame/anger; preoccupation with thoughts
of deceased
24 General extent of grief
Bereavement Phenomenology
Byrne & Raphael 1994 22 General extent of grief: focus on male grief experience
Bereavement Risk Index Parkes 1993 8 Asks for general risk factors, such as demographic information, some
psychological symptoms (anger, social contacts)