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Remission from post-traumatic stress disorder in adults: A systematic review and meta-analysis of long term outcome studies

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Remission from post-traumatic stress disorder in adults: A systematic
review and meta-analysis of long term outcome studies
Nexhmedin Morina
a,
, Jelte M. Wicherts
b
, Jakob Lobbrecht
a
, Stefan Priebe
c
a
Department of Clinical Psychology, University of Amsterdam, Amsterdam, The Netherlands
b
Department of Methodology and Statistics, Tilburg University, The Netherlands
c
Unit for Social and Community Psychiatry, Queen Mary University of London, UK
HIGHLIGHTS
We conducted a meta-analysis on spontaneous long-term remission from PTSD.
Remission was dened as reporting PTSD at baseline and not after at least ten months.
42 studies and 81,642 participants were included.
Overall, 44.0% of participants remitted from PTSD after a mean of 40 months.
abstractarticle info
Article history:
Received 16 November 2013
Received in revised form 7 February 2014
Accepted 7 March 2014
Available online 14 March 2014
Keywords:
Post-traumatic stress disorder
Prospective studies
Meta-analysis
Posttraumatic stress disorder (PTSD) is a frequent mental disorder associated with signicant distress and high
costs. We conducted the rst systematic review and meta-analysis on spontaneous long-term remission rates,
i. e., without specic treatment. Data sources were searches of databases, hand searches, and contact with
authors. Remission estimates were obtained from observational prospective studies of PTSD without specic
treatment. Remission was dened as the actual percentage of PTSD cases at baseline who are non-cases after a
minimum of ten months. Forty-two studies with a total of 81,642 participants were included. The mean observa-
tion period was40 months. Acrossall studies, an average of 44.0% of individuals with PTSD at baseline were non-
cases at follow-up. Remission varied between 8 and 89%. In studies with the baseline within the rst ve months
following trauma the remission rate was 51.7% as compared to 36.9% in studies with the baseline later than ve
months following trauma. Publications on PTSD related to natural disaster reported the highest mean of remis-
sion rate (60.0%), whereas those on PTSD related to physical disease reported the lowest mean of remission
rate from PTSD (31.4%). When publications on natural disaster were used as a reference group, the only type
of traumatic events to differ from natural disaster was physical disease. No other measured predictors were
associated with remission from PTSD. Long-term remission from PTSD without specic treatment varies widely
and is higher in studies with the baseline within ve months following trauma.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Epidemiological research indicates that most people experience at
least one potentially traumatic event during their lifetime (Breslau,
Davis, Andreski, & Peterson, 1991; Creamer, Burgess, & McFarlane,
2001; Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995; Perkonigg,
Kessler, Storz, & Wittchen, 2000). In many parts of the world, individ-
uals are exposed to large-scale traumatic events, such as wars or natural
disasters (Neria, Nandi, & Galea, 2008; Priebe et al., 2010). Whilst
traumatic experiences can lead to a range of mental health problems,
post-traumatic stress disorder (PTSD) is the most documented disorder
following trauma. The diagnostic criteria for PTSD require the onset of
characteristic symptoms following exposure to a traumatic event that
must be present for more than one month (American Psychiatric Asso-
ciation, 2000). The prevalence estimates of PTSD are high. For example,
in the European and US general population the 12-month prevalence of
PTSD has been estimated between 2.0 and 3.5% (Kessler, Chiu, Demler,
Merikangas, & Walters, 2005; Wittchen et al., 2011). PTSD is associated
with signicant mental and physical distress (Nemeroff et al., 2006)as
well as high economic burden (Kessler, 2000; Sabes-Figuera et al.,
2012; Wittchen et al., 2011).
There is good empirical evidence for the moderate efcacy of
trauma-focused psychological interventions (Ehlers et al., 2010) and
Clinical Psychology Review 34 (2014) 249255
Correspondingauthor at: Universityof Amsterdam, Department of Clinical Psychology,
Weesperplein 4, 1018 XA Amsterdam, The Netherlands. Tel.: +31 20 525 8607; fax: + 31
20 525 6810.
E-mail address: n.morina@uva.nl (N. Morina).
http://dx.doi.org/10.1016/j.cpr.2014.03.002
0272-7358/© 2014 Elsevier Ltd. All rights reserved.
Contents lists available at ScienceDirect
Clinical Psychology Review
to a lesser degree for pharmacotherapy (Stein, Ipser, & McAnda, 2009).
Yet, a signicant number of individuals with PTSD do not seek treat-
ment for their complaints (Gavrilovic, Schützwohl, Fazel, & Priebe,
2005), or fail to receive treatment, e.g., when they live in areas with lim-
ited or no access to mental health services after war or natural disasters
(Morina, Rushiti, Salihu, & Ford, 2010). The question arises as to how
important it is to expand the provision of treatment to all those people
with PTSD who are currently without treatment. This can only be
assessed based on data about the long-term outcomes of PTSD without
treatment. Available prospective studies on the course of PTSD indicate
different trajectories in different populations. Differences across studies
are presumed to occur due to the different nature of traumatic events,
methodological differences, current living conditions, and psychological
factors (Brewin, Andrews, & Valentine, 2000; Ozer, Best, Lipsey, &
Weiss, 2003; Schnurr, Lunney, & Sengupta, 2004). There is lack of a pub-
lished systematic review on the remission rate of PTSD without specic
treatment. Accordingly, we conducted a systematic review and meta-
analysis of prospective studies to assess the remission rate of PTSD
without specic treatment. Furthermore, the study aimed at identifying
variables that explain variations in remission estimates across studies.
2. Method
Observational prospective studies on the natural course of PTSD
published since 1980 (i.e., since the introduction of PTSD in DSM-III)
(American Psychiatric Association, 1980) were located in the following
computerized bibliographic databases: PUBMED, PsycINFO, and the
PILOTS database managed by the US National Center for PTSD. The
followingsearch terms were used: post-traumatic stress disorder or post-
traumatic stress disorder or PTSD AND long* or prognos* or follow-up or
prospect* or cohort* or endur* or prolong* or persist* or ongoing or contin*
or durable or outcome study or natural history or clinical course.Inaddi-
tion, a hand search of the following journals assumedto be likely to pub-
lish relevant articles was conducted: American Journal of Psychiatry,
Archives of General Psychiatry, British Journal of Psychiatry, Journal of
Nervous and Mental Disease, and Journal of Traumatic Stress. Finally, an
iterative bibliography search was performed on citations published of
all articles included in the review. The last search was conducted in
March 2013.
Publications had to meet the following criteria: 1) use of a prospec-
tive design, 2) a sample size of at least 40 participants at the rst assess-
ment; 3) at least 80% of participants older than 17 years; 4) report of
remission rates of PTSD, 5) use of a validated PTSD measurement (diag-
nostic interview or self-report) that was based on either DSM or ICD
criteria for PTSD, 6) follow-up conducted at least ten months after the
rst assessment, 7) report of response and drop-out rates, and 8) the
majority of participants were not treated for PTSD during the study
(i.e., intervention studies were excluded as well as studies reporting
that the majority of participants had received PTSD-related treatment
during the observation period of the study). We decided to include
studies with a follow-up conducted at least ten months after the rst
assessment in order to examine the long term course of the diagnosis
of PTSD. If a publication provided information on more than one
follow-up being conducted at least ten months after the rst assess-
ment, we used the data from the last follow-up period if this provided
the necessary information on remission from PTSD.
Relevant data from relevant publications were extracted using a
construed coding protocol. In studies with more than two measurement
points, the rst valid assessment and the last assessment were used. Age
was entered as a mean for each single study. If age was reported in cat-
egories, mean age was attained by multiplying number of participants
with the median age in the respective category. The median of the
category 65 + was 75 years. The marital status of participants was
determined in percentages per sample, with cohabiting and married
participants being the same category. The remaining participants were
coded as not living together. The response rate at baseline was the
percentage of participants who were included at baseline compared to
all those contacted who met study criteria. Number of drop-outs was
attained by subtracting the number of study completers from the total
of included participants at baseline.
The following variables were used as study-level predictors: type of
sampling (population based vs. critical population), type of instrument
used to assess PTSD (self-report measurement vs. diagnostic interview),
nature of assessment (face-to-face vs. via telephone), gender (propor-
tion men), age at study baseline, partnership at baseline, employment
status at baseline, country where study conducted (Western vs. non-
Western), treatment between baseline and follow-up, time between
trauma and baseline (bsix months vs. ), time between assessments
(months between baseline and last assessment), drop-out rate at
follow-up, type of traumatic exposure (abbreviated vs. extended), co-
morbid depression or anxiety disorders at baseline, and nature of the
trauma (separately analyzed using dichotomous variables, e.g. natural
disaster vs. accidental injury). In four studies, the time between trauma
and baselinecould not be estimated due to missing information. Comor-
bid depression or anxiety disorders at baseline were used as predictors
if the authors had reported co-occurring depressionor anxiety disorders
at baseline among individuals with PTSD. The temporal component of
trauma events was dummy coded according to Terr's proposition
(Terr, 1991). Type 1 corresponded to a relatively abbreviated exposure
such as a motor vehicle accident. Prolonged exposure to traumatic
events such as exposure to war-related events was dened as Type 2.
The nature of thetraumatic event was classied as one of eleven catego-
ries: natural disaster, war-related events among veterans, war-related
events among civilians, accidental injury, re/explosion, terrorist attack,
interpersonal violence, imprisonment, disease, death of signicant
others, or as a combination of the categories above. In total, no more
than two studies were based on war veterans, re/explosion, imprison-
ment, and death of signicant others, respectively, therefore these cate-
gories were not included in the analyses. However, the two studies
conducted among war veterans were combined with the studies con-
ducted with civilian war survivors as part of the category war survivors.
With regard to the examination of the association between nature of
traumatic events and remission from PTSD, we decided to use natural
disaster as the reference group. The decision was based on the ndings
that exposure to naturaldisasters is associated with lowerlevels of PTSD
than exposure to other traumatic events (Neria et al., 2008). According-
ly, we expected that remission from PTSD will be highest in studies
following exposure to natural disaster.
2.1. Statistical analysis
Theprimaryoutcomevariablewastheactualpercentageofindivid-
uals meeting criteria for PTSD at baseline and not at follow-up (remis-
sion). The relevant frequencies were transformed using the Freeman
Tukey transformation to allow for pooling of the samples. To account
for the differences in sample sizes, an inverse-variance weighted effect-
size was computed for the included studies (Borenstein, Hedges,
Higgins, & Rothstein, 2009). As larger sample sizes yield more accurate
estimates of the effect sizes found in the population compared to smaller
sample sizes, they were attributed a larger weight.
Because a preliminary analysis indicated substantial heterogeneity
in the data (Q
41
= 1250.66, p b0.001, I
2
= 97%), we used random-
effects model to estimate the mean and variance of remission and
mixed effects models in the subsequent meta-regression analyses
(Raudenbush, 2009). In addition, prospective studies are prone to high
dropout rates, which could obscure an accurate estimate of the course.
To account for the inuence of dropout, an estimate of the number of
PTSD cases among the dropouts was calculated using available data
regarding PTSD cases lost during follow-up. Four large-scale studies in-
cluded in the meta-analysis were reported on these data (Berninger
et al., 2010; Brackbill et al., 2009; Hedtke et al., 2008; Koren, Arnon, &
Klein, 2001). The estimate revealed that individuals with PTSD at
250 N. Morina et al. / Clinical Psychology Review 34 (2014) 249255
baselinewere 1.3 times morelikely to drop out than individuals without
PTSD. This estimate was applied when the relevant data was missing by
multiplying the number of dropouts in the study by the estimate. This
was inversed to correct for dropout regarding new cases.
2.2. Meta-regression analysis
Mixed-model meta-regression models were used to explain the
amount of heterogeneity in the data by extracted variables of interest
(Borenstein et al., 2009; Raudenbush, 2009). First, the inuence of dif-
ferences in study methodology and sample characteristics was exam-
ined. Subsequently, the predictive power of the main predictors was
examined: time between exposure to traumatic events and rst assess-
ment, time between assessments,type of trauma, and nature of trauma.
Comparable to a regression procedure, the change in predictive power
of the model using the variables was evaluated, i.e., the change in
Cochran's heterogeneity Q-statistic and the p-value of that statistic.
Meta-regressions were conducted for each predictor separately. In
light of the relatively low power associated with the current set of 42
samples, we used p = .10 as the nominal signicance level (Hedges &
Pigott, 2001).
Analyses were performed using the metafor package in R
(Viechtbauer, 2010). Reported results are expressed in the Free-
manTukey effect size and based on Restricted Maximum Likelihood
(Raudenbush, 2009). Percentages presented below were back-
transformed (Miller, 1978). We used a funnel plot analysis to assess
the likelihood of publication bias.
3. Results
3.1. Selection and inclusion of studies
The initial search identied 21.029 potential hits (see Fig. 1 for the
ow diagram). The rst review resulted in a total of 99 publications
eligible for inclusion. After contacting authors regarding missing infor-
mation related to the prevalence of PTSD at both assessment points in
potentially relevant articles, 49 publications were excluded because of
missing information and eight publications were identied as double
publications of already included studies. A total of 42 studies were nal-
ly included. Data were extracted by the rst and the third author. An
inter-rater reliability analysis regarding the coded information from
the included articles and using the kappa statistic for dichotomous
variables and intraclass correlation (ICC) for continuous variables was
performed to determine consistency among raters. This resulted in an
excellent inter-rater reliability of R = 0.90. Disagreements were jointly
discussed until an agreement was reached. Of all publications, 41 were
in English and one in German.
3.2. Characteristics of included studies
The included studies provided data from an aggregate sample of
81,642 participants from ve continents. Their mean age was 42.3
(SD = 11.7) and 48.8% of participants were male.
The rst assessment took place after a mean of 43.1 months (SD =
106.2, range: 1593, median = 7.5) following trauma (N-weighted
M = 32.9, SD = 35.6, median = 30). The follow-up took place
after a weighed mean of 40.0 months (SD = 43.3 range: 10204;
median = 24) after the rst assessment (N-weighted M = 29.4, SD =
15.6, median = 30). Study and sample characteristics, main outcome
variables, and remission rates for each included study are summarized
in the online Supplementary material.
3.3. Remission from PTSD
The funnel plot in Fig. 2 depicts the effect sizes for remission from
PTSD against studies' standard error, along with the type of PTSD
found in each included study. The funnel plot did not appear asymmet-
ric:Z= 0.39, p = 0.69. Overall, in a random effects model, the mean ef-
fect size for remission from PTSD was 0.75 (95% CI = 0.680.83, k = 42,
I
2
= 97%). Stated in percentages, 44.0% of participants remitted from
PTSD after a mean of 40 months. Remission rates among all studies varied
substantially, ranging from 8% to 89%. Fig. 3 shows the attributed weight,
effect size, and type of PTSD (i.e., Type 1 or 2) across included studies.
3.4. Meta-analytic regression
The association between study characteristics and methodologyand
remission rate was analyzed by separate meta-analytic regressions. Due
to the small number of studies reporting specic treatment, the treat-
ment categories concerning psychological treatment were collapsed
into one category treatment. The results are presented in Table 1.
Studies with the baseline conducted within the rst ve months
(a total of eleven studies) were more likely to have reported higher
remission rates. Of individuals with PTSD at baseline in these studies,
51.7% (ES = 0.84) did not meet criteria for PTSD at follow-up as com-
pared to 36.9% (ES = 0.68) of those with the baseline later than ve
months following trauma (a total of 27 studies). None of the other
investigated study characteristics was signicantly associated with
remission from PTSD.
Publications with participants with PTSD following exposure to a nat-
ural disaster reported the highest mean of remission rate (60.0%), where-
as publications with participants with PTSD associated with a physical
disease (such as myocardial infarction, subarachnoid hemorrhage,
or acute coronary syndrome) reported the lowest mean of remission
rate from PTSD (31.4%). Table 2 presents the results of the univariate re-
gression analysis on the nature of traumatic events with natural disaster
as the reference group. The mean remission rate in studies on PTSD relat-
ed to a disease was signicantly lower than the mean remission rate in
studies on PTSD following exposure to a natural disaster (p = 0.045).
The other types of traumatic events did not signicantly differ from the
category of natural disaster (see Table 2).
3.5. Sensitivity analyses
Given that the samplein the study by Brackbill et al. (2009)wa s larg-
er than the number of the remaining studies combined, all analyses
were repeated excluding the study by Brackbill. The mean effect size
for remission from PTSD among the 41 remaining studies was 0.75
(95% CI = 0.680.83; I
2
= 95%). Stated in percentages, 44.4% of partic-
ipants remitted from PTSD after a mean of 40 months. Finally, all meta-
analytic regression analysis reported above were re-conducted without
the study by Brackbill. Similarly to the main analyses, time between
trauma and baseline was the only variable associated with remission
from PTSD (R
2
= 0.10, p = 0.09). The study by Brackbill was conducted
later than ve months after trauma. When this study was removed from
the analysis, 37.0% (ES = 0.69) of participants in the remaining studies
with the baseline later than ve months following trauma were remit-
ted from PTSD at follow-up as compared to 51.7% (ES = 0.84) of
those with a baseline within the rst ve months following trauma.
No other variable about characteristics of the study or study methodol-
ogy was signicantly associated with remission rates of PTSD.
4. Discussion
The meta-analysis shows that the number of participants remitting
from PTSD after at least ten months varies greatly. On average nearly
half of participants diagnosed with PTSD remit from this disorder after
a mean of more than three years. Studies with the rst assessment of
PTSD within the rst ve months following trauma reported a higher
remission rate of PTSD than those with a later rst assessment of
PTSD. Further, participants with PTSD in relation to physical disease re-
ported a lower remission rate than participants with PTSD following a
251N. Morina et al. / Clinical Psychology Review 34 (2014) 249255
natural disaster. No other assessed variable was associated with remis-
sion from PTSD.
Strengths of the meta-analysis include the large amount of partici-
pants from 42 prospective studies as well as the fact that the studies
were conducted in different contexts, following exposure to a variety
of traumatic events and in different continents. Different factors were
tested as moderators, and sensitivity analyses were conducted while ex-
cluding the survey with the largest sample size (Brackbill et al., 2009).
The meta-analysis has also limitations. Most importantly, the number
of assessed potential factors to be associated with remission from
Freeman-Tukey effect size
Standard Error
0.316 0.237 0.158 0.079 0.000
0.00 0.50 1.00 1.50
Fig. 2. Funnel plot of the included studies (n = 42). Note: open circles represent short-
lived traumatic events (Type 1).
50 100 150 200
0.4 0.6 0.8 1.0 1.2
Time between T1 and follow-up (in months)
Freeman-Tukey effect size
Fig. 3. Effect size, attributed weight, and type of trauma across included studies (n = 42).
Note: open circles represent short-lived traumatic events (Type 1).
20,288 records identified through
electronic databases 16 records identified through iterative
bibliography search and
725 records identified through hand-search
21,029 records screened
for possible inclusion
99 full-text publications
screened
42 studies included in meta-
analysis
20,930 publications
excluded due to not
meeting inclusion criteria
57 publications excluded:
- Missing information
after contacting
authors (n=49)
- Double publications
(n=8)
Fig. 1. Flowchart of study selection.
252 N. Morina et al. / Clinical Psychology Review 34 (2014) 249255
PTSD was limited. For instance, only ve and four publications reported
comorbidity rates of depression or anxiety, respectively, among partici-
pants with PTSD at baseline.
Research on the development of PTSD has suggested several factors
to be associated with PTSD, such as characteristics of traumatic events,
peri-traumatic psychological reactions, occurrence of acute PTSD, per-
sonality factors, additional life stress, lack of social support, and demo-
graphic variables (Brewin et al., 2000; Ehlers, Mayou, & Bryant, 1998;
Ozer et al., 2003). Most of these factors were not assessed in the studies
included in the current meta-analysis. From the factors included (see
Tables 1 and 2), time of baseline and PTSD in relation to disease were
the only factors associated with remission from PTSD. The signicant
difference in remission rates from PTSD in studies with the rst assess-
ment within the rst ve months following trauma as compared to
those with a later rst assessment (51.7% vs. 36.9%) indicates that
PTSD assessed after ve months following trauma is somewhat more
likely to be chronic. The studies with a baseline within ve months
following trauma included a range of traumatic events, such as disease,
accidental injury,terrorist attack, interpersonal violence, or mixed trau-
ma (see Supplementary material). This reects the nature of traumatic
events reported in the studies with a baseline later than ve months
following trauma. Furthermore, none of the included studies assessed
PTSD in relation to childhood traumatic events. It should be noted, how-
ever, that regardless of the time of rst assessment, the number of indi-
viduals still suffering from PTSD more than three years after the initial
assessment of this diagnosis is very high indicating a chronic character
of PTSD. Accordingly, our results point towards a need for concerted
action at different levels, including increased funding for clinical and
public health research to identify effective strategies for prevention
and early treatment for PTSD following exposure to traumatic events.
Early prevention programs as well as early interventions for those
with chronic PTSD would not only decrease subjective distress but
also overall societal burden due to high health care costs and other
costs associated with PTSD (Sabes-Figuera et al., 2012). Over the last
decades, several specic interventions for PTSD have been developed
and trauma-focused psychological interventions have demonstrated
effectiveness in rigorous clinical trials (Bisson et al., 2007; Ehlers et al.,
2010; Foa, Keane, Friedman, & Cohen, 2009). For example, the meta-
analysis by Bisson et al. (2007) yielded that trauma focused cognitive
behavior interventions are signicantly more effective than waiting
lists regarding both clinician-rated (standardized mean differences
[SMD] = 1.40) and self-rated PTSD symptoms (SMD = 1.70). A SMD
of 1.40 or higher indicates that more than 90% of patients receiving trau-
ma focused interventions had signicantly less symptoms of PTSD than
the average patient on the waiting list. Established effective treatments
need to be made widely available for individuals with PTSD, whilst re-
search should develop effective prevention interventions for individuals
exposed to traumatic events.
The highest remission rate was reported in studies on PTSD among
survivors of naturaldisaster. This nding is in line with studies revealing
that the PTSD prevalence rate in survivors of natural disasters is some-
what lower than in survivors of other forms of traumatic events
(Neria et al., 2008). However, it is rather surprising that the remission
rate of PTSD in the course of physical disease was the only one to signif-
icantly differ from the remission rate of PTSDamong survivors ofnatural
disaster. This may be explained by the fact that the remission rate of
Table 1
Univariate meta-regression analysis of study characteristics.
Variable Remission from PTSD
B
0
SE B
1
SE R
2
k
Population-based sampling 0.813** 0.103 0.069 0.112 0.000 42
Diagnosticinterview 0.706** 0.051 0.117 0.079 0.041 42
Face-to-face assessment 0.711** 0.071 0.064 0.086 0.000 42
Gender: male vs. female 0.858** 0.095 0.002 0.002 0.001 22
Age (baseline) 0.699* 0.276 0.001 0.007 0.002 16
Partner 0.918** 0.230 0.003 0.003 0.000 10
Employment 0.737** 0.162 0.001 0.002 0.000 10
Western country 0.682** 0.084 0.093 0.095 0.000 42
Treatment 1.077** 0.296 0.009 0 .006 0.129 7
Baseline 5 months 0.839** 0. 077 0.156+ 0.090 0.054 38
Baseline until follow-up 0.725** 0.054 0.001 0.001 0.000 42
Drop-out at follow-up 0.745** 0.076 0.000 0.002 0.000 42
Comorbid depression at baseline 0.666 0.439 0.002 0.009 0.000 5
Comorbid anxiety disorders at baseline 0.759** 0.085 0.003 0.002 NA 4
Note: ** = p b.01; * = p b.05; + = p b.10; For a predictor to be signicant, B
1
must be signicant; B = regression coefcients; SE = standard error; k = number of studi es;
NA = not applicable because no heterogeneity observed in this subset.
Table 2
Univariate meta-regression analysis regarding the nature of traumatic events.
Remission from PTSD
Variable B
0
SE B
1
SE R
2
Natural disaster (k = 5) [Reference] [Reference] [Reference] [Reference] [Reference]
War survivors (k = 7) (veterans and civilians) 0.890** 0.110 0.228 0.144 0.135
Civilian war survivors (k = 5) 0.890** 0.119 0.255 0.167 0.134
Accidental injury (k = 5) 0.890** 0.118 0.226 0.175 0.075
Terrorist attack (k = 10) 0.890** 0.111 0.055 0.135 0.000
Interpersonal violence (k = 4) 0.889** 0.132 0.080 0.203 0.000
Physical disease (k = 5) 0.890** 0.098 0.287* 0.144 0.266
Notes: Reference group : natural disaster; ** = p b.01; * p b.05; k is the number of studies; for a predictor to be signicant, B
1
must be signicant; B = regression coefcient;
SE = standard error.
253N. Morina et al. / Clinical Psychology Review 34 (2014) 249255
PTSD varied fundamentally in the studies within the single categories of
traumatic events (see Supplementary material). For example, the re-
mission rate in the studies on PTSD among survivors of accidental injury
varied between 70.2% (Blanchard et al., 1996)and13%(Bryant &
Harvey, 2002). The nding that individuals with PTSD due to a physical
illness reported the lowest remission from PTSD might be explained by
the notion that these individuals carry in them the illness that caused
the disorder and thus may not only be constantly reminded about it
but also be physically less capable of coping with it.
The other assessed factors were not signicantly associated with
remission from PTSD. Perhaps mostsurprising is the nding that remis-
sion from PTSD does not increase with longer observation periods. This
nding may be surprising, considering the large range of the follow-up
that extended between 10 and 204 months, with a weighed mean of
40 months after the rst assessment. The reviewed studies do not
support the notion that time heals all wounds. However, there is a
large variability of the remission rate between all studies, regardless of
the time period between baseline and follow-up (see Supplementary
material). For example, in studies with a longer follow-up than
100 months, the rate of remission from PTSD rages from 27.3%
(Maercker, Gaebler, & Schuetzwohl, 2013) to 75.0% (Perkonigg et al.,
2005). This large variability in the rate of remission from PTSD cannot
be explained by the factors assessed in the reviewed studies. Future
research should identify more relevant predictors of remission from
PTSD. Such research should include pre-traumatic, peri-traumatic as
well as post-traumatic conditions, as potential predictors.
One important issue is whether the instruments used to establish
PTSD were valid. Instruments with poor validity may overestimate
the prevalence of PTSD at baseline or at follow-up. Yet, the use of
more valid diagnostic interviews was not associated with a different
remission rate as compared to self-report measurements. PTSD in the
included studies was diagnosed based on symptoms in the past
month. Given that PTSD symptoms can uctuate, remission rates re-
ported in the studies might be rather positive as patients not meeting
PTSD criteria in the previous month, but before or after that month,
would be considered as a remission. This indicates that some of the in-
dividuals not meeting criteria for PTSD at follow-up might not have
been in permanent remission from PTSD.Accordingly,thissuggests
that spontaneous long-term permanent remission from PTSD is
likely to be even lower than the reported average remission rate of
44.0%.
The high variability across studies makes prognoses in specicsam-
ples and contexts difcult. Future research on remission from PTSD
should assess different potential factors that might explain the wide
variability in remission from PTSD, such as details of social support
which has been shown to impact on the development of PTSD and
might also be relevant for overcoming it (Brewin et al., 2000; Ozer
et al., 2003). Reporting of these factors should be provided separately
for individuals with PTSD at baseline, if appropriate. Most of the studies
included in the current review reported for example on employment
rates for the whole sample, yet failed to provide this information for in-
dividuals with PTSD at baseline separately. Knowledge about factors
inuencing remission from PTSD might help improve preventing PTSD
as well as treatment of PTSD.
Overall, PTSD tends to remit in only about half of individuals after a
period of more than three years, and the prognosis deteriorates if PTSD
is diagnosedlater than ve monthsfollowing trauma. This indicates that
effective treatmentshould be widely provided for individuals with PTSD
to avoid long term distress and reduce the associated costs for the af-
fected individuals, their families, and society at large.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.cpr.2014.03.002.
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Errors in Byline, Author Affiliations, and Acknowledgment. In the Original Article titled “Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication,” published in the June issue of the ARCHIVES (2005;62:617-627), an author’s name was inadvertently omitted from the byline on page 617. The byline should have appeared as follows: “Ronald C. Kessler, PhD; Wai Tat Chiu, AM; Olga Demler, MA, MS; Kathleen R. Merikangas, PhD; Ellen E. Walters, MS.” Also on that page, the affiliations paragraph should have appeared as follows: Department of Health Care Policy, Harvard Medical School, Boston, Mass (Drs Kessler, Chiu, Demler, and Walters); Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, Md (Dr Merikangas). On page 626, the acknowledgment paragraph should have appeared as follows: We thank Jerry Garcia, BA, Sara Belopavlovich, BA, Eric Bourke, BA, and Todd Strauss, MAT, for assistance with manuscript preparation and the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on the data analysis. We appreciate the helpful comments of William Eaton, PhD, Michael Von Korff, ScD, and Hans-Ulrich Wittchen, PhD, on earlier manuscripts. Online versions of this article on the Archives of General Psychiatry Web site were corrected on June 10, 2005.
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IntroductionIndividual studiesThe summary effectHeterogeneity of effect sizesSummary points
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A formula for the inverse of the Freeman–Tukey double arcsine transformation is derived. This formula is useful when expressing means of double arcsines as retransformed proportions. When the mean is taken from original proportions involving different n's, it is suggested that the harmonic mean of the n's be used in the inversion formula.