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Behaviour Research and Therapy 57 (2014) 21e28

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Behaviour Research and Therapy

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Does dissociation moderate treatment outcomes of narrative exposuretherapy for PTSD? A secondary analysis from a randomized controlledclinical trial

Joar Øveraas Halvorsen a,*, Håkon Stenmark b, Frank Neuner c, Hans M. Nordahl a

aDepartment of Psychology, Norwegian University of Science and Technology, N-7491 Trondheim, NorwaybCentre on Violence, Traumatic Stress and Suicide Prevention, Mid-Norway, St. Olavs University Hospital, Schwacks gt. 1, N-7030 Trondheim, NorwaycDepartment of Clinical Psychology and Psychotherapy, Bielefeld University, 33501 Bielefeld, Germany

a r t i c l e i n f o

Article history:Received 12 November 2013Received in revised form27 March 2014Accepted 31 March 2014Available online 12 April 2014

Keywords:Narrative exposure therapyPosttraumatic stress disorderDepersonalisationDerealisationModeratorsTreatment outcome

* Corresponding author. Tel.: þ47 73597811.E-mail addresses: joar.halvorsen@svt.ntnu.no, joar

(J.Ø. Halvorsen).

http://dx.doi.org/10.1016/j.brat.2014.03.0100005-7967/� 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

Dissociative symptoms, especially depersonalisation and derealisation, are often perceived as a contra-indication for exposure-based treatments of posttraumatic stress disorder (PTSD) despite limitedempirical evidence. The present paper examines whether derealisation and depersonalisation influencethe treatment outcomes of narrative exposure therapy (NET) and treatment as usual (TaU) amongseverely traumatised asylum seekers and refugees. We performed a secondary analysis of a recentlypublished randomized controlled multicentre trial comparing NET and TaU for the treatment of PTSD inasylum seekers and refugees. In order to investigate whether depersonalisation and derealisationmoderate treatment outcomes, a number of moderated multiple, blockwise regression analyses wereconducted. Missing data were handled with multiple imputation. The main finding from intention-to-treat analyses is that derealisation and depersonalisation overall do not moderate the treatment out-comes of either NET or TaU. The treatment condition was the most stable predictor of residual gain scoresacross outcome measures, with NET being associated with lower residual gain scores indicating bettertreatment outcomes. The present study substantiates and extends previous research indicating thatdissociative symptoms such as derealisation and depersonalisation do not moderate the treatmentoutcome of exposure-based treatments for PTSD.ClinicalTrials.gov identifier: NCT00218959.

� 2014 Elsevier Ltd. All rights reserved.

Narrative exposure therapy (NET), a recently developed stand-ardised, short-term treatment for posttraumatic stress disorder(PTSD) in survivors of armed conflict, political violence and torture(Schauer, Neuner, & Elbert, 2005), is based on the principles ofprolonged exposure therapy (Foa, Hembree, & Rothbaum, 2007)and testimony therapy (Cienfuegos & Monelli, 1983). Specifically,NET has two distinctive features: It uses the chronicity of testimonytherapy and, instead of identifying the worst traumatic event as atarget in therapy, the survivor constructs a narrative of his or herwhole life, and is exposed to all the traumatic experiences in his orher life through imaginal reliving. Imaginal exposure for traumaticexperiences is performed as in prolonged exposure therapy, how-ever, there is no explicit focus on in-vivo exposure. Thus, the focus

.overaas.halvorsen@stolav.no

of NET is twofold. As with prolonged exposure therapy, one aim isto reduce the posttraumatic symptomatology by confronting thememories of the traumatic events. The second aim is to reconstructthe autobiographical memory of the traumatic events and create aconsistent narrative or testimony as in testimony therapy. In linewith the fact that exposure-based psychological treatments havethe most and the methodological strongest evidence for its efficacyin the treatment of PTSD (Bisson et al., 2007; Institute of Medicine,2008), NET has been found to be effective in treating both PTSD andcomorbid disorders in a number of randomized controlled trials ina variety of refugee and asylum-seeking samples (see Robjant &Fazel, 2010 for a recent review) and is probably the treatmentmodality with the most empirical support to date for this specificpatient group (Crumlish & O’Rourke, 2010).

Although exposure therapy is a highly effective treatment forPTSD (Powers, Halpern, Ferenschak, Gillihan, & Foa, 2010), a sub-stantial minority of patients either drop-out of treatment, presentsubstantial residual symptoms after treatment or do not respond to

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e2822

treatment at all (Bradley, Greene, Russ, Dutra, & Westen, 2005;Schottenbauer, Glass, Arnkoff, Tendick, & Gray, 2008). The samereservations are in place for NET. As evident from Stenmark, Catani,Neuner, Elbert, and Holen (2013), there are large variations intreatment responses to NET: Over 50% still satisfied the diagnosticcriteria for PTSD at 6 months follow-up, while 36% did not achieveclinically significant symptom remission. Therefore, it is importantto identify potential moderators of treatment outcomes (Kraemer,Frank, & Kupfer, 2006; Kraemer, Wilson, Fairburn, & Agras, 2002)in an effort to personalise treatments (Simon & Perlis, 2010) forPTSD.

Dissociation has been suggested by a number of researchers andtrauma therapists as an important moderator of treatment out-comes for PTSD. Despite controversy, the recently published DSM-5(American Psychiatric Association, 2013) includes a dissociativesubtype of PTSD marked by prominent depersonalisation (i.e.,feeling as if oneself is not real) and derealisation (i.e., feeling as iftheworld is not real) symptoms.Whereas Friedman, Resick, Bryant,and Brewin (2011) concluded that sufficient evidence for a disso-ciative subtype of PTSD is lacking, others have argued that currentresearch points toward the existence of such a subtype (Dalenberg& Carlson, 2012; Lanius, Brand, Vermetten, Frewen, & Spiegel,2012). Recent research in both civilian (Steuwe, Lanius, & Frewen,2012) and military samples (Wolf, Lunney, et al., 2012; Wolf,Miller, et al., 2012) indicates that derealisation and depersonalisa-tion are salient features of PTSD in a subset of individuals with thedisorder. The same pattern has also been found in a recent cross-cultural epidemiologic survey (Stein et al., 2013). The inclusion ofsuch a subtype of PTSD rests partly on demonstrating that thesedissociative symptoms moderate treatment outcomes of alreadyexisting efficacious treatments for PTSD (Bryant, 2012; Resick,Bovin, et al., 2012). Several authors emphasise that this dissocia-tive subtype of PTSD might be associated with treatment outcomes(Feeny & Danielson, 2004; Ginzburg & Neria, 2011; Lanius et al.,2010; Lanius et al., 2012; Steuwe et al., 2012; Wolf, Lunney, et al.,2012; Wolf, Miller, et al., 2012), notably with a poor response toordinary cognitive behavioural treatment. In linewith this, a surveyamong more than 200 practicing psychologists indicated that amajority experienced symptoms of dissociation as a significantcontraindication to use exposure therapy for PTSD (Becker, Zayfert,& Anderson, 2004).

Indeed, dissociative symptoms are associated with poorertreatment outcomes for in-patient dialectical behaviour therapy forborderline personality disorder (Kleindienst et al., 2011), cognitivebehavioural treatment for panic disorder with agoraphobia(Michelson, June, Vives, Testa, & Marchione, 1998) and obsessiveecompulsive disorder (Rufer et al., 2006), as well as for in-patientbrief psychodynamic psychotherapy for affective, anxiety andsomatoform disorders (Spitzer, Barnow, Freyberger, & Grabe, 2007).However, although the above mentioned theoretical assumptionsand empirical studies indicate that dissociation is generally relatedto poorer treatment outcomes, the existing research on the influ-ence of dissociation on treatment outcomes for PTSD is not as clear.

Several clinical trials have examined whether dissociation is apredictor or a moderator of treatment outcomes of exposure-basedtreatments for PTSD. Overall, dissociation does not seem to be apredictor of treatment outcomes (Hagenaars, van Minnen, &Hoogduin, 2010; Jaycox, Foa, & Morral, 1998; Speckens, Ehlers,Hackmann, & Clark, 2006; Taylor, 2003).

Secondary data analyses from two dismantling randomizedcontrolled trials have investigated whether dissociation moderatetreatment outcomes. In the first trial, Cloitre, Petkova,Wang, and Lu(2012) found that severity of dissociative symptoms at pre-treatment did not moderate the treatment outcomes of skillstraining in affective and interpersonal regulation followed by

narrative storytelling (STAIReNST) and the constituent parts of themanual.

In the second trial, comparing the different elements of cogni-tive processing therapy (i.e., the full manual, cognitive therapy onlyandwritten trauma account only) in the treatment of PTSD, severityof dissociative symptoms at pre-treatment did not influencetreatment outcomes when averaged across treatment conditions(Resick, Suvak, Johnides, Mitchell, & Iverson, 2012). However, pa-tients with more severe dissociative symptoms, especially deper-sonalisation symptoms, had better outcomes if they received thefull manual as compared to cognitive therapy only, whereas pa-tients with less severe dissociative symptoms had better treatmentresponses to cognitive therapy only compared to the full manual.Thus, these results indicate that therapeutic tasks with elements ofexposure therapy might be especially indicated in patients withsevere dissociative symptoms.

Of note, both Hagenaars et al. (2010) and Cloitre et al. (2012)found that higher levels of dissociation at baseline was associ-ated with more severe PTSD-symptoms at both pre- and post-treatment.

The comorbidity between depression and depersonalisation andderealisation is high (Hunter, Sierra, & David, 2004) and thedissociative subtype of PTSD has higher comorbidity with depres-sion as compared to “classical” PTSD (Steuwe et al., 2012). As such,it is important to examine whether dissociative symptoms influ-ence treatment outcomes for comorbid depressive symptoms.

Moreover, as pinpointed by Hagenaars et al. (2010) treatmentefficacy concerns both improvement and drop-out. Dissociation hasbeen found to predict drop-out from CBT treatment for OCD (Ruferet al., 2006). However, whereas Hagenaars et al. found that baselinedissociation was not related to drop-out from exposure therapy forPTSD, Cloitre et al. (2012) found that patients with high ascompared to low dissociation were less likely to drop-out oftreatment. Thus, it is also important to investigate whether disso-ciation predicts drop-out.

Dissociation is a multidimensional phenomenon (Briere,Weathers, & Runtz, 2005) and as such Bryant (2007) underlinedthat research on dissociative phenomena should be based on spe-cific symptoms rather than the global construct of dissociation.Furthermore, according to Wolf (2013), derealisation and deper-sonalisation “reflect more pathological forms of dissociative phe-nomena that are distinct from other types of dissociation” (p. 2).Thus, the present paper set out to examine whether derealisationand depersonalisation moderate treatment outcomes of NET andtreatment as usual (TaU) among severely traumatised asylumseekers and refugees.

The present exploratory analysis aims to extend previousresearch in several ways. First, to our knowledge, this is the firstpaper to examine whether dissociative symptoms moderatetreatment outcomes of both NET and TaU. Furthermore, no otherstudies have investigated the role of dissociation in treatmentoutcomes in this specific patient population, i.e. severely trauma-tised asylum seekers and refugees. In addition, whereas most otherstudies have used global constructs of dissociation, we set out toexamine whether specific symptoms of dissociation, i.e. dereal-isation and depersonalisation, moderate treatment outcomesindependently.

Method

The present paper is based on exploratory secondary analysesfrom a recently published randomized controlled multicentre trialcomparing NET and TaU for the treatment of PTSD in asylumseekers and refugees (Stenmark et al., 2013), and the details willonly be briefly reviewed herein. The main finding of the trial was

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e28 23

that NET is superior to TaU in reducing PTSD symptom severity, butnot severity of depressive symptoms.

Participants

The sample consists of 81 participants recruited among refugeesand asylum-seekers referred to psychological treatment at outpa-tient clinics in the Mid-Norway health region. The inclusion criteriawere (1) a primary PTSD diagnosis according to the DSM-IV(American Psychiatric Association, 1994) criteria and (2) �18years of age. The exclusion criteria were (1) psychotic disorders, (2)current severe substance abuse, or (3) severe suicidal ideations. Themajority of the sample was male (69%) andmost of the participantswere from Iraq (27%), Afghanistan (15%) or African countries (26%).The mean age of the sample was 35.55 (SD ¼ 11.05), and mostcompleted primary and secondary school (59%). Mean time spentin Norway was 55.99 months (SD ¼ 50.58) and a substantial mi-nority were asylum seekers at pre-treatment (38%). Based on TheLife Events Checklist of the CAPS, which assesses a total of 16potentially traumatic life events, the participants reported experi-encing multiple traumatic life experiences (M ¼ 8.11, SD ¼ 2.51). Ofnote, a substantial minority reported having survived one or moreinstances of torture (43%). There were no significant differencesbetween participants randomized to NET or TaU on any of the de-mographic variables measured (Stenmark et al., 2013).

Instruments

The following instruments were used:

Clinician-administered PTSD scaleThe Clinician-Administered PTSD Scale (CAPS; Blake et al., 1995)

is widely recognised as the gold standard for assessment of PTSD.The CAPS assesses all 17 core symptoms of PTSD, in addition to 5associated features where two itemsmeasure feelings of guilt (guiltover omission or commission and survivor guilt) and three itemsmeasure dissociative symptoms (derealisation, depersonalisationand reduction in awareness of surroundings). The CAPS containsseparate frequency and intensity rating scales for each of thesymptoms. The frequency and intensity of each symptom are ratedon a five-point Likert scale (0e4), and these ratings can be summedto create a nine-point (0e8) severity score for each symptom. TheCAPS has excellent psychometric properties and has consistentlybeen found to have an inter-rater reliability at the 0.90 level andabove (Weathers, Keane, & Davidson, 2001). Based on the Jacobsonand Truax (1991) criteria, and in line with Hien et al. (2009), wedefined clinically significant change as a reduction in CAPS totalscore of �30 points, which is approximately equivalent to �2 SDsbelow the baseline mean.

In line with previous research (Armour, Karstoft, & Richardson,2014; Wolf, Lunney, et al., 2012; Wolf, Miller, et al., 2012), dereal-isation and depersonalisation were measured using the relevant/specific items from the CAPS. Wolf, Miller, et al. reported highintraclass correlation coefficients for the dissociation items of theCAPS (ICC ¼ 0.79).

Hamilton Rating Scale for DepressionThe Hamilton Rating Scale for Depression (HRSD; Hamilton,

1960) is a widely used clinician rating scale for assessing theseverity of depression. The scale consists of 17 items measuringdepression severity. The items are scored on either a three-point(0e2) or a five-point scale (0e4). HRSD has adequate psychomet-ric properties (Trajkovi�c et al., 2011), including inter-rater reliability(Morriss, Leese, Chatwin, Baldwin, & Thread Study Group, 2008;Trajkovi�c et al., 2011).

Procedure

The method and design of the randomized controlled multi-centre trial the present paper is based on has been reported indetail elsewhere (Stenmark et al., 2013), and therefore only a briefdescription is given here.

The Regional Committee for Medical Research Ethics in Mid-Norway approved the project. Participants were block randomizedto treatment conditions, in which 2/3 of the participants were allo-cated to NETand 1/3 allocated toTaU. Assessments took place beforetreatment, onemonth after treatment and a follow-up at sixmonths.

Therapists and assessorsTwenty-four experienced mental health professionals (psy-

chologists, psychiatrists, psychiatric nurses and clinical socialworkers) situated at 11 different outpatient clinics in Mid-Norwayhealth region were recruited as therapists and assessors. The pro-fessionals were trained in NET and the application of the assessorinstruments included in the study during a 5-day workshop. Sub-sequently, the professionals participated in 2-day workshops everysix months to maintain their skills. In addition, the professionalsreceived individual supervision after the 1st, 4th, 6th, and 9thsessions of therapy for each patient. Assessors and therapist wereindependent of each other, i.e. the professionals could not be boththerapist and assessor for the same patient. The assessors were notaware of allocation, and in order to maintain blindness we alwaysaimed for assessments to be undertaken by assessors from differentclinics where the patients received their treatment. Furthermore,the therapists were instructed not to reveal the type of treatmenttheir patients were given. Despite these measures, it appeared thatin a substantial minority of cases (20%), the patients revealed in-formation about their treatment to the assessors. As reported byStenmark et al. (2013), a statistical analysis showed no significantdifferences of these post-tests from the other assessments.

TreatmentTreatment consisted of 10 sessions lasting 90 min in both con-

ditions. NET was performed according to the manual as outlined bySchauer et al. (2005). Treatment adherence and competence wasmonitored and ensured through (1) the individual supervision and(2) a self-report measure, where the therapists had to report aftereach session whether they had used the main ingredients of NET,such as psychoeducation, the life-line exercise and prolongedexposure to memories of traumatic experiences. No major de-viations from the NET-protocol as described in Schauer et al. (2005)were identified.

In the TaU condition, the therapists were instructed to use anyintervention that they would normally use, except for the in-terventions specific to NET. Based on information gathered throughsupervision and therapists self-report, it seems TaU mainly con-sisted of help with problems such as sleep difficulties, depressivesymptoms, problems related to the asylum procedure and practicalmatters. During the 10 TaU sessions, an average of 86minwas spenton talking about traumatic events, mainly to give the therapist anoverview of the patients’ history.

Data analyses

As our primary aim of the present paper is to examine whetherderealisation and depersonalisationmoderate treatment outcomes,we utilised multiple, blockwise regression analyses with interac-tion terms (Frazier, Tix, & Barron, 2004; Warner, 2013). The mainmultiple, blockwise regression analyses were performed with CAPSresidual gain scores at post-treatment and follow-up as outcome/dependent variables. In the first block, we entered treatment arm

Table 1Clinical characteristics of the sample at pre-treatment (N ¼ 78).

NET TaU Total sample

M (SD) M (SD) M (SD)

CAPS total score 83.31 (15.58) 83.17 (16.59) 83.26 (15.85)HRSD total score 18.41 (6.90) 19.52 (5.83) 18.82 (6.5)Derealisation 0.87 (1.46) 2.15 (2.10) 1.35 (1.82)Depersonalisation 0.47 (1.29) 0.86 (1.46) 0.61 (1.36)

Note. CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale fordepression. NET ¼ Narrative exposure therapy. TaU ¼ Treatment as usual.

Table 2Pooled outcome of moderated multiple, blockwise regression analysis with CAPSresidual gain scores at post-treatment as the dependent variable (N ¼ 78).

B SE t p FMI

Block 1Constant .116 .081 1.436 .151 .019Treatment �.187 .102 �1.839 .066 .16

Block 2Constant .603 .158 3.812 .000 .021Treatment �.215 .095 �2.257 .024 .017HRSD �.025 .007 �3.495 .000 .024

Block 3Constant .660 .159 4.139 .000 .028Treatment �.283 .099 �2.848 .004 .019HRSD �.022 .007 �3.015 .003 .023Derealisation �.058 .028 �2.039 .041 .034Depersonalisation .005 .036 .152 .879 .043

Block 4Constant .723 .270 2.680 .007 .016Treatment �.271 .100 �2.698 .007 .018HRSD �.022 .013 �1.692 .091 .020Derealisation �.057 .038 �1.515 .130 .021Depersonalisation �.055 .053 �1.034 .301 .012Treatment � HRSD �.001 .101 �.007 .995 .016Treatment � Derealisation �.008 .113 �.067 .947 .045Treatment � Depersonalisation .184 .125 1.475 .140 .045

Note. CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale fordepression. B ¼ Unstandardised regression coefficient. SE ¼ Standard error.FMI ¼ Fraction of missing data.

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e2824

(0 ¼ TaU, 1 ¼ NET), in the second block total HRSD score at pre-treatment, in the third block derealisation and depersonalisationtotal scores at pre-treatment, and in the fourth and last blockinteraction terms between treatment and HRSD, treatment anddepersonalisation, and treatment and derealisation. As recom-mended by Frazier et al. (2004), continuous variables were stand-ardised before computation of interaction terms. Residual gainscores (Steketee & Chambless, 1992) were chosen as outcome/dependent variables to reflect change in symptoms and to controlfor both initial differences and measurement errors inherent inrepeated administration of the same instruments.

As secondary analyses, we performed moderated multiple,blockwise regression analyses with HRSD residual gain scores atpost-treatment and follow-up as dependent variables. We alsoperformed a binary logistic regression analysis with drop-outbefore planned treatment termination as an outcome variable.

We identified three influential outliers (i.e., �3 SD from themean). All had high scores on depersonalisation at pre-treatment,and were removed prior to final modelling.

We also divided the sample into three subgroups according tothe severity of both derealisation and depersonalisation andexamined Hedges g effect sizes between the groups. No or lowderealisation or depersonalisation was defined as a total score of 0.Moderate derealisation or depersonalisation was defined as a totalscore of 1e3, and severe derealisation or depersonalisation wasclassified as a total score of �4 on either scale. In addition, weexamined rates of clinically significant change in CAPS total scoresfrom pre-treatment to follow-up based on baseline severity ofderealisation and depersonalisation.

Missing dataMissing data were handled with multiple imputation (Graham,

2009, 2012; Schafer & Graham, 2002). The Little’s MCAR (MissingCompletely At Random) test was not significantðc21248 ¼ 618:37; p ¼ 1:00Þ, indicating that the data could beconsidered to be missing completely at random. We utilised item-level imputation (Gottschall, West, & Enders, 2012) to generate/produce 20 imputed data sets. Multiple imputation has been foundto perform very well with large multiple regression models withlarge portions of missing data, even with small sample sizes(Graham, 2009). Whereas it is often considered sufficient toperform five to ten imputations (Schafer, 1999), Graham,Olchowski, and Gilreath (2007) recommended performing manymore imputations beyond what is usually considered sufficient. Asmissing data at post-test and follow-up ranged from 25.9% to 30.9%,based on recommendations by Graham et al. (2007), we generated20 imputed data sets. We constrained minimum and maximumallowable imputed values in accordancewith the range of values onthe instruments, i.e., items on the CAPS range from 0 to 4 andimputed values were constrained to be in this range. However, asrecommended by Graham (2009), we set no constraints onrounding. As IBM PASW Statistics 18 does not provide pooledoutcomes for all statistics (e.g., standard deviations), we calculatedsome of these outcomes manually. The main results will be re-ported in line with recommendations made by Graham (2012).

Results

Table 1 presents means and standard deviations at pre-treatment on the measures relevant for this paper in the twotreatment arms.

At baseline, there were no significant differences between thetwo treatment conditions on any of the measures, except forderealisation in which the TaU-condition had a significantly highermean score compared to the NET-condition (t ¼ 2.87, p � 0.05).

Moderators of treatment outcome for PTSD

The results of the moderated multiple, blockwise regressionanalysis with CAPS residual gain score at post-treatment are pre-sented in Table 2. In the final block, only treatment predicted CAPSresidual gain score at post-treatment. The NET condition wasassociated with lower residual gain score, indicating lower symp-tom severity at post-treatment compared to the TaU condition. IBMPASW Statistics 18 does not provide a pooled outcome for the F-values, but all 20models were significant at p� 0.009. The DurbineWatson values for the 20 models ranged from 2.208 to 2.350,indicating that the residuals were independent. Furthermore, thereseems to be no substantial multicollinearity within our data as thevariance inflation factor (VIF) did not exceed 3.655 and the lowestTolerance statistics was 0.274.

Table 3 presents the results of the moderated multiple, block-wise regression analysis with CAPS residual gain score at follow-up.As for the foregoing analysis, in the final block only treatmentcondition predicted CAPS residual gain score at follow-up, with NETbeing associated with a lower residual gain score indicating betteroutcomes. All 20 models were significant at p� 0.034. The DurbineWatson value ranged from 1.876 to 1.996 for the 20models, and thehighest VIF value was �3.655 whereas the lowest Tolerance sta-tistics was �0.274.

Figs. 1 and 2 depicts CAPS mean scores at pre-treatment, post-treatment and follow-up for NET and TaU based on severity ofderealisation or depersonalisation at pre-treatment, respectively.

Table 3Pooled outcome of moderated multiple, blockwise regression analysis with CAPSresidual gain scores at follow-up as the dependent variable (N ¼ 78).

B SE t p FMI

Block 1Constant .119 .070 1.699 .089 .009Treatment �.191 .088 �2.172 .030 .005

Block 2Constant .485 .140 3.457 .001 .022Treatment �.212 .084 �2.524 .012 .006HRSD �.019 .006 �2.960 .003 .028

Block 3Constant .523 .143 3.666 .000 .019Treatment �.257 .089 �2.894 .004 .006HRSD �.017 .006 �2.563 .010 .028Derealisation �.038 .026 �1.491 .136 .036Depersonalisation .003 .032 .089 .929 .029

Block 4Constant .481 .246 1.954 .051 .033Treatment �.246 .090 �2.732 .006 .005HRSD �.012 .012 �1.025 .305 .041Derealisation �.041 .034 �1.222 .222 .019Depersonalisation �.036 .048 �.744 .457 .012Treatment � HRSD �.044 .092 �.474 .636 .033Treatment � Derealisation .011 .102 .113 .910 .036Treatment � Depersonalisation .119 .112 1.063 .288 .037

Note. CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale fordepression. B ¼ Unstandardised regression coefficient. SE ¼ Standard error.FMI ¼ Fraction of missing data.

Fig. 2. Change in CAPS total score from pre-treatment to follow-up for treatment asusual (TaU; n ¼ 30) and narrative exposure therapy (NET; n ¼ 51) based on severity ofdepersonalisation (DP) at pre-treatment.

Table 4Pooled outcome of moderated multiple, blockwise regression analysis with HRSDresidual gain scores at post-treatment as the dependent variable (N ¼ 78).

B SE t p FMI

Block 1

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e28 25

Moderators of treatment outcome for depression

Table 4 displays the results of the moderated multiple, block-wise regression analysis with HRSD residual gain score at post-treatment as the dependent variable.

As can be seen from Table 4, treatment condition and dereal-isation at pre-treatment were significant predictors of depressionat post-treatment. More specifically, both NET and derealisationwere associated with better treatment outcomes at post-treatment.However, the interaction term treatment � derealisation was notsignificant, indicating that derealisation at pre-treatment did notmoderate treatment outcomes more in one treatment armcompared to the other. As such, derealisation seems to be a moregeneric predictor of treatment outcomes among traumatisedasylum seekers and refugees rather than a specific moderator ofoutcomes in specific psychological treatments. Three of the 20models were not significant, but the remaining 17 models were allsignificant at the p � 0.05 level. DurbineWatson values of the 20

Fig. 1. Change in CAPS total score from pre-treatment to follow-up for treatment asusual (TaU; n ¼ 30) and narrative exposure therapy (NET; n ¼ 51) based on severity ofderealisation (DR) at pre-treatment.

models ranged from 1.827 to 2.031, while the VIF values did notexceed 2.698 and the Tolerance statistic was �0.371.

None of the variables investigated predicted HRSD residual gainscore at follow-up, and as such none of the 20 models were sig-nificant. DurbineWatson values ranged from 1.558 to 1.780, the VIFvalues were �2.822 and the Tolerance statistic �0.354.

Visual inspection of the normal probability plots indicated thatthe residuals were normally distributed, and visual inspection ofthe scatter plots indicated that the assumption of linearity was metwith no substantial heteroscedasticity within our data. Thus, theassumptions underlying linear regression analyses are deemed tobe met.

We also performed moderated multiple, blockwise regressionanalyses without excluding the three outliers. Overall, these ana-lyses did not differ from the analyses excluding the outliers.However, when using HRSD residual gain scores at post-treatmentas the dependent variable, the interaction between treatment anddepersonalisation approached significance (B ¼ 0.472; SE ¼ 0.244;t ¼ 1.934; p ¼ 0.053). Visual inspection of the 20 scatterplots for

Constant .188 .183 1.024 .306 .44Treatment �.336 .230 �1.462 .144 .030

Block 2Constant �.500 .612 �.817 .414 .030Treatment �.337 .229 �1.471 .141 .030CAPS .008 .007 1.177 .239 .029

Block 3Constant �.426 .595 �.717 .474 .034Treatment �.512 .236 �2.168 .030 .023CAPS .011 .007 1.522 .128 .028Derealisation �.168 .067 �2.488 .013 .054Depersonalisation .100 .084 1.189 .235 .035

Block 4Constant �1.033 .908 �1.138 .255 .027Treatment �.474 .234 �2.024 .043 .025CAPS .021 .011 1.905 .057 .020Derealisation �.200 .087 �2.296 .022 .052Depersonalisation �.064 .126 �.511 .609 .038Treatment � CAPS �.279 .224 �1.248 .212 .029Treatment � Derealisation .165 .263 .629 .530 .051Treatment � Depersonalisation .480 .295 1.626 .104 .070

Note. CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale fordepression. B ¼ Unstandardised regression coefficient. SE ¼ Standard error.FMI ¼ Fraction of missing data.

Table 6Pooled outcome of binary logistic regression analyses with drop-out before plannedtreatment termination as the dependent variable (N ¼ 78).

B SE ta p Exp(B) FMI

Treatment .177 .606 .292 .771 1.193 .003CAPS �.011 .030 �.367 .717 .989 .008HRSD .093 .087 1.069 .285 1.098 .028Derealisation .219 .210 1.043 .297 1.245 .003Depersonalisation �.031 .327 �.095 .925 .970 .001Treatment � CAPS .250 .643 .389 .697 1.284 .005Treatment � HRSD �1.080 .680 �1.589 .112 .340 .019Treatment � Derealisation �.644 .651 �.989 .323 .525 .006Treatment � Depersonalisation .290 .722 .402 .688 1.337 .004Constant �2.230 2.296 �.971 .331 .108 .001

CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale fordepression. B ¼ Unstandardised regression coefficient. SE ¼ Standard error.FMI ¼ Fraction of missing data.

a t-values were not given in the pooled outcomes in IBM PASW Statistics 18 andthe values shown in the table above were calculated manually (t ¼ B/SE).

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e2826

HRSD residual gain score at post-treatment by depersonalisation atpre-treatment with case markers for treatment condition all indi-cated the same pattern; severe depersonalisation at pre-treatmentis associated with higher HRSD residual gain scores at post-treatment in the NET condition.

Effect sizes

Within-group Hedges g effect sizes according to the severity ofderealisation and depersonalisation at pre-treatment are presentedin Table 5. Although there are some notable differences in effectsizes across the subgroups, these differences must be interpretedwith caution due to the low number of patients in the subgroupswith moderate and severe symptoms. However, the effect sizesseem to underscore that even patients with moderate and severedissociative symptoms can achieve substantial symptom remissionon par with patients without dissociative symptoms at pre-treatment.

Clinically significant change

We also estimated the percentage of patients pooled across the20 imputed datasets that achieved clinically significant change intheir CAPS total scores from pre-treatment to follow-up based onthe severity of derealisation and depersonalisation at baseline.

In the TaU-condition, none of the patients with no or lowderealisation at pre-treatment achieved clinically significantchange from pre-treatment to follow-up. Of the patients withmoderate derealisation at pre-treatment, approximately 9% ach-ieved clinically significant change, whereas approximately 42% ofthe patients with severe derealisation at pre-treatment achievedclinically significant symptom remission from pre-treatment tofollow-up.

Approximately 45% of patients receiving NET with no or lowderealisation at pre-treatment achieved clinically significantchange. Of the patients receiving NET with moderate and severederealisation at pre-treatment, approximately 63% and 50% ach-ieved clinically significant symptom remission from pre-treatmentto follow-up, respectively.

In the TaU-condition, 14% of the patients with no or lowdepersonalisation at pre-treatment achieved clinically significantchange, whereas approximately 19% and 25% of patients withmoderate or severe depersonalisation achieved clinically signifi-cant symptom remission, respectively.

Of the patients receiving NET, approximately 50% with no or lowdepersonalisation at pre-treatment achieved clinically significantsymptom remission from pre-treatment to follow-up. Of the pa-tients with moderate or severe depersonalisation at pre-treatment,

Table 5Within-group Hedges g effect sizes based on level of derealisation and depersonalisation

CAPS pre-post

TaU Low derealisation (n ¼ 11) 0.49Moderate derealisation (n ¼ 10) 0.43Severe derealisation (n ¼ 9) 1.51Low depersonalisation (n ¼ 20) 0.55Moderate depersonalisation (n ¼ 6) 1.03Severe depersonalisation (n ¼ 4) 1.23

NET Low derealisation (n ¼ 33) 1.06Moderate derealisation (n ¼ 11) 2.40Severe derealisation (n ¼ 7) 1.36Low depersonalisation (n ¼ 42) 1.38Moderate depersonalisation (n ¼ 4) 0.85Severe depersonalisation (n ¼ 5) 0.97

Note. CAPS ¼ Clinician-administered PTSD scale. HRSD ¼ Hamilton rating scale for depr

approximately 43% and 50% achieved clinically significant changein their CAPS total scores, respectively.

Predictors of drop-out

None of the variables examined predicted drop-out fromtreatment before planned termination (see Table 6).

Discussion

The main result from this exploratory secondary analysis is thatdepersonalisation and derealisation do not seem to substantiallymoderate the treatment outcomes of either NET or TaU amongseverely traumatised asylum seekers and refugees. This is contraryto prevalent theoretical assumptions (Feeny & Danielson, 2004;Ginzburg & Neria, 2011; Lanius et al., 2010; Lanius et al., 2012;Steuwe et al., 2012; Wolf, Lunney, et al., 2012; Wolf, Miller, et al.,2012), but in line with most empirical treatment research to date(Cloitre et al., 2012; Hagenaars et al., 2010; Resick, Suvak, et al.,2012; Speckens et al., 2006; for a recent review see van Minnen,Harned, Zoellner, & Mills, 2012).

The present results substantiate and extend previous findings.Although we replicate what seems to be a rather consistent finding,that dissociative phenomena do not moderate the treatmentoutcome of exposure-based treatments for PTSD in any significantdegree, our results extend this finding to NET and among severelytraumatised asylum seekers and refugees in which a substantialminority were torture survivors. Thus, dissociative symptoms donot seem to be an overall contraindication for exposure basedtreatments for PTSD among this specific patient group.

at pre-treatment (N ¼ 81).

CAPS pre-FU HRSD pre-post HRSD pre-FU

0.50 0.40 0.850.66 �0.31 �0.051.27 1.93 0.760.65 0.46 0.550.82 1.04 0.361.09 0.64 0.57

1.24 0.52 0.362.43 1.37 1.230.98 1.02 0.511.46 0.80 0.601.41 0.16 0.230.83 0.35 0.22

ession. TaU ¼ Treatment as usual. NET ¼ Narrative exposure therapy.

J.Ø. Halvorsen et al. / Behaviour Research and Therapy 57 (2014) 21e28 27

The most consistent finding in the present study is that NET wasassociated with superior outcomes compared to TaU, except fordepressive symptoms at follow-up. No other stable predictors ormoderators of treatment outcomes emerged from the present an-alyses. While several of the variables entered in the third block ofthe models emerged as significant predictors, they were no longersignificant following the insertion of the interaction terms in thefourth block. When interaction terms are not significant, we needto decide whether to retain the interaction terms in the models orremove them (Frazier et al., 2004; Warner, 2013). Due to thetheoretically proposed importance of dissociative symptoms inpredicting treatment outcomes, we retained the interaction termsin the analyses although they were non-significant.

There are some nuances to this general finding, specifically inrelation to depressive symptoms at post-treatment. When usingHRSD residual gain score at post-treatment as the dependent var-iable, two variables emerged as significant predictors of outcomes.Both NET and derealisation predicted more depressive symptomremission at post-treatment. It is especially interesting to note thatderealisation might be related to better treatment outcomes indepressive symptomatology. However, none of the interactionterms were significant, indicating that the aforementioned vari-ables are general predictors of treatment outcomes abreast treat-ment modalities rather than specific moderators of specifictreatment modalities (Kraemer et al., 2002; Simon & Perlis, 2010). Itis difficult to speculate why derealisation might be associated withless depressive symptoms at post-treatment. One reasonableexplanation is that comorbidity is a predictor for better treatmentoutcomes (Olatunji, Cisler, & Tolin, 2010). However, it is importantto note that patients withmore severe derealisation at baseline alsohad higher HRSD total scores at baseline. Thus, the finding thatderealisation predicted greater reductions in depression severitymight be explained by the fact that these patients had more roomfor improvement in their depressive symptoms than other patientswith lower symptom severity at baseline.

Neither NET nor derealisation were significant predictors whenHRSD residual gain score at follow-up was used as the dependentvariable, indicating that these effects are either transient/tempo-rary or that the present findings are unstable. In addition, thesefindings might indicate that other variables not investigated in thepresent analyses are important for depressive symptomatology inthe long term after trauma-focused treatments for PTSD in asylumseekers and refugees.

The present paper extends previous research in several ways. Asmentioned, this is the first study to our knowledge to investigatewhether dissociative symptoms moderate treatment outcome in asample of severely traumatised asylum seekers and refugees, ofwhich a substantial minority has been tortured, residing in awestern country. Furthermore, the present paper has some meth-odological strengths (compared to earlier studies), especially withrespect to handling missing data with multiple imputation and theuse of multiple, blockwise regression analyses with interactionterms. An additional strength of the present paper is that our an-alyses are based on the specific symptoms of derealisation anddepersonalisation rather than the global construct of dissociation.In addition, we did not limit our analyses to only PTSD, but alsoanalysed the impact of these dissociative symptoms on depressivesymptomatology after treatment. And whereas all previous studiesinvestigating the impact of dissociation on treatment outcomes inPTSD consisted of samples with a vastmajority of females, from 73%(Speckens et al., 2006) to 100% (Cloitre et al., 2012; Resick, Suvak,et al., 2012), the present sample consisted of a majority of males.

However, the present paper also has several noteworthy limi-tations. Secondary analyses are prone to Type I errors and signifi-cant associations should therefore be interpreted with caution. On

the other hand, the data in the present paper was primarilycollected to investigate the differential effectiveness between NETand TaU and thus no power analysis for moderationwas conducteda priori. Furthermore, the unequal sample sizes between thetreatment arms might lower power (Frazier et al., 2004). Thus, thepresent study might not have enough power to detect significantinteraction effects. It is also important to note that the variance insymptom severity of derealisation and depersonalisation is modestand the majority of patients scored in the lower range of symptomseverity. The limited variance may be a risk factor for false-negativefindings. However, the variance in symptom severity in the presentstudy is on par or higher than in some previous published studies(e.g., Hagenaars et al., 2010). The use of single items to assessderealisation and depersonalisation is also a major limitation,although in line with previous research (Armour et al., 2014; Wolf,Lunney, et al., 2012; Wolf, Miller, et al., 2012).

Despite these potential limitations, the present paper sub-stantiates and extends previous research indicating that dissocia-tive symptoms should not be regarded as a universalcontraindication either for exposure-based treatments for PTSDspecifically or for PTSD-treatment generally.

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