Psychological Assessment 2014, Vol. 26, No. 4, 1155-1161

© 2014 American Psychological Association 1040-3590/14/$ 12.00 http://dx.doi.org/10.1037/a0037272

Different Profiles of Acute Stress Disorder Differentially Predict Posttraumatic Stress Disorder in a Large Sample of Female Victims of Sexual Trauma Mark Shevlin

Philip Hyland

University of Ulster and Southern University of Denmark

National College of Ireland

Ask Elklit Southern University of Denmark and University of Ulster This study aimed to test the dimensional structure of acute stress disorder (ASD). Latent profile analysis was conducted on scores from the Acute Stress Disorder Scale (Bryant, Moulds, & Guthrie, 2000) using a large sample of female victims of sexual trauma. Four distinct classes were found. Two of the classes represented high and low levels of ASD, and the high ASD class was associated with a high probability of subsequent posttraumatic stress disorder (PTSD). There were 2 intermediate classes that were differentiated by the number of arousal symptoms, and the class with high levels of arousal symptoms had a higher risk of PTSD. The results suggested that ASD is best described by qualitatively and quantitatively differing subgroups in this sample, whereas previous research has assumed ASD to be dimensional. This may explain the limited success of using ASD to predict subsequent PTSD. Keywords: acute stress disorder, posttraumatic stress disorder, latent profile analysis

Acute stress disorder (ASD) is a psychiatric condition charac­ terized by acute stress responses that may last from 2 days to 4 weeks subsequent to the experience of a traumatic life event. In addition to the experience of a traumatic life event, a diagnosis of ASD requires that a person experiences an intense emotional reaction to this stressor, along with a specific constellation of symptoms that lead to significant impairment or distress. In the newly published Diagnostic and Statistical Manual o f Mental Disorders (5th ed.; DSM-5\ American Psychiatric Association, 2013), ASD is no longer listed as an anxiety disorder but rather as a trauma- or stressor-related disorder. The DSM-5 has deemphasized the focus placed on the dissociation symptoms highlighted in the previous edition and now states that a diagnosis of ASD can be made if a person displays any nine of 14 symptoms in the areas of intrusions, negative mood, dissociation, avoidance, and arousal. ASD was introduced to the DSM -IV (American Psychiatric Association, 1994) as a condition characterized by four symptom classes; dissociation, re-experiencing, avoidance, and arousal. The introduction of ASD to the DSM -IV was done so for two reasons.

The primary purpose was to describe the acute phase of stress responses experienced by many sufferers of traumatic events prior to the time frame in which a diagnosis of posttraumatic stress disorder (PTSD) could be made. The secondary purpose was to identify those trauma survivors who were at a high risk for devel­ oping PTSD (Koopman, Classen, & Spiegel, 1994). With respect to this secondary objective of the ASD classification, a substantial body of empirical evidence has called into question the predictive utility of ASD. Accurately assessing the predictive utility of ASD necessitates the use of a psychometrically valid measure of the disorder. Unlike the assessment of PTSD in which a range of reliable and valid measures exist (see Bovin & Weathers, 2012), the assessment of ASD has been problematic given the absence of a gold standard method of assessment (see Edmondson, Mills, & Park, 2010). The Acute Stress Disorder Interview (ASDI; Bryant, Harvey, Dang, & Sackville, 1998) is a structured clinical interview based upon the diagnostic criteria outlined in DSM-IV. ASDI scores have been shown to possess satisfactory internal consis­ tency (Cronbach’s a = .90) as well as test-retest reliability (r = .88). A subsequent confirmatory factor analytic (CFA) study indi­ cated that the latent structure of the ASDI is best represented by the four-factor model outlined in the DSM -IV (Brooks et al., 2008). In addition to the ASDI, two self-report measures of ASD are commonly employed. The Stanford Acute Stress Reaction Ques­ tionnaire (SASRQ; Cardena, Koopman, Classen, Waelde, & Spie­ gel, 2000) has been used in a number of studies (e.g., Classen, Koopman, Hales, & Spiegel, 1998; Koopman, Classen, & Spiegel, 1994), and the scores have demonstrated good internal reliability (Cronbach’s as = .90 and .91, respectively) as well as good concurrent validity with scores on the Impact of Events Scale (r =

This article was published Online First June 30, 2014. Mark Shevlin, School of Psychology and Psychology Research Institute, University of Ulster, and National Center of Psychotraumatology, Univer­ sity of Southern Denmark; Philip Hyland, School of Business, National College of Ireland; Ask Elklit, National Center of Psychotraumatology, University of Southern Denmark, and School of Psychology and Psychol­ ogy Research Institute, University of Ulster. Correspondence concerning this article should be addressed to Mark Shevlin, School of Psychology and Psychology Research Institute, Uni­ versity of Ulster, Magee Campus, Co. Londonderry BT48 7JL, United Kingdom. E-mail: [email protected]

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.52-69; see Cardena et al., 2000). The most recently developed and widely used self-report measure of ASD is the Acute Stress Disorder Scale (ASDS; Bryant, Moulds, & Guthrie, 2000), and scores on the scale have been shown to have high test-retest reliability (r = .94), sensitivity (95%), and specificity (83%). Results from CFA studies to determine the latent structure of ASDS scores have been inconsistent. Wang, Li, Shi, Zhang, and Shen (2010) found support for the DSM -IVs four-factor concep­ tualization, whereas Edmondson et al. (2010) supported a hierar­ chical model containing a second-order distress factor (with re­ experiencing, arousal, and avoidance first-order factors) that was correlated with a dissociation single first-order factor. Other stud­ ies have supported a three-factor model (dissociation, avoidance, and re-experiencing/arousal; Armour, Elklit, & Shevlin, 2013) and the DSM -IVs four-factor model (Hansen, Lasgaard, & Elklit, 2013). Initially, there was evidence that a diagnosis of ASD could be used to effectively predict the subsequent development of PTSD (Harvey & Bryant, 1998, 1999; Spiegel, Koopman, Cardena, & Classen, 1996). However, more recent findings began to challenge this conclusion. For example, in a longitudinal study of cancer patients, Kangas, Henry, and Bryant (2005) found that 53% of individuals diagnosed with ASD subsequently met the criteria for PTSD 6 months later; however, only 36% of those who developed PTSD satisfied the criteria for ASD during the immediate aftermath of their traumatic experience. The limited positive predictive power and poor sensitivity of ASD in this study were consistent with other findings (e.g., Brewin, Andrews, & Rose, 2003; Bryant, 2003; Harvey & Bryant, 2002). Bryant (2011) recently conducted a large-scale meta-analysis to determine the ability of ASD to predict subsequent PTSD. The review included 22 longitudinal studies consisting of a total of 3,335 participants for whom follow-up data were available. The results served to further under­ mine the utility of ASD to predict PTSD. ASD was found to have modest positive predictive power, with the majority of studies demonstrating that only 50% of individuals who received a diag­ nosis of ASD subsequently developed PTSD. The sensitivity of ASD was also found to be poor, with just 48% of those who eventually received a diagnosis of PTSD initially satisfying the criteria for ASD in the first month posttrauma. These results served to demonstrate that an ASD diagnosis fails to identify more than half of all individuals who subsequently develop PTSD. A number of plausible explanations have been advanced for the poor predictive ability of ASD. Bryant’s (2011) review indicated that the sensitivity of ASD could be improved by adopting a subsyndromal classification in which the dissociation criteria were ignored. By adopting a conceptualization of ASD that more closely represents the PTSD diagnostic model, the predictive ability of ASD was found to be improved. It has also been suggested that the less-restrictive diagnostic criteria for ASD relative to PTSD, par­ ticularly with respect to the arousal and avoidance symptoms, is a cause of the poor predictive power. The less-restrictive diagnostic criteria for ASD means that while a person could meet the criteria for ASD 3 weeks posttrauma, that person would not meet the criteria for PTSD 1 week later, even if his or her symptoms remained constant (Bryant, Friedman, Spiegel, Ursano, & Strain, 2011). In light of the evidence that ASD fails to adequately predict the subsequent development of PTSD, Bryant et al, (2011) have

recommended abandoning the predictive role of ASD and in­ stead solely focusing on ASD as a method of capturing acute stress responses to traumatic life events. However, the failure of ASD to predict subsequent PTSD may be due to the underlying assumption that ASD is dimensional in nature, that is, that people diagnosed with ASD differ only quantitatively. The assumption that differences in severity of disorders can only be described quantitatively has been challenged by recent studies that have reported different “types” of PTSD. For example, Maguen et al. (2013) conducted a latent class analysis of PTSD symptoms using a sample of veterans from the Iraq and Af­ ghanistan wars and found three groups that differed quantita­ tively in symptom severity (high-symptom, intermediatesymptom, and low-symptom groups). The fourth group was similar to the intermediate-symptom group but differed quali­ tatively due to having very low probabilities of endorsing three emotional numbing symptoms; this group was labeled as inter­ mediate symptom with low emotional numbing. Similarly, Wolf et al. (2012) conducted a latent class analysis on items from the Clinician-Administered PTSD Scale (Weathers, Ruscio, & Keane, 1999) using a sample of veterans and argued for a dissociative subtype of PTSD based on a small group that had elevated probabilities of endorsing the symptoms related to flashbacks, derealization, and depersonalization. These studies suggest that PTSD may not be dimensional; rather it could be that those suffering from PTSD comprise groups that differ qualitatively and quantitatively. There have been no similar studies on ASD to determine if the underlying latent variable is dimensional or categorical. If ASD was found to be best de­ scribed by groups that differ qualitatively rather than quantita­ tively in overall severity, this may go some way in explaining the poor predictive power of ASD in predicting PTSD. Partic­ ular profiles, or configurations, of symptom severity may confer greater risk of PTSD than others, even when the overall levels of severity are similar. The aim of this study- was to test the underlying structure of ASD symptoms using data from a large sample of female sexual trauma victims using latent profile analysis (LPA) and to assess the relationship with PTSD. LPA is a method for identifying homogeneous groups, or latent classes, that share similar symp­ tom profiles. It was predicted that there would be classes that differed quantitatively, with those classes higher in ASD sever­ ity having a higher probability of subsequently developing PTSD. The relationship between the classes and the probability of PTSD should be “dose-response” in nature. It is also pre­ dicted that there may be classes that are qualitatively different to the other classes and that association with PTSD for these classes would be inconsistent with the dose-response relation­ ship of the quantitatively differing classes. This aspect of the study is exploratory as existing research findings and theory are insufficient to guide specific hypotheses about qualitatively different classes. Large-scale meta-analysis (Brewin, Andrews, & Valentine, 2000) and multisample studies (Ditlevsen & Elklit, 2010) have indicated that younger age at exposure to a traumatic event is related to higher levels of posttraumatic stress severity. As similar findings have been reported for acute stress severity (Cardena, Dennis, Winkel, & Skitka, 2005; Co­ hen, 2008), age was used a covariate in the LPA.

PTSD IN SEXUAL TRAUMA VICTIMS

Method Participants Participants were recruited from the 1,127 female rape victims who contacted the Center for Rape Victims (CRV) at the Univer­ sity Hospital of Aarhus (Denmark) from 2002 to 2012. The CRV offers help to victims who contact the center within 30 days after being raped. During the initial contact (Tl), victims were asked to provide demographic information and details on a number of assault-related issues. Within 2 weeks after coming into contact with the center (T2), the participants were asked to complete a short battery of questionnaires, one of which assessed acute stress disorder (ASD). Approximately 3 months later (T3), participants were asked to fill out another questionnaire that assessed symp­ toms of PTSD. Information on age was available for all partici­ pants at T l (N = 590), and complete data at T2 and T3 were available for 471 and 352 participants, respectively. The pairwise percentage of data present was high between age (Tl) and T2 scores for dissociation (80%), re-experiencing (82%), avoidance (82%), and arousal (80%). The pairwise percentage of data present was lower between PTSD scores (T3) and age (60%), dissociation (43%), re-experiencing (44%), avoidance (44%), and arousal (43%). Listwise deletion would result in a sample size of 237; however, full-information maximum-likelihood estimation allows all the available information on 590 participants (for whom data were available at T l and either T2 or T3) to be used in the analyses as “missingness” is only on the endogenous variables under the assumption of data being missing at random (Schafer & Graham,

2002). Most victims (61.5%) had experienced an assault that involved penetration. Other victims had primarily been exposed to at­ tempted rape (12.3%) or molestation (8.7%) or could not remem­ ber the specific type of assault they had experienced (9.2%). Most (85.5%) were of Danish origin, and their ages ranged from 10 to 71 years. The mean age of the sample was 22.49 years (SD = 9.2). This sample was significantly older than the remaining women who visited the CRV, r( 1125) = 3.71, p < .001, and were not included in the study, although the difference was small (2.35 years).

Measures The Acute Stress Disorder Scale (ASDS; Bryant et al., 2000). The ASDS is a 19-item self-report measure based on the DSM -IV diagnostic criteria of dissociation (five items), re-experiencing (four items), avoidance (four items), and arousal (six items) symp­ toms. The ASDS has a 5-point Likert scale ranging from 1 (not at all) to 5 (very much). Individual item scores were recoded to indicate the absence (score s 3 = 0) or presence (score > 4 = 1 ) of a symptom, and a summed total symptom score for dissociation (possible scores 0-5), re-experiencing (possible scores 0 -4 ), avoidance (possible scores 0 -4 ), and arousal (possible scores 0 -6 ) was calculated. A DSM-IV diagnosis of ASD requires at least one symptom to be present for re-experiencing, avoidance, and arousal, and three symptoms to be present for dissociation. Bryant et al. (2000) showed that the subscales of the ASDS were highly correlated with the subscales of the ASDI, ranging from .69 for dissociation to .84 for arousal. Furthermore, the ASDS was

1157

reported to have satisfactory sensitivity (.95) and specificity (.83) in detecting ASD as determined by the ASDI. Bryant et al. (2000) reported high levels of internal consistency (Cronbach’s a) for the total scale (.96) and for the subscales (dissociation = .84, re­ experiencing = .87, avoidance = .92, arousal = .93). Alpha coefficients in this study were lower (total scale = .84, dissocia­ tion = .69, re-experiencing = .66, avoidance = .66, and arousal = .75). The Harvard Trauma Q uestionnaire-Part IV (HTQ: Mollica et al., 1992). The HTQ can be used to identify partici­ pants reporting symptoms consistent with DSM -IV PTSD diag­ nostic criteria and also provides a measure of PTSD severity. The first 16 items were derived directly from the 17 DSM -IV criteria for PTSD. The HTQ uses one item to assess both psychological and physiological reactions to events that symbolize or resemble aspects of the traumatic event (in accordance with DSM-IV, this item is part of the re-experiencing cluster). The items are divided into three subscales that correspond to the three main symptom groups of PTSD: re-experiencing, avoidance, and arousal. The HTQ requires the respondents to rate how much each symptom has bothered them in the last week on a 4-point Likert-type scale (1 = not at all, 4 = all the time). Mollica et al. (1992) and Elklit and Shevlin (2007) reported high estimates of reliability for each of the subscales and the scale as a whole. Participants with high likeli­ hood of a diagnosis of PTSD were identified if they reported at least one re-experiencing symptom, three avoidance symptoms, and two arousal symptoms as being present. A symptom was rated as present if the item corresponding to the symptom was scored 3 (quite a bit) or greater. Mollica et al. (1992) reported 88% con­ cordance between those reporting symptoms consistent with PTSD diagnostic criteria based on the HTQ and a diagnostic interview to assess PTSD. In this study, the internal consistency of the total scale and the three subscales scores were high (Cronbach’s as in parentheses): total scale (.84), re-experiencing (.77), avoidance (.77), and arousal (.80).

Analysis Latent profile analysis (LPA) is a statistical method used to identify homogeneous groups, or classes, from multivariate data. The analysis involved three linked elements. First, a LPA was conducted to determine the number of classes of ASD and assess if they differed qualitatively or quantitatively. In the LPA part of the model, the four total symptom scores are used for each of the four ASD dimensions. This ensured that scores captured clinically meaningful responses and also provided the necessary score vari­ ability for the analysis. Second, age was included in the model as a covariate, and third the PTSD variable was a distal outcome. The fit of five models (two-class model through to six-class model) was assessed. The models were estimated using robust maximum likelihood (Yuan & Bender, 2000). To avoid solutions based on local maxima, we used 500 random sets of starting values initially and 100 final-stage optimizations. The relative fit of the models were compared using three information-theory-based fit statistics: the Akaike information criterion (AIC; Akaike, 1987), the Bayesian information criterion (BIC; Schwarz, 1978), and sample-size-adjusted Bayesian information criterion (ssaBIC; Sclove, 1987). The model that produces the lowest values can be judged the best model. Evidence from simulation studies has

SHEVLIN, HYLAND, AND ELKLIT

1158

indicated that the BIC was the best information criterion for identifying the correct number of classes (Nylund, Asparouhov, & Muthen, 2007). In addition, the Lo-Mendell-Rubin adjustedlikelihood ratio test (LMR-A; Lo, Mendell, & Rubin, 2001) and the bootstrapped likelihood ratio test (BLRT; McLachlan & Peel, 2000) were used to compare models with increasing numbers of latent classes. When a nonsignificant value (p > .05) occurs, this suggests that the model with one less class should be accepted. All analyses were conducted using Mplus Version 7.00 (Muthen & Muthen, 2012).

Results Most of the participants reported one or more symptoms of dissociation (77.5%; M = 3.50, SD = 1.36), re-experiencing (93.8%; M = 2.45, SD = 1.21), and avoidance (91.9%; M = 2.59, SD = 1.25), and three or more symptoms of arousal (97.7%; M = 4.17, SD = 1.65), while 68.8% reported combined symptoms consistent with ASD diagnostic criteria. Almost half of the partic­ ipants (48.3%) who completed the HTQ (A = 352) reported symptoms consistent with PTSD diagnostic criteria. A cross­ tabulation of variables representing ASD and PTSD was statisti­ cally significant, x2(U N = 237) = 16.11, p < .01, and indicated that 79.8% of those with a high likelihood of PTSD initially reported symptoms consistent with ASD diagnostic criteria, and 45.1% failed to meet the diagnostic criteria for PTSD and ASD. The percentage of participants with a high likelihood of ASD but who did not meet the diagnostic criteria for PTSD was 54.9%, and 20.2% of individuals did not report symptoms consistent with ASD or PTSD. The fit statistics for the LPA are presented in Table 1. The BIC is lowest for the four-class model, and the LMR-A indicated that there was no significant improvement in fit for the five-class model. However, the AIC and the ssaBIC both decrease for models with two to six classes; however the decrease is markedly smaller after four classes. The BLRT values were similar to those for the LMR-A but remained statistically significant for all models. Al­ though the BLRT has been reported to perform well in a simula­ tion study (Nylund et al., 2007), it also has been reported to be inconsistent with the LMR-A by remaining statistically nonsignif­ icant (Jager & Muthen, 2009). On the basis of this information, the four-class solution was considered the best-fitting model. Figure 1 shows the profile plot for the four-class solution. Class 4 (N = 299, 50.7%) was the largest and was characterized by high mean scores on all ASD symptom clusters. This class was labeled high ASD. Class 3 (N — 46, 7.8%) was the smallest and was characterized by low mean scores on all ASD symptom clusters.

This class was labeled low ASD. There were two intermediate classes that were similar in the mean number of dissociation and re-experiencing symptoms. Class 2 (N = 87, 14.7%) differed from Class 1 with a lower number of avoidance symptoms and higher number of arousal symptoms and was labeled low avoidance-high arousal. Class 1 was labeled intermediate class (N = 158, 26.8%). The association between age and class membership was esti­ mated as a multinomial logistic regression. With the low ASD class as a reference category, age significantly decreased the likelihood of membership in the intermediate class— odds ratio (OR) = 0.93, 95% confidence interval (Cl) [.88, .99], p < .05— but did not significantly predict membership of the other two classes. Table 2 shows the conditional probabilities for having a high likelihood of PTSD diagnosis based on class membership. For the low-ASD group, the probability was not significantly different from zero, and for the high-ASD group, the probability was high (Pr = .701). For the two intermediate groups, the low-avoidancehigh-arousal group had a higher probability than the intermediate group, and the difference in the probabilities equates to the lowavoidance-high-arousal group being almost three times more likely to report symptoms consistent with PTSD diagnostic criteria than the intermediate group, OR = 2.97, 95% Cl [1.20, 7.35], p < .05.

Discussion The primary purpose of the current study was to investigate the assumed dimensional structure of ASD. In order to test our hy­ pothesis of the presence of both quantitatively and qualitatively distinct latent classes of ASD, we conducted LPA on data from the ASDS (Bryant et al., 2000) based on a large sample of female sexual trauma victims. Results indicated the presence of four latent classes. The high-ASD class was the largest group, accounting for slightly more than half of the sample. These participants displayed high levels of dissociation, re-experiencing, avoidance, and arousal symptoms. The low-ASD class included the fewest number of participants, and this class exhibited low levels of each of the four symptoms groups. Two intermediate classes were observed, one of which comprised a group of individuals who displayed moderate levels of dissociation, re-experiencing, and arousal symptoms and comparatively higher levels of avoidance symptoms (intermediate class). The second intermediate class (low-avoidance-higharousal) was comparable to the intermediate class in that partici­ pants displayed moderate levels of dissociation and re­ experiencing symptoms; however, this class was characterized by very low level of avoidance symptoms, akin to those observed in

Table 1 Fit Statistics fo r the Latent Profile Analysis o f Acute Stress Disorder and Posttraumatic Stress Disorder Model

Log-likelihood

AIC

BIC

ssaBIC

LMR-A

P

BLRT

P

Two-class Three-class Four-class Five-class Six-class

-3332.70 -3286.98 -3249.91 -3237.10 -3223.16

6695.41 6615.97 6553.82 6540.21 6524.33

6761.11 6707.95 6672.08 6684.76 6695.15

6713.49 6641.28 6586.36 6579.99 6571.34

406.10 89.10 72.26 24.95 27.17

.00 .00 .01 .58 .23

416.71 91.43 74.15 25.60 27.88

.00 .00 .00 .00 .00

Note. AIC = Akaike information criterion; BIC = Bayesian information criterion; ssaBIC = sample size adjusted Bayesian information criterion; LMR-A = Lo-Mendell-Rubin sample-size-adjusted likelihood ratio test; BLRT = bootstrapped likelihood ratio test.

PTSD IN SEXUAL TRAUMA VICTIMS

1159

6

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i

4

-

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o

’

/

( S 2 .4 % ) # * ^ ^ (82.4% )».

b

m

(100%)

d o o m /

C100%)

{69.4%}*. ----- + (98.3%)

£ I 2 ''V

(7 3 .3 % )/

(79.1%)

(73.3%) (64,4%)

D issociation

Re-experiencing

—* - C l a $ s i (26.8%)

3.05

1.58

3.OS

2.74

- • - C l a s s 2 (14.7%)

3.56

2.41

1.05

4.35

—• —C la ss3 (7.8%)

1.58

1.18

0.93

1.61

- ♦ - C l a s s 4 (50 7%)

4.1 3

3.22

3.31

5.39

Avoidance

Arousal

Figure 1. Profile plot showing mean acute stress disorder(ASD) scores and percentages meeting diagnostic criteria in each class. Class 4 (labeled high ASD\ N = 299, 50.7%) was the largest and was characterized by high mean scores on all ASD symptom clusters. Class 3 (labeled low ASD\ N = 46, 7.8%) was the smallest and was characterized by low mean scores on all ASD symptom clusters. Two intermediate classes similar in the mean number of dissociation and re-experiencing symptoms: Class 2 (N = 87, 14.7%) differed from Class 1 with a lower number of avoidance symptoms and higher number of arousal symptoms and was labeled low avoidancehigh arousal. Class 1 was labeled intermediate class (N = 158; 26.8%).

the low-ASD class, and very high levels of arousal symptoms, similar to those observed within the high-ASD class. The symptom profiles for the high-ASD and low-ASD classes were similar and suggest a quantitative distinction between these classes. Contrastingly, the intermediate and low-avoidance-high arousal classes displayed qualitatively distinct symptom profiles from each other, and each class also possessed qualitatively dis­ tinct profiles from the high- and low-ASD classes, respectively. These findings are consistent with the study’s initial hypothesis and provide the first piece of empirical evidence that the latent structure of ASD is best explained by qualitatively and quantita­ tively differing subgroups rather than dimensional scores. Current results are therefore congruent with recent findings from the wider trauma literature that suggests that PTSD is not dimensional but is rather composed of a series of qualitatively distinct classes or subtypes (e.g., Maguen et al., 2013; Shevlin & Elklit, 2012; Wolf et al., 2012). Table 2 Conditional Probability o f PTSD Diagnosis Based on Class Membership

Class 1. 2. 3. 4.

Intermediate Low-avoidance-high-arousal Low-ASD High-ASD

Probability of PTSD conditional on class membership

SE

P

.247 .493 .114 .701

.062 .073 .075 .047

.00 .00 .13 .00

Note. PTSD = posttraumatic stress disorder; SE = standard error; ASD = acute stress disorder.

Probabilities of reporting symptoms consistent with PTSD diagnostic criteria were subsequently investigated based upon membership of each of the four classes. With respect to the quantitatively distinct classes (the high-ASD and low-ASD classes), a clear dose-response effect was observed. Individuals belonging to the low-ASD class had a probability of developing PTSD that was not significantly different from zero, whereas membership of the high-ASD class conferred a 70% probability of developing PTSD. Also in line with predictions, the proba­ bilities of self-reported PTSD based upon membership of the two qualitatively differing intermediate classes did not follow a traditional dose-response relationship. Individuals belonging to the intermediate class had a 25% probability of developing PTSD, whereas the probability for the low-avoidance-higharousal class twice as high (49%). The results indicate that although individuals in each of the two intermediate classes experience very similar overall levels of dis­ tress, a person’s risk of later developing PTSD is doubled if they report experiencing high levels of arousal. The LPA showed that it is the combinations of high levels of arousal and low levels of avoidance that define members of this class, and variable-centered rather than person-centered analyses could not have identified this factor. This suggests that symptoms of arousal, rather than symp­ toms of dissociation, may be the most critical factor in the predic­ tion of PTSD. Previous findings have suggested that improvements in the classification of ASD, and its predictive power, could be obtained by shifting the emphasis from dissociation to arousal symptoms (Brewin, Andrews, Rose, & Kirk, 1999; Harvey & Bryant, 1999). Current and past findings therefore support the recent revisions to the diagnostic criteria in DSM -5, which has

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eliminated the emphasis placed on dissociation symptoms as the primary symptom cluster of ASD. The present study has a number of important implications for clinical practice. Current findings indicate that increased levels of physiological arousal in the immediate aftermath of a trauma are the most prominent factor in identifying those who are most vulnerable to PTSD. Therefore, when performing initial risk as­ sessments, clinicians should be cognizant that simply determining overall symptom severity is not sufficient for identifying those who are most at risk of developing PTSD. Clinicians would be advised to instead take a more symptom-specific perspective, particularly with respect to the arousal symptoms, in order to identify those who have the highest risk of developing PTSD. Moreover, treatment strategies that serve to reduce levels of arousal in the acute phase following exposure to trauma would appear prudent as such strategies would substantially reduce an individual’s likelihood of going on to develop PTSD. Conclusions drawn from the current study must necessarily be considered in light of a number of limitations. First, the nature of the sample is limited to a very specific group of trauma victims who characteristically display high levels of ASD and PTSD symptomology. Replication of the current analysis with more diverse trauma populations is clearly warranted. Additionally, par­ ticipants were recruited from the Danish population; therefore, it is unknown whether current results would generalize to other popu­ lations. Second, the analyses for the current study were based upon the use of self-report measures of ASD (ASDS; Bryant et al., 2000) and PTSD (HTQ; Mollica et al., 1992). Clinician based measures such as the ASDI (Bryant et al., 1998) and the ClinicianAdministered PTSD scale (Blake et al., 1995) would have been preferable. Third, the reliability of the ASDS subscales were low compared with those reported in previous ASD studies. This may be attributable to the varied forms of sexual victimization experi­ enced by the participants, whereas previous samples have experi­ enced the same event (e.g., survivors of bushfires; Bryant et al., 2000).

In conclusion, we found that symptom endorsement that is consistent with ASD has strong predictive power for identifying female sexual trauma victims who later have a high likelihood of a diagnosis of PTSD. Additionally, we found the latent structure of ASD to consist of a series of distinct classes that differed not only quantitatively but also qualitatively. It was notable that although the two intermediate classes were comparable in overall severity of ASD, their unique symptom profiles resulted in substantially dif­ ferent probabilities of developing PTSD. A clear pattern was identified across the four latent classes, which indicated that higher levels of arousal symptoms were associated with increased prob­ abilities of being diagnosed with PTSD. These results offer addi­ tional evidence that arousal symptoms, rather than dissociation symptoms, are the most important component of ASD in predict­ ing the subsequent emergence of PTSD.

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Received May 16, 2013 Revision received April 28, 2014 Accepted May 16, 2014 ■

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