Two major criticisms of the ASD diagnosis are that it is based on a theoretical construct rather than empirical evidence of the disorder it purports to describe (see Harvey & Bryant, 2002
, for a review), and it elevates a risk factor for PTSD (i.e., dissociation) to a core feature of a new disorder (Marshall et al., 1999
). The ASDS is a self-report measure based on the four-factor theoretical ASD construct that has not heretofore been subjected to a rigorous examination of its proposed four-factor structure. The present study assessed the factor structure of the ASDS and found that the proposed four-factor structure (Model 1) was not a good fit to the observed data in this sample. However, a 2-factor model that included a second-order Distress factor (Model 3), on which Reexperiencing, Arousal, and Avoidance loaded strongly, which correlated moderately strongly with a 4-item Dissociation factor fit the data well. In that model, a great deal of the variance in the first-order Reexperiencing, Arousal, and Avoidance factors was explained by the higher-order Distress factor, and error in a number of their indicators was correlated across those three first-order factors. This suggests that, in the immediate wake of a severe traumatic experience, the ASDS appears to capture the degree of distress and PTSD-like symptoms that respondents are feeling, as well as a distinct set of dissociative symptoms. However, distinctions between first-order factors corresponding to symptoms of reexperiencing, arousal, and avoidance are much less clear, as the three first-order factors seem to constitute a higher-order phenomenon. Our findings could reflect problems in the ASD construct itself, the measurement of ASD using the ASDS, or the expression or measurement of ASD in this particular population under these extreme circumstances.
If our findings are interpreted as indicative of problems with the ASD construct, then the two-factor structure we observed may somewhat strengthen theoretically-based claims that ASD’s dissociation component should be discarded in future conceptualizations of acute stress response. That is, given that dissociation is distinct from the core symptoms of PTSD that comprise the rest of the ASD construct, and its inclusion seems to impair prediction of later PTSD relative to prediction models including only the other three subscales (i.e., a major justification for establishing the diagnosis; e.g., Harvey & Bryant, 1998
; also see Isserlin, Zerach, & Solomon, 2008
, for a brief review), then perhaps it is indeed better thought of as a predictor of posttraumatic stress response rather than a diagnostic feature of ASD. Of course, without the dissociation component, ASD differs little from PTSD aside from the timing of the diagnosis vis-à-vis the traumatic event.
We believe that the lack of distinction between the three first-order symptom factors that comprised the Distress factor may have important implications for the ASD construct, as well as its measurement. First, the possibility that the symptom clusters proposed to constitute ASD are not distinct should be considered. It is possible that in the peri-traumatic period (i.e., the period immediately around the trauma), distinct symptom clusters have not yet arisen, but would become distinct for those who go on to develop PTSD. This interpretation might also hold important implications for understanding why peri-traumatic dissociation is among the strongest and most consistently reported peri-traumatic predictors of later PTSD (Ozer et al., 2003
), given that dissociation seems to be the only distinct symptom cluster. However, it should also be noted that in a recent multi-site study of ASD to PTSD prediction, cutoff scores on the Arousal subscale showed the best sensitivity and specificity for subsequent PTSD diagnosis (Bryant, Creamer, O’Donnell, Silove, & McFarlane, 2008
One could also make the case that the three symptom clusters that loaded onto the second-order Distress factor actually comprise early PTSD symptoms. In that interpretation, dissociation is merely a related phenomenon that may occur alongside PTSD symptoms within the first month post-trauma. If that is the case, then models predicting PTSD symptoms from ASDS scores show stronger relationships when dissociation is not considered because such models predict subsequent PTSD symptoms from the very same PTSD symptoms measured within the first month post-trauma. In this scenario, those relationships are better thought of as estimates of PTSD symptom stability.
In terms of the measurement of ASD using the ASDS, the measure itself seems to perform fairly well across studies, and its factor structure may be more consistent than the initial report’s EFAs (Bryant et al., 2000
) would suggest. In relation to other studies that used the ASDS, we found a high mean score for the full scale, 61.61 (SD=19.38), as compared to a mean of 44.65 (SD=15.45) for family members of critical care patients (Auerbach et al., 2007), 44.93 (SD=22.24) for accident and assault victims referred to a PTSD clinic (Bryant et al., 2000
), and 65.00 (SD=15.50) and 66.46 (SD=13.21) for accident and assault victims diagnosed with ASD
(Nixon et al., 2008
)]. This major discrepancy between sample mean scores without a corresponding discrepancy in score variance suggests that the ASDS is sensitive to a broad range of acute stress responses, and likely reflects both the horrific nature of Katrina and her aftermath and the homogeneity of participants’ experiences during the ordeal (see Mills et al., 2007
In comparison to the only other CFA of ASD symptoms (i.e., using the ASDI; Brooks et al., 2008
), our findings for model fit, factor loadings, and intercorrelations among factors were remarkably similar. The similarity is remarkable in that the samples in the two studies were markedly different and the responses on the ASDI are dichotomous, so measurement error in the indicators is not directly comparable to that of our continuous self-report indicators. As in Brooks et al. (2008)
, our final model fit reasonably well, all of the indicators loaded on their respective factors at expected magnitudes except for Item 5 (amnesia; discussed below), and the three non-Dissociation factors were very highly correlated. Our results differ from Brooks et al. (2008)
in that our four-factor model of ASD was not a good fit to the data (in part due to unspecified covariance among measurement error that may not have been present to the same degree in the ASDI’s dichotomous indicators), and we did not accept models in which factors were so highly correlated as to suggest a lack of discriminant validity. Thus, while the relationships between the DSM-IV first-order factors and their indicators, as well as among first-order factors, were very similar across our study and Brooks et al. (2008)
, we believe that our model represents a better estimate of the latent structure of ASD by explicitly modeling the higher-order factor that we believe was present in Brooks et al. (2008)
At the subscale level, most of the indicators performed well. As in Brooks et al. (2008)
, the only major problem was the dissociative amnesia item of the dissociation subscale (i.e., “Have you been unable to recall important aspects of the disaster?”), a result that was not unexpected given its performance in the initial investigation of the scale (Bryant et al., 2000
), as well as that of a similar item in studies investigating the factor structure of PTSD (e.g., Palmieri, Weathers, Difede, & King, 2007
). However, measurement errors among items within each of the subscales (except for reexperiencing) were correlated in the present study. For instance, the measurement errors in the two items of the Dissociation factor that tap perceptual irregularities were moderately correlated, suggesting that another latent construct may have been present. While this is not the only plausible explanation, competing explanations such as the presence of shared method variance seem unlikely given that all items represent self-reported symptoms modeled directly on DSM-IV-TR criteria.
This limitation, along with the problematic dissociative amnesia item, suggests that the dissociation subscale (as originally proposed) might be particularly weak as a distinct, unified construct. This further legitimizes controversy over the reliance on dissociative symptoms for the diagnosis of ASD (e.g., Marshall et al., 1999
), and arguments that such reliance may inhibit the predictive power of ASD to subsequent PTSD (Kleim, Ehlers, & Glucksman, 2007
With respect to the possibility that our results were substantially influenced by the population and extreme circumstances from which these data arise, we cannot know the extent to which the measurement issues revealed by these analyses were simply due to unique characteristics of this sample, such as the residence of participants together in a temporary community of fellow survivors or being involved in a highly publicized and political tragedy (Brinkley, 2006
). However, it behooves trauma researchers to consider the potential implications of these findings for ASD. We believe it is unlikely that our results merely reveal ASDS measurement problems, given that the items are modeled directly on DSM-IV ASD criteria and that the factor structure of the ASDS conforms so closely to that of the ASDI. We believe that it is more likely that these findings reflect difficulties with the construct of ASD itself. If our results are replicated by researchers studying ASD in other samples, it will be necessary to revisit this diagnostic classification and revise it to conform to the symptoms as they exist in samples of individuals recently exposed to trauma (or discard the diagnosis entirely). Revisions in measurement or diagnostic categorization will lead to a better understanding of the immediate and short-term impact of trauma and may lead to a better understanding of longer-term adjustment trajectories as well.
Limitations of this study must be acknowledged. While it is not unusual, given the difficulty associated with obtaining such data, for factor analytic studies of acute posttraumatic responses to have fewer participants than ideal (e.g., 120 Spanish speakers, Marshall, 2004
; 142 breast cancer survivors, Cordova et al., 2000
), the rule of thumb most often stated for sample size in CFA is 200 (Hoelter, 1983
). Thus, an awareness of the potential influence of small sample size when interpreting of our results is warranted. Our sample size was smaller than ideal, especially given our use of confirmatory factor analysis, however, artificially nonsignificant x2
values (artificial good
fit) are associated with smaller sample sizes (Kline, 2005
). That is, a significant x2
suggesting poor model fit is less likely when sample size is small (Kim, 2005
), so it is particularly unlikely that sample size was the reason that the four-factor model we tested was not a good fit to the data. The other fit indices we used for the four-factor model are not as heavily influenced by sample size (Bollen, 1990
). Indeed, our power estimates for the RMSEA test of close fit suggested that our study possessed ample power to determine whether our models were a close fit to the data. The sample size therefore appeared adequate to examine the fit of the four-factor model, and the within-subscale measurement issues discussed above appear responsible for the poor model fit we observed. Further, the 2-factor model which we found to be a good fit to the data conforms well with one diagnostic use of the scale suggested by its authors (i.e., privilege the dissociation scale in diagnosis while scoring the other subscales together, Bryant et al., 2000
) and with previous critiques concerning dissociation’s tangential relationship to the rest of the scale in ASD to PTSD prediction models (Harvey & Bryant, 1998
), and was remarkably similar to the ASDI CFA discussed above.
Another cautionary note concerns our use of modification indexes to improve model fit through allowing measurement error in indicators within each latent variable to covary. This is potentially problematic for two reasons. First, modification indexes are sample specific and may capitalize on chance covariance to improve fit. Future research should validate the intercorrelations we specified in an independent but comparable sample. Second, although the ability to explicitly model error covariance is a strength of CFA, it is generally preferable to set error covariances to 0 rather than to allow them to covary at all. Also, when error covariances are specified, they should be theoretically justified. Aside from the error covariance discussed above within the Dissociation factor, two primary theoretically justifiable patterns of error covariance were specified within the higher-order Distress factor. First, error in items tapping uncontrollable cognitive sequelae of trauma (i.e. intrusive memories, concentration deficits, and insomnia) covaried with error in items tapping efforts to control triggers for those symptoms (i.e., avoidance of talking about, being reminded of, or feeling emotions related to the trauma). Second, error in the item tapping subjective distress at reminders of the trauma covaried with error in items tapping evidence of distress (i.e., physiological reactivity and concentration deficits). We believe that the error covariances we allowed to vary were theoretically justifiable, and that our strategy of only specifying covariances among error in indicators that comprised a shared higher-order factor strengthens the case for allowing those covariances to vary. However, we are aware that many find specification of error covariances problematic.
A further limitation is that participants in this study were survivors of a very specific, complex, publicized, and ongoing (at the time of measurement) traumatic event, the features of which may have uniquely influenced the presentation of ASD in the sample. We also were unable to follow these individuals over time, so we are unable to speak to the issue of how well the ASDS predicted PTSD in our sample.
In spite of these limitations, the present findings represent the most thorough examination of the factor structure of the ASDS to date and provide important information on this scale, which has implications for the ASD construct itself. Future research is needed to expand this line of research, potentially by revising either how the ASD construct is generally measured or how it is theorized to express itself in the special case of victims of mass trauma such as natural disasters. Indeed, future research is needed to determine the utility of the diagnostic category itself.