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Longitudinal associations between post-traumatic distress and depressive symptoms following a traumatic event: a test of three models

Published online by Cambridge University Press:  11 January 2010

I. Schindel-Allon
Affiliation:
Psychology Department and Gonda Brain Research Center, Bar-Ilan University, Israel
I. M. Aderka
Affiliation:
Psychology Department and Gonda Brain Research Center, Bar-Ilan University, Israel
G. Shahar
Affiliation:
Psychology Department, Ben-Gurion University of the Negev, Israel Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
M. Stein
Affiliation:
The Trauma Unit, Department of General Surgery, Rabin Medical Center – Beilinson Hospital, Petach-Tikva, Israel
E. Gilboa-Schechtman*
Affiliation:
Psychology Department and Gonda Brain Research Center, Bar-Ilan University, Israel
*
*Address for correspondence: E. Gilboa-Schechtman, Ph.D., Psychology Department and Gonda Brain Research Center, Ramat Gan, Israel 52900. (Email: evagilboa@gmail.com).
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Abstract

Background

Symptoms of post-traumatic stress disorder (PTSD) and depression are highly co-morbid following a traumatic event. Nevertheless, decisive evidence regarding the direction of the relationship between these clinical entities is missing.

Method

The aim of the present study was to examine the nature of this relationship by comparing a synchronous change model (PTSD and depression are time synchronous, possibly stemming from a third common factor) with a demoralization model (i.e. PTSD symptoms causing depression) and a depressogenic model (i.e. depressive symptoms causing PTSD symptoms). Israeli adult victims of single-event traumas (n=156) were assessed on measures of PTSD and depression at 2, 4 and 12 weeks post-event.

Results

A cross-lagged structural equation modeling (SEM) analysis provided results consistent with the synchronous change model and the depressogenic model.

Conclusions

Depressive symptoms may play an important role in the development of post-traumatic symptoms.

Information

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2010
Figure 0

Table 1. Demographic and clinical measures of the total sample (n=156)

Figure 1

Table 2. Correlations between all manifest variables

Figure 2

Table 3. Loadings of the manifest variables onto their respective latent factors

Figure 3

Fig. 1. Most parsimonious model obtained by structural equation modeling (SEM) analysis. Numbers are standardized path coefficients (all p<0.001).

Figure 4

Table 4. Correlations among the latent variables