Influence of trauma type on feigned Posttraumatic Stress Disorder (PTSD) symptom profiles

ABSTRACT

Posttraumatic Stress Disorder (PTSD) is susceptible to feigning and it can be challenging to differentiate between genuine and feigned cases. Past studies have shown that in genuine cases the symptom profiles varies as a function of trauma type; but it is less clear if this variation occurs for feigned PTSD. Sixty participants were randomly assigned to one of two experimental conditions. In both conditions the participants were coached about PTSD, and then they were instructed to feign PTSD, as if for financial gain. The trigger event in the conditions was manipulated in a vignette and this was depicted as a sexual assault (SA) or a motor vehicle collision (MVC). The effects were measured via standardized measures for PTSD symptoms (PCL-5) and profile invalidity (Structured Inventory of Malingered Symptomology [SIMS]). The PCL-5 scores of the participants were indicative of PTSD. There were no statistically significant group differences on either measure at the overall or subscale level. Unlike the pattern for genuine PTSD, the symptom profile for simulated PTSD did not differ by trauma type. If understanding of these profiles can be further developed, it may assist clinicians when evaluating feigned PTSD.

KEYWORDS:

• Posttraumatic stress disorder
• trauma
• compensation
• psychopathology
• clinical psychology

Acknowledgments

The Queensland University of Technology (QUT) the provided ethical clearance for this study (HREC #: 1700000299) and approved the study risk assessment (number 685). The Queensland University of Technology funded the gift cards that were used in this study. The authors acknowledge the contribution of Elizabeth Szogi to early discussions about the design of this study.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes

1. The vignettes can be viewed in Appendix A.

2. The Fisher’s Exact Test of independence (FET) was used compare groups with very small and uneven-sized samples.

3. The missing values analysis for dependent variables revealed that 21.67% of participants were missing between 0.9 and 6.1% of data. There was a maximum of 1.7% missing data per item for continuous variables. These data were missing completely at random (Little’s MCAR, χ(765) = 44.005, p = 1.00). There was not change in the pattern of results for the imputed versus non-imputed data; therefore, the results for the imputed data set are reported.

4. Two participants did not answer this question.