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Changes in the dynamic network structure of PTSD symptoms pre-to-post combat

Published online by Cambridge University Press:  28 March 2019

Adva Segal*
Affiliation:
School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
Ilan Wald
Affiliation:
School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
Gad Lubin
Affiliation:
Division of Mental Health, Medical Corps, Israel Defense Forces, Ramat Gan, Israel
Eyal Fruchter
Affiliation:
Division of Mental Health, Medical Corps, Israel Defense Forces, Ramat Gan, Israel
Keren Ginat
Affiliation:
Division of Mental Health, Medical Corps, Israel Defense Forces, Ramat Gan, Israel
Ariel Ben Yehuda
Affiliation:
Division of Mental Health, Medical Corps, Israel Defense Forces, Ramat Gan, Israel
Daniel S. Pine
Affiliation:
National Institutes of Mental Health, Bethesda, Maryland, USA
Yair Bar-Haim
Affiliation:
School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
*
Author for correspondence: Adva Segal, E-mail: advasegal@tau.ac.il

Abstract

Background

Combat exposure is associated with elevated risk for post-traumatic stress disorder (PTSD). Despite considerable research on PTSD symptom clustering, it remains unknown how symptoms of PTSD re-organize following combat. Network analysis provides a powerful tool to examine such changes.

Methods

A network analysis approach was taken to examine how symptom networks change from pre- to post-combat using longitudinal prospective data from a cohort of infantry male soldiers (Mage = 18.8 years). PTSD symptoms measured using the PTSD Checklist (PCL) were assessed after 6 months of combat training but before deployment and again after 6 months of combat (Ns = 910 and 725 at pre-deployment and post-combat, respectively)

Results

Stronger connectivity between PTSD symptoms was observed post-combat relative to pre-deployment (global strength values of the networks were 7.54 pre v. 7.92 post; S = .38, p < 0.05). Both the re-experiencing symptoms cluster (1.92 v. 2.12; S = .20, p < 0.03) and the avoidance symptoms cluster (2.61 v. 2.96; S = .35, p < 0.005) became more strongly inter-correlated post-combat. Centrality estimation analyses revealed that psychological reaction to triggers was central and linked the intrusion and avoidance sub-clusters at post-combat. The strength of associations between the arousal and reactivity symptoms cluster remained stable over time (1.85 v. 1.83; S = .02, p = .92).

Conclusions

Following combat, PTSD symptoms and particularly the re-experiencing and avoidance clusters become more strongly inter-correlated, indicating high centrality of trigger-reactivity symptoms.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2019

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References

American Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental Health Disorders (DSM-III-R). Washington, DC: American Psychiatric Association.Google Scholar
American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5, 5th Edn. Washington, DC: American Psychiatric Association.Google Scholar
Armour, C, Tsai, J, Durham, TA, Charak, R, Biehn, TL, Elhai, JD and Pietrzak, RH (2015) Dimensional structure of DSM-5 posttraumatic stress symptoms: support for a hybrid Anhedonia and Externalizing Behaviors model. Journal of Psychiatric Research 61, 106113.CrossRefGoogle ScholarPubMed
Armour, C, Fried, EI, Deserno, MK, Tsai, J and Pietrzak, RH (2017) A network analysis of DSM-5 posttraumatic stress disorder symptoms and correlates in U.S. military veterans. Journal of Anxiety Disorders 45, 4959.CrossRefGoogle ScholarPubMed
Blanchard, EB, Jones-Alexander, J, Buckley, TC and Forneris, CA (1996) Psychometric properties of the PTSD checklist (PCL). Behaviour Research and Therapy 34, 669673.CrossRefGoogle Scholar
Borsboom, D and Cramer, AOJ (2013) Network analysis: an integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology 9, 91121.CrossRefGoogle ScholarPubMed
Boschloo, L, Van Borkulo, CD, Rhemtulla, M, Keyes, KM, Borsboom, D and Schoevers, RA (2015) The network structure of symptoms of the diagnostic and statistical manual of mental disorders. PLoS ONE 10, e0137621.CrossRefGoogle Scholar
Briganti, G, Kempenaers, C, Braun, S, Fried, EI and Linkowski, P (2018) Network analysis of empathy items from the Interpersonal Reactivity Index in 1973 young adults. Psychiatry Research 265, 8792.CrossRefGoogle ScholarPubMed
Bryant, RA, Creamer, M, O'Donnell, M, Forbes, D, McFarlane, AC, Silove, D and Hadzi-Pavlovic, D (2017) Acute and chronic posttraumatic stress symptoms in the emergence of posttraumatic stress disorder: a network analysis. JAMA Psychiatry 74, 135142.CrossRefGoogle ScholarPubMed
Ehlers, A and Clark, DM (2000) A cognitive model of posttraumatic stress disorder. Behaviour Research and Therapy 38, 319345.CrossRefGoogle ScholarPubMed
Elhai, JD, Ford, JD, Ruggiero, KJ and Frueh, BC (2009) Diagnostic alterations for post-traumatic stress disorder: examining data from the National Comorbidity Survey Replication and National Survey of Adolescents. Psychological Medicine 39, 19571966.CrossRefGoogle ScholarPubMed
Elhai, JD, Biehn, TL, Armour, C, Klopper, JJ, Frueh, BC and Palmieri, PA (2011) Evidence for a unique PTSD construct represented by PTSD's D1–D3 symptoms. Journal of Anxiety Disorders 25, 340345.CrossRefGoogle ScholarPubMed
Engdahl, RM, Elhai, JD, Richardson, JD and Frueh, BC (2011) Comparing posttraumatic stress disorder's symptom structure between deployed and nondeployed veterans. Psychological Assessment 23, 1.Google ScholarPubMed
Epskamp, S, Borsboom, D and Fried, EI (2018) Estimating psychological networks and their accuracy: a tutorial paper. Behavior Research Methods 50, 195212.CrossRefGoogle ScholarPubMed
Foa, EB and Rothbaum, BO (1998) Treating the Trauma of Rape: Cognitive Behavioral Therapy for PTSD. New York: Guilford Press.Google Scholar
Foa, EB, Hembree, E and Rothbaum, B (2007) Prolonged Exposure Therapy for PTSD: Emotional Processing of Traumatic Experiences. New York, NY: Oxford University PressGoogle Scholar
Friedman, MJ, Keane, TM and Resick, PA (2007) Handbook of PTSD: Science and Practice. New York: The Guilford Press.Google Scholar
Friedman, J, Hastie, T and Tibshirani, R (2008) Sparse inverse covariance estimation with the graphical lasso. Biostatistics (Oxford, England) 9, 432441.CrossRefGoogle ScholarPubMed
Friedman, MJ, Kilpatrick, DG and Schnurr, PP (2016) Changes to the definition of posttraumatic stress disorder in the DSM-5 – reply. JAMA Psychiatry 73, 1203.CrossRefGoogle ScholarPubMed
Fruchterman, TM and Reingold, EM (1991) Graph drawing by force‐directed placement. Software: Practice and Experience 21, 11291164.Google Scholar
Guina, J (2016) Changes to the definition of posttraumatic stress disorder in the DSM-5. JAMA Psychiatry 73, 12011202.CrossRefGoogle ScholarPubMed
Hofmann, SG, Curtiss, J and McNally, RJ (2016) A complex network perspective on clinical science. Perspectives on Psychological Science 11, 597605.CrossRefGoogle ScholarPubMed
Hoge, CW (2016) Changes to the definition of posttraumatic stress disorder in the DSM-5 – reply. JAMA Psychiatry 73, 12021203.CrossRefGoogle ScholarPubMed
Hoge, CW, Castro, CA, Messer, SC, McGurk, D, Cotting, DI and Koffman, RL (2004) Combat duty in Iraq and Afghanistan, mental health problems, and barriers to care. New England Journal of Medicine 351, 1322.CrossRefGoogle ScholarPubMed
Hoge, CW, Yehuda, R, Castro, CA, McFarlane, AC, Vermetten, E, Jetly, R, Koenen, KC, Greenberg, N, Shalev, AY, Rauch, SA and Marmar, CR (2016) Unintended consequences of changing the definition of posttraumatic stress disorder in DSM-5 critique and call for action. JAMA Psychiatry 73, 750752.CrossRefGoogle ScholarPubMed
Horowitz, MJ (1986) Stress-response syndromes: a review of posttraumatic and adjustment disorders. Psychiatric Services 37, 241249.CrossRefGoogle ScholarPubMed
Keane, TM, Zimering, RT and Caddell, JM (1985) A behavioral formulation of posttraumatic stress disorder in Vietnam veterans. Behavior Therapist 8, 912.Google Scholar
King, DW, Leskin, GA, King, LA and Weathers, FW (1998) Confirmatory factor analysis of the clinician-administered PTSD Scale: evidence for the dimensionality of posttraumatic stress disorder. Psychological Assessment 10, 90.CrossRefGoogle Scholar
Liu, P, Wang, L, Cao, C, Wang, R, Zhang, J, Zhang, B, Wu, Q, Zhang, H, Zhao, Z, Fan, G and Elhai, JD (2014) The underlying dimensions of DSM-5 posttraumatic stress disorder symptoms in an epidemiological sample of Chinese earthquake survivors. Journal of Anxiety Disorders 28, 345351.CrossRefGoogle Scholar
McFarlane, AC (1992) Avoidance and intrusion in posttraumatic stress disorder. Journal of Nervous and Mental Disease 180, 439445.CrossRefGoogle ScholarPubMed
McNally, RJ, Robinaugh, DJ, Wu, GWY, Wang, L, Deserno, MK and Borsboom, D (2015) Mental disorders as causal systems: a network approach to posttraumatic stress disorder. Clinical Psychological Science 3, 836849.CrossRefGoogle Scholar
Opsahl, T, Agneessens, F and Skvoretz, J (2010) Node centrality in weighted networks: generalizing degree and shortest paths. Social Networks 32, 245251.CrossRefGoogle Scholar
Rubin, DC, Berntsen, D and Johansen, MK (2008) A memory based model of posttraumatic stress disorder: evaluating basic assumptions underlying the PTSD diagnosis. Psychological Review 115, 9851011.CrossRefGoogle ScholarPubMed
Santos, HP Jr, Kossakowski, JJ, Schwartz, TA, Beeber, L and Fried, EI (2018). Longitudinal network structure of depression symptoms and self-efficacy in low-income mothers. PLoS ONE 13, e0191675.CrossRefGoogle ScholarPubMed
Shalev, AY, Peri, T, Canetti, L and Schreiber, S (1996) Predictors of PTSD in injured trauma survivors: a prospective study. American Journal of Psychiatry 153, 219225.Google ScholarPubMed
Shalev, AY, Freedman, S, Peri, T, Brandes, D, Sahar, T, Orr, SP and Pitman, RK (1998) Prospective study of posttraumatic stress disorder and depression following trauma. American Journal of Psychiatry 155, 630637.CrossRefGoogle ScholarPubMed
Simms, LJ, Watson, D and Doebbelling, BN (2002). Confirmatory factor analyses of posttraumatic stress symptoms in deployed and nondeployed veterans of the Gulf War. Journal of Abnormal Psychology 111, 637.CrossRefGoogle ScholarPubMed
Solomon, Z and Mikulincer, M (2006) Trajectories of PTSD: a 20-year longitudinal study. American Journal of Psychiatry 163, 659666.CrossRefGoogle ScholarPubMed
Solomon, Z, Horesh, D and Ein-Dor, T (2009) The longitudinal course of posttraumatic stress disorder symptom clusters among war veterans. The Journal of Clinical Psychiatry 70, 837843.CrossRefGoogle ScholarPubMed
Solomon, Z, Horesh, D, Ein-Dor, T and Ohry, A (2012) Predictors of PTSD trajectories following captivity: a 35-year longitudinal study. Psychiatry Research 199, 188194.CrossRefGoogle ScholarPubMed
Spiller, TR, Schick, M, Schnyder, U, Bryant, RA, Nickerson, A and Morina, N (2017) Symptoms of posttraumatic stress disorder in a clinical sample of refugees: a network analysis. European Journal of Psychotraumatology 8, 1318032.CrossRefGoogle Scholar
Stein, MB, Walker, JR, Hazen, AL and Forde, DR (1997) Full and partial posttraumatic stress disorder: findings from a community survey. The American Journal of Psychiatry 154, 11141119.Google ScholarPubMed
Thomas, JL, Wilk, JE, Riviere, LA, McGurk, D, Castro, CA and Hoge, CW (2010) Prevalence of mental health problems and functional impairment among active component and national guard soldiers 3 and 12 months following combat in Iraq. Archives of General Psychiatry 67, 614623.CrossRefGoogle Scholar
Tibshirani, R (2011) Regression shrinkage and selection via the lasso: a retrospective. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 73, 273282.CrossRefGoogle Scholar
Tsai, J, Harpaz-Rotem, H, Armour, C, Southwick, SM, Krystal, JH and Pietrzak, RH (2015) Dimensional structure of DSM-5 posttraumatic stress disorder symptoms: results from the National Health and Resilience in Veterans Study. The Journal of Clinical Psychiatry 76, 546553.Google ScholarPubMed
van Borkulo, CD (2015) Network comparison test: permutation-based test of differences in strength of networks. Available at https://github.com/cvborkulo/NetworkComparisonTest (Accessed 4 August 2016).Google Scholar
van Borkulo, CD, Borsboom, D, Epskamp, S, Blanken, TF, Boschloo, L, Schoevers, RA and Waldorp, LJ (2014) A new method for constructing networks from binary data. Scientific Reports 4, 5918.Google ScholarPubMed
Wald, I, Degnan, KA, Gorodetsky, E, Charney, DS, Fox, NA, Fruchter, E, Goldman, D, Lubin, G, Pine, DS and Bar-Haim, Y (2013) Attention to threats and combat-related posttraumatic stress symptoms: prospective associations and moderation by the serotonin transporter gene. JAMA Psychiatry 70, 401408.CrossRefGoogle ScholarPubMed
Yang, Z, Algesheimer, R and Tessone, CJ (2016) A comparative analysis of community detection algorithms on artificial networks. Scientific Reports 6, 30750.10.1038/srep30750CrossRefGoogle ScholarPubMed
Yehuda, R, McFarlane, A and Shalev, A (1998) Predicting the development of posttraumatic stress disorder from the acute response to a traumatic event. Biological Psychiatry 44, 13051313.CrossRefGoogle ScholarPubMed
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