Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-22T13:27:31.879Z Has data issue: false hasContentIssue false
  • English
  • Français

Symptoms of persistent complex bereavement disorder, depression, and PTSD in a conjugally bereaved sample: a network analysis

Published online by Cambridge University Press:  18 July 2018

Matteo Malgaroli Open the ORCID record for Matteo Malgaroli [Opens in a new window] ,
Fiona Maccallum  and
George A. Bonanno
Matteo Malgaroli*
Affiliation:
Teachers College, Columbia University, New York, NY 10027, USA
Fiona Maccallum
Affiliation:
University of New South Wales, Sidney, Australia
George A. Bonanno
Affiliation:
Teachers College, Columbia University, New York, NY 10027, USA
*
Author for correspondence: Matteo Malgaroli, PhD E-mail: mm4408@columbia.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Complicated and persistent grief reactions afflict approximately 10% of bereaved individuals and are associated with severe disruptions of functioning. These maladaptive patterns were defined in Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) as persistent complex bereavement disorder (PCBD), but its criteria remain debated. The condition has been studied using network analysis, showing potential for an improved understanding of PCBD. However, previous studies were limited to self-report and primarily originated from a single archival dataset. To overcome these limitations, we collected structured clinical interview data from a community sample of newly conjugally bereaved individuals (N = 305).

Methods

Gaussian graphical models (GGM) were estimated from PCBD symptoms diagnosed at 3, 14, and 25 months after the loss. A directed acyclic graph (DAG) was generated from initial PCBD symptoms, and comorbidity networks with DSM-5 symptoms of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) were analyzed 1 year post-loss.

Results

In the GGM, symptoms from the social/identity PCBD symptoms cluster (i.e. role confusion, meaninglessness, and loneliness) tended to be central in the network at all assessments. In the DAG, yearning activated a cascade of PCBD symptoms, suggesting how symptoms lead into psychopathological configurations. In the comorbidity networks, PCBD and depressive symptoms formed separate communities, while PTSD symptoms divided in heterogeneous clusters.

Conclusions

The network approach offered insights regarding the core symptoms of PCBD and the role of persistent yearnings. Findings are discussed regarding both clinical and theoretical implications that will serve as a step toward a more integrated understanding of PCBD.

Keywords

Bereavementdepressiongriefnetwork analysisPTSD
Type
Original Articles
Information
Psychological Medicine , Volume 48 , Issue 14 , October 2018 , pp. 2439 - 2448
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders, 5th Edn. Washington, DC: American Psychiatric Association.Google Scholar
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 US military veterans. Journal of Anxiety Disorders 45, 49–59.Google Scholar
Bernstein, EE, Heeren, A and McNally, RJ (2017) Unpacking rumination and executive control: a network perspective. Clinical Psychological Science 5, 816–826.Google Scholar
Boelen, PA and Prigerson, HG (2012) Commentary on the inclusion of persistent complex bereavement-related disorder in DSM 5. Death Studies 36, 771–794.Google Scholar
Boelen, PA and van den Bout, J (2005) Complicated grief, depression, and anxiety as distinct postloss syndromes: a confirmatory factor analysis study. The American Journal of Psychiatry 162, 2175–2177.Google Scholar
Bonanno, GA (2004) Loss, trauma, and human resilience: have we underestimated the human capacity to thrive after extremely aversive events? American Psychologist 59, 20–28.Google Scholar
Bonanno, GA, Neria, Y, Mancini, A, Coifman, KG, Litz, B and Insel, B (2007) Is there more to complicated grief than depression and posttraumatic stress disorder? A test of incremental validity. Journal of Abnormal Psychology 116, 342–351.Google Scholar
Bonanno, GA, Wortman, CB, Lehman, DR, Tweed, RG, Haring, M, Sonnega, J, Carr, D and Neese, RM (2002) Resilience to loss and chronic grief: a prospective study from pre-loss to 18 months post-loss. Journal of Personality and Social Psychology 83, 1150–1164.Google Scholar
Borsboom, D and Cramer, AOJ (2013) Network analysis: an integrative approach to the structure of psychopathology. In Annual Review of Clinical Psychology, vol. 9, pp. 91–121.Google Scholar
Boschloo, L, van Borkulo, CD, Borsboom, D and Schoevers, RA (2016) A prospective study on how symptoms in a network predict the onset of depression. Psychotherapy and Psychosomatics 85, 183–184.Google Scholar
Bryant, RA (2014) Prolonged grief: where to after Diagnostic and Statistical Manual of Mental Disorders, 5th Edition? Current Opinion in Psychiatry 27, 21–26.Google Scholar
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, 135–142.Google Scholar
Bryant, RA, Kenny, L, Joscelyne, A, Rawson, N, Maccallum, F, Cahill, C, Hopwood, S, Aderka, I and Nickerson, A (2014) Treating prolonged grief disorder: a randomized controlled trial. JAMA Psychiatry 71, 1332–1339.Google Scholar
Cozza, SJ, Fisher, JE, Mauro, C, Zhou, J, Ortiz, CD, Skritskaya, N, Wall, MM, Fullerton, CS, Ursano, RJ and Shear, MK (2016) Performance of DSM-5 persistent complex bereavement disorder criteria in a community sample of bereaved military family members. American Journal of Psychiatry 173, 919–929.Google Scholar
Cramer, AOJ, Waldorp, LJ, van der Maas, HLJ and Borsboom, D (2010) Comorbidity: a network perspective. Behavioral and Brain Sciences 33, 137–193.Google Scholar
Csardi, G and Nepusz, T (2006) The igraph software package for complex network research. International Journal of Complex Systems 1695, 1–9.Google Scholar
Daly, R and Shen, Q (2007) Methods to accelerate the learning of Bayesian network structures. In Proceedings of the 2007 UK workshop on computational intelligence. Citeseer.Google Scholar
Epskamp, S, Cramer, AOJ, Waldorp, LJ, Schmittmann, VD and Borsboom, D (2012) Qgraph: network visualizations of relationships in psychometric data. Journal of Statistical Software 48, 1–18.Google Scholar
Epskamp, S and Fried, EI (2018) A tutorial on regularized partial correlation networks. Psychological Methods 50, 195–212.Google Scholar
Epskamp, S, Kruis, J and Marsman, M (2017 a) Estimating psychopathological networks: be careful what you wish for. PLoS ONE 12, e0179891.Google Scholar
Epskamp, S, Borsboom, D and Fried, EI (2018 a) Estimating psychological networks and their stability: a tutorial paper. Behavior Research Methods 50, 195–212.Google Scholar
Epskamp, S, Waldorp, LJ, Mottus, R and Borsboom, D (2018 b) Discovering psychological dynamics: the Gaussian graphical model in cross-sectional and time-series data. Multivariate Behavioral Research, 1–28.Google Scholar
Foygel, R and Drton, M (2010) Extended Bayesian information criteria for Gaussian graphical models. Advances in Neural Information Processing Systems, 604–612.Google Scholar
Fried, EI, Bockting, C, Arjadi, R, Borsboom, D, Amshoff, M, Cramer, AOJ, Epskamp, S, Tuerlinckx, F, Carr, D and Stroebe, M (2015) From loss to loneliness: the relationship between bereavement and depressive symptoms. Journal of Abnormal Psychology 124, 256–265.Google Scholar
Fried, EI and Cramer, AO (2017) Moving forward: challenges and directions for psychopathological network theory and methodology. Perspectives on Psychological Science 12, 999–1020.Google Scholar
Fried, EI, Eidhof, MB, Palic, S, Costantini, G, Huisman-van Dijk, HM, Bockting, CL, Engelhard, I, Armour, C, Nielsen, AB and Karstoft, KI (2018) Replicability and generalizability of posttraumatic stress disorder (PTSD) networks: a cross-cultural multisite study of PTSD symptoms in four trauma patient samples. Clinical Psychological Science 6, 335–351.Google Scholar
Friedman, J, Hastie, T and Tibshirani, R (2008) Sparse inverse covariance estimation with the graphical lasso. Biostatistics (Oxford, England) 9, 432–441.Google Scholar
Galatzer-Levy, IR and Bryant, RA (2013) 636120 ways to have posttraumatic stress disorder. Perspectives on Psychological Science 8, 651–662.Google Scholar
Goodyer, I, Park, R, Netherton, C and Herbert, J (2001) Possible role of cortisol and dehydroepiandrosterone in human development and psychopathology. The British Journal of Psychiatry 179, 243–249.Google Scholar
Haag, C, Robinaugh, DJ, Ehlers, A and Kleim, B (2017) Understanding the emergence of chronic posttraumatic stress disorder through acute stress symptom networks. JAMA Psychiatry 74, 649–650.Google Scholar
Hofmann, SG, Curtiss, J and McNally, RJ (2016) A complex network perspective on clinical science. Perspectives on Psychological Science 11, 597–605.Google Scholar
Horowitz, MJ (1986) Stress-response syndromes: a review of posttraumatic and adjustment disorders. Psychiatric Services 37, 241–249.Google Scholar
Kiecolt-Glaser, JK, Derry, HM and Fagundes, CP (2015) Inflammation: depression fans the flames and feasts on the heat. American Journal of Psychiatry 172, 1075–1091.Google Scholar
Liu, H, Lafferty, J and Wasserman, L (2009) The nonparanormal: semiparametric estimation of high dimensional undirected graphs. Journal of Machine Learning Research 10, 2295–2328.Google Scholar
Lundorff, M, Holmgren, H, Zachariae, R, Farver-Vestergaard, I and O'Connor, M (2017) Prevalence of prolonged grief disorder in adult bereavement: a systematic review and meta-analysis. Journal of Affective Disorders 212, 138–149.Google Scholar
Maccallum, F and Bryant, RA (2013) A Cognitive Attachment Model of prolonged grief: integrating attachments, memory, and identity. Clinical Psychology Review 33, 713–727.Google Scholar
Maccallum, F, Galatzer-Levy, IR and Bonanno, GA (2015) Trajectories of depression following spousal and child bereavement: a comparison of the heterogeneity in outcomes. Journal of Psychiatric Research 69, 72–79.Google Scholar
Maccallum, F, Malgaroli, M and Bonanno, GA (2017) Networks of loss: relationships among symptoms of prolonged grief following spousal and parental loss. Journal of Abnormal Psychology 126, 652–662.Google Scholar
Maciejewski, PK, Maercker, A, Boelen, PA and Prigerson, HG (2016) ‘Prolonged grief disorder’ and ‘persistent complex bereavement disorder’, but not ‘complicated grief’, are one and the same diagnostic entity: an analysis of data from the Yale Bereavement Study. World Psychiatry 15, 266–275.Google Scholar
Maercker, A, Brewin, CR, Bryant, RA, Cloitre, M, Reed, GM, van Ommeren, M, Humayun, A, Jones, LM, Kagee, A, Llosa, AE, Rousseau, C, Somasundaram, DJ, Souza, R, Suzuki, Y, Weissbecker, I, Wessely, SC, First, MB and Saxena, S (2013) Proposals for mental disorders specifically associated with stress in the International Classification of Diseases-11. The Lancet 381, 1683–1685.Google Scholar
McNally, RJ (2016) Can network analysis transform psychopathology? Behavioral Research and Therapy 86, 95–104.Google Scholar
McNally, RJ, Heeren, A and Robinaugh, DJ (2017 a) A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse. European Journal of Psychotraumatology 8(suppl. 3), 1341276.Google Scholar
McNally, RJ, Mair, P, Mugno, BL and Riemann, BC (2017) Co-morbid obsessive-compulsive disorder and depression: a Bayesian network approach. Psychological Medicine 47, 1204–1214.Google Scholar
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 Psychology Science 3, 836–849.Google Scholar
Moffa, G, Catone, G, Kuipers, J, Kuipers, E, Freeman, D, Marwaha, S, Lennox, BR, Broome, MR and Bebbington, P (2017) Using directed acyclic graphs in epidemiological research in psychosis: an analysis of the role of bullying in psychosis. Schizophrenia Bulletin 43, 1273–1279.Google Scholar
Neimeyer, RA (2016) Meaning reconstruction in the wake of loss: evolution of a research program. Behaviour Change 33, 65–79.Google Scholar
O'Connor, MF, Wellisch, DK, Stanton, AL, Eisenberger, NI, Irwin, MR and Lieberman, MD (2008). Craving love? Enduring grief activates brain's reward center. NeuroImage 42, 969–972.Google Scholar
Parkes, CM and Prigerson, HG (2013) Bereavement: Studies of Grief in Adult Life. New York, NY: Routledge.Google Scholar
Pearl, J (2009) Causality. New York, NY: Cambridge University Press.Google Scholar
Prigerson, HG, Horowitz, MJ, Jacobs, SC, Parkes, CM, Aslan, M, Goodkin, K, Raphael, B, Marwit, SJ, Wortman, C, Neimeyer, RA, Bonanno, GA, Block, SD, Kissane, D, Boelen, PA, Maercker, A, Litz, BT, Johnson, JG, First, MB and Maciejewski, PK (2009) Prolonged grief disorder: psychometric validation of criteria proposed for DSM-V and ICD-11. PLoS Medicine 6, e1000121.Google Scholar
Prigerson, HG and Maciejewski, PK (2017) Rebuilding consensus on valid criteria for disordered grief. JAMA Psychiatry 74, 435–436.Google Scholar
R Core Team (2016) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Reichardt, J and Bornholdt, S (2006) Statistical mechanics of community detection. Physical Review E 74, 016110.Google Scholar
Reynolds, CF, Cozza, SJ and Shear, MK (2017) Clinically relevant diagnostic criteria for a persistent impairing grief disorder putting patients first. JAMA Psychiatry 74, 433–434.Google Scholar
Robinaugh, DJ, LeBlanc, NJ, Vuletich, HA and McNally, RJ (2014) Network analysis of persistent complex bereavement disorder in conjugally bereaved adults. Journal of Abnormal Psychology 123, 510–522.Google Scholar
Santos, H, Fried, EI, Asafu-Adjei, J and Ruiz, RJ (2017) Network structure of perinatal depressive symptoms in Latinas: relationship to stress and reproductive biomarkers. Research in Nursing & Health 40, 218–228.Google Scholar
Schmittmann, VD, Cramer, AOJ, Waldorp, LJ, Epskamp, S, Kievit, RA and Borsboom, D (2013) Deconstructing the construct: a network perspective on psychological phenomena. New Ideas in Psychology 31, 43–53.Google Scholar
Schneck, N, Tu, T, Michel, CA, Bonanno, GA, Sajda, P and Mann, JJ (2017) Attentional bias to reminders of the deceased as compared with a living attachment in grieving. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 3, 107–115.Google Scholar
Scutari, M (2010) bnlearn: Bayesian network structure learning. R package.Google Scholar
Scutari, M and Denis, J-B (2014) Bayesian Networks: With Examples in R. Boca Raton, FL: CRC press.Google Scholar
Scutari, M and Nagarajan, R (2013) Identifying significant edges in graphical models of molecular networks. Artificial Intelligence in Medicine 57, 207–217.Google Scholar
Shear, MK, Reynolds, CF, Simon, NM, Zisook, S, Wang, Y, Mauro, C, Duan, N, Lebowitz, B and Skritskaya, N (2016) Optimizing treatment of complicated grief: a randomized clinical trial. JAMA Psychiatry 73, 685–694.Google Scholar
Shear, MK, Simon, N, Wall, M, Zisook, S, Neimeyer, R, Duan, N, Reynolds, C, Lebowitz, B, Sung, S, Ghesquiere, A, Gorscak, B, Clayton, P, Ito, M, Nakajima, S, Konishi, T, Melhem, N, Meert, K, Schiff, M, O'Connor, M-F, First, M, Sareen, J, Bolton, J, Skritskaya, N, Mancini, AD and Keshaviah, A (2011) Complicated grief and related bereavement issues for DSM-5. Depression and Anxiety 28, 103–117.Google Scholar
Simon, NM, Shear, KM, Thompson, EH, Zalta, AK, Perlman, C, Reynolds, CF, Frank, E, Melhem, NM and Silowash, R (2007) The prevalence and correlates of psychiatric comorbidity in individuals with complicated grief. Comprehensive Psychiatry 48, 395–399.Google Scholar
Stroebe, MS and Schut, H (2001) Models of coping with bereavement: a review. In. Stroebe MS, Stroebe W and Hansson RO (Eds.), Handbook of bereavement: Theory, research, and intervention, pp. 375–403.Google Scholar
Stroebe, MS, Schut, H and Stroebe, W (2007) Health outcomes of bereavement. The Lancet 370, 1960–1973.Google Scholar
van Borkulo, CD, Waldorp, LJ, Boschloo, L, Kossakowski, J, TioP, L P, L, Schoevers, RA and Borsboom, D (2016) Comparing network structures on three aspects: A permutation test. doi: 10.13140/RG.2.2.29455.38569.Google Scholar
Yan, OH and Bonanno, GA (2015) How self-enhancers adapt well to loss: the mediational role of loneliness and social functioning. The Journal of Positive Psychology 10, 370–382.Google Scholar
Zhao, T, Liu, H, Roeder, K, Lafferty, J and Wasserman, L (2012) The huge package for high-dimensional undirected graph estimation in R. Journal of Machine Learning Research 13, 1059–1062.Google Scholar
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 1

Download Malgaroli et al. supplementary material(PDF)
PDF 413.9 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 2

Download Malgaroli et al. supplementary material(PDF)
PDF 447.4 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 3

Download Malgaroli et al. supplementary material(PDF)
PDF 395.1 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 4

Download Malgaroli et al. supplementary material(PDF)
PDF 876.3 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 5

Download Malgaroli et al. supplementary material(PDF)
PDF 1.6 MB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 6

Download Malgaroli et al. supplementary material(PDF)
PDF 370 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 7

Download Malgaroli et al. supplementary material(PDF)
PDF 181.4 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 8

Download Malgaroli et al. supplementary material(PDF)
PDF 392.9 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 9

Download Malgaroli et al. supplementary material(PDF)
PDF 94.8 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 10

Download Malgaroli et al. supplementary material(PDF)
PDF 744.5 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 11

Download Malgaroli et al. supplementary material(PDF)
PDF 389.9 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 12

Download Malgaroli et al. supplementary material(PDF)
PDF 184.3 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 13

Download Malgaroli et al. supplementary material(PDF)
PDF 443.9 KB
Supplementary material: PDF

Malgaroli et al. supplementary material

Malgaroli et al. supplementary material 14

Download Malgaroli et al. supplementary material(PDF)
PDF 85.2 KB