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. 2020 Jan;37(1):26-34.
doi: 10.1002/da.22880. Epub 2019 Feb 6.

Symptomatology following loss and trauma: Latent class and network analyses of prolonged grief disorder, posttraumatic stress disorder, and depression in a treatment-seeking trauma-exposed sample

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Symptomatology following loss and trauma: Latent class and network analyses of prolonged grief disorder, posttraumatic stress disorder, and depression in a treatment-seeking trauma-exposed sample

A A A Manik J Djelantik et al. Depress Anxiety. 2020 Jan.

Abstract

Background: Although bereavement is likely a common stressor among patients referred to a psychotrauma clinic, no study has yet examined the co-occurrence and relationships between symptoms of prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD), and major depressive disorder symptoms in this population.

Method: In a sample of patients seeking treatment following psychological trauma (n = 458), we used latent class analysis to identify classes of patients sharing the same profile of PGD, PTSD, and depression symptoms. We then used network analysis to investigate the relationships among these symptoms and with loss-related variables.

Results: Most participants (65%) were members of a class that exhibited elevated endorsement of PGD symptoms. PGD, PTSD, and depression symptoms hung together as highly overlapping but distinguishable communities of symptoms. Symptoms related to social isolation and diminished sense of self bridged these communities. Violent loss was associated with more difficulty accepting the loss. The loss of close kin was most strongly associated with difficulty moving on in life.

Conclusions: PGD symptoms are common in trauma-exposed bereaved adults and closely associated with symptoms of PTSD and depression, illustrating the importance of assessing bereavement and PGD symptoms in those seeking treatment following trauma.

Keywords: bereavement; depression; latent class analysis; network analysis; posttraumatic stress disorder; prolonged grief disorder; trauma.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Symptom endorsement probability for the four‐class solution of the latent class analysis
Figure 2
Figure 2
Analysis of shared community membership. Darker cells represent a higher proportion of the 10,000 iterations of the spinglass community detection algorithm in which the relevant symptoms appeared in the same community
Figure 3
Figure 3
Analysis of intra‐ and intercommunity relationships. Intracommunity edges are depicted in panel (a). Intercommunity edges are depicted in panel (b). For both panels (a) and (b), blue edges represent positive associations and red edges represent negative associations. Thicker edges represent stronger associations. PGD, depression, and PTSD symptoms are represented by orange, blue, and green nodes, respectively. The intracommunity expected influence of each symptom (i.e., the sum of the edge weights between a given symptom and other symptoms of the same community) appear in panel (c). The intercommunity expected influence of each symptom (i.e., the sum of the edge weights between a given symptom and other symptoms of the other communities) appears in panel (d). Intracommunity edges (M edge weight = 0.15) tended to be stronger than intercommunity edges (M = 0.04)
Figure 4
Figure 4
Analysis of loss‐related risk factors and their association with symptoms of PGD, PTSD, and depression. Symptom profile plots between groups with and without a history of violent loss (a) and those who did versus did not lose a partner/child (b) identify symptoms elevated in those with each risk factor. Panels (c) and (d) depict the associations between these risk factors and symptoms of PGD, depression, and PTSD symptoms after controlling for all other symptoms. PGD, depression, and PTSD symptoms appear in orange, blue, and green, respectively. *< 0.05

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