» Articles » PMID: 35401947

Network Analysis of PGD, PTSD and Insomnia Symptoms in Chinese Shidu Parents with PGD

Overview
Date 2022 Apr 11
PMID 35401947
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Chinese shidu parents (bereaved parents over the age of 49 who have lost their only child) are potentially at a high risk of prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD) and insomnia.

Objective: The current study aimed to estimate three network models in 310 shidu parents who met the ICD-11 criteria for PGD: (1) a PGD network to identify central symptoms; (2) a comorbidity network to explore bridge symptoms between PGD and PTSD; (3) a comorbidity network to examine the associations between PGD and insomnia symptoms.

Methods: The R-packages bootnet, qgraph and networktools were used to investigate the structure of network models and centrality indices of symptoms. In addition, robustness and significance analyses for the edge weights and the order of centrality were performed.

Results: Emotional pain and numbness emerged as the most central symptoms in the PGD network. In the PGD-PTSD comorbidity network, the highest bridge strength symptoms were inability to trust others (PGD) and feeling upset (PTSD). Inability to trust others (PGD), avoidance (PGD), and impairment of life quality (insomnia) were possible bridge symptoms connecting PGD and insomnia.

Conclusions: Reducing emotional pain and numbness may be a viable target in PGD interventions for shidu parents. Additionally, findings suggest that future studies could examine the role of inability to trust others and avoidance in PGD comorbidities.

Highlights: • Emotional pain and numbness were the most influential symptoms in shidu parents with PGD. The role of PGD symptoms of inability to trust others and avoidance in the comorbidities of PGD with PTSD and insomnia might be worthy of further study.

Citing Articles

Living with grief and thriving after loss: a qualitative study of Chinese parents whose only child has died.

Xu X, Wen J, Qian W, Zhou N, Jiang W Eur J Psychotraumatol. 2024; 15(1):2418767.

PMID: 39485312 PMC: 11536679. DOI: 10.1080/20008066.2024.2418767.


Machine learning and Bayesian network analyses identifies associations with insomnia in a national sample of 31,285 treatment-seeking college students.

Calderon A, Baik S, Ng M, Fitzsimmons-Craft E, Eisenberg D, Wilfley D BMC Psychiatry. 2024; 24(1):656.

PMID: 39367432 PMC: 11452987. DOI: 10.1186/s12888-024-06074-7.


Exploring the interconnections of anxiety, depression, sleep problems and health-promoting lifestyles among Chinese university students: a comprehensive network approach.

Sun C, Zhu Z, Zhang P, Wang L, Zhang Q, Guo Y Front Psychiatry. 2024; 15:1402680.

PMID: 39077626 PMC: 11284064. DOI: 10.3389/fpsyt.2024.1402680.


Network analysis of smoking-related sleep characteristics in Chinese adults.

Xie Y, Sun P, Huang H, Wu J, Ba Y, Zhou G Ann Med. 2024; 56(1):2332424.

PMID: 38527416 PMC: 10964831. DOI: 10.1080/07853890.2024.2332424.


Central Symptoms of Insomnia in Relation to Depression and COVID-19 Anxiety in General Population: A Network Analysis.

Cha E, Jeon H, Chung S J Clin Med. 2022; 11(12).

PMID: 35743484 PMC: 9224757. DOI: 10.3390/jcm11123416.

References
1.
Hittner J, May K, Silver N . A Monte Carlo evaluation of tests for comparing dependent correlations. J Gen Psychol. 2003; 130(2):149-68. DOI: 10.1080/00221300309601282. View

2.
Borsboom D . A network theory of mental disorders. World Psychiatry. 2017; 16(1):5-13. PMC: 5269502. DOI: 10.1002/wps.20375. View

3.
Nappi C, Drummond S, Hall J . Treating nightmares and insomnia in posttraumatic stress disorder: a review of current evidence. Neuropharmacology. 2011; 62(2):576-85. PMC: 5154613. DOI: 10.1016/j.neuropharm.2011.02.029. View

4.
Maccallum F, Malgaroli M, Bonanno G . Networks of loss: Relationships among symptoms of prolonged grief following spousal and parental loss. J Abnorm Psychol. 2017; 126(5):652-662. PMC: 5523866. DOI: 10.1037/abn0000287. View

5.
Hofmann S, Curtiss J, McNally R . A Complex Network Perspective on Clinical Science. Perspect Psychol Sci. 2016; 11(5):597-605. PMC: 5119747. DOI: 10.1177/1745691616639283. View