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Realistic networks are rich in information. Often too rich for all that information to be easily conveyed. Summarizing the network then becomes useful, often necessary, for communication and understanding but, being wary, of course, that a summary necessarily loses information about the network. Further, networks often do not exist in isolation. Multiple networks may arise from a given dataset or multiple datasets may each give rise to different views of the same network. In such cases and more, researchers need tools and techniques to compare and contrast those networks. In this chapter, In this chapter, well show you how to summarize a network, using statistics, visualizations, and even other networks. From these summaries we then describe ways to compare networks, defining a distance between networks for example. Comparing multiple networks using the techniques we describe can help researchers choose the best data processing options and unearth intriguing similarities and differences between networks in diverse fields.
Bereavement is a globally prevalent life stressor, but in some instances, it may be followed by a persistent condition of grief and distress, codified within the 11th edition of the International Classification of Diseases (ICD-11) as prolonged grief disorder (PGD). Network analysis provides a valuable framework for understanding psychological disorders at a nuanced symptom-based level.
Aim
This study novelly explores the network structure of ICD-11 PGD symptomology in a non-Western sample and assesses the replication of this across three African country sub-samples in these data.
Methodology
Network models were estimated using the “Inventory of Complicated Grief-Revised” in a sample of trauma-exposed individuals who experienced bereavement throughout life (N = 1,554) from three African countries (Ghana, n = 290; Kenya, n = 619; Nigeria, n = 645). These networks were statistically evaluated using the network comparison test.
Results
It was found that “Feelings of Loss” and “Difficulty moving on” were the most central symptoms in the combined sample network. These findings were largely consistent for the Ghana and Nigeria sub-samples, however, network structure differences were noted in the Kenya sub-sample.
Conclusion
The identified PGD network highlights particular indicators and associations across three African samples. Implications for the assessment and treatment of PGD in these cultural contexts warrant consideration.
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