Exploring the interconnectedness of fatigue, depression, anxiety and potential risk and protective factors in cancer patients: A network approach

Melanie Schellekens*, Marije Wolvers, Maya Schroevers, Tom Bootsma, Angélique Cramer, Marije Liesbeth van der Lee

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Researchers have extensively studied fatigue, depression and anxiety in cancer patients. Several risk and protective factors have been identified for these symptoms. As most studies address these constructs, independently from other symptoms and potential risk and protective factors, more insight into the complex relationships among these constructs is needed. This study used the multivariate network approach to gain a better understanding of how patients’ symptoms and risk and protective factors (i.e. physical symptoms, social withdrawal, illness cognitions, goal adjustment and partner support) are interconnected. We used cross-sectional data from a sample of cancer patients seeking psychological care (n = 342). Using network modelling, the relationships among symptoms of fatigue, depression and anxiety, and potential risk and protective factors were explored. Additionally, centrality (i.e. the number and strength of connections of a construct) and stability of the network were explored. Among risk factors, the relationship of helplessness and physical symptoms with fatigue stood out as they were stronger than most other connections in the network. Among protective factors, illness acceptance was most centrally embedded within the network, indicating it had more and stronger connections than most other variables in the network. The network identified key connections with risk factors (helplessness, physical symptoms) and a key protective factor (acceptance) at the group level. Longitudinal studies should explore these risk and protective factors in individual dynamic networks to further investigate their causal role and the extent to which such networks can inform us on what treatment would be most suitable for the individual cancer patient.
Original languageEnglish
JournalJournal of Behavioral Medicine
DOIs
Publication statusE-pub ahead of print - 2020

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