The fear of cancer recurrence (FCR) is a significant concern for ovarian cancer patients, with a high prevalence of at least 65% reporting moderate to severe fear. This fear can lead to negative psychological and physical health outcomes, including depression, anxiety, pain, fatigue, and sleep disturbances.
Cancer-related sleep disorders (CRSD), also known as cancer-related insomnia, are common among cancer patients and can be caused by the disease itself, treatments like chemotherapy, or the psychosocial stress associated with cancer. These sleep disturbances can further exacerbate FCR, creating a vicious cycle.
The traditional approach to understanding psychopathological disorders has been through latent variable theory, which treats symptoms as resulting from common underlying factors. However, this approach fails to consider the interactions between symptoms, which are crucial for identifying intervention targets and pathways.
Network analysis, based on psychopathological theory, offers a new perspective by constructing a network model that visualizes the complex associations between variables. It identifies core variables and key nodes, providing valuable insights for intervention research.
Previous studies have applied network analysis to explore the relationships within and between mental disorders, such as fear of recurrence, anxiety, depression, and sleep disorders. These studies have found that intervening in core symptoms can improve the overall network of symptoms, with better outcomes compared to intervening in non-core symptoms.
This study aimed to conduct a network analysis of the core symptoms of FCR in ovarian cancer patients and their interaction with sleep disorders. By understanding these relationships, the study aimed to provide more targeted mental health support and a scientific basis for prevention and intervention strategies.
The study was conducted at a gynecology center in a university hospital in China's Northwest region from September 2024 to July 2025. A total of 248 ovarian cancer patients undergoing chemotherapy were included, with a 54.3% incidence of FCR and a 66.2% incidence of sleep disturbances.
Multiple linear regression analysis revealed that sleep disturbances and age were the main influencing factors of FCR in these patients. Sleep disturbances were positively correlated with FCR, while age was negatively correlated.
Network analysis identified the top three core symptoms of FCR as "worried that the drug will damage the body," "worried about some major treatments," and "worried about what will happen to the family if something happens to me." These symptoms were found to have the strongest associations with other symptoms in the network, indicating their potential as key intervention targets.
The network analysis also revealed a potential association between FCR and sleep quality. The symptom "sleep problems" exhibited the highest bridge strength centrality, suggesting it acts as an internal bridging symptom connecting FCR and sleep disturbances. This symptom, which includes "easy awakening at night or early awakening," "needing to use the toilet at night," and "feeling hot," was found to be a key target for intervention in the FCR-sleep disorder network system.
The study's findings provide important insights into the interaction mechanisms among FCR symptoms in ovarian cancer patients. By accurately identifying core symptoms and bridging symptoms, the study offers a basis for designing targeted prevention programs and intervention strategies for FCR and sleep disturbances in this patient population.
However, the study had some limitations. It adopted a cross-sectional design, which limits the ability to establish causal relationships between FCR and sleep disorders. Additionally, the study did not conduct a stratified discussion by age, preventing an exploration of characteristic differences among different age groups.
Future studies could address these limitations by adopting longitudinal data tracking, expanding the sample size, and conducting age-stratified analyses. Furthermore, exploring the emotional regulation mechanisms and cognitive processing modes underlying the relationship between FCR and sleep quality could uncover more potential network influence mechanisms, enhancing the accuracy and generalizability of the research results.
In conclusion, this study highlights the importance of understanding the complex interactions between FCR symptoms and sleep disturbances in ovarian cancer patients. By utilizing network analysis, researchers can identify key intervention targets and design effective prevention and intervention strategies to improve the mental health and well-being of these patients.
