Network Structure and Variability of Recurrence Fear in Early-Stage Non-Small Cell Lung Cancer:A Symptom Network Analysis

Background:Lung cancer,one of the most prevalent and deadly malignancies worldwide,not only poses a significant physical burden but also a profound psychological challenge to patients.Among these psychological challenges,the fear of recurrence stands out as a particularly distressing issue.This fear,often rooted in the patients’past experiences with the disease and its treatment,can significantly impact their quality of life,mental health,and even compliance with follow-up care.Moreover,this fear can be exacerbated by the lack of understanding and support from healthcare professionals and family members,further isolating patients and compounding their psychological burden.Therefore,understanding and addressing the fear of recurrence in lung cancer patients is crucial for improving their overall well-being and outcomes.Aims:This study aims to develop a symptom network model for fear of recurrence in early-stage lung cancer patients,analyzing symptom correlations to enhance healthcare providers’understanding and management of these symptoms,thereby improving patient outcomes and quality of life.Design:A cross-sectional study design was used.Method:We employed convenience sampling to recruit 551 lung cancer patients from the Thoracic Surgery Department of a tertiary hospital in Beijing between January 2023 and December 2023.A cross-sectional study was conducted using the General Information Questionnaire,Fear of Disease Progression Scale,and Level of Hope Scale.Network analysis was performed with JASP 0.18.3.0 using the EBICglasso method,and centrality metrics including Betweenness,Closeness,Degree centrality,and Expected influence were calculated.Results:Symptom network analysis identified fear of family impact and future work disruption as central to recurrence fear in these patients.Gender-based analysis revealed‘fear of being unable to continue work’as central in males,while‘fear of affecting family members’was central in females.Among adolescents,concerns about future work,medication side effects,and family impact showed the highest expected influence.In contrast,older patients predominantly feared major treatment implications.One-way ANOVA indicated that older age correlated with reduced recurrence fear,and higher hope levels significantly mitigated this fear.Conclusion:This study broadens understanding of fear of recurrence across demographic variables like gender and age,elucidating symptom interrelations and impacts.Future strategies should focus on patient-specific differences in recurrence fear to formulate targeted interventions.Relevance to Clinical Practice:Through in-depth analysis of the symptom network,healthcare professionals can more comprehensively understand the psychological responses of lung cancer patients when they face the risk of recurrence,and then formulate more precise and personalized treatment plans.At the same time,doctors and nurses can adjust treatment strategies in a timely manner according to the changes in the patient’s symptom network and provide more comprehensive psychological support,thus enhancing the patient’s treatment adherence and outcome.Patient Contribution:People who were invited to participate voluntarily completed a range of questionnaires.

SEQUENTIAL DIAGNOSIS FOR A CENTRIFUGAL PUMP BASED ON FUZZY NEURAL NETWORK

A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.

Psychological consistency network characteristics and influencing factors in patients after percutaneous coronary intervention treatment

BACKGROUND A psychological sense of coherence(SOC)in percutaneous coronary intervention(PCI)patients is important for disease prognosis,and there is considerable variation between their symptoms.In contrast,network analysis provides a new approach to gaining insight into the complex nature of symptoms and symptom clusters and identifying core symptoms.AIM To explore the psychological coherence of symptoms experienced by PCI patients,we aim to analyze differences in their associated factors and employ network analysis to characterize the symptom networks.METHODS A total of 472 patients who underwent PCI were selected for a cross-sectional study.The objective was to investigate the association between general patient demographics,medical coping styles,perceived stress status,and symptoms of psychological coherence.Data analysis was conducted using a linear regression model and a network model to visualize psychological coherence and calculate a centrality index.RESULTSPost-PCI patients exhibited low levels of psychological coherence, which correlated with factors such as education,income, age, place of residence, adherence to medical examinations, perceived stress, and medical coping style.Network analysis revealed that symptoms within the sense of psychological coherence were strongly interconnected,particularly with SOC2 and SOC8, demonstrating the strongest correlations. Among these, SOC10 emergedas the symptom with the highest intensity, centrality, and proximity, identifying it as the most central symptom.CONCLUSIONThe network model has strong explanatory power in describing the psychological consistency symptoms ofpatients after PCI, identifying the central SOC symptoms, among which SOC10 is the key to overall SOCenhancement, and there is a strong positive correlation between SOC2 and SOC8, emphasizing the need to considerthe synergistic effect of symptoms in intervention measures.