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 challen...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.展开更多
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 an...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.展开更多
Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive s...Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive symptoms and their relationships with QoL in stroke survivors.Aims This study aimed to explore the network structure of depressive symptoms in PSD and investigate the interrelationships between specific depressive symptoms and QoL among older stroke survivors.Methods This study was based on the 2017–2018 collection of data from a large national survey in China.Depressive symptoms were assessed using the 10-item Centre for Epidemiological Studies Depression Scale(CESD),while QoL was measured with the World Health Organization Quality of Life-brief version.Network analysis was employed to explore the structure of PSD,using expected influence(EI)to identify the most central symptoms and the flow function to investigate the association between depressive symptoms and QoL.Results A total of 1123 stroke survivors were included,with an overall prevalence of depression of 34.3%(n=385;95%confidence interval 31.5%to 37.2%).In the network model of depression,the most central symptoms were CESD3(‘feeling blue/depressed’,EI:1.180),CESD6(‘feeling nervous/fearful’,EI:0.864)and CESD8(‘loneliness’,EI:0.843).In addition,CESD5(‘hopelessness’,EI:−0.195),CESD10(‘sleep disturbances’,EI:−0.169)and CESD4(‘everything was an effort’,EI:−0.150)had strong negative associations with QoL.Conclusion This study found that PSD was common among older Chinese stroke survivors.Given its negative impact on QoL,appropriate interventions targeting central symptoms and those associated with QoL should be developed and implemented for stroke survivors with PSD.展开更多
基金supported by Beijing Hope Run Special Fund of Cancer Foundation of China(LC2022C05).
文摘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.
基金Supported by the Self-funded Research Project of Health Commission of Guangxi Zhuang Autonomous Region,No.Z-A20220509.
文摘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.
基金supported by Beijing High Level Public Health Technology Talent Construction Project(Discipline Backbone-01-028)the Beijing Municipal Science&Technology Commission(No.Z181100001518005)+2 种基金the Capital's Funds for Health Improvement and Research(CFH 2024-2-1174)the University of Macao(MYRG-GRG2023-00141-FHS,CPG2025-00021-FHS)the Science and Technology Plan Foundation of Guangzhou(No.202201011663).
文摘Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive symptoms and their relationships with QoL in stroke survivors.Aims This study aimed to explore the network structure of depressive symptoms in PSD and investigate the interrelationships between specific depressive symptoms and QoL among older stroke survivors.Methods This study was based on the 2017–2018 collection of data from a large national survey in China.Depressive symptoms were assessed using the 10-item Centre for Epidemiological Studies Depression Scale(CESD),while QoL was measured with the World Health Organization Quality of Life-brief version.Network analysis was employed to explore the structure of PSD,using expected influence(EI)to identify the most central symptoms and the flow function to investigate the association between depressive symptoms and QoL.Results A total of 1123 stroke survivors were included,with an overall prevalence of depression of 34.3%(n=385;95%confidence interval 31.5%to 37.2%).In the network model of depression,the most central symptoms were CESD3(‘feeling blue/depressed’,EI:1.180),CESD6(‘feeling nervous/fearful’,EI:0.864)and CESD8(‘loneliness’,EI:0.843).In addition,CESD5(‘hopelessness’,EI:−0.195),CESD10(‘sleep disturbances’,EI:−0.169)and CESD4(‘everything was an effort’,EI:−0.150)had strong negative associations with QoL.Conclusion This study found that PSD was common among older Chinese stroke survivors.Given its negative impact on QoL,appropriate interventions targeting central symptoms and those associated with QoL should be developed and implemented for stroke survivors with PSD.
