期刊文献+
共找到4篇文章
< 1 >
每页显示 20 50 100
症状网络分析在癌症病人焦虑、抑郁症状管理中的应用研究进展
1
作者 张娟 徐令婕 +1 位作者 王润秋 李秀川 《循证护理》 2025年第1期97-100,共4页
从症状网络分析的概念、基本原理、方法出发,阐述其在癌症病人焦虑、抑郁症状管理方面的应用,以及我国未来的研究方向,以期为癌症病人焦虑、抑郁的研究提供新思路。
关键词 癌症 症状网络分析 焦虑 抑郁 综述
在线阅读 下载PDF
首发脑卒中患者创伤后应激障碍症状的网络分析及护理对策 被引量:2
2
作者 侯佳雨 杨丽 +1 位作者 李佳 吕润田 《中华护理杂志》 CSCD 北大核心 2024年第8期953-959,共7页
目的通过网络分析模型探究首发脑卒中患者创伤后应激障碍症状网络的核心症状及护理对策,为症状的精准干预与护理提供依据。方法采用横断面研究,便利抽取2022年10月—2023年4月在青岛市某三级甲等综合医院神经内科住院的232例首发脑卒中... 目的通过网络分析模型探究首发脑卒中患者创伤后应激障碍症状网络的核心症状及护理对策,为症状的精准干预与护理提供依据。方法采用横断面研究,便利抽取2022年10月—2023年4月在青岛市某三级甲等综合医院神经内科住院的232例首发脑卒中患者为调查对象,采用修订版创伤后应激障碍症状筛查量表进行调查,应用R软件进行创伤后应激障碍症状网络分析,包括网络关系分析、核心症状分析及网络结构的准确性和稳定性分析。结果症状网络分析显示,症状“高警觉”和“惊跳反应过度”、“回避与创伤事件相关的想法或感觉”和“回避易使人联想起创伤事件的活动或情景”、“负性信念”和“责备自己或怪罪他人”之间的关系最强,正则化偏相关系数分别为0.650、0.635、0.381;症状“与创伤相关的遗忘”的可预测性最高;症状“难以体验积极的情绪”的预期影响最高,该症状与其他症状的连接更紧密。经检验,网络的准确性和稳定性较好,网络模型较为可靠。结论该研究利用症状网络分析法探究首发脑卒中患者创伤后应激障碍的症状网络,针对网络中关系最强及可预测性高的症状,提示临床医护人员在干预过程中要预防性地切断这些症状间的较强连接,提高干预效率;“难以体验积极的情绪”是网络中最核心的症状,提示在未来研究中为提高患者的创伤后应激障碍控制效果,促进心理康复,应将该症状作为干预的靶点,拟订科学的心理干预措施,促进患者心理健康状况的改善。 展开更多
关键词 脑卒中 创伤后应激障碍 症状网络分析 核心症状 护理
原文传递
Network analysis of the relationships between depressive symptoms and social participation activities among Chinese older adults and its implications for nursing
3
作者 Yebo Yu Hewei Min +3 位作者 Wei Pan Ping Chen Xuxi Zhang Xinying Sun 《International Journal of Nursing Sciences》 CSCD 2024年第4期465-472,I0002,共9页
Objective:Network analysis was used to explore the complex inter-relationships between social participation activities and depressive symptoms among the Chinese older population,and the differences in network structur... Objective:Network analysis was used to explore the complex inter-relationships between social participation activities and depressive symptoms among the Chinese older population,and the differences in network structures among different genders,age groups,and urban-rural residency would be compared.Methods:Based on the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey(CLHLS),12,043 people aged 65 to 105 were included.The 10-item Center for Epidemiologic Studies Depression(CESD)Scale was used to assess depressive symptoms and 10 types of social participation activities were collected,including housework,tai-chi,square dancing,visiting and interacting with friends,garden work,reading newspapers or books,raising domestic animals,playing cards or mahjong,watching TV or listening to radio,and organized social activities.R 4.2.1 software was used to estimate the network model and calculate strength and bridge strength.Results:21.60%(2,601/12,043)of the participants had depressive symptoms.The total social participation score was negatively associated with depressive symptoms after adjusting for sociodemographic factors.The network of social participation and depressive symptoms showed that“D9(Inability to get going)”and“S9(Watching TV and/or listening to the radio)”had the highest strength within depressive symptoms and social participation communities,respectively,and“S1(Housework)”,“S9(Watching TV and/or listening to the radio)”,and“D5(Hopelessness)”were the most prominent bridging nodes between the two communities.Most edges linking the two communities were negative.“S5(Graden work)-D5(Hopelessness)”and“S6(Reading newspapers/books)-D4(Everything was an effort)”were the top 2 strongest negative edges.Older females had significantly denser network structures than older males.Compared to older people aged 65e80,the age group 81e105 showed higher network global strength.Conclusions:This study provides novel insights into the complex relationships between social participation and depressive symptoms.Except for doing housework,other social participation activities were found to be protective for depression levels.Different nursing strategies should be taken to prevent and alleviate depressive symptoms for different genders and older people of different ages. 展开更多
关键词 Depressive symptoms Network analysis Older adults Sex characteristics Social participation
在线阅读 下载PDF
Exploring core symptoms and symptom clusters among patients with neuromyelitis optica spectrum disorder: A network analysis
4
作者 Hao Liang Jiehan Chen +4 位作者 Lixin Wang Zhuyun Liu Haoyou Xu Min Zhao Xiaopei Zhang 《International Journal of Nursing Sciences》 2025年第2期152-160,共9页
Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to p... Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD. 展开更多
关键词 Neuromyelitis optica spectrum disorder Network analysis Symptom Symptom clusters Nursing
在线阅读 下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部