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肺癌住院患者焦虑抑郁现状及影响因素分析
王伟杰1,陆晓芳2,孙昊1,刘毅1,赵毓源1,苏彤1*
0
(1. 海军军医大学(第二军医大学)心理系医学心理学教研室, 上海 200433;
2. 海军军医大学(第二军医大学)长海医院实验诊断科, 上海 200433
*通信作者)
摘要:
目的 了解肺癌住院患者焦虑和抑郁症状流行现状及其影响因素。方法 选择2016年11月至2017年5月于海军军医大学(第二军医大学)长海医院住院治疗的肺癌患者100例作为研究对象。采用横断面调查设计,用自编调查表收集肺癌住院患者的人口学、社会学信息及临床特征,用焦虑自评量表(SAS)和抑郁自评量表(SDS)分别评价肺癌住院患者的焦虑、抑郁症状。采用Pearson相关分析、Fisher确切概率检验、χ2检验、多重线性回归分析等方法探讨肺癌住院患者焦虑、抑郁症状的相关性及影响因素。结果 肺癌住院患者焦虑和抑郁的发生率分别为20.0%(20/100)和48.0%(48/100),SAS和SDS得分均高于常模(P均<0.01)。肺癌住院患者的SAS得分与SDS得分呈正相关(r=0.409,P<0.001),焦虑和抑郁的共病率较高,焦虑患者中共病抑郁的比例为85.0%(17/20),抑郁患者共病焦虑的比例为35.4%(17/48)。单因素分析结果表明子女数目和是否有肿瘤转移与肺癌住院患者焦虑症状有关,有0~1个子女的患者焦虑的发生率高于有≥2个子女的患者(P=0.042),有肿瘤转移的患者焦虑的发生率高于无转移患者(P=0.044)。多重线性回归分析表明子女数目和肿瘤临床分期是肺癌住院患者焦虑程度的影响因素(标准回归系数分别为-0.238和0.202,P均<0.05)。结论 肺癌住院患者焦虑和抑郁发生率高,二者相关性强;子女数目、肿瘤临床分期和肿瘤转移均会影响患者的焦虑程度;医护人员应积极关注肺癌患者的心理状况,及时识别焦虑、抑郁症状,并根据患者的不同特点开展个体化的心理治疗和药物治疗。
关键词:  肺肿瘤  住院患者  焦虑  抑郁  影响因素
DOI:10.16781/j.0258-879x.2019.04.0444
投稿时间:2018-10-11修订日期:2019-03-05
基金项目:国家自然科学基金(81602734),第二军医大学青年启动基金(2012QN02),第二军医大学本科学员创新实践能力孵化基地(FH2016114).
Anxiety, depression and related factors in lung cancer inpatients
WANG Wei-jie1,LU Xiao-fang2,SUN Hao1,LIU Yi1,ZHAO Yu-yuan1,SU Tong1*
(1. Department of Medical Psychology, Faculty of Psychology, Naval Medical University(Second Military Medical University), Shanghai 200433, China;
2. Department of Laboratory Medicine, Changhai Hospital, Naval Medical University(Second Military Medical University), Shanghai 200433, China
*Corresponding author)
Abstract:
Objective To investigate the status of anxiety and depression in lung cancer inpatients and to explore their influencing factors. Methods One hundred lung cancer patients, who were treated in Changhai Hospital of Naval Medical University (Second Military Medical University) from Nov. 2016 to May 2017, were enrolled in this study. The demographic, sociological and clinical characteristics of the inpatients were collected by self-designed questionnaires through cross-sectional survey. The self-rating anxiety scale (SAS) and self-rating depression scale (SDS) were employed to evaluate the anxiety and depression symptoms of the lung cancer inpatients, respectively. Pearson correlation analysis, Fisher exact test, χ2 test and multiple linear regression analysis were used to analyze the correlation of anxiety and depression and the related factors. Results The incidence rates of depression and anxiety in lung cancer inpatients was 20.0% (20/100) and 48.0% (48/100), respectively. The SAS and SDS scores of lung cancer inpatients were significantly higher than the normal values (both P<0.01). SAS score was positively correlated with SDS score (r=0.409, P<0.001). The rate of comorbidity of depresson and anxiety was high. The proportion of anxiety inpatients with comorbid depression was 85.0% (17/20). The proportion of depressive inpatients with comorbid anxiety was 35.4% (17/48). Univariate analysis showed that child number and tumor metastasis were significantly correlated with anxiety symptoms in the lung cancer inpatients. The inpatients having 0-1 child had significantly higher incidence of anxiety versus those having 2 or more children (P=0.042). The inpatients with tumor metastasis had significantly higher incidence of anxiety versus those without metastasis (P=0.044). Multiple linear regression analysis showed that child number and clinical stage of tumor were the influencing factors of anxiety in the lung cancer inpatients, with the standard regression coefficients being -0.238 and 0.202, respectively (both P<0.05). Conclusion The incidence rates of anxiety and depression are high in lung cancer inpatients, and there is a strong correlation between depression and anxiety. Number of child, clinical stage of tumor and tumor metastasis can influence the severity of anxiety. Clinicians should pay attention to the psychological status of lung cancer patients, identify depression and anxiety symptoms in time, and carry out individualized psychological therapy and drug therapy according to the characteristics of patients.
Key words:  lung neoplasms  inpatients  anxiety  depression  influencing factors