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多发性硬化症患者抑郁症状的患病率及其相关因素的验证研究。

Validation study of prevalence and correlates of depressive symptomatology in multiple sclerosis.

作者信息

Bamer Alyssa M, Cetin Karynsa, Johnson Kurt L, Gibbons Laura E, Ehde Dawn M

机构信息

Department of Rehabilitation Medicine, National Rehabilitation Research and Training Center on Multiple Sclerosis, University of Washington, Box 356490, Seattle, WA 98195, USA.

出版信息

Gen Hosp Psychiatry. 2008 Jul-Aug;30(4):311-7. doi: 10.1016/j.genhosppsych.2008.04.006.

Abstract

OBJECTIVE

To validate previous research findings on the prevalence of and factors associated with depressive symptoms in a community-dwelling sample of individuals with multiple sclerosis (MS).

METHOD

A cross-sectional survey study of 530 individuals with MS from Eastern Washington (EW) was conducted and compared to a previous cross-sectional survey study of 738 individuals with MS from Western Washington (WW). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and multivariate logistic regression was employed to detect related factors.

RESULTS

Prevalence of depressive symptoms was similar in both populations (EW 51%, WW 45%). Factors associated with a clinically significant level of depressive symptoms (CES-D > or =16) in both groups were greater disease severity, shorter disease duration, lower education and less social support (all P<.01). Lower age was also associated with a significant level of depressive symptoms in the WW but not in the EW sample.

CONCLUSIONS

Despite differences in disease-related and demographic factors, predictors of depressive symptoms were highly similar in both MS study populations.

摘要

目的

验证先前关于多发性硬化症(MS)社区居住样本中抑郁症状患病率及相关因素的研究结果。

方法

对来自华盛顿东部(EW)的530名MS患者进行了横断面调查研究,并与先前对来自华盛顿西部(WW)的738名MS患者进行的横断面调查研究进行比较。使用流行病学研究中心抑郁量表(CES-D)评估抑郁症状,并采用多因素逻辑回归来检测相关因素。

结果

两个群体中抑郁症状的患病率相似(EW为51%,WW为45%)。两组中与临床显著水平的抑郁症状(CES-D≥16)相关的因素包括疾病严重程度更高、病程更短、教育程度更低和社会支持更少(所有P<0.01)。年龄较小在WW样本中也与显著水平的抑郁症状相关,但在EW样本中并非如此。

结论

尽管在疾病相关和人口统计学因素方面存在差异,但两个MS研究群体中抑郁症状的预测因素高度相似。

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