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对精神分裂症患者的社会距离和污名化:在一个城市非裔美国人社区样本中的研究结果。

Social distance and stigma toward individuals with schizophrenia: findings in an urban, African-American community sample.

作者信息

Broussard Beth, Goulding Sandra M, Talley Colin L, Compton Michael T

机构信息

Department of Psychiatry and Behavioral Sciences, The George Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA.

出版信息

J Nerv Ment Dis. 2012 Nov;200(11):935-40. doi: 10.1097/NMD.0b013e3182718c1b.

Abstract

Because schizophrenia is arguably among the most stigmatized health conditions, research assessing correlates of stigma is essential. This study examined factors associated with stigma in predominantly Protestant, low-income, urban African Americans in the Southeastern United States. A survey was distributed to 282 patrons of an inner-city food court/farmers' market. Associations were assessed between two measures of stigma--an adapted version of the Social Distance Scale (SDS) and a Semantic Differential Measure (SDM) of attributes such as dangerousness, dirtiness, and worthlessness--and several key variables addressing sociodemographic characteristics and exposure to/familiarity with mental illnesses. Independent predictors of scores on the two measures were identified using linear regression modeling. Higher stigma (as measured by the SDM) was predicted by a family history of psychiatric treatment, whereas lower stigma (as indicated by the SDS) was predicted by personal psychiatric treatment history and higher annual income. The results suggest special considerations when working with disenfranchised populations, especially family members of individuals with mental illnesses, in treatment settings.

摘要

由于精神分裂症可以说是最受污名化的健康状况之一,评估污名相关因素的研究至关重要。本研究调查了美国东南部以新教为主、低收入的城市非裔美国人中与污名相关的因素。对一个市中心美食广场/农贸市场的282名顾客进行了一项调查。评估了两种污名测量方法——社会距离量表(SDS)的改编版和对危险性、肮脏性和无价值等属性的语义差异测量(SDM)——与几个涉及社会人口特征以及对精神疾病的接触/熟悉程度的关键变量之间的关联。使用线性回归模型确定了这两种测量方法得分的独立预测因素。精神科治疗家族史预测了较高的污名(由SDM测量),而个人精神科治疗史和较高的年收入则预测了较低的污名(由SDS表示)。结果表明,在治疗环境中与被剥夺权利的人群,特别是患有精神疾病个体的家庭成员打交道时,需要特别考虑。

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