特朗普政府时期州心理健康立法中结构性污名的预测因素

IF 1.1 Q3 SOCIAL WORK

Social Work in Mental Health Pub Date : 2022-04-10 DOI:10.1080/15332985.2022.2062272

David L. Conley, Melinda J. Baum

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引用次数: 2

摘要

精神卫生保健干预措施是有效的，但服务和访问仍然有限，因为大多数法案和拨款失败。在精神卫生保健政策制定中存在各种形式的结构性污名，但有关影响其存在的因素的研究有限。因此，对精神健康相关立法进行了内容分析，以确定结构性耻辱的形式以及任何立法影响。结果表明:(1)立法者政党、议院和性别都与结构性耻辱感显著相关，(2)共和党成员是结构性耻辱感的显著预测因子。心理健康倡导者可以利用这些发现，以政策制定者为目标，努力减少耻辱感。

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Predictors of structural stigma in state mental health legislation during the Trump administration

ABSTRACT Mental healthcare interventions are effective, yet services and access remain limited, as most bills and appropriations fail. Forms of structural stigma exist in mental healthcare policymaking, but research is limited regarding factors affecting their presence. Thus, a content analysis was conducted on mental health-related legislation in order to identify forms of structural stigma as well as any legislative influences. Findings indicated that (1) legislator political party, chamber, and gender were all significantly associated with structural stigma, while (2) Republican party membership was a significant predictor. Mental health advocates may utilize these findings when targeting policymakers in their stigma reduction efforts.

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来源期刊

Social Work in Mental Health SOCIAL WORK-

CiteScore

1.90

自引率

0.00%

发文量

期刊介绍： Social Work in Mental Health is an exciting contribution from the editors of our highly respected journal, Social Work in Health Care. This journal offers quality articles on clinical practice, education, research, collaborative relationships, mental health policy, and the delivery of mental health care services. This scholarly, creative, and lively journal presents material valuable to social workers in all sectors of mental health care. It is devoted to social work theory, practice, and administration in a wide variety of mental health care settings. Social Work in Mental Health will help you improve your practice in these areas, demonstrating the vital role of social services in mental health care delivery systems.