Expanding language choices to reduce stigma

Author:

Ashford Robert DavidORCID,Brown Austin,Curtis Brenda

Abstract

Purpose Public perception has been found to be influenced by the words used to describe those with behavioral health disorders, such that using terms like “substance abuser” can lead to higher levels of stigma. The purpose of this paper is to identify additional stigmatizing and empowering terms that are commonly used by different stakeholders. Design/methodology/approach Using digital Delphi groups, the paper identifies positive and negative terms related to substance use disorder (SUD) from three distinct stakeholder groups: individuals in recovery, impacted family members and loved ones, and professionals in the treatment field. Findings Participants identified 60 different terms that are considered stigmatizing or positive. Previously identified stigmatizing terms (abuser, addict) were present for all stakeholder groups, as was the positive term person with a SUD. Additional stigmatizing terms for all groups included junkie and alcoholic. Additional positive terms for all groups included long-term recovery. Social implications The results suggest that the continued use of terms like addict, alcoholic, abuser and junkie can induce stigma in multiple stakeholders. The use of more positive terms such as person with a SUD or person in recovery is suggested to reduce stigma. Originality/value The use of digital Delphi groups to solicit feedback from multiple stakeholder groups from the substance use community is innovative and allows for the comparison of linguistics among and between the groups.

Publisher

Emerald

Subject

Public Health, Environmental and Occupational Health,Education

Reference21 articles.

1. Substance use, recovery, and linguistics: the impact of word choice on explicit and implicit bias;Drug and Alcohol Dependence,2018

2. ‘Abusing addiction’: our language still isn’t good enough;Alcoholism Treatment Quarterly,2018

3. The language of substance use and recovery: novel use of the go/no go association task to measure implicit bias;Health Communication,2018

4. Guidelines for authors;Journal of Early Intervention,1991

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3