Self-stigmatization and treatment preferences: Measuring the impact of treatment labels on choices for depression medications

Author:

Gonzalez Sepulveda Juan MarcosORCID,Townsend Michael,Waters Heidi C.,Brubaker Maalak,Wallace Matthew,Johnson Reed

Abstract

Objective To collect evidence on the possibility that patients with depression experience self-stigmatization based on label information for medications. Methods We developed a discrete-choice experiment (DCE) survey instrument that asked respondents to make choices between hypothetical treatments for major depressive disorder (MDD). We also included treatment type (antidepressants versus antipsychotics) and approved indications for the medication. The choice questions mimicked the information presented in product inserts and required systematic tradeoffs between treatment efficacy, treatment type, and indication. We calculated how many patients were willing to forgo efficacy to avoid treatments with information associated with self-stigmatization, and how much efficacy they were willing to forgo. We also evaluated the impact of contextualizing the treatment information to reduce self-stigmatization by randomizing respondents who received additional context. Results A total of 501 patients with MDD were recruited to complete the DCE survey. Respondents had well-defined preferences for treatment outcomes. Over 60% (63.4%) of respondents were found to be significantly affected by treatment indication. These respondents were willing to forgo about 2.5 percentage points in the chance of treatment efficacy to avoid treatments indicated for schizophrenia. We also find that some level of contextualization of the treatment details could help reduce the negative impact of treatment type and indications. Conclusions Product-label treatment indication can potentially lead to patient self-stigmatization as shown by patients’ avoidance of treatments that are also used to treat schizophrenia. While the effect appears to be relatively small, results suggests that the issue is likely pervasive.

Funder

Otsuka Pharmaceutical Development & Commercialization, Inc

Lundbeck, LLC

Publisher

Public Library of Science (PLoS)

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