Evidence Hub

Stigmatizing Terminology for Outcomes and Processes (STOP) in Alcohol Research: A Meta-epidemiologic Assessment of Language Used in Clinical Trial Publications

M. Hartwell, Vanessa Lin, M. Hester, Nicholas B. Sajjadi, K. Dunn, J. Morris, K. Witkiewitz

Journal of addiction medicine, 2022

6 citations

Abstract

Introduction Stigmatizing language used to describe patients and medical conditions is associated with poorer health outcomes. A recent investigation showed that approximately 80% of medical literature focused on alcohol use disorder (AUD) contained stigmatizing terms related to individuals; however, the quantification of stigmatizing terminology for outcomes and processes (STOP) among AUD research is unknown. Thus, our primary objective was to evaluate publications of clinical trials for their inclusion of STOP. Methods We performed a systematic search of PubMed for AUD clinical trials between January 1, 2017 and June 30, 2021. Article screening and data extraction were performed in a masked, duplicate manner by 2 investigators. We searched the full text of included manuscripts for STOP. We reported the frequency and percentage of manuscripts with STOP and individual terms. We evaluated associations between STOP usage and several clinical trial characteristics via logistic regression. Results Our search returned 1552 articles, which were then randomized and the first 500 were screened for inclusion. Of 147 included articles, 115 (78.2%) included STOP. The most common STOP were “drop out” (38.78%; 57/147), “relapse” (36.05%; 53/ 147), and “adherent, nonadherence” (35.37%; 52/147). No significant associations were found between STOP usage and trial characteristics. Discussion STOP was found in a majority of AUD clinical trial publications. As AUD is highly stigmatized, steps…

How strong is the evidence?

Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free