Written Communication Jan 2021 OA PDF

The Opioid Epidemic and the Pursuit of Moral Medicine: A Computational-Rhetorical Analysis

S. Scott Graham The University of Texas at Austin

Abstract

This article offers a longitudinal computational-rhetorical analysis of biomedical writing on opioids. Using a corpus of 1,467 articles and essays published in the New England Journal of Medicine and the Journal of the American Medical Association between 1959 and May 2019, this study evaluates diachronic shifts in (a) the framing of opioid pharmacology, (b) the relative attention paid to pain management versus opioid dependence risks, and (c) the distribution of statements related to physicians’ primary ethical obligations. The results of these analyses largely disconfirm different current accounts of shifting physician rhetoric around opioids and pain management leading up to the recognition opioid epidemic. Most notably, the results also suggest that biomedical debates surrounding opioids are serving as proxy arguments for shifting primary bioethical obligations from individual patients to public health.

Journal
Written Communication
Published
2021-01-01
DOI
10.1177/0741088320944918
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Open Access
OA PDF Bronze
Topics
rhetorical criticism
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Citation Context

Cited by in this index (6)

  1. Deets et al. (2024)
    Content Analysis, Construct Validity, and Artificial Intelligence: Implications…
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  2. Yang et al. (2024)
    Pathological Liars: Algorithmic Knowing in the Rhetorical Ecosystem of Wallstreetbets
    Rhetoric Society Quarterly
  3. Majdik et al. (2024)
    Rhetoric of/with AI: An Introduction
    Rhetoric Society Quarterly
  4. Madson (2024)
    Cannabis Risk Communication: A Scoping Review with a Research Agenda
    Technical Communication Quarterly
  5. Majdik et al. (2023)
    Building Better Machine Learning Models for Rhetorical Analyses: The Use of Rhe…
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Show all 6 →
  1. Graham et al. (2022)
    AI for Social Justice: New Methodological Horizons in Technical Communication
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CrossRef global citation count: 10 View in citation network → Build reading path →

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