Inequality in the Origins and Experiences of Pain: What “Big (Qualitative) Data” Reveal About Social Suffering in the United States

Corey M. Abramson, Zhuofan Li, Tara Prendergast, Martín Sánchez-Jankowski

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This study examines how Americans’ narratives of pain are connected to social inequalities using more than 1,500 in-depth interviews collected as part of the American Voices Project. Our novel mixed-method approach to these “big (qualitative) data” uses machine learning and qualitative analysis to demonstrate that discussions of physical pain are prevalent across groups, but narrative content varies by demographics including educational background and gender identity. Our findings demonstrate (1) that pain is commonly described as a challenge that shapes everyday life, (2) that pain narratives often invoke morality and distinction, and (3) that narratives diverge around discussions of unequal medical treatment, illness identities, vulnerability and suffering. We discuss the implications of our findings for scholarship on inequality and experience, social scientific methods, and health policy.

Original languageEnglish (US)
Pages (from-to)34-65
Number of pages32
JournalRSF
Volume10
Issue number5
DOIs
StatePublished - Sep 1 2024
Externally publishedYes

Keywords

  • computational ethnography
  • culture
  • health
  • in-depth interviews
  • inequality
  • machine learning
  • mixed-methods
  • pain
  • social determinants of health
  • suffering

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)

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