Defining suffering in pain: a systematic review on pain-related suffering using natural language processing

Niklas Noe-Steinmüller, Dmitry Scherbakov, Alexandra Zhuravlyova, Tor D. Wager, Pavel Goldstein, Jonas Tesarz

Research output: Contribution to journalArticlepeer-review


Understanding, measuring, and mitigating pain-related suffering is a key challenge for both clinical care and pain research. However, there is no consensus on what exactly the concept of pain-related suffering includes, and it is often not precisely operationalized in empirical studies. Here, we (1) systematically review the conceptualization of pain-related suffering in the existing literature, (2) develop a definition and a conceptual framework, and (3) use machine learning to cross-validate the results. We identified 111 articles in a systematic search of Web of Science, PubMed, PsychINFO, and PhilPapers for peer-reviewed articles containing conceptual contributions about the experience of pain-related suffering. We developed a new procedure for extracting and synthesizing study information based on the cross-validation of qualitative analysis with an artificial intelligence-based approach grounded in large language models and topic modeling. We derived a definition from the literature that is representative of current theoretical views and describes pain-related suffering as a severely negative, complex, and dynamic experience in response to a perceived threat to an individual's integrity as a self and identity as a person. We also offer a conceptual framework of pain-related suffering distinguishing 8 dimensions: social, physical, personal, spiritual, existential, cultural, cognitive, and affective. Our data show that pain-related suffering is a multidimensional phenomenon that is closely related to but distinct from pain itself. The present analysis provides a roadmap for further theoretical and empirical development.

Original languageEnglish
Pages (from-to)1434-1449
Number of pages16
Issue number7
StatePublished - 1 Jul 2024

Bibliographical note

Publisher Copyright:
Copyright © 2024 The Author(s).


  • ChatGPT
  • Definition
  • GPT-3
  • LDA
  • Machine learning
  • Natural language processing
  • Pain
  • Suffering
  • Topic modeling

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Anesthesiology and Pain Medicine


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