Literature DB >> 32542226

Pain-Linguistics and Natural Language Processing.

Luke A Carlson1, W Michael Hooten1.   

Abstract

Entities:  

Year:  2020        PMID: 32542226      PMCID: PMC7283550          DOI: 10.1016/j.mayocpiqo.2020.01.005

Source DB:  PubMed          Journal:  Mayo Clin Proc Innov Qual Outcomes        ISSN: 2542-4548


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To the Editor: Leveraging the natural language of unstructured electronic health records for research purposes has robust potential for the study of pain. The purpose of this letter is to parse a metaphorical linguistics framework for the word pain that could augment natural language processing (NLP) research methods and broaden the understanding of the effects of pain on health outcomes. Natural language processing is a branch of artificial intelligence broadly aimed at “exploiting rich knowledge resources with the goal of understanding, extraction and retrieval [of information] from unstructured text.” As the field of NLP advances, it will become increasingly important to understand the definitions and uses of the word pain in natural language. The word pain has an interesting history in the English language. Originating from the Latin word poena, meaning “penalty” or “punishment,” pain has been variously used to refer to physical distress, legal punishment, and existential suffering. Although the meaning of the word pain has come to be dominated by the biomedical definition, exemplified by the International Association for the Study of Pain’s characterization of pain as “an unpleasant sensory or emotional experience” that has intrinsic associations with “actual or potential tissue damage,” remnants of the word’s origins are evident in phrases such as “on pain of death” and apologizing “for being a pain.” Perhaps even more interesting than the origins of the word is the way the word pain is used in natural language. According to Lakoff and Johnson’s conceptual metaphor theory, many words are routinely used metaphorically to convey the meaning of concepts. For example, the conceptual metaphor “argument is war” can be seen in the following statements: (1) “Your claims are indefensible”; and (2) “I demolished his argument.” Regarding the word and concept of pain, 2 highly pervasive metaphorical frameworks manifest in discourse including pain as an object and pain as an adversary. The difference between these 2 metaphors is largely dependent on agency; objects are conceptualized as being inanimate, but adversaries are conceptualized as having volition (Table).
Table

Metaphorical Framework for the Word Pain

Pain as an objectPain as an adversary
• Can be described• Disrupts activities
• Can be located• Acts with intent
• Can be visualized• Inherently negative
• Neutral character• Potential for personification
Metaphorical Framework for the Word Pain These 2 metaphors highlight different aspects of pain. The object metaphor is useful for encoding the quality, intensity, and location of pain (eg, “sharp pain in my leg”), but it does not convey a comprehensive understanding of the experiential aspects of pain. The adversarial metaphor imbues pain with agency; thus, when pain is conceptualized as having volition or is negatively personified (eg, “this pain is killing me” or “my pain rarely gives me a break”), an in-depth understanding of the relationship between the sufferer and the pain experience emerges. Furthermore, sensitivity to the diversity of “pain vs sufferer” expressions can give insight into the reasons behind the variable and highly individualized phenotypes of commonly occurring pain syndromes (eg, fibromyalgia, chronic low back pain), which, in turn, can augment the clinical assessment and documentation of pain by practitioners. Incorporating rigorous linguistic approachs with ongoing advancements in NLP could drive development of metaphorically informed analyses that reflect the objective and adversarial metaphors of pain. Widespread deployment of these enhanced NLP techniques could open new avenues of epidemiological research and lead to a broader understanding of the effects of pain on health care resource utilization.
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Review 1.  Natural Language Processing methods and systems for biomedical ontology learning.

Authors:  Kaihong Liu; William R Hogan; Rebecca S Crowley
Journal:  J Biomed Inform       Date:  2010-07-18       Impact factor: 6.317

  1 in total
  2 in total

Review 1.  Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches.

Authors:  Sara E Berger; Alexis T Baria
Journal:  Front Pain Res (Lausanne)       Date:  2022-06-02

2.  Development of a Lexicon for Pain.

Authors:  Jaya Chaturvedi; Aurelie Mascio; Sumithra U Velupillai; Angus Roberts
Journal:  Front Digit Health       Date:  2021-12-13
  2 in total

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