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Related Concept Videos

Analgesia and Pain Management01:25

Analgesia and Pain Management

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Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
623

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#ChronicPain: Automated Building of a Chronic Pain Cohort from Twitter Using Machine Learning.

Abeed Sarker1, Sahithi Lakamana1, Yuting Guo1

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Researchers used social media data to identify effective alternative therapies for chronic pain. This approach can build a large, growing cohort for studying opioid alternatives.

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Area of Science:

  • Computational Social Science
  • Digital Health
  • Public Health

Background:

  • Chronic pain poses a significant public health burden, necessitating alternatives to opioid therapies.
  • Social media offers a rich source of self-reported data from individuals experiencing chronic pain.

Purpose of the Study:

  • To assess the feasibility of using Twitter data to identify chronic pain sufferers.
  • To develop and apply natural language processing (NLP) and machine learning (ML) models for analyzing self-reported chronic pain experiences.
  • To collect longitudinal data for understanding patient-reported outcomes and therapies.

Main Methods:

  • Collected Twitter data using chronic pain-related hashtags and keywords.
  • Manually annotated 4,998 posts for self-reported chronic pain experiences.
  • Trained and evaluated NLP/ML models, deploying the best-performing RoBERTa classifier (F1 score: 0.84).
  • Analyzed over 3 million posts from 22,795 identified chronic pain sufferers.

Main Results:

  • Successfully identified a large cohort of chronic pain sufferers on Twitter.
  • The RoBERTa model demonstrated high performance in classifying self-reported pain posts.
  • Analysis revealed insights into alternative treatments, patient sentiments, side effects, and self-management strategies.

Conclusions:

  • A social media-based approach can create a continuously growing cohort for chronic pain research.
  • This data can be leveraged to discover effective opioid-alternative therapies for various chronic pain conditions.