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Analgesia and Pain Management

Analgesia and Pain Management

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...

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Updated: Jun 16, 2026

Author Spotlight: Quantifying Pain Experience – An Illustrative Approach Using the Pain Body Diagram

Author Spotlight: Quantifying Pain Experience – An Illustrative Approach Using the Pain Body Diagram

Published on: July 7, 2023

SOMAScience: A Novel Platform for Multidimensional, Longitudinal Pain Assessment.

Chloe Zimmerman Gunsilius^1,2,3, Joseph Heffner⁴, Sienna Bruinsma^1,5

¹Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.

JMIR Mhealth and Uhealth

|January 12, 2024

Summary

This summary is machine-generated.

SOMAScience is a new mobile health platform for collecting detailed chronic pain data. It empowers users and researchers with insights for better pain management and treatment.

Keywords:

EMA ESM acute pain acute-chronic pain transition chronic pain clinical outcome measurement digital health ecological momentary assessment experience sampling methodology mHealth mobile health pain management pain self-management patient reported outcomes smartphone app

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Last Updated: Jun 16, 2026

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Area of Science:

Digital Health
Pain Medicine
Health Informatics

Background:

Chronic pain affects over 20% of the US population, posing a significant health crisis.
Current pain assessment methods are limited by sparse data collection, hindering prediction of disease progression and treatment outcomes.
Reliable predictors for chronic pain development, progression, and treatment success are critically needed.

Purpose of the Study:

To introduce SOMAScience, a novel mobile health platform designed for large-scale chronic pain data collection.
To facilitate the acquisition, transfer, and analysis of longitudinal, multidimensional, self-report pain data for research and clinical use.
To empower individuals with insights into their daily pain dynamics for improved self-management.

Main Methods:

Development of a user-friendly smartphone app (SOMA) utilizing experience sampling methodology.
Collection of momentary and daily assessments including pain intensity, unpleasantness, interference, location, mood, and activities.
Implementation of data visualization tools to track pain trends over time.

Main Results:

SOMAScience enables efficient collection of comprehensive, longitudinal pain datasets.
The platform provides users with personal insights into daily pain dynamics through data visualization.
It lowers barriers for researchers and clinicians in obtaining crucial pain data.

Conclusions:

SOMAScience offers a valuable tool for both clinical studies and individual pain self-management.
The platform has the potential to improve the prevention, diagnosis, and treatment of chronic pain.
It addresses the need for robust, multidimensional pain data in research and clinical practice.