Evidence map›Paper›PMID 38214952›Full record

ArticleJMIR mHealth and uHealth2024

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

Chloe Zimmerman Gunsilius, Joseph Heffner, Sienna Bruinsma, Madison Corinha, Maria Cortinez, Hadley Dalton, Ellen Duong, Joshua Lu, Aisulu Omar, Lucy Long Whittington Owen and 3 more

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 1 country.

Chloe Zimmerman Gunsilius *Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.ORCID 0000-0003-0532-0903
Joseph Heffner *Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, United States.ORCID 0000-0001-6757-3397
Sienna BruinsmaRobert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.ORCID 0000-0003-3314-306X
Madison CorinhaRobert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.ORCID 0009-0000-1529-6471
Maria CortinezWarren Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0009-0008-7619-2826
Hadley DaltonCenter for Computation and Visualization, Brown University, Providence, RI, United States.ORCID 0009-0000-2629-1967
Ellen DuongCenter for Computation and Visualization, Brown University, Providence, RI, United States.ORCID 0009-0006-1567-6910
Joshua LuCenter for Computation and Visualization, Brown University, Providence, RI, United States.ORCID 0009-0004-5223-8069
Aisulu OmarCenter for Computation and Visualization, Brown University, Providence, RI, United States.ORCID 0000-0002-7866-7206
Lucy Long Whittington OwenRobert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.ORCID 0000-0003-1844-6011
Bradford Nazario RoarrCenter for Computation and Visualization, Brown University, Providence, RI, United States.ORCID 0009-0003-5998-9757
Kevin TangIndustrial Design, Rhode Island School of Design, Providence, RI, United States.ORCID 0009-0006-1582-7838
Frederike H PetzschnerRobert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, United States.ORCID 0000-0003-4108-2105
Brown University · USAllen Institute for Brain Science · USRhode Island School of Design · US

Funding

The neural basis of sequential control in human and non-human primatesP20GM103645 · NIGMS · BROWN UNIVERSITY · PI PETZSCHNER, FREDERIKE HERMI · 2013 to 2022
$22.9M
Brown Postdoctoral Training Program in Computational PsychiatryT32MH126388 · NIMH · BROWN UNIVERSITY · PI MICHAEL J. FRANK, STEPHANIE Ruggiano JONES · 2021 to 2026
$2.1M
Identifying EEG Markers of Altered Interoceptive Processing in Chronic PainF30AT012306 · NCCIH · BROWN UNIVERSITY · PI ZIMMERMAN, CHLOE S · 2023 to 2024
$106k
NCCIH NIH HHS F30 AT012306NIGMS NIH HHS P20 GM103645NIMH NIH HHS T32 MH126388
6 · The paper itself

Abstract

Chronic pain is one of the most significant health issues in the United States, affecting more than 20% of the population. Despite its contribution to the increasing health crisis, reliable predictors of disease development, progression, or treatment outcomes are lacking. Self-report remains the most effective way to assess pain, but measures are often acquired in sparse settings over short time windows, limiting their predictive ability. In this paper, we present a new mobile health platform called SOMAScience. SOMAScience serves as an easy-to-use research tool for scientists and clinicians, enabling the collection of large-scale pain datasets in single- and multicenter studies by facilitating the acquisition, transfer, and analysis of longitudinal, multidimensional, self-report pain data. Data acquisition for SOMAScience is done through a user-friendly smartphone app, SOMA, that uses experience sampling methodology to capture momentary and daily assessments of pain intensity, unpleasantness, interference, location, mood, activities, and predictions about the next day that provide personal insights into daily pain dynamics. The visualization of data and its trends over time is meant to empower individual users' self-management of their pain. This paper outlines the scientific, clinical, technological, and user considerations involved in the development of SOMAScience and how it can be used in clinical studies or for pain self-management purposes. Our goal is for SOMAScience to provide a much-needed platform for individual users to gain insight into the multidimensional features of their pain while lowering the barrier for researchers and clinicians to obtain the type of pain data that will ultimately lead to improved prevention, diagnosis, and treatment of chronic pain.

Indexed as

Chronic PainMobile ApplicationsHumansPain ManagementPain MeasurementSelf Reportacute-chronic pain transitionacute painchronic painclinical outcome measurementdigital healthecological momentary assessmentEMAESMexperience sampling methodologymHealthmobile healthpain managementpain self-managementpatient reported outcomessmartphone app

Identifiers

PMID38214952
PMCPMC10818247
OpenAlexW4389168942

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.