Evidence map›Paper›PMID 33935700›Full record

ReviewFrontiers in pharmacology2021

Bridging the Translational Divide in Pain Research: Biological, Psychological and Social Considerations.

Chulmin Cho, Harashdeep K Deol, Loren J Martin

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Pain Research and Treatment: Policy Implications.Policy insights from the behavioral and brain sciences · 2024
    Article
  6. Review
  7. Article
  8. Review
  9. Article
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

3 authors at 1 institution in 1 country.

Chulmin ChoDepartment of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada.
Harashdeep K DeolDepartment of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada.
Loren J MartinDepartment of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada.
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A gap exists between translating basic science research into effective pain therapies in humans. While preclinical pain research has primarily used animal models to understand biological processes, a lesser focus has been toward using animal models to fully consider other components of the pain experience, such as psychological and social influences. Herein, we provide an overview of translational studies within pain research by breaking them down into purely biological, psychological and social influences using a framework derived from the biopsychosocial model. We draw from a wide landscape of studies to illustrate that the pain experience is highly intricate, and every attempt must be made to address its multiple components and interactors to aid in fully understanding its complexity. We highlight our work where we have developed animal models to assess the cognitive and social effects on pain modulation while conducting parallel experiments in people that provide proof-of-importance for human pain modulation. In some instances, human pain research has sparked the development of novel animal models, with these animal models used to better understand the complexity of phenomena considered to be uniquely human such as placebo responses and empathy.

Indexed as

biopsychosocialmemorymousepainsocialtranslation

Identifiers

PMID33935700
PMCPMC8082136
OpenAlexW3155544403

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.