Evidence map›Paper›PMID 37637508›Full record

ArticleFrontiers in pain research (Lausanne, Switzerland)2023

Understanding chronic pain in the ubiquitous community: the role of open data.

Federico Monaco, Emmanouil Georgiadis, Kakia Chatsiou, Antonio Bonacaro

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pain research (Lausanne, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 2 countries.

Federico MonacoDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Emmanouil GeorgiadisSchool of Social Sciences and Humanities, University of Suffolk, Ipswich, United Kingdom.
Kakia ChatsiouSchool of Engineering, Arts, Science & Technology, University of Suffolk, Ipswich, United Kingdom.
Antonio BonacaroDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
University of Suffolk · GBUniversity of Parma · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The combined use of social media, open data, and Artificial Intelligence has the potential to support practitioners and empower patients/citizens living with persistent pain, both as local and online communities. Given the wide availability of digital technology today, both practitioners and interested individuals can be connected with virtual communities and can support each other from the comfort of their homes. Digital means may represent new avenues for exploring the complexity of the pain experience. Online interactions of patients, data on effective treatments, and data collected by wearable devices may represent an incredible source of psychological, sociological, and physiological pain-related information. Digital means might provide several solutions that enhance inclusiveness and motivate patients to share personal experiences, limiting the sense of isolation in both rural and metropolitan areas. Building on the consensus of the usefulness of social media in enhancing the understanding of persistent pain and related subjective experiences via online communities and networks, we provide relevant scenarios where the effectiveness and efficiency of healthcare delivery might be improved by the adoption of the digital technologies mentioned above and repeated subsequently. The aim of this perspective paper is to explore the potential of open data, social media, and Artificial Intelligence in improving the prevention and management of persistent pain by adopting innovative non-biomedical approaches.

Indexed as

artificial intelligencechronic painnon-biomedical approachopen datapatient empowerment

Identifiers

PMID37637508
PMCPMC10456860
OpenAlexW4385755339

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.