Evidence map›Paper›PMID 27089351›Full record

SynthesisInternational journal of environmental research and public health2016

Pain Assessment--Can it be Done with a Computerised System? A Systematic Review and Meta-Analysis.

Nuno Pombo, Nuno Garcia, Kouamana Bousson, Susanna Spinsante, Ivan Chorbev

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. 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

5 authors.

Nuno PomboInstituto de Telecomunicações (Telecommunications Institute), University of Beira Interior, Covilhã 6200-001, Portugal. ngpombo@ubi.pt.
Nuno GarciaInstituto de Telecomunicações (Telecommunications Institute), University of Beira Interior, Covilhã 6200-001, Portugal. ngarcia@di.ubi.pt.
Kouamana BoussonDepartment of Aerospace Sciences, University of Beira Interior, Covilhã 6200-001, Portugal. bousson@ubi.pt.
Susanna SpinsanteDipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona 60121, Italy. s.spinsante@univpm.it.
Ivan ChorbevFaculty of Computer Science and Engineering, Ss. Cyril and Methodius University Skopje, Skopje 1000, Macedonia. ivan.chorbev@finki.ukim.mk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile and web technologies are becoming increasingly used to support the treatment of chronic pain conditions. However, the subjectivity of pain perception makes its management and evaluation very difficult. Pain treatment requires a multi-dimensional approach (e.g., sensory, affective, cognitive) whence the evidence of technology effects across dimensions is lacking. This study aims to describe computerised monitoring systems and to suggest a methodology, based on statistical analysis, to evaluate their effects on pain assessment.

methodsWe conducted a review of the English-language literature about computerised systems related to chronic pain complaints that included data collected via mobile devices or Internet, published since 2000 in three relevant bibliographical databases such as BioMed Central, PubMed Central and ScienceDirect. The extracted data include: objective and duration of the study, age and condition of the participants, and type of collected information (e.g., questionnaires, scales).

resultsSixty-two studies were included, encompassing 13,338 participants. A total of 50 (81%) studies related to mobile systems, and 12 (19%) related to web-based systems. Technology and pen-and-paper approaches presented equivalent outcomes related with pain intensity.

conclusionsThe adoption of technology was revealed as accurate and feasible as pen-and-paper methods. The proposed assessment model based on data fusion combined with a qualitative assessment method was revealed to be suitable. Data integration raises several concerns and challenges to the design, development and application of monitoring systems applied to pain.

Indexed as

Age FactorsChronic PainEnvironmentHumansInternetMobile ApplicationsPain MeasurementSex Factorschronic painmhealthpain assessmentpain diariespain scales

Identifiers

PMID27089351
PMCPMC4847077

What OpenQuestion holds

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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.