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Breaking barriers: Artificial intelligence interpreting the interplay between mental illness and pain as defined by the international association for the study of pain

Title
Breaking barriers: Artificial intelligence interpreting the interplay between mental illness and pain as defined by the international association for the study of pain
Type
Article in International Scientific Journal
Year
2023
Authors
Franciele Parolini
(Author)
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Klaus Becker
(Author)
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Cristofthe Fernandes
(Author)
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Ricardo J. Fernandes
(Author)
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Ulysses F. Ervilha
(Author)
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Rubim Santos
(Author)
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João Paulo Vilas-Boas
(Author)
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Journal
Title: BiomedicinesImported from Authenticus Search for Journal Publications
Vol. 23
Final page: 2042
Publisher: MDPI
Indexing
Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Scientific classification
FOS: Social sciences
Other information
Authenticus ID: P-00Y-TC2
Abstract (EN): Low back pain is one of the main causes of motor disabilities and psychological stress, with the painful process encompassing sensory and affective components. Noxious stimuli originate on the periphery; however, the stimuli are recombined in the brain and therefore processed differently due to the emotional environment. To better understand this process, our objective was to develop a mathematical representation of the International Association for the Study of Pain (IASP) model of pain, covering the multidimensional representation of this phenomenon. Data from the Oswestry disability index; the short form of the depression, anxiety, and stress scale; and pain catastrophizing daily questionnaires were collected through online completion, available from 8 June 2022, to 8 April 2023 (1021 cases). Using the information collected, an artificial neural network structure was trained (based on anomaly detection methods) to identify the patterns that emerge from the relationship between the variables. The developed model proved to be robust and able to show the patterns and the relationship between the variables, and it allowed for differentiating the groups with altered patterns in the context of low back pain. The distinct groups all behave according to the main finding that psychological and pain events are directly associated. We conclude that our proposal is effective as it is able to test and confirm the definition of the IASP for the study of pain. Here we show that the fiscal and mental dimensions of pain are directly associated, meaning that mental illness can be an enhancer of pain episodes and functionality.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 12
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