Evidence map›Paper›PMID 41064189›Full record

ArticleJournal of pain research2025

Modelling Pain Perception Using Fuzzy Cognitive Maps.

Hojjatollah Farahani, Nataša Kovač, Helal Fardi, Peter Charles Watson

Abstract read
In one paragraph

Article in Journal of pain research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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.

Hojjatollah FarahaniDepartment of Psychology, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran.ORCID 0000-0002-9799-7008
Nataša KovačFaculty of Applied Sciences, University of Donja Gorica, Podgorica, Montenegro.ORCID 0000-0002-6671-2938
Helal FardiDepartment of Psychology, Faculty of Education and Psychology, University of Tehran, Tehran, Iran.
Peter Charles WatsonMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-9436-0693

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Perception of pain is a multifactorial mechanism involving physiological, psychological and social factors; only by understanding the interplays of these factors can we hope to develop effective management strategies for pain. To that effect, we developed a computational model using Fuzzy Cognitive Maps (FCMs) to simulate and predict individual pain experiences, based on expert input across multiple disciplines. This framework has potential application in individualized pain management, drug development and pain research. Patients and Methods: The Method of the study is an FCM model based on expert-sourced data for pain perception. A total of 20 experts were recruited using a snowball sampling technique, divided into five specialist groups: neurologists, pain specialists, psychologists, sociologists, and geneticists, with four experts in each group. The experts contributed input in CSV file format specifying concept associations and linguistic terms. Therefore, three types of data collection were used: questionnaires for capturing inter-factor interactions, fuzzy matrices measuring strengths of influences and interviewing in order to validate relationships. The data was then analyzed by summing up expert-defined causal relationships based on fuzzy logic rules, allowing for the construction of the initial weight matrix that reflects both the strength and direction of influence between concepts. Results: The built FCM model integrates six significant concepts that influence pain perception: brain and neural basis of pain, psychological factors, social factors, individual differences, type of tissue damage and general pain perception. The model structure indicates strong reinforcing influences between psychological and neural factors, while social influences tend to inhibit perceived pain. Centrality analysis highlighted individual differences as a critical mediating node in the system. The model stabilized to an internally consistent fixed point under a variety of initial conditions, providing internal stability. Conclusion: The findings indicate that the FCM model provides a useful framework for representing interactions between pain and its influencing factors. The model was validated through expert consensus and scenario-based simulations. Future work will include empirical validation using standardized psychological instruments to compare FCM outcomes with real-world psychological profiles.

Indexed as

elements of pain perceptionfuzzy cognitive mapsmedical decision support systemspain managementpain perception

Identifiers

PMID41064189
PMCPMC12502976

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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.