The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions

Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While prior research largely focused on sensory profiles to distinguish pain mechanisms, this study adopted a biopsychosocial perspective with the key addition of experimental pain paradigms to identify factors explaining variance in chronic pain severity across diverse etiologies. The dataset comprised 101 individuals with chronic pain and 63 pain-free controls. Participants were classified into three groups (no pain, mild-to-moderate pain, and severe pain) using three models: a sensory-profile-based model including quantitative sensory testing (QST model), a biopsychosocial model incorporating QST alongside psychological and social variables (biopsychosocial model), and a model using the same biopsychosocial data but excluding QST measures (noQST model). The QST model achieved an accuracy of 0.51 and an F1-score of 0.48. In contrast, the biopsychosocial model performed best, with both accuracy and F1-score of 0.71, while the noQST model reached 0.60 for both metrics. Key predictors in the best-performing model included quality of life, loss of sensation, depressive mood, pain catastrophizing, anxiety, fatigue, and general health. Overall, biopsychosocial factors enhanced chronic pain severity classification beyond sensory profiles alone across heterogeneous pain etiologies.

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Publication Details

Journal
Scientific Reports
Published
2026-05-29
DOI
https://doi.org/10.1038/s41598-026-46612-9
Primary Topic
Musculoskeletal pain and rehabilitation
Type
article
Field-Weighted Citation Impact
0.00

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article

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions

María Monzón, Robin Lütolf, Michèle Hubli, Iara De Schoenmacker et al.
Scientific Reports
Musculoskeletal pain and rehabilitation
article

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions

María Monzón, Robin Lütolf, Michèle Hubli, Iara De Schoenmacker, Jan Rösner, Petra Schweinhardt, Laura Sirucek, Armin Curt, Florian Brunner, Lindsay Gorrell, Catherine R. Jutzeler, Paulina S. Scheuren
article en

Abstract

Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While prior research largely focused on sensory profiles to distinguish pain mechanisms, this study adopted a biopsychosocial perspective with the key addition of experimental pain paradigms to identify factors explaining variance in chronic pain severity across diverse etiologies. The dataset comprised 101 individuals with chronic pain and 63 pain-free controls. Participants were classified into three groups (no pain, mild-to-moderate pain, and severe pain) using three models: a sensory-profile-based model including quantitative sensory testing (QST model), a biopsychosocial model incorporating QST alongside psychological and social variables (biopsychosocial model), and a model using the same biopsychosocial data but excluding QST measures (noQST model). The QST model achieved an accuracy of 0.51 and an F1-score of 0.48. In contrast, the biopsychosocial model performed best, with both accuracy and F1-score of 0.71, while the noQST model reached 0.60 for both metrics. Key predictors in the best-performing model included quality of life, loss of sensation, depressive mood, pain catastrophizing, anxiety, fatigue, and general health. Overall, biopsychosocial factors enhanced chronic pain severity classification beyond sensory profiles alone across heterogeneous pain etiologies.

Scientific Reports
SIB Swiss Institute of Bioinformatics (CH), University of British Columbia (CA), University of Zurich (CH), Aarhus University (DK), ETH Zurich (CH), Universitätsklinik Balgrist (CH), International Collaboration On Repair Discoveries (CA), Danish Pain Research Center (DK), Aalborg University (DK)
Michael Smith Health Research BC, International Foundation for Research in Paraplegia, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Lundbeckfonden
Openalex Percentile: Top 7%
Musculoskeletal pain and rehabilitation
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