Classification of psychosocial risk factors (yellow flags) for the development of chronic low back and leg pain using artificial neural network

Dirk Hallner; Monika Hasenbring

doi:10.1016/j.neulet.2003.12.107

Classification of psychosocial risk factors (yellow flags) for the development of chronic low back and leg pain using artificial neural network

Neurosci Lett. 2004 May 6;361(1-3):151-4. doi: 10.1016/j.neulet.2003.12.107.

Authors

Dirk Hallner¹, Monika Hasenbring

Affiliation

¹ Department of Medical Psychology and Medical Sociology, Medical Faculty MA 0/145, Ruhr-University Bochum, Universitätsstrasse 150, 44780 Bochum, Germany.

PMID: 15135916
DOI: 10.1016/j.neulet.2003.12.107

Abstract

Due to international guidelines of treatment of acute low back pain (LBP), psychosocial risk factors like depressive mood and maladaptive pain-related coping strategies ('yellow flags') have to be assessed in the early phase of acute pain. Within this longitudinal study in patients with LBP and leg pain, we used an artificial neural network (ANN) to classify the pain intensity 6 months after the onset of treatment. Psychosocial risk factors were used as input neurons. The training of the three-layer ANN using the back-propagation algorithm yields to an accuracy of 83.1%. Further on, the complexity of this structure indicated the necessity of an early screening procedure that allows a differentiation between several high risk groups and a low risk profile in order to predict the long-term development of pain intensity.

MeSH terms

Adaptation, Psychological / physiology
Algorithms*
Chronic Disease
Depressive Disorder / complications
Depressive Disorder / psychology
Humans
Longitudinal Studies
Low Back Pain / psychology*
Mass Screening / methods
Neural Networks, Computer*
Predictive Value of Tests
Prognosis
Psychology
Reproducibility of Results
Risk Factors
Sciatica / psychology*