The biopsychosocial model (BPSM) on chronic pain is an interactive psychophysiological behavior pattern that cannot be separated into different independent components. However, the epistemological analysis of the classic BPSM, based on “biopsychosocial factors,” can be reduced to a list of biological, psychological and social factors, which can be addressed simultaneously, but independently, where simultaneity is seen as relationality. The purpose of this paper is to achieve a systemic and transdisciplinary vision of the idea of simultaneity and multidisciplinarity of the BPSM and propose a new model for the diagnosis and treatment of chronic pain.
Based on the following conceptual triad, co-autonomy, centralization and non-requisite variety, to constitute systemic indicators, the authors design a new conceptual model of cohesion, communication, conduction and coordination (CO4) model to deal with the relational system of chronic pain patients.
The indicators of the CO4 system as transdisciplinary structure create and focus a completely new relationship regarding the relational system of the chronic pain patients. This new conceptual framework transcends the objects and frameworks of each discipline separately, going beyond the multidisciplinary model.
The CO4 model allows a diagnostic and therapeutic standardization as a new model on chronic pain, improving therapeutic efficiency, resource use and laying the foundation for a common language in future chronic pain research.
Future perspectives: Implement the CO4 BC model in the diagnosis and treatment of patients Orofacial Pain, Pain Unit, Hospital Clínico Mutual de Seguridad, Santiago, Chile with chronic pain and other chronic diseases, in a transdisciplinary and coordinated manner, from primary health care to more complex pain units.
Thanks: Special thanks to Dr Kenneth Massey for his support in the translation and interpretation of the writing.
Hormazabal, F., Lavanderos, L. and Malpartida, A. (2020), "Biocybernetic model for the diagnosis and treatment of chronic pain: An approximation from cognitive neurosciences and the theory of complexity", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-07-2019-0469Download as .RIS
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