Semi-automated socio-anthropologic analysis of themedical discourseon rheumatoid arthritis: potential impact in public health

Abstract

AbstractThe debilitating effects of non-communicable diseases (NCDs) and the accompanying chronic inflammation, represent a significant obstacle for the sustainability of our development, with efforts being spread worldwide to contrast NCDs’ diffusion, as per the United Nations Sustainable Development Goals (SDG 3). In fact, despite efforts of variable intensities in numerous directions (from innovations in biotechnology to lifestyle modifications), NCDs’ incidence remains pandemic.The present work wants to contribute to this major concern with a specific focus on the fragmentation of the medical approaches, via an interdisciplinary analysis of themedical discourse, i.e. the heterogenous reporting that biomedical scientific literature uses to describe the anti-inflammatory therapeutic landscape in NCDs. The aim is to better capture the roots of this compartmentalization and the power relations existing among three segregatedpharmacological, experimentalandunstandardizedbiomedical approaches, to ultimately empower collaboration beyond medical specialties and possibly untap a more ample and effective reservoir of integrated therapeutic opportunities.Using as exemplar disease rheumatoid arthritis (RA), twenty-eight articles were manually translated each into a nine-dimensional categorical variable of medical socio-anthropological relevance, relating in particular (but not only) tolegitimacy, temporalityandspatialization. This digitalized picture (9 × 28 table) of the medical discourse was further analyzed by simple automatic learning approaches to identify differences and highlight commonalities among the biomedical categories.Interpretation of these results gives original insights including the suggestion to: empower scientific communication betweenunstandardizedapproaches and basic biology; promote non-pharmacological therapies repurposing to enhance robustness ofexperimentalapproaches; align the spatial representation of diseases and therapies inpharmacologyto effectively embrace thesystemicapproach promoted by modern personalized and preventive medicines. We hope this original work may expand and foster interdisciplinarity among public health stakeholders, ultimately contributing to the achievement of SGD3.