Que fatores influenciam no aparecimento de subprocessos de hibridização em contextos de intermedicalidade?

Abstract

Local medical systems (SML), which comprise local perceptions of disease, prevention and treatment strategies, including treatment assessments, are complex and dynamic. These SMLs are not isolated and interact with other medical systems such as the cosmopolitan medical system (SMC). The interaction of these two systems creates a “contact zone”, which is called intermedicality, involving interactions of competition and complementarity. However, little in the literature is discussed about the complexity of these interactions and the impact that different interactions can have on SMLs. In this work, we analyze the interactions that can occur between SMLs and biomedicine in human groups located in rural areas in the light of hybridization, and the factors that can influence the registration of the following hybridization subprocesses: I) fusion, II) recombination, III) restructuring , IV) relocation, V) new developments in practices, circulation and consumption, VI) coexistence of symbolic universes and; VI) segregation. The first chapter of the dissertation is aimed at situating the work theoretically, as well as presenting the adaptations made to understand the interactions of biomedicine with SMLs in non-urban contexts. Furthermore, we propose a flowchart that can be used to identify, in future works, 4 of these hybridization sub-processes in intermedicality contexts, important to evaluate the interactions between medicinal plants and medicines of biomedical origin. This chapter also conceptually and methodologically guided the second chapter of the dissertation, in which a systematic review was carried out in order to understand whether factors related to the academic background of the author and the area of the journal can influence the investigation of hybridization subprocesses. For this, a systematic review was carried out in the Scopus, Scielo, PubMed and Web of Science databases. We performed generalized linear models to verify the effect of predictor variables on response variables. Our findings did not reveal a significant effect of the predictor variables on the number of subprocesses that occurred in the literature. If this trend continues, in future studies it will be possible to verify which other factors may be behind the occurrence of specific subprocesses and what is the impact of the occurrence of these subprocesses for the resilience of SML.