Causal Criteria in Medical and Biological Disciplines: History, Essence, and Radiation Aspect. Report 1. Problem Statement, Conception of Causes and Causation, False Associations

详细

Report 1 of a three-part review examines the conceptual formulation and relevance of the problem, including weak penetration of specific methodologies for causation proving into experimental and descriptive disciplines that study the effects of the radiation factor on living organisms. The philosophical and scientific concepts necessary for understanding the meaning, essence, and possibility of practical application of the criteria (rules, principles) for establishing the truth of associations revealed in medical and biological disciplines are presented. Five types of definitions of the causes and causality were found, which vary from the simplest explanatory (“by production”) to the complex, for deterministic and stochastic effects (necessary and sufficient causes, component causes, probabilistic causes, and counterfactual causes). Many of these definitions originate from famous philosophers (mostly D. Hume). A selection of statements revealing the scientific, practical and social goals of epidemiology and other causality studies important for human life and activity is presented. These goals are primarily related with evidence of the truth of the revealed dependences of effects on agents and impacts, however methods for their achievement can be based on different rules and ethical foundations established on scientific or social tasks. In the second case, the “precautionary principle” is used, and the norms of research developed for application in the scientific community are simplified, in may respects being replaced by prevention or at least reduction of risks, even if the reality of the latter does not have strict scientific evidence. Examples of false but statistically significant associations from various biomedical and social spheres (including estimates of effects of radiation exposure) caused by confound factors are presented. These examples indicate the need to use standardized criteria for assessing the truth of causality.