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食品科学与营养研究中的经验归纳法和/或假说演绎法:为了实现更好的全球健康,应倾向于哪种方法?

Empirico-inductive and/or hypothetico-deductive methods in food science and nutrition research: which one to favor for a better global health?

作者信息

Fardet Anthony, Lebredonchel Louis, Rock Edmond

机构信息

INRAE, Université Clermont Auvergne, UNH, Unité de Nutrition Humaine, CRNH Auvergne, F-63000, Clermont-Ferrand, France.

CERREV - Centre de Recherche Risques & Vulnérabilités - EA 3918 Université de Caen Normandie MRSH, Caen Cedex 5, France.

出版信息

Crit Rev Food Sci Nutr. 2023;63(15):2480-2493. doi: 10.1080/10408398.2021.1976101. Epub 2021 Sep 8.

Abstract

Scientific research generally follows two main methods: empirico-inductive (EI), gathering scattered, real-world qualitative/quantitative data to elaborate holistic theories, and the hypothetico-deductive (HD) approach, testing the validity of hypothesized theory in specific conditions, generally according to reductionist methodologies or designs, with the risk of over simplifying the initial complexity empirically perceived in its holistic view. However, in current food and nutrition research, new hypotheses are often elaborated from reductionist data obtained with the HD approach, and aggregated to form (ultra)reductionist theories, with no application of EI observations, limiting the applicability of these hypotheses in real life. This trend and the application of the EI method are illustrated as regards with the global health issue through the examples of food classifications/scoring, clinical studies, the definition of a sustainable diet, the "matrix effect"-related hypothesis, the concept of healthy core metabolism, and obesity prevention within the perspective of social sciences. To be efficient for producing food and nutritional data appropriable by the society, it finally appears that not only both approaches are necessary, starting with the EI method then the HD one, but also a back and forth between the two, this being not always realized, potentially leading to confusion and misunderstanding in society.

摘要

科学研究一般遵循两种主要方法

经验归纳法(EI),即收集零散的现实世界定性/定量数据以构建整体理论;以及假设演绎法(HD),即在特定条件下检验假设理论的有效性,通常依据还原论方法或设计,但存在过度简化从整体视角实证感知到的初始复杂性的风险。然而,在当前的食品与营养研究中,新假设往往源自通过HD方法获得的还原论数据,并汇总形成(超)还原论理论,而未应用EI观察结果,从而限制了这些假设在现实生活中的适用性。通过食品分类/评分、临床研究、可持续饮食的定义、“基质效应”相关假设、健康核心代谢概念以及社会科学视角下的肥胖预防等实例,阐述了这种趋势以及EI方法在全球健康问题方面的应用。为了有效地生成社会可用的食品和营养数据,最终似乎不仅两种方法都必不可少,首先是EI方法,然后是HD方法,而且还需要在两者之间反复,而这一点并不总是能够实现,可能会导致社会上的困惑和误解。

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