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在情境化衰老研究中考虑情境多样性——关于方法论视角的观点

Considering Situational Variety in Contextualized Aging Research - Opinion About Methodological Perspectives.

作者信息

Wolf Friedrich, Seifert Alexander, Martin Mike, Oswald Frank

机构信息

Interdisciplinary Ageing Research (IAW), Department of Educational Sciences, Goethe University Frankfurt, Frankfurt, Germany.

Center for Gerontology, University of Zurich, Zurich, Switzerland.

出版信息

Front Psychol. 2021 Apr 12;12:570900. doi: 10.3389/fpsyg.2021.570900. eCollection 2021.

Abstract

Due to the increasingly heterogeneous trajectories of aging, gerontology requires theoretical models and empirical methods that can meaningfully, reliably, and precisely describe, explain, and predict causes and effects within the aging process, considering particular contexts and situations. Human behavior occurs in contexts; nevertheless, situational changes are often neglected in context-based behavior research. This article follows the tradition of environmental gerontology research based on Lawton's Person-Environment-Interaction model (P-E model) and the theoretical developments of recent years. The authors discuss that, despite an explicit time component, current P-E models could be strengthened by focusing on detecting P-E interactions in various everyday situations. Enhancing Lawton's original formula via a situationally based component not only changes the theoretical perspectives on the interplay between person and environment but also demands new data collection approaches in empirical environmental research. Those approaches are discussed through the example of collecting mobile data with smartphones. Future research should include the situational dimension to investigate the complex nature of person environment interactions.

摘要

由于衰老轨迹日益多样化,老年学需要理论模型和实证方法,这些方法要能在特定背景和情形下,有意义、可靠且精确地描述、解释和预测衰老过程中的因果关系。人类行为发生在特定背景中;然而,情境变化在基于背景的行为研究中常常被忽视。本文遵循基于劳顿的人-环境交互模型(P-E模型)及近年来理论发展的环境老年学研究传统。作者讨论了,尽管当前的P-E模型有明确的时间要素,但通过专注于在各种日常情境中检测人-环境交互作用可对其进行强化。通过基于情境的要素来完善劳顿的原始公式,不仅会改变关于人与环境相互作用的理论视角,还要求在实证环境研究中有新的数据收集方法。通过使用智能手机收集移动数据的例子对这些方法进行了讨论。未来研究应纳入情境维度,以探究人-环境交互作用的复杂本质。

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Mobile Data Collection: Smart, but Not (Yet) Smart Enough.移动数据收集:智能,但(目前)还不够智能。
Front Neurosci. 2018 Dec 18;12:971. doi: 10.3389/fnins.2018.00971. eCollection 2018.

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