Studying Behaviour Change Mechanisms under Complexity.
Studying Behaviour Change Mechanisms under Complexity.
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DOI：
10.3390/bs11050077
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发表时间：
2021-05-14
期刊：
影响因子：
--
通讯作者：
Hankonen N
中科院分区：
文献类型：
--
作者：
Heino MTJ;Knittle K;Noone C;Hasselman F;Hankonen N
了解行为改变干预措施影响的潜在机制对于积累有效的科学证据至关重要，并且有助于为跨多个领域的实践和决策提供信息。这种评价的传统方法采用了研究设计和统计模型，这些模型隐含地假设变化是线性的、恒定的，并且是由对行为的独立影响（例如行为改变技术）引起的。本文阐述了这些标准工具的局限性，并考虑了采用复杂自适应系统方法进行行为变化研究的好处。它(1)概述了行为和行为改变干预措施的复杂性；(2)向读者介绍复杂系统的一些关键特征，以及这些特征与人类行为变化的关系；(3)为研究人员在分析变化机制时如何更好地解释复杂性的含义提供了建议。我们关注复杂系统的三个共同特征（即互联性、非遍历性和非线性），并介绍递归分析，一种能够量化复杂动力学的非线性时间序列分析方法。补充网站为实际分析应用提供示例代码和数据。复杂适应系统方法可以通过开辟理解和理论化行为变化动力学的新途径来补充传统的研究。
Understanding the mechanisms underlying the effects of behaviour change interventions is vital for accumulating valid scientific evidence, and useful to informing practice and policy-making across multiple domains. Traditional approaches to such evaluations have applied study designs and statistical models, which implicitly assume that change is linear, constant and caused by independent influences on behaviour (such as behaviour change techniques). This article illustrates limitations of these standard tools, and considers the benefits of adopting a complex adaptive systems approach to behaviour change research. It (1) outlines the complexity of behaviours and behaviour change interventions; (2) introduces readers to some key features of complex systems and how these relate to human behaviour change; and (3) provides suggestions for how researchers can better account for implications of complexity in analysing change mechanisms. We focus on three common features of complex systems (i.e., interconnectedness, non-ergodicity and non-linearity), and introduce Recurrence Analysis, a method for non-linear time series analysis which is able to quantify complex dynamics. The supplemental website provides exemplifying code and data for practical analysis applications. The complex adaptive systems approach can complement traditional investigations by opening up novel avenues for understanding and theorising about the dynamics of behaviour change.
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影响因子：
7.4
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通讯作者：
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3.8
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通讯作者：
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