Social epidemiology and complex system dynamic modelling as applied to health behaviour and drug use research.

Social epidemiology and complex system dynamic modelling as applied to health behaviour and drug use research.
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社会流行病学和复杂系统动态建模应用于健康行为和药物使用研究。

DOI:
10.1016/j.drugpo.2008.08.005
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发表时间:
2009-05
影响因子:
4.4
通讯作者:
Kaplan, George A.
Kaplan, George A.
中科院分区:
医学2区
文献类型:
--
作者:
Galea, Sandro;Hall, Chris;Kaplan, George A.

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社会流行病学的观点考虑了多个影响水平的因素(例如,社交网络、社区、州),这些网络可能单独地或共同地影响健康和健康行为。这提供了一个有用的透镜,通过它可以了解一般健康行为的产生,特别是吸毒情况。然而,在人口健康科学中普遍应用的分析模型限制了我们能够通过可能相互关联的因素来确定健康行为的推断。复杂系统动态建模技术可能有助于在健康行为和药物使用研究中采用社会流行病学方法。我们提供了一个模型的例子,旨在将多个层次的影响因素在理解药物依赖。最后,我们建议在该领域的未来发展方向,以及如何将这些模型作为虚拟实验室,旨在改善健康行为的政策实验。
A social epidemiologic perspective considers factors at multiple levels of influence (e.g., social networks, neighborhoods, states) that may individually or jointly affect health and health behaviour. This provides a useful lens through which to understand the production of health behaviours in general, and drug use in particular. However, the analytic models that are commonly applied in population health sciences limit the inference we are able to draw about the determination of health behaviour by factors, likely interrelated, across levels of influence. Complex system dynamic modelling techniques may be useful in enabling the adoption of a social epidemiologic approach in health behaviour and drug use research. We provide an example of a model that aims to incorporate factors at multiple levels of influence in understanding drug dependence. We conclude with suggestions about future directions in the field and how such models may serve as virtual laboratories for policy experiments aimed at improving health behaviour.
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发表时间: 2005-06-01
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