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首页> 外文期刊>Nonlinear dynamics, psychology and life sciences >Social-support Moderated Stress: A Nonlinear Dynamical Model and the Stress-Buffering Hypothesis
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Social-support Moderated Stress: A Nonlinear Dynamical Model and the Stress-Buffering Hypothesis

机译：社会支持中度压力：非线性动力学模型和压力缓冲假说

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Health psychology has studied the cross-sectional, stationary relationships linking stress, social support, and health. Levels of stress-related illness are generally modeled by including a nonlinear multiplicative or "buffering" effect, corresponding to the interaction of stressor levels with social support from family and friends. The motivation of the present research is to extend an iterative, dynamic model of this well-investigated psychological process using a dynamical systems model expressed as a set of continuous, nonlinear differential equations similar to those of the "Oregonator," a model of a nonlinear dynamic chemical system. This model of the behavior of an individual is amenable to numerical investigation of its stationary-state stability properties, temporal evolution, and cause-effect relationships. The continuous variables in this new approach refer to varying states of an individual; they are Perceived stress (X), Symptoms (Y), and Social support (Z). It is expected that poor health in this model, represented by Symptoms (Y), is directly related to Perceived stress, as well as being tied in more complicated ways to Social support. A number of such models may be envisioned, some including a multiplicative, "buffering" (- X × Z) effect of social support dependent on stress levels. We explore the behavior of this model over ranges of parameter values and initial conditions and relate these results to how an individual reacts to environmental challenges at various levels of stressors and social-support recruitment. Data generated by the model are in turn analyzed with a traditional cross-sectional statistical technique. Similarities and differences between chemical and psychological systems are discussed.
机译：健康心理学研究了联系压力，社会支持和健康的横断面固定关系。压力相关疾病的水平通常通过包括非线性乘法或“缓冲”效应来建模，该效应对应于压力水平与家人和朋友的社会支持之间的相互作用。本研究的动机是使用动态系统模型（表示为一组连续的非线性微分方程，类似于“ Oregonator”（非线性模型）的动力学系统模型）来扩展此经过充分研究的心理过程的迭代动态模型。动态化学系统。这种个人行为模型适合于对其稳态稳定性，时间演变和因果关系的数值研究。这种新方法中的连续变量指的是个体的不同状态。他们是感知压力（X），症状（Y）和社会支持（Z）。可以预期的是，以症状（Y）表示的该模型中的不良健康状况与感知压力直接相关，并且以更复杂的方式与社会支持联系在一起。可以设想许多这样的模型，其中一些包括取决于压力水平的社会支持的乘性“缓冲”（-X×Z）效应。我们探索了该模型在参数值和初始条件范围内的行为，并将这些结果与个人如何应对各种压力源和社会支持招聘的环境挑战。该模型生成的数据又使用传统的横截面统计技术进行分析。讨论了化学和心理系统之间的异同。

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