Field Richard J, Schuldberg David
Department of Chemistry, University of Montana, Missoula, MT, USA.
Nonlinear Dynamics Psychol Life Sci. 2011 Jan;15(1):53-85.
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 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.
健康心理学研究了压力、社会支持和健康之间的横断面静态关系。与压力相关的疾病水平通常通过纳入非线性乘法或“缓冲”效应来建模，这对应于压力源水平与来自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一个动态系统模型来扩展这个经过充分研究的心理过程的迭代动态模型，该动态系统模型表示为一组连续的非线性微分方程，类似于“俄勒冈振子”（一种非线性动态化学系统模型）。这个个体行为模型适合对其稳态稳定性特性、时间演化和因果关系进行数值研究。这种新方法中的连续变量指的是个体的不同状态；它们是感知压力（X）、症状（Y）和社会支持（Z）。预计在这个模型中，由症状（Y）表示的健康不佳与感知压力直接相关，并且以更复杂的方式与社会支持相关联。可以设想许多这样的模型，其中一些包括社会支持依赖于压力水平的乘法“缓冲”（-X×Z）效应。我们在参数值和初始条件的范围内探索这个模型的行为，并将这些结果与个体在不同压力源和社会支持募集水平下对环境挑战的反应方式联系起来。然后，使用传统的横断面统计技术对模型生成的数据进行分析。讨论了化学系统和心理系统之间的异同。
