A simple guide to chaos and complexity

Emotion modelling towards affective pathogenesis

Objective: There is a need in psychiatry for models that integrate pathological states with normal systems. The interaction of arousal and emotion is the focus of an exploration of affective pathogenesis. Method: Given that the explicit causes of affective disorder remain nascent, methods of linking emotion and disorder are evaluated. Results: A network model of emotional families is presented, in which emotions exist as quantal gradients. Morbid emotional states are seen as the activation of distal emotion sites. The phenomenology of affective disorders is described with reference to this model. Recourse is made to non-linear dynamic theory. Conclusions: Metaphoric emotion models have face validity and may prove a useful heuristic.

Theorising interventions as events in systems

Conventional thinking about preventive interventions focuses over simplistically on the "package" of activities and/or their educational messages. An alternative is to focus on the dynamic properties of the context into which the intervention is introduced. Schools, communities and worksites can be thought of as complex ecological systems. They can be theorised on three dimensions: (1) their constituent activity settings (e.g., clubs, festivals, assemblies, classrooms); (2) the social networks that connect the people and the settings; and (3) time. An intervention may then be seen as a critical event in the history of a system, leading to the evolution of new structures of interaction and new shared meanings. Interventions impact on evolving networks of person-time-place interaction, changing relationships, displacing existing activities and redistributing and transforming resources. This alternative view has significant implications for how interventions should be evaluated and how they could be made more effective. We explore this idea, drawing on social network analysis and complex systems theory.

Movement variability and the use of nonlinear tools: principles to guide physical therapist practice

Fields studying movement generation, including robotics, psychology, cognitive science, and neuroscience, utilize concepts and tools related to the pervasiveness of variability in biological systems. The concepts of variability and complexity and the nonlinear tools used to measure these concepts open new vistas for physical therapist practice and research in movement dysfunction of all types. Because mounting evidence supports the necessity of variability for health and functional movement, this perspective article argues for changes in the way therapists view variability, both in theory and in action. By providing clinical examples, as well as applying existing knowledge about complex systems, the aim of this article is to create a springboard for new directions in physical therapist research and practice.

Community health assessment using self-organizing maps and geographic information systems

Background

From a public health perspective, a healthier community environment correlates with fewer occurrences of chronic or infectious diseases. Our premise is that community health is a non-linear function of environmental and socioeconomic effects that are not normally distributed among communities. The objective was to integrate multivariate data sets representing social, economic, and physical environmental factors to evaluate the hypothesis that communities with similar environmental characteristics exhibit similar distributions of disease.

Results

The SOM algorithm used the intrinsic distributions of 92 environmental variables to classify 511 communities into five clusters. SOM determined clusters were reprojected to geographic space and compared with the distributions of several health outcomes. ANOVA results indicated that the variability between community clusters was significant with respect to the spatial distribution of disease occurrence.

Conclusion

Our study demonstrated a positive relationship between environmental conditions and health outcomes in communities using the SOM-GIS method to overcome data and methodological challenges traditionally encountered in public health research. Results demonstrated that community health can be classified using environmental variables and that the SOM-GIS method may be applied to multivariate environmental health studies.

Complex interventions or complex systems? Implications for health economic evaluation

Although guidelines exist for evaluating complex interventions, they may be of little help in dealing with the multiple effects of interventions in complex systems such as hospitals. Alan Shiell, Penelope Hawe, and Lisa Gold explain why it is important to distinguish the two types of complexity