摘要：Public health asks of systems science, as it did of sociology 40 years ago, that it help us unravel the complexity of causal forces in our varied populations and the ecologically layered community and societal circumstances of public health practice. We seek a more evidence-based public health practice, but too much of our evidence comes from artificially controlled research that does not fit the realities of practice. What can we learn from our experience with sociology in the past that might guide us in drawing effectively on systems science? THIS ISSUE OF THE JOURNAL offers examples and promise of an underutilized methodology and a theoretical approach to some of the complex problems of public health on which other methodologies and disciplines have foundered. A central question posed by this collection is whether systems approaches can fill the gap that is felt most acutely by public health as it strives to rise to the paradoxical challenge of evidence-based practice. The challenge is that most of the evidence is not very practice-based. The evidence given greatest credence and therefore the most play in evidence-based guidelines comes from highly controlled trials, ideally controlled by random assignment, but in fact made more artificial or unrepresentative by whatever methods of control are used. These methods are ineffective for taking into consideration the large numbers of variables, the great variability within them, and the diverse circumstances of public health practice. Indeed, they seek to take these variables out of consideration by controlling them, equalizing them, or holding them constant rather than variable. Systems thinking and modeling seems to offer, among other things, an alternative to the controlled trial with simulation rather than control as the major source of evidence. It treats the multiplicity of variables as a resource to be used for deeper analysis rather than as a nemesis to be controlled. This, then, is the hope we harbor and the plea we seem to be making to systems scientists: Bring your theoretical and methodological tools for network analysis, knowledge transfer approaches, and systems organizing methods (including participatory research) to help us get a handle on the multiplicity of influences at work in the real world of practice, so that the evidence from our study of interventions and programs can reflect that complex reality rather than mask it.
